Contract No 11-323

QuantifyingtheComprehensiveGreenhouseGasCo-Benefits of GreenBuildings

FINALREPORT

Principal Investigators

ProfsLouiseMozingoandEdArens

Preparedby

TheCenterforResourceEfficientCommunities and TheCenterfortheBuiltEnvironment UniversityofCalifornia ndash Berkeley 2150ShattuckAveSuite313 BerkeleyCA94704-5940

August 212014

PreparedfortheCaliforniaAirResourcesBoardandtheCaliforniaEnvironmentalProtectionAgency

Disclaimer

The statements and conclusions in this reportare those of the contractor and notnecessarily those of the California Air Resources Board The mentionof commercial products their source or their use inconnectionwith material reported hereinis not to be construed as actual or impliedendorsement of suchproducts

ii

Acknowledgements

The principal investigators would like to thank the CREC and CBE staff who executed thisproject William Eisenstein KimberlySeigel and John Goins UC-Berkeley graduate students Gwen Fuertes SoazigKaam Bin Chen Michelle Gonzales and Joe Zissman alsoprovided invaluable research support

Thanks are also due to the US GreenBuilding Council Research Programwhich made the key researchdataset onLEED-certified existing buildings availableto theresearch team Additional data is available to the public through the Green Building Information Gatewaywwwgbigorg

CRECbenefitedgreatly from the able contract management and overall guidance of DanaPapke Waters at the California Air Resources Board (ARB)Annmarie RodgersCourtney Smithand other ARB Research Division staffalong with Dana offeredimportant insights questions and assistance in quarterly progress report calls LarryHunsaker of ARB alsoprovided important assistance

CRECandCBE would alsolike tothank NancyCarrStephen ShepherdMatt StClairRob Sofio Ken Cleaveland SaraNeff Mark Palmer Leslie Giovanelli Liore Elcott David LerherPaul Lilley Martha Cox-Nitikman Tom Padia Dieter Eckels Dennis Murphy Amy CarriganGreg Scharleman Sara Neff Lynell Fuller Liliian Lainez Linda Enger Lori Negrete PeggyLopipero-Langmo Kathleen Hennesey OsamaYounan Daniel Kim SmithKitporka DanBurgoyne Rebecca Kirk Rosemary Kirk and Bernard Chua for various forms of assistancethroughoutthe project

This Report was submitted infulfillment ofARB Contract No 11-323 ldquoQuantifying the Comprehensive Greenhouse Gas Co-Benefits of Green Buildingsrdquoby the CenterforResource Efficient Communities and the Center for the BuiltEnvironmentat UC-Berkeley under the sponsorship of the CaliforniaAir Resources Board This report was completedon August 212014

iii

Disclaimer

The statements and conclusions in this reportare those of the contractor and notnecessarily those of the California Air Resources Board The mentionof commercial products their source or their use inconnectionwith material reported hereinis not to be construed as actual or impliedendorsement of suchproducts

ii

Acknowledgements

The principal investigators would like to thank the CREC and CBE staff who executed thisproject William Eisenstein KimberlySeigel and John Goins UC-Berkeley graduate students Gwen Fuertes SoazigKaam Bin Chen Michelle Gonzales and Joe Zissman alsoprovided invaluable research support

Thanks are also due to the US GreenBuilding Council Research Programwhich made the key researchdataset onLEED-certified existing buildings availableto theresearch team Additional data is available to the public through the Green Building Information Gatewaywwwgbigorg

CRECbenefitedgreatly from the able contract management and overall guidance of DanaPapke Waters at the California Air Resources Board (ARB)Annmarie RodgersCourtney Smithand other ARB Research Division staffalong with Dana offeredimportant insights questions and assistance in quarterly progress report calls LarryHunsaker of ARB alsoprovided important assistance

CRECandCBE would alsolike tothank NancyCarrStephen ShepherdMatt StClairRob Sofio Ken Cleaveland SaraNeff Mark Palmer Leslie Giovanelli Liore Elcott David LerherPaul Lilley Martha Cox-Nitikman Tom Padia Dieter Eckels Dennis Murphy Amy CarriganGreg Scharleman Sara Neff Lynell Fuller Liliian Lainez Linda Enger Lori Negrete PeggyLopipero-Langmo Kathleen Hennesey OsamaYounan Daniel Kim SmithKitporka DanBurgoyne Rebecca Kirk Rosemary Kirk and Bernard Chua for various forms of assistancethroughoutthe project

This Report was submitted infulfillment ofARB Contract No 11-323 ldquoQuantifying the Comprehensive Greenhouse Gas Co-Benefits of Green Buildingsrdquoby the CenterforResource Efficient Communities and the Center for the BuiltEnvironmentat UC-Berkeley under the sponsorship of the CaliforniaAir Resources Board This report was completedon August 212014

iii

Acknowledgements

The principal investigators would like to thank the CREC and CBE staff who executed thisproject William Eisenstein KimberlySeigel and John Goins UC-Berkeley graduate students Gwen Fuertes SoazigKaam Bin Chen Michelle Gonzales and Joe Zissman alsoprovided invaluable research support

Thanks are also due to the US GreenBuilding Council Research Programwhich made the key researchdataset onLEED-certified existing buildings availableto theresearch team Additional data is available to the public through the Green Building Information Gatewaywwwgbigorg

CRECbenefitedgreatly from the able contract management and overall guidance of DanaPapke Waters at the California Air Resources Board (ARB)Annmarie RodgersCourtney Smithand other ARB Research Division staffalong with Dana offeredimportant insights questions and assistance in quarterly progress report calls LarryHunsaker of ARB alsoprovided important assistance

CRECandCBE would alsolike tothank NancyCarrStephen ShepherdMatt StClairRob Sofio Ken Cleaveland SaraNeff Mark Palmer Leslie Giovanelli Liore Elcott David LerherPaul Lilley Martha Cox-Nitikman Tom Padia Dieter Eckels Dennis Murphy Amy CarriganGreg Scharleman Sara Neff Lynell Fuller Liliian Lainez Linda Enger Lori Negrete PeggyLopipero-Langmo Kathleen Hennesey OsamaYounan Daniel Kim SmithKitporka DanBurgoyne Rebecca Kirk Rosemary Kirk and Bernard Chua for various forms of assistancethroughoutthe project

This Report was submitted infulfillment ofARB Contract No 11-323 ldquoQuantifying the Comprehensive Greenhouse Gas Co-Benefits of Green Buildingsrdquoby the CenterforResource Efficient Communities and the Center for the BuiltEnvironmentat UC-Berkeley under the sponsorship of the CaliforniaAir Resources Board This report was completedon August 212014

iii

TableofContents

Introductionhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip1

Materials and Methodshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip3

Resultshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip22

Recommendationshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip42

Glossary of Terms Abbreviations and Symbolshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip46

Discussionhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip30

Summaryand Conclusionshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip41

Referenceshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip44

iv

List ofTables

Table 1 Definitions of baseline predicted and measured valueshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip2Table 2 Number of qualifying LEED-EBOM buildings with data ineach resource areaby regionhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip4Table 3 Water baselines considered for use inanalysishelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip6Table 4 Predicted indoor water use from 2010CalGreenandCA Plumbing Codehelliphelliphelliphelliphelliphellip7 Table 5 Predicted irrigationusage from CalGreencodehelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip8 Table 6 Energy and GHGintensities for regional marginal water supplieshelliphelliphelliphelliphelliphelliphelliphelliphellip11Table 7 Counties included inmajor CA metropolitanplanning organizationshelliphelliphelliphelliphelliphelliphellip15 Table 8 Sample AmericanCommunity Survey commute date for Alameda Countyhelliphelliphelliphellip15Table 9 Baseline average vehicle ridership(AVR) for major CA regionshelliphelliphelliphelliphelliphelliphelliphelliphelliphellip16 Table 10 Distributionof points for the SSc4 credit in LEED-EBOM v 2008helliphelliphelliphelliphelliphelliphelliphelliphellip19 Table 11 Distributionof points for the SSc4 credit inLEED-EBOM v 2009helliphelliphelliphelliphelliphelliphelliphelliphellip19 Table 12 Assumed measured AVRs for each LEED-EBOM point binrsquos lower thresholdhelliphellip20Table 13 Water usage and associated GHGemissions inCAcertified green buildingshelliphelliphellip23 Table 14 Solid waste disposal rates and associated GHGemissioninCA certified greenbuildingshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip23Table 15 Analysis of buildings earning LEED-EBOM water performance credithelliphelliphelliphelliphelliphellip24Table 16 Analysis of buildings earning LEED-EBOM waste performance credithelliphelliphelliphelliphelliphellip24Table 17 Transportationrates and associated GHGemissions inCA certified greenbuildingshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip26Table 18 Summary of GHGemissionsratesfrom water waste and transportation in CAcertified green office buildingshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip26Table 19 Summary of GHGemissions co-benefits from water waste and transportationin CA office buildingshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip28Table 20 Comparative GHGintensities of waterhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip36

v

List ofTables

Table 1 Definitions of baseline predicted and measured valueshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip2Table 2 Number of qualifying LEED-EBOM buildings with data ineach resource areaby regionhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip4Table 3 Water baselines considered for use inanalysishelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip6Table 4 Predicted indoor water use from 2010CalGreenandCA Plumbing Codehelliphelliphelliphelliphelliphellip7 Table 5 Predicted irrigationusage from CalGreencodehelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip8 Table 6 Energy and GHGintensities for regional marginal water supplieshelliphelliphelliphelliphelliphelliphelliphelliphellip11Table 7 Counties included inmajor CA metropolitanplanning organizationshelliphelliphelliphelliphelliphelliphellip15 Table 8 Sample AmericanCommunity Survey commute date for Alameda Countyhelliphelliphelliphellip15Table 9 Baseline average vehicle ridership(AVR) for major CA regionshelliphelliphelliphelliphelliphelliphelliphelliphelliphellip16 Table 10 Distributionof points for the SSc4 credit in LEED-EBOM v 2008helliphelliphelliphelliphelliphelliphelliphelliphellip19 Table 11 Distributionof points for the SSc4 credit inLEED-EBOM v 2009helliphelliphelliphelliphelliphelliphelliphelliphellip19 Table 12 Assumed measured AVRs for each LEED-EBOM point binrsquos lower thresholdhelliphellip20Table 13 Water usage and associated GHGemissions inCAcertified green buildingshelliphelliphellip23 Table 14 Solid waste disposal rates and associated GHGemissioninCA certified greenbuildingshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip23Table 15 Analysis of buildings earning LEED-EBOM water performance credithelliphelliphelliphelliphelliphellip24Table 16 Analysis of buildings earning LEED-EBOM waste performance credithelliphelliphelliphelliphelliphellip24Table 17 Transportationrates and associated GHGemissions inCA certified greenbuildingshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip26Table 18 Summary of GHGemissionsratesfrom water waste and transportation in CAcertified green office buildingshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip26Table 19 Summary of GHGemissions co-benefits from water waste and transportationin CA office buildingshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip28Table 20 Comparative GHGintensities of waterhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip36

v

List ofFigures

Figure 1 Diverted and divertible waste material in CAlarge office buildings 2005helliphellip12 Figure 2 Equations for calculatingtransit mode share asa function of distance of destinationtotransithelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip17 Figure 3 Process for calculatingpredictedregional AVR (Sacramentoexample)helliphelliphelliphelliphelliphellip18 Figure 4 Percentage of solidwaste disposedanddiverted bymaterialhelliphelliphelliphelliphelliphelliphelliphelliphelliphellip32

vi

ABSTRACT

This report quantifies for the first time the greenhouse gas (GHG) emissions co-benefitsassociated with water waste and transportation usage in certified green commercial officebuildings inCalifornia The study comparesthe measured valuesof water waste and transportation usage self-reported by a set of office buildingscertified underthe Leadershipin Energy and Environmental Design rating system for Existing Building Operations andMaintenance (LEED-EBOM) to both baseline values of conventional Californiaoffice buildings and predicted values based uponstate standards for greenbuildings and GHG impact prediction methods The greenbuildings inthe LEED-EBOM dataset produced50less GHGs due to water consumption than baseline buildings 48 less due to solid wastemanagement and5 less due totransportation If appliedtothe entire California office building stock performance typical of the certified green buildings would save0703 MMTCO2eyr from transportation 0084 MMTCO2eyr from water and 0044 MMTCO2eyr from waste for a totalpotential savings of about 0831MMTCO2eyr relative toconventional construction In addition buildings earning additional credits for specifiedperformance thresholds for water and waste in the LEED-EBOM code attained performancelevels even higher than required by the code provisionssuggesting that such code provisions inother contexts may helpincentivize larger GHGemissions reductions than anticipated

vii

EXECUTIVESUMMARY

This report quantifies for the first time the greenhouse gas (GHG) emissions co-benefitsassociated with water waste and transportation usage in certified green commercial officebuildings inCalifornia The study compares the measured values of water waste andtransportation usage self-reported by a set of office buildingscertified underthe Leadershipin Energy and Environmental Design rating system for Existing Building Operations andMaintenance (LEED-EBOM) to both baseline values of conventional California officebuildings and predicted values based uponstate standards for greenbuildings and GHG impact prediction methods

Background

Transportation water use and decompositionof waste inlandfills account for more than40 of Californiarsquos greenhouse gas emissionsWhile each of these resource areas is the subject of emissionscontrol strategieswithin the AB 32 Scoping Plan thatrequires GHG emissions levels to return to 1990 levels by2020the plan and its 2014 Update alsoidentify green buildings as anemissions control strategy that cuts across a variety of resource areas Previous researchhas focusedonthe operational energy performance of greenbuildings and its GHG consequencesbut little has beendone toquantify the GHG consequences ofother building operations and management strategies rewarded by greenbuilding certification systems like LEED Quantification of these GHG co-benefits may thereforecontribute to future GHG policy and regulatory decisions made for the post-2020period

Objectives and methods

The objective of this research project was to compile and analyze adatabase of certified green buildings in Californiathat includes performance metrics that can be used tomeasure the impactof these buildings on GHG emissions due to transportation water use and solidwaste disposal This was accomplished by obtaining access to the project reports submittedby buildings applying for certification under LEED-EBOM in California which include datareported by the LEED-certified professionals on behalf of buildingoperators andsubject tothird-party review on water use waste disposal andtransportation usage The researchteam also had to develop methods to identify baseline and predicted values for usage ofeach of theseresourceareas Baseline values(usage ratestypical of conventional non-greenbuildings) were generated by assembling disparate informationfrom previous studiesbuilding codes and the US Census Predicted values (usagerates expected of green buildings inCalifornia) were generated by consulting state laws and green building codesas well as the GHG quantification guidance issued bythe CaliforniaAir Pollution Control Officers Association (CAPCOA)

In addition the research team identified GHG intensitiesforwater waste and transportation thatwere used to establish emissions levels associated with the baselinepredicted and measured values for each of the three resource areas Because some of the baselines and GHG intensities vary regionally the research team divided thestateinto fivemajor regions ndash the Bay Area Los Angeles Sacramento San Diego and the restof California ndash and performed each step of the analysis for each of these regions independently beforere-combining them into statewide results Regional-scale resultsforthe Bay Area and LosAngeles regions are also reported

viii

Results

The greenbuildings inthe LEED-EBOM dataset produced50less GHGs due to water consumption than baseline buildings 48 less due to solid waste management and5 less due totransportation Ifapplied to an average-sized California office buildingof almost 13000square feet performance typical of the certifiedgreenbuildings wouldsave 800MTCO2eyr from transportation 096 MTCO2eyr from water and 050 MTCO2eyr from waste for a total potential savings of 946 MTCO2eyr relativetoconventional construction If applied to the entire California office building stock (about 114 billionsquare feet)performance typical of the certified green buildings would save 0703 MMTCO2eyr from transportation 0084 MMTCO2eyr from water and 0044 MMTCO2eyr from waste for atotal potential savings of about 0831 MMTCO2eyr relative toconventional construction In addition buildings earning additional credits for specified performance thresholds forwater and waste in the LEED-EBOM code attained performance levels even higher thanrequired by the code provisionssuggesting that suchcode provisions inother contexts may help incentivize larger emissions reductions thananticipated Finally GHG emissionsassociated with measured values for the LEED-EBOM buildings out-performed predictedvalues for water and waste but wereabout 6 worse than predictionfor transportation

Conclusions

The results showthat there are important GHG co-benefits being realized incommercial office buildings relative totypical construction While the percentage improvement relativeto baseline is lower in transportation than in water or waste transportation improvementsare byfar the most important in absolute termsTransportation is over 100 times more GHG-intense per square foot ofoffice building than either water or waste and is alsomore than twice as GHG-intense per square foot of office building as operational energy soincreased attention to building-leveltransportation strategies is essentialPrediction methods should alsobe improved to enable better estimationof GHG co-benefits for policy making Overall these results support the idea that greater GHG co-benefits thanthose quantifiedhere are available from future updates togreen buildingstandards especiallyif increased emphasis is placed on transportation and that such standards can play animportant role in future GHGemissions control efforts

ix

Introduction

Transportation water use and decomposition of waste in landfills account for well morethan 40 of greenhouse gas emissions (GHG) in California according to the AB 32 ScopingPlan (ARB2008) Thoughtful building design and siting can ensurethat a building is accessible viashorter trips and bynon-automobile transportation as well as reducingon-site waterconsumption and waste generation This has the co-benefit of reducing GHG emissions associated with theconsumption of automobilefueland ofthe energy needed to transport distribute and process water and waste

The California Air Resources Board (ARB) and other agencies are increasingly looking togreen buildingpolicies tohelp meet climate goalsThe First Update to the Climate Change ScopingPlan (ARB 2014p82) statesthat green buildingsldquooffera comprehensive approach to supportCaliforniarsquos climate change goals across multiple sectorsrdquo and ldquorepresenta fundamentalshift toward a cross-sectorand integrated climate policy frameworkrdquo but quantifying the GHG emissions reductions due to the non-energybuilding strategies used ingreen building is challenging No full accounting ofthe potential GHG co-benefits from non-energygreen building strategies has previouslyexisted makingit difficult for state and localclimate policies to quantify and incorporate the effects ofthese strategies in climate planning

This project fills a critical part of this gapby assessing for the first time the GHGemissions co-benefits associated with water waste and transportation strategies in certified greencommercial office buildings in California The results serve as animportant guidepost for future updates to state GHGemissions reduction planslocal climate action plansand commercial building standards

The analysis hereinis based upona dataset of California commercial office buildingscertified under the Leadership in EnergyandEnvironmental Design ratingsystem for Existing Building Operations and Maintenance (LEED-EBOM)1Unlike various other LEEDrating systemsthatapply primarily to the design and construction phasesbuildings seeking certification under this rating system must measure and report operational performance data relatedtothe credits they are seeking These data ndash referred to in this study as ldquomeasured valuesrdquondash provided the basis for quantitative analysis of these buildingsrsquo performance with respect to water waste and transportation compared both toconventional non-green commercial office buildings and to the performance expected ofCalifornia green buildings at the time these buildings were certified (see Table 1)

Quantification of conventional building performance ndash referred to in this study as ldquobaseline valuesrdquo ndash was assembled from a variety of datasources includingthe US Census theAmerican Community Survey statewide waste characterization reports and technicalstudieson waterconservation potential Quantification of expected green building performance ndash referred to in this study as ldquopredicted valuesrdquondash was assembled from state green buildingstandards state waste management legislation and the CaliforniaAir PollutionControl Officers Associationrsquos (CAPCOA) guidance onquantificationof GHG emissions control strategies In addition GHGintensities for water waste and

1 The name of this rating system has changed a number of times and is now known as LEED OampM BuildingOperations and Maintenance This report uses the name that applied to the versions of the rating system thatprovided the data used herein

1

ABSTRACT

This report quantifies for the first time the greenhouse gas (GHG) emissions co-benefitsassociated with water waste and transportation usage in certified green commercial officebuildings inCalifornia The study comparesthe measured valuesof water waste and transportation usage self-reported by a set of office buildingscertified underthe Leadershipin Energy and Environmental Design rating system for Existing Building Operations andMaintenance (LEED-EBOM) to both baseline values of conventional Californiaoffice buildings and predicted values based uponstate standards for greenbuildings and GHG impact prediction methods The greenbuildings inthe LEED-EBOM dataset produced50less GHGs due to water consumption than baseline buildings 48 less due to solid wastemanagement and5 less due totransportation If appliedtothe entire California office building stock performance typical of the certified green buildings would save0703 MMTCO2eyr from transportation 0084 MMTCO2eyr from water and 0044 MMTCO2eyr from waste for a totalpotential savings of about 0831MMTCO2eyr relative toconventional construction In addition buildings earning additional credits for specifiedperformance thresholds for water and waste in the LEED-EBOM code attained performancelevels even higher than required by the code provisionssuggesting that such code provisions inother contexts may helpincentivize larger GHGemissions reductions than anticipated

vii

EXECUTIVESUMMARY

This report quantifies for the first time the greenhouse gas (GHG) emissions co-benefitsassociated with water waste and transportation usage in certified green commercial officebuildings inCalifornia The study compares the measured values of water waste andtransportation usage self-reported by a set of office buildingscertified underthe Leadershipin Energy and Environmental Design rating system for Existing Building Operations andMaintenance (LEED-EBOM) to both baseline values of conventional California officebuildings and predicted values based uponstate standards for greenbuildings and GHG impact prediction methods

Background

Transportation water use and decompositionof waste inlandfills account for more than40 of Californiarsquos greenhouse gas emissionsWhile each of these resource areas is the subject of emissionscontrol strategieswithin the AB 32 Scoping Plan thatrequires GHG emissions levels to return to 1990 levels by2020the plan and its 2014 Update alsoidentify green buildings as anemissions control strategy that cuts across a variety of resource areas Previous researchhas focusedonthe operational energy performance of greenbuildings and its GHG consequencesbut little has beendone toquantify the GHG consequences ofother building operations and management strategies rewarded by greenbuilding certification systems like LEED Quantification of these GHG co-benefits may thereforecontribute to future GHG policy and regulatory decisions made for the post-2020period

Objectives and methods

The objective of this research project was to compile and analyze adatabase of certified green buildings in Californiathat includes performance metrics that can be used tomeasure the impactof these buildings on GHG emissions due to transportation water use and solidwaste disposal This was accomplished by obtaining access to the project reports submittedby buildings applying for certification under LEED-EBOM in California which include datareported by the LEED-certified professionals on behalf of buildingoperators andsubject tothird-party review on water use waste disposal andtransportation usage The researchteam also had to develop methods to identify baseline and predicted values for usage ofeach of theseresourceareas Baseline values(usage ratestypical of conventional non-greenbuildings) were generated by assembling disparate informationfrom previous studiesbuilding codes and the US Census Predicted values (usagerates expected of green buildings inCalifornia) were generated by consulting state laws and green building codesas well as the GHG quantification guidance issued bythe CaliforniaAir Pollution Control Officers Association (CAPCOA)

In addition the research team identified GHG intensitiesforwater waste and transportation thatwere used to establish emissions levels associated with the baselinepredicted and measured values for each of the three resource areas Because some of the baselines and GHG intensities vary regionally the research team divided thestateinto fivemajor regions ndash the Bay Area Los Angeles Sacramento San Diego and the restof California ndash and performed each step of the analysis for each of these regions independently beforere-combining them into statewide results Regional-scale resultsforthe Bay Area and LosAngeles regions are also reported

viii

Results

The greenbuildings inthe LEED-EBOM dataset produced50less GHGs due to water consumption than baseline buildings 48 less due to solid waste management and5 less due totransportation Ifapplied to an average-sized California office buildingof almost 13000square feet performance typical of the certifiedgreenbuildings wouldsave 800MTCO2eyr from transportation 096 MTCO2eyr from water and 050 MTCO2eyr from waste for a total potential savings of 946 MTCO2eyr relativetoconventional construction If applied to the entire California office building stock (about 114 billionsquare feet)performance typical of the certified green buildings would save 0703 MMTCO2eyr from transportation 0084 MMTCO2eyr from water and 0044 MMTCO2eyr from waste for atotal potential savings of about 0831 MMTCO2eyr relative toconventional construction In addition buildings earning additional credits for specified performance thresholds forwater and waste in the LEED-EBOM code attained performance levels even higher thanrequired by the code provisionssuggesting that suchcode provisions inother contexts may help incentivize larger emissions reductions thananticipated Finally GHG emissionsassociated with measured values for the LEED-EBOM buildings out-performed predictedvalues for water and waste but wereabout 6 worse than predictionfor transportation

Conclusions

The results showthat there are important GHG co-benefits being realized incommercial office buildings relative totypical construction While the percentage improvement relativeto baseline is lower in transportation than in water or waste transportation improvementsare byfar the most important in absolute termsTransportation is over 100 times more GHG-intense per square foot ofoffice building than either water or waste and is alsomore than twice as GHG-intense per square foot of office building as operational energy soincreased attention to building-leveltransportation strategies is essentialPrediction methods should alsobe improved to enable better estimationof GHG co-benefits for policy making Overall these results support the idea that greater GHG co-benefits thanthose quantifiedhere are available from future updates togreen buildingstandards especiallyif increased emphasis is placed on transportation and that such standards can play animportant role in future GHGemissions control efforts

ix

Introduction

Transportation water use and decomposition of waste in landfills account for well morethan 40 of greenhouse gas emissions (GHG) in California according to the AB 32 ScopingPlan (ARB2008) Thoughtful building design and siting can ensurethat a building is accessible viashorter trips and bynon-automobile transportation as well as reducingon-site waterconsumption and waste generation This has the co-benefit of reducing GHG emissions associated with theconsumption of automobilefueland ofthe energy needed to transport distribute and process water and waste

The California Air Resources Board (ARB) and other agencies are increasingly looking togreen buildingpolicies tohelp meet climate goalsThe First Update to the Climate Change ScopingPlan (ARB 2014p82) statesthat green buildingsldquooffera comprehensive approach to supportCaliforniarsquos climate change goals across multiple sectorsrdquo and ldquorepresenta fundamentalshift toward a cross-sectorand integrated climate policy frameworkrdquo but quantifying the GHG emissions reductions due to the non-energybuilding strategies used ingreen building is challenging No full accounting ofthe potential GHG co-benefits from non-energygreen building strategies has previouslyexisted makingit difficult for state and localclimate policies to quantify and incorporate the effects ofthese strategies in climate planning

This project fills a critical part of this gapby assessing for the first time the GHGemissions co-benefits associated with water waste and transportation strategies in certified greencommercial office buildings in California The results serve as animportant guidepost for future updates to state GHGemissions reduction planslocal climate action plansand commercial building standards

The analysis hereinis based upona dataset of California commercial office buildingscertified under the Leadership in EnergyandEnvironmental Design ratingsystem for Existing Building Operations and Maintenance (LEED-EBOM)1Unlike various other LEEDrating systemsthatapply primarily to the design and construction phasesbuildings seeking certification under this rating system must measure and report operational performance data relatedtothe credits they are seeking These data ndash referred to in this study as ldquomeasured valuesrdquondash provided the basis for quantitative analysis of these buildingsrsquo performance with respect to water waste and transportation compared both toconventional non-green commercial office buildings and to the performance expected ofCalifornia green buildings at the time these buildings were certified (see Table 1)

Quantification of conventional building performance ndash referred to in this study as ldquobaseline valuesrdquo ndash was assembled from a variety of datasources includingthe US Census theAmerican Community Survey statewide waste characterization reports and technicalstudieson waterconservation potential Quantification of expected green building performance ndash referred to in this study as ldquopredicted valuesrdquondash was assembled from state green buildingstandards state waste management legislation and the CaliforniaAir PollutionControl Officers Associationrsquos (CAPCOA) guidance onquantificationof GHG emissions control strategies In addition GHGintensities for water waste and

1 The name of this rating system has changed a number of times and is now known as LEED OampM BuildingOperations and Maintenance This report uses the name that applied to the versions of the rating system thatprovided the data used herein

1

EXECUTIVESUMMARY

This report quantifies for the first time the greenhouse gas (GHG) emissions co-benefitsassociated with water waste and transportation usage in certified green commercial officebuildings inCalifornia The study compares the measured values of water waste andtransportation usage self-reported by a set of office buildingscertified underthe Leadershipin Energy and Environmental Design rating system for Existing Building Operations andMaintenance (LEED-EBOM) to both baseline values of conventional California officebuildings and predicted values based uponstate standards for greenbuildings and GHG impact prediction methods

Background

Transportation water use and decompositionof waste inlandfills account for more than40 of Californiarsquos greenhouse gas emissionsWhile each of these resource areas is the subject of emissionscontrol strategieswithin the AB 32 Scoping Plan thatrequires GHG emissions levels to return to 1990 levels by2020the plan and its 2014 Update alsoidentify green buildings as anemissions control strategy that cuts across a variety of resource areas Previous researchhas focusedonthe operational energy performance of greenbuildings and its GHG consequencesbut little has beendone toquantify the GHG consequences ofother building operations and management strategies rewarded by greenbuilding certification systems like LEED Quantification of these GHG co-benefits may thereforecontribute to future GHG policy and regulatory decisions made for the post-2020period

Objectives and methods

The objective of this research project was to compile and analyze adatabase of certified green buildings in Californiathat includes performance metrics that can be used tomeasure the impactof these buildings on GHG emissions due to transportation water use and solidwaste disposal This was accomplished by obtaining access to the project reports submittedby buildings applying for certification under LEED-EBOM in California which include datareported by the LEED-certified professionals on behalf of buildingoperators andsubject tothird-party review on water use waste disposal andtransportation usage The researchteam also had to develop methods to identify baseline and predicted values for usage ofeach of theseresourceareas Baseline values(usage ratestypical of conventional non-greenbuildings) were generated by assembling disparate informationfrom previous studiesbuilding codes and the US Census Predicted values (usagerates expected of green buildings inCalifornia) were generated by consulting state laws and green building codesas well as the GHG quantification guidance issued bythe CaliforniaAir Pollution Control Officers Association (CAPCOA)

In addition the research team identified GHG intensitiesforwater waste and transportation thatwere used to establish emissions levels associated with the baselinepredicted and measured values for each of the three resource areas Because some of the baselines and GHG intensities vary regionally the research team divided thestateinto fivemajor regions ndash the Bay Area Los Angeles Sacramento San Diego and the restof California ndash and performed each step of the analysis for each of these regions independently beforere-combining them into statewide results Regional-scale resultsforthe Bay Area and LosAngeles regions are also reported

viii

Results

The greenbuildings inthe LEED-EBOM dataset produced50less GHGs due to water consumption than baseline buildings 48 less due to solid waste management and5 less due totransportation Ifapplied to an average-sized California office buildingof almost 13000square feet performance typical of the certifiedgreenbuildings wouldsave 800MTCO2eyr from transportation 096 MTCO2eyr from water and 050 MTCO2eyr from waste for a total potential savings of 946 MTCO2eyr relativetoconventional construction If applied to the entire California office building stock (about 114 billionsquare feet)performance typical of the certified green buildings would save 0703 MMTCO2eyr from transportation 0084 MMTCO2eyr from water and 0044 MMTCO2eyr from waste for atotal potential savings of about 0831 MMTCO2eyr relative toconventional construction In addition buildings earning additional credits for specified performance thresholds forwater and waste in the LEED-EBOM code attained performance levels even higher thanrequired by the code provisionssuggesting that suchcode provisions inother contexts may help incentivize larger emissions reductions thananticipated Finally GHG emissionsassociated with measured values for the LEED-EBOM buildings out-performed predictedvalues for water and waste but wereabout 6 worse than predictionfor transportation

Conclusions

The results showthat there are important GHG co-benefits being realized incommercial office buildings relative totypical construction While the percentage improvement relativeto baseline is lower in transportation than in water or waste transportation improvementsare byfar the most important in absolute termsTransportation is over 100 times more GHG-intense per square foot ofoffice building than either water or waste and is alsomore than twice as GHG-intense per square foot of office building as operational energy soincreased attention to building-leveltransportation strategies is essentialPrediction methods should alsobe improved to enable better estimationof GHG co-benefits for policy making Overall these results support the idea that greater GHG co-benefits thanthose quantifiedhere are available from future updates togreen buildingstandards especiallyif increased emphasis is placed on transportation and that such standards can play animportant role in future GHGemissions control efforts

ix

Introduction

Transportation water use and decomposition of waste in landfills account for well morethan 40 of greenhouse gas emissions (GHG) in California according to the AB 32 ScopingPlan (ARB2008) Thoughtful building design and siting can ensurethat a building is accessible viashorter trips and bynon-automobile transportation as well as reducingon-site waterconsumption and waste generation This has the co-benefit of reducing GHG emissions associated with theconsumption of automobilefueland ofthe energy needed to transport distribute and process water and waste

The California Air Resources Board (ARB) and other agencies are increasingly looking togreen buildingpolicies tohelp meet climate goalsThe First Update to the Climate Change ScopingPlan (ARB 2014p82) statesthat green buildingsldquooffera comprehensive approach to supportCaliforniarsquos climate change goals across multiple sectorsrdquo and ldquorepresenta fundamentalshift toward a cross-sectorand integrated climate policy frameworkrdquo but quantifying the GHG emissions reductions due to the non-energybuilding strategies used ingreen building is challenging No full accounting ofthe potential GHG co-benefits from non-energygreen building strategies has previouslyexisted makingit difficult for state and localclimate policies to quantify and incorporate the effects ofthese strategies in climate planning

This project fills a critical part of this gapby assessing for the first time the GHGemissions co-benefits associated with water waste and transportation strategies in certified greencommercial office buildings in California The results serve as animportant guidepost for future updates to state GHGemissions reduction planslocal climate action plansand commercial building standards

The analysis hereinis based upona dataset of California commercial office buildingscertified under the Leadership in EnergyandEnvironmental Design ratingsystem for Existing Building Operations and Maintenance (LEED-EBOM)1Unlike various other LEEDrating systemsthatapply primarily to the design and construction phasesbuildings seeking certification under this rating system must measure and report operational performance data relatedtothe credits they are seeking These data ndash referred to in this study as ldquomeasured valuesrdquondash provided the basis for quantitative analysis of these buildingsrsquo performance with respect to water waste and transportation compared both toconventional non-green commercial office buildings and to the performance expected ofCalifornia green buildings at the time these buildings were certified (see Table 1)

Quantification of conventional building performance ndash referred to in this study as ldquobaseline valuesrdquo ndash was assembled from a variety of datasources includingthe US Census theAmerican Community Survey statewide waste characterization reports and technicalstudieson waterconservation potential Quantification of expected green building performance ndash referred to in this study as ldquopredicted valuesrdquondash was assembled from state green buildingstandards state waste management legislation and the CaliforniaAir PollutionControl Officers Associationrsquos (CAPCOA) guidance onquantificationof GHG emissions control strategies In addition GHGintensities for water waste and

1 The name of this rating system has changed a number of times and is now known as LEED OampM BuildingOperations and Maintenance This report uses the name that applied to the versions of the rating system thatprovided the data used herein

1

Results

The greenbuildings inthe LEED-EBOM dataset produced50less GHGs due to water consumption than baseline buildings 48 less due to solid waste management and5 less due totransportation Ifapplied to an average-sized California office buildingof almost 13000square feet performance typical of the certifiedgreenbuildings wouldsave 800MTCO2eyr from transportation 096 MTCO2eyr from water and 050 MTCO2eyr from waste for a total potential savings of 946 MTCO2eyr relativetoconventional construction If applied to the entire California office building stock (about 114 billionsquare feet)performance typical of the certified green buildings would save 0703 MMTCO2eyr from transportation 0084 MMTCO2eyr from water and 0044 MMTCO2eyr from waste for atotal potential savings of about 0831 MMTCO2eyr relative toconventional construction In addition buildings earning additional credits for specified performance thresholds forwater and waste in the LEED-EBOM code attained performance levels even higher thanrequired by the code provisionssuggesting that suchcode provisions inother contexts may help incentivize larger emissions reductions thananticipated Finally GHG emissionsassociated with measured values for the LEED-EBOM buildings out-performed predictedvalues for water and waste but wereabout 6 worse than predictionfor transportation

Conclusions

The results showthat there are important GHG co-benefits being realized incommercial office buildings relative totypical construction While the percentage improvement relativeto baseline is lower in transportation than in water or waste transportation improvementsare byfar the most important in absolute termsTransportation is over 100 times more GHG-intense per square foot ofoffice building than either water or waste and is alsomore than twice as GHG-intense per square foot of office building as operational energy soincreased attention to building-leveltransportation strategies is essentialPrediction methods should alsobe improved to enable better estimationof GHG co-benefits for policy making Overall these results support the idea that greater GHG co-benefits thanthose quantifiedhere are available from future updates togreen buildingstandards especiallyif increased emphasis is placed on transportation and that such standards can play animportant role in future GHGemissions control efforts

ix

Introduction

Transportation water use and decomposition of waste in landfills account for well morethan 40 of greenhouse gas emissions (GHG) in California according to the AB 32 ScopingPlan (ARB2008) Thoughtful building design and siting can ensurethat a building is accessible viashorter trips and bynon-automobile transportation as well as reducingon-site waterconsumption and waste generation This has the co-benefit of reducing GHG emissions associated with theconsumption of automobilefueland ofthe energy needed to transport distribute and process water and waste

The California Air Resources Board (ARB) and other agencies are increasingly looking togreen buildingpolicies tohelp meet climate goalsThe First Update to the Climate Change ScopingPlan (ARB 2014p82) statesthat green buildingsldquooffera comprehensive approach to supportCaliforniarsquos climate change goals across multiple sectorsrdquo and ldquorepresenta fundamentalshift toward a cross-sectorand integrated climate policy frameworkrdquo but quantifying the GHG emissions reductions due to the non-energybuilding strategies used ingreen building is challenging No full accounting ofthe potential GHG co-benefits from non-energygreen building strategies has previouslyexisted makingit difficult for state and localclimate policies to quantify and incorporate the effects ofthese strategies in climate planning

This project fills a critical part of this gapby assessing for the first time the GHGemissions co-benefits associated with water waste and transportation strategies in certified greencommercial office buildings in California The results serve as animportant guidepost for future updates to state GHGemissions reduction planslocal climate action plansand commercial building standards

The analysis hereinis based upona dataset of California commercial office buildingscertified under the Leadership in EnergyandEnvironmental Design ratingsystem for Existing Building Operations and Maintenance (LEED-EBOM)1Unlike various other LEEDrating systemsthatapply primarily to the design and construction phasesbuildings seeking certification under this rating system must measure and report operational performance data relatedtothe credits they are seeking These data ndash referred to in this study as ldquomeasured valuesrdquondash provided the basis for quantitative analysis of these buildingsrsquo performance with respect to water waste and transportation compared both toconventional non-green commercial office buildings and to the performance expected ofCalifornia green buildings at the time these buildings were certified (see Table 1)

Quantification of conventional building performance ndash referred to in this study as ldquobaseline valuesrdquo ndash was assembled from a variety of datasources includingthe US Census theAmerican Community Survey statewide waste characterization reports and technicalstudieson waterconservation potential Quantification of expected green building performance ndash referred to in this study as ldquopredicted valuesrdquondash was assembled from state green buildingstandards state waste management legislation and the CaliforniaAir PollutionControl Officers Associationrsquos (CAPCOA) guidance onquantificationof GHG emissions control strategies In addition GHGintensities for water waste and

1 The name of this rating system has changed a number of times and is now known as LEED OampM BuildingOperations and Maintenance This report uses the name that applied to the versions of the rating system thatprovided the data used herein

1

Introduction

Transportation water use and decomposition of waste in landfills account for well morethan 40 of greenhouse gas emissions (GHG) in California according to the AB 32 ScopingPlan (ARB2008) Thoughtful building design and siting can ensurethat a building is accessible viashorter trips and bynon-automobile transportation as well as reducingon-site waterconsumption and waste generation This has the co-benefit of reducing GHG emissions associated with theconsumption of automobilefueland ofthe energy needed to transport distribute and process water and waste

The California Air Resources Board (ARB) and other agencies are increasingly looking togreen buildingpolicies tohelp meet climate goalsThe First Update to the Climate Change ScopingPlan (ARB 2014p82) statesthat green buildingsldquooffera comprehensive approach to supportCaliforniarsquos climate change goals across multiple sectorsrdquo and ldquorepresenta fundamentalshift toward a cross-sectorand integrated climate policy frameworkrdquo but quantifying the GHG emissions reductions due to the non-energybuilding strategies used ingreen building is challenging No full accounting ofthe potential GHG co-benefits from non-energygreen building strategies has previouslyexisted makingit difficult for state and localclimate policies to quantify and incorporate the effects ofthese strategies in climate planning

This project fills a critical part of this gapby assessing for the first time the GHGemissions co-benefits associated with water waste and transportation strategies in certified greencommercial office buildings in California The results serve as animportant guidepost for future updates to state GHGemissions reduction planslocal climate action plansand commercial building standards

The analysis hereinis based upona dataset of California commercial office buildingscertified under the Leadership in EnergyandEnvironmental Design ratingsystem for Existing Building Operations and Maintenance (LEED-EBOM)1Unlike various other LEEDrating systemsthatapply primarily to the design and construction phasesbuildings seeking certification under this rating system must measure and report operational performance data relatedtothe credits they are seeking These data ndash referred to in this study as ldquomeasured valuesrdquondash provided the basis for quantitative analysis of these buildingsrsquo performance with respect to water waste and transportation compared both toconventional non-green commercial office buildings and to the performance expected ofCalifornia green buildings at the time these buildings were certified (see Table 1)

Quantification of conventional building performance ndash referred to in this study as ldquobaseline valuesrdquo ndash was assembled from a variety of datasources includingthe US Census theAmerican Community Survey statewide waste characterization reports and technicalstudieson waterconservation potential Quantification of expected green building performance ndash referred to in this study as ldquopredicted valuesrdquondash was assembled from state green buildingstandards state waste management legislation and the CaliforniaAir PollutionControl Officers Associationrsquos (CAPCOA) guidance onquantificationof GHG emissions control strategies In addition GHGintensities for water waste and

1 The name of this rating system has changed a number of times and is now known as LEED OampM BuildingOperations and Maintenance This report uses the name that applied to the versions of the rating system thatprovided the data used herein

1

transportation were calculated and applied to measured baseline and predicted values inorder toquantifythe GHG emissions avoided(ornot)by certified greenbuildings These were assembled from a combination of CAPCOA guidance Air Resources Board (ARB)guidance and previous technical reports

Tableamp1ampDefinitionsampofampbaselineampmeasuredampandamppredictedampvalues

Baselineampvalue

Measuredampvalue

Predictedampvalue

Definition Water

Majordatasources

Waste Transportation

Performanceoftypicalnon1green officebuildingsinCalifornia

Performanceexpectedofgreenoffice buildingatthetimeofcertification

Actualperformanceofgreenoffice buildings

Gleicketel(2003)

CaliforniaGreenBuilding StandardsCode2010edition

(CalGreen)

Performancedatafromcertified LEED1EBOMofficebuildings

CalRecycle(2006)

AB341

Performancedatafromcertified LEED1EBOMofficebuildings

200812012AmericanCommunity Survey

CAPCOA(2010)

Performancedatafromcertified LEED1EBOMofficebuildings

The study also takes into account important regional variations withinCalifornia The energyintensityof water for example varies substantiallybetween themajor urbanregionsof the state depending upon the origins of their water supplies Though the energy and GHG intensityof transportation modes is constant throughout the state the baselinetransportation performance of conventional commercial office buildings varies regionallyespeciallyin thetransit-rich Bay Area Forthese reasons the research team created separate transportation baseline valuesforfive majorCalifornia regions(the Bay Area LosAngeles San Diego and Sacramento metropolitan areas as well as aldquorest-of-staterdquoregion) and calculated separate GHG intensities for water for the five regionsThese regional differences informedthe statewide comparisons betweenmeasured baseline andpredicted values Intwo regions the Bay Area andLos Angeles there were enoughmeasured building performance values in the LEED-EBOM dataset to enable reporting ofregion-specific comparisonsthat furtherinform the overall conclusions

Finally the studyalsorecognizes that GHG co-benefits may be achieved by buildingscertified under different green rating systems or by buildings that are uncertified by anyrating system Though the resultswere generated using data from existing buildings thisreport exploresthe implicationsof the findingsfornew office constructionandthe commercial office building stock as a whole LEED-EBOM contains credits that reward higher performance inwater efficiency andwaste management andanalysis of theperformance of buildings achieving these credits enables additional insight intothe role thatgreen rating systems can play with respectto new constructionnot just existing buildings This report also contains recommendations for data gathering strategies thatwould enable analysis of GHG co-benefits of building designandmanagement strategies undertakenby commercial office buildings not certified under any rating system The resultsreported herein will therefore advance best practice in setting building design andconstruction standards as well as assisting state and local climate planners in settingadditional GHG emissions reductions goals

2

Materials and Methods

The discussionbelow describes how the dataset of certified green California office buildingswas compiled and what methods were used to determine baseline predicted andmeasured values for water waste and transportation usage respectively Because the studyinvolves comparing three different data points for three different resource areas severaldifferent data sources andmethods wereused

Office building dataset acquisition andprocessing

Acentral task for the successful execution of this project was the acquisition of measureddata on green buildingperformance in California The primarysource of this datawas the US Green Building Council (USGBC) the organization that created and oversees theLeadership in EnergyandEnvironmental Design (LEED) ratingsystems The researchteam obtainedpermissionto access the data submitted by buildings seeking certification under the LEED ExistingBuildings Operations andMaintenance (LEED-EBOM)rating system versions 2008 and 2009 via USGBCrsquos Project Directory and USGBCrsquos online credit database LEED-EBOM is a voluntary green construction standard thathas become the industry standard definition for high-performance buildings To achieve certification a buildingmust demonstrate attainment of certain pre-requisites plusa given numberof voluntarycredits that add up to the desired certification threshold (standard silver gold or platinum)

The researchteam first identified the LEED-EBOM credits relevant to this study from withinthe LEED-EBOM 2008and2009 submittal data only The prior version of theratingsystem(known as LEED-EBOM 20) was based on credits that were not performance-basedand hence wouldnot have the measureddata neededLEED-EBOM v4which strengthened some of the standardsrelevant to thisstudy (including making watermetering and waste audits mandatorypre-requisites) was launched too recently for there to be sufficientsubmittal data collected

The LEED-EBOM 2008and2009credits2 relevant to the co-benefits study included the following

- Sustainable Sites credit 4 (SSc4) ndash Alternative Transportation Commuting - Water Efficiency credits 11 and 12(WEc11and12) ndash Water Performance

Measurement - Water Efficiency credit 2 (WEc2) ndash Indoor Water Efficiency - Water Efficiency credit 3 (WEc3) ndash Landscape Irrigation Efficiency - Material amp Resources credit 6 (MRc6)ndash Solid Waste Management ndash Waste Stream

Audit - Material amp Resources credit 7 (MRc7) ndash Solid Waste Management ndash Ongoing

consumables

2 The labeling descriptionand point distributionof these creditsvariesslightly between versions2008 and 2009 but because this analysis is basedonthe actual reportedperformance dataandnot the points receivedunder LEED-EBOM these differences are largely ignored inthis study

3

The USGBC Project Directory provided readily available informationoneach non-confidential LEED-certified buildingrsquos location certification type (ie what rating system itis certified under) project type owners square footage and date of certification3 The research team used this information as input data for the search fields in the online creditdatabase in order to gather information on the specific credits achieved by each building ofinterest Because one of the researchteam members alsoservedas aUSGBCResearchProgram intern she was able to collaborate withUSGBC staff and obtain accessto portionsof the online credit database that are not publiclyaccessible Access to the data was accompanied byaresponsibilitytorespect and enforce USGBC policies with respect todataaggregation and privacy with which the research team complied

The researchteam first gathered data on allCalifornia buildings labeled as ldquocommercialrdquo by the LEED database then discarded from the datasetall commercial buildings thatare notpredominantly office buildingsThis narrowing was done inorder to ensure that the building uses were similar enough to support direct comparative analysis of their waterwaste and transportation usage patterns The commercial real estate database Loopnetcom was usedtoassist in distinguishingbetween office buildings andnon-office commercial buildings

In addition inclusion in the Project Directory database does not guarantee that creditinformation will be available in the online credit databasebuildings for which this was true were also discarded from the database The team thenassigned building identificationnumbers to each remaining record and categorized all recordsinto one of five California regionsforanalytical purposes(Bay Area LA region Sacramento region San Diego region and Rest-of-State) Not every building thatsought certification achieved all relevant credits For instance thereareseveral buildings that achieved MRc6 and SSc4 but notWEc1 For this reason the research team analyzed datasamples bycredit isolatingbuildingperformance data by resource area (transportation water or waste) as opposedtoanalyzing buildings intheir entirety (see Table 2)

Tableamp2ampQualifyingampLEED3EBOMampbuildingsampwithampdataampinampeachampresourceampareaampbyampregion

Transportation Water Waste

SFBayArea 99 89 105 LAmetro 54 63 74 Sacramentometro 21 22 31 SanDiegometro 16 11 14 RestofCA 6 6 9

Total 196 191 233

WEc11 and 12 (water)submittalsreport waterconsumption data from building water meter readings This potentially includes sub-metering for indoor useirrigationcooling towers domestichot water heaters and process water ifthe applicant so chooses All water consumption dataincluding irrigation data was converted into a unit of gallons per

3 SomeLEED certifications are kept confidential upon agreement bythe buildingowner andthe USGBC these buildings were not available for analysis inthis study

4

Materials and Methods

The discussionbelow describes how the dataset of certified green California office buildingswas compiled and what methods were used to determine baseline predicted andmeasured values for water waste and transportation usage respectively Because the studyinvolves comparing three different data points for three different resource areas severaldifferent data sources andmethods wereused

Office building dataset acquisition andprocessing

Acentral task for the successful execution of this project was the acquisition of measureddata on green buildingperformance in California The primarysource of this datawas the US Green Building Council (USGBC) the organization that created and oversees theLeadership in EnergyandEnvironmental Design (LEED) ratingsystems The researchteam obtainedpermissionto access the data submitted by buildings seeking certification under the LEED ExistingBuildings Operations andMaintenance (LEED-EBOM)rating system versions 2008 and 2009 via USGBCrsquos Project Directory and USGBCrsquos online credit database LEED-EBOM is a voluntary green construction standard thathas become the industry standard definition for high-performance buildings To achieve certification a buildingmust demonstrate attainment of certain pre-requisites plusa given numberof voluntarycredits that add up to the desired certification threshold (standard silver gold or platinum)

The researchteam first identified the LEED-EBOM credits relevant to this study from withinthe LEED-EBOM 2008and2009 submittal data only The prior version of theratingsystem(known as LEED-EBOM 20) was based on credits that were not performance-basedand hence wouldnot have the measureddata neededLEED-EBOM v4which strengthened some of the standardsrelevant to thisstudy (including making watermetering and waste audits mandatorypre-requisites) was launched too recently for there to be sufficientsubmittal data collected

The LEED-EBOM 2008and2009credits2 relevant to the co-benefits study included the following

- Sustainable Sites credit 4 (SSc4) ndash Alternative Transportation Commuting - Water Efficiency credits 11 and 12(WEc11and12) ndash Water Performance

Measurement - Water Efficiency credit 2 (WEc2) ndash Indoor Water Efficiency - Water Efficiency credit 3 (WEc3) ndash Landscape Irrigation Efficiency - Material amp Resources credit 6 (MRc6)ndash Solid Waste Management ndash Waste Stream

Audit - Material amp Resources credit 7 (MRc7) ndash Solid Waste Management ndash Ongoing

consumables

2 The labeling descriptionand point distributionof these creditsvariesslightly between versions2008 and 2009 but because this analysis is basedonthe actual reportedperformance dataandnot the points receivedunder LEED-EBOM these differences are largely ignored inthis study

3

The USGBC Project Directory provided readily available informationoneach non-confidential LEED-certified buildingrsquos location certification type (ie what rating system itis certified under) project type owners square footage and date of certification3 The research team used this information as input data for the search fields in the online creditdatabase in order to gather information on the specific credits achieved by each building ofinterest Because one of the researchteam members alsoservedas aUSGBCResearchProgram intern she was able to collaborate withUSGBC staff and obtain accessto portionsof the online credit database that are not publiclyaccessible Access to the data was accompanied byaresponsibilitytorespect and enforce USGBC policies with respect todataaggregation and privacy with which the research team complied

The researchteam first gathered data on allCalifornia buildings labeled as ldquocommercialrdquo by the LEED database then discarded from the datasetall commercial buildings thatare notpredominantly office buildingsThis narrowing was done inorder to ensure that the building uses were similar enough to support direct comparative analysis of their waterwaste and transportation usage patterns The commercial real estate database Loopnetcom was usedtoassist in distinguishingbetween office buildings andnon-office commercial buildings

In addition inclusion in the Project Directory database does not guarantee that creditinformation will be available in the online credit databasebuildings for which this was true were also discarded from the database The team thenassigned building identificationnumbers to each remaining record and categorized all recordsinto one of five California regionsforanalytical purposes(Bay Area LA region Sacramento region San Diego region and Rest-of-State) Not every building thatsought certification achieved all relevant credits For instance thereareseveral buildings that achieved MRc6 and SSc4 but notWEc1 For this reason the research team analyzed datasamples bycredit isolatingbuildingperformance data by resource area (transportation water or waste) as opposedtoanalyzing buildings intheir entirety (see Table 2)

Tableamp2ampQualifyingampLEED3EBOMampbuildingsampwithampdataampinampeachampresourceampareaampbyampregion

Transportation Water Waste

SFBayArea 99 89 105 LAmetro 54 63 74 Sacramentometro 21 22 31 SanDiegometro 16 11 14 RestofCA 6 6 9

Total 196 191 233

WEc11 and 12 (water)submittalsreport waterconsumption data from building water meter readings This potentially includes sub-metering for indoor useirrigationcooling towers domestichot water heaters and process water ifthe applicant so chooses All water consumption dataincluding irrigation data was converted into a unit of gallons per

3 SomeLEED certifications are kept confidential upon agreement bythe buildingowner andthe USGBC these buildings were not available for analysis inthis study

4

The USGBC Project Directory provided readily available informationoneach non-confidential LEED-certified buildingrsquos location certification type (ie what rating system itis certified under) project type owners square footage and date of certification3 The research team used this information as input data for the search fields in the online creditdatabase in order to gather information on the specific credits achieved by each building ofinterest Because one of the researchteam members alsoservedas aUSGBCResearchProgram intern she was able to collaborate withUSGBC staff and obtain accessto portionsof the online credit database that are not publiclyaccessible Access to the data was accompanied byaresponsibilitytorespect and enforce USGBC policies with respect todataaggregation and privacy with which the research team complied

The researchteam first gathered data on allCalifornia buildings labeled as ldquocommercialrdquo by the LEED database then discarded from the datasetall commercial buildings thatare notpredominantly office buildingsThis narrowing was done inorder to ensure that the building uses were similar enough to support direct comparative analysis of their waterwaste and transportation usage patterns The commercial real estate database Loopnetcom was usedtoassist in distinguishingbetween office buildings andnon-office commercial buildings

In addition inclusion in the Project Directory database does not guarantee that creditinformation will be available in the online credit databasebuildings for which this was true were also discarded from the database The team thenassigned building identificationnumbers to each remaining record and categorized all recordsinto one of five California regionsforanalytical purposes(Bay Area LA region Sacramento region San Diego region and Rest-of-State) Not every building thatsought certification achieved all relevant credits For instance thereareseveral buildings that achieved MRc6 and SSc4 but notWEc1 For this reason the research team analyzed datasamples bycredit isolatingbuildingperformance data by resource area (transportation water or waste) as opposedtoanalyzing buildings intheir entirety (see Table 2)

Tableamp2ampQualifyingampLEED3EBOMampbuildingsampwithampdataampinampeachampresourceampareaampbyampregion

Transportation Water Waste

SFBayArea 99 89 105 LAmetro 54 63 74 Sacramentometro 21 22 31 SanDiegometro 16 11 14 RestofCA 6 6 9

Total 196 191 233

WEc11 and 12 (water)submittalsreport waterconsumption data from building water meter readings This potentially includes sub-metering for indoor useirrigationcooling towers domestichot water heaters and process water ifthe applicant so chooses All water consumption dataincluding irrigation data was converted into a unit of gallons per

3 SomeLEED certifications are kept confidential upon agreement bythe buildingowner andthe USGBC these buildings were not available for analysis inthis study

4

building square foot to adjust for building size and ensure comparability WEc 12 submittals reported on totalbuilding usage for those building seeking to earn extra pointsfor reducing their water usage up to 30 below the calculated LEED baseline There were 71suchsubmittals includedinthe analysis after the cleaning of the dataset described in the section on methodsof calculating measured wateruse

MRc6 (waste)submittalsreport on awaste stream audit duringaperformance period ranging from one daytoseveral months This waste datacan be reported by volumeor by weight Volumetric data wasconverted to weight using standard reference sources(see subsection on waste methodsbelow) to ensure comparability The submittalsincluded information on amounts disposed to landfills and amounts diverted to recycling orcomposting facilities enabling the research team to calculate disposal and diversionpercentages for each building The data also included measurement of the compositionof the waste stream broken down into standard categories (paper plastics wetwaste etc)MRc7 submittals included the same data for buildings seeking to earn extra points forachievingat least 50 diversion of their waste streams There were 144 such submittals included in the analysis after the cleaning ofthe dataset described in the section on methods of calculating measured waste

The SSc4 (transportation)recordscontained data on the percentage reduction inconventional commuting trips using a metricknown as Average Vehicle Ridership (AVR) AVRis essentially the ratio of the number of building occupants to the number ofautomobiles used to deliver them to the building each dayaveraged over a period of recording (usually one week) If every occupant drivesa single-occupancyautomobile to the building the AVR will equal 10 The more non-automobile modes (eg bus rail bicycle walking)and carpooling are used to deliveroccupants to the building the higherthe AVR will be

The research team also attempted tocollect measured datafrom commercial office buildings certified under otherLEED rating systems including LEED forNew Construction (LEED-NC) LEEDfor Core and Shell (LEED-CS) andLEED for CommercialInteriors (LEED-CI) by issuing a survey to owners operators and managers of buildings certified underthese systems throughout California Unlike LEED-EBOM these are point-of-construction rating systemsforwhich there are not yet any performance data at the time of certificationObtaining operational data for these buildings would have enabled analysis of theperformance of LEED-certified commercial office buildings relative to the performancepredicted or implied by the rating systems and the GHG estimationmethods for building strategiespromulgated by CAPCOA

The research team developed surveys of building operators (for water and wasteperformance data) and building occupants (for transportationperformance data) andinvested considerable effort in developing contacts among the operators ofthese LEED-certified buildings (ie the prospective respondents) The research team also developedcontacts among key staff at large associations of building owners and operators such as theBuilding Owners and Managers Association (BOMA) and United States Green BuildingCouncil (USGBC) chapters within California to assist with distribution of the survey fromAugust to October 2013 Despite these efforts the number of returned and fully completed surveyswasinsufficientto supportuseful findings due to the reluctance of mostcommercial building operators to record andor discloseperformancedata on their buildings

5

Water

Baseline water use

To determine the baseline for water use we identified two existing studies that examinedwater use in commercial office buildings with a focus onCalifornia These studies Dziegielewski (2000)and Gleick etal (2003) provided a total of three potential baselines shown in Table 3 Each baseline was normalized to units of annual gallons per 1000square feet

Tableamp3ampWaterampbaselinesampconsideredampforampuseampinampanalysis (gallonssfyr)

Dziegielewski

(AWWA5survey)

Indoor 730 Irrigation 3652 Cooling 661

Total 5043

Gleick51 (Pacific5Inst5from5 MWD5survey)

744 725 439

1908

Gleick52

(Pacific5Inst5modeled)

421 311 349

1081

Sources5Derived5from5Dziegielewski5(2000)5Gleick5et5al5(2003)

The Dziegielewski (2000) baseline was generated by a survey of commercial officebuildings inLos Angeles SanDiego Santa Monica Irvine and Phoenix The two baselines inthe Gleick etal (2003)reportwere generated in differentways The firstbaseline is derived from data about water use in various employment sectors (inthis case commercial officebuildings) modified by empirical data from a survey of office buildings conducted by theMetropolitan Water District of Southern California (MWD) that calculated the typicalproportionof total water use devoted to indoor use irrigation and cooling tower usein office buildings in southern California The secondbaseline was calculatedbyestimatingtypical water flow from indoor fixtures and fittings irrigation needs and cooling towersthen adding these together

The research team elected to use the second Gleick et al (2003)baselineiethe modeled approach for this study The Dziegielewski (2000) baselines thoughbasedonempirical data resultedinvery highirrigationestimates that may be inappropriate for this analysisThe estimates reported inthat survey were characterized by very large standard deviations(often twice the size of the mean) suggesting thatthe reported estimates were pulled upwards by outliers onthe high-usage end of the distribution In addition the survey onlycovered cities in southern California and included Phoenix AZ possibly biasing the sampletoward locations with particularly high irrigation demand relative to the conditionsin California as a whole Finally given the specificlocations under study in that survey the sampled buildings may have beendisproportionately situated on large parcelsin suburban

6

settings(hence with high irrigation demand per building square foot) relative to thepopulationof California office buildings as a whole

The Gleick et al (2003) baselines though not as directly based onempirical data lack these shortcomingsand are based on estimatespertinent to the entire state The second baseline ultimately was selected because it uses the same method that this study uses to generate apredicted value for office building water use (see below) meaning that discrepanciesbetweenthe two due to methodological differences would be minimized This baseline also has the lowest estimates of the three options enablingthis studytoerr on the side of conservatism in comparisons between baseline predicted and measured values for water use

Predicted water use

Values for predicted water use were derived from the 2010 California GreenBuilding Standards Code (the ldquoCalGreenrdquo code in Title 24 Part 11)and the 2010 California Plumbing Code These codes were selectedbecause at the time most of the buildings under studywere certified under LEED-EBOMthese codes represented the statersquos official standard of how a new green buildingin Californiashould performBecause the LEED-EBOM data ongreen buildingperformance available tothe research team did not include information on precisely what actions building designers and managers tookto achieve water use performance it was not possible to directly predict the water usage expected from thoseactions Instead the research team could onlycompare the water use expected from compliance with the statersquos green building code for new construction ndash reflecting the prevailing expectations of how a state-of-the-art green buildingshould perform ndash with the actual performance of these existingbuildings beingcertifiedas green but not subject to the official state green building standards in question

The CalGreen code containsstandardsforthe indoorfixturesand fittingsto be used in new green commercial office buildings as well as information on the flow rates durations ofusage and frequency of usage for each Whencombined with plumbing code standardsforoccupant loadfactors (ie employees per square foot) these were usedtogenerate estimates of anticipated water useper squarefoot for indoor usage as shown in Table4

Tableamp4ampPredictedampindoorampwaterampuseampfromamp2010ampCalGreenampandampCAampPlumbingampCodes (Relevant)fixtures)and)characteristics)only)

Fixture Flow(rate( Duration Daily(uses Fixture(water(use Occupant(load Fixture(water(use galmin galcycle galflush (min flush all male female (galoccupantworkday (sfoccupant) (galtsfworkday galsfyr

Lavatory(faucets 05 025 3 04 200 188 05 Kitchen(faucets 22 4 1 88 200 4400 114 Metering(faucets 025 025 3 02 200 094 02 Water(closets 16 1 1 3 64 200 3200 83 Urinals 1 1 2 20 200 1000 26

Totalampindoor 8881 231

CalGreen alsocontains information that enables a prediction of irrigation water usage whencombined with the California Department of Water Resourcesrsquo (DWR 2010) data on

7

evapotranspiration rates for various municipalities around thestate(seeTable5) Foreach of the major metropolitan regions usedin this study the selected evapotranspiration ratewas that of the largest city within the regionexcept in the Bay Area where Oakland was used because it represents a reasonable climatic average betweenthe Bay Arearsquos two major office cores in San FranciscoandSan JoseSilicon Valley The evapotranspirationrate for Redding was selected to represent the rest-of-California region since most coastal areas arewithin one of the other regions and yet the largest cities in the Central Valley (eg FresnoBakersfield) are too hot anddrytoreflect anyaveragingfrom the northern andmountain regionsof the state

The research team then used the method inDWR (2010) to calculate Estimated Total Water Use (ETWU)persquare footfor landscaping for each ofthese five citiesassuming an average plant factor of 06 (in the middle of the possible range)the default irrigation efficiency(71) and noldquospecial landscape areardquo such as vegetable gardens or areasirrigated with recycled waterThe ETWU was initially calculated per square foot of irrigated area The research team then converted this tobe expressed per square foot of building area(toensure comparabilitywith other results) usingthe ratioof averageirrigated area to average building area (034) found among the 72 commercial officebuildings surveyed by Dziegielewski (2000)

Tableamp5ampPredictedampirrigationampusageampfromampCalGreenampcode

Sac$metro (Sacramento)

Bay$Area (Oakland)

LA$metro (LA)

SD$metro (SD)

Rest$of$CA (Redding)

Evapotranspiration$rate$(inyr) Estimated$Total$Water$Use$(galirrigated$sfyr) Estimated$Total$Water$Use$(galbuilding$sfyr)

519 272 92

418 219 74

501 262 89

465 244 83

488 256 87

Sources$2010$California$Green$Building$Standards$Code$Section$53041

DWR$2010$Water$Budget$Workbook$Beta$Version$101

CalGreen does not contain any standards for cooling towers sothe baseline value for cooling tower usage was used as the predicted value as well Predicted whole-building water use is simply the sumof indoor irrigation and cooling tower usage4

Measured water use

The 2008 and 2009 LEED-EBOM rating systemsenable applicantsto seek optional credits for metering water use (WEc11)for sub-metering atleastone sub-system (WEc12)and for achieving performance standards for indoor usage (WEc2) andor irrigation usage(WEc3)The research team used the information on total building water usage and building square footage to expressall usage on a per-square-foot basis Buildings with water usages

4 Process water (ie water usedto create products or runmechanical processes) is negligible inoffice buildings

8

Water

Baseline water use

To determine the baseline for water use we identified two existing studies that examinedwater use in commercial office buildings with a focus onCalifornia These studies Dziegielewski (2000)and Gleick etal (2003) provided a total of three potential baselines shown in Table 3 Each baseline was normalized to units of annual gallons per 1000square feet

Tableamp3ampWaterampbaselinesampconsideredampforampuseampinampanalysis (gallonssfyr)

Dziegielewski

(AWWA5survey)

Indoor 730 Irrigation 3652 Cooling 661

Total 5043

Gleick51 (Pacific5Inst5from5 MWD5survey)

744 725 439

1908

Gleick52

(Pacific5Inst5modeled)

421 311 349

1081

Sources5Derived5from5Dziegielewski5(2000)5Gleick5et5al5(2003)

The Dziegielewski (2000) baseline was generated by a survey of commercial officebuildings inLos Angeles SanDiego Santa Monica Irvine and Phoenix The two baselines inthe Gleick etal (2003)reportwere generated in differentways The firstbaseline is derived from data about water use in various employment sectors (inthis case commercial officebuildings) modified by empirical data from a survey of office buildings conducted by theMetropolitan Water District of Southern California (MWD) that calculated the typicalproportionof total water use devoted to indoor use irrigation and cooling tower usein office buildings in southern California The secondbaseline was calculatedbyestimatingtypical water flow from indoor fixtures and fittings irrigation needs and cooling towersthen adding these together

The research team elected to use the second Gleick et al (2003)baselineiethe modeled approach for this study The Dziegielewski (2000) baselines thoughbasedonempirical data resultedinvery highirrigationestimates that may be inappropriate for this analysisThe estimates reported inthat survey were characterized by very large standard deviations(often twice the size of the mean) suggesting thatthe reported estimates were pulled upwards by outliers onthe high-usage end of the distribution In addition the survey onlycovered cities in southern California and included Phoenix AZ possibly biasing the sampletoward locations with particularly high irrigation demand relative to the conditionsin California as a whole Finally given the specificlocations under study in that survey the sampled buildings may have beendisproportionately situated on large parcelsin suburban

6

settings(hence with high irrigation demand per building square foot) relative to thepopulationof California office buildings as a whole

The Gleick et al (2003) baselines though not as directly based onempirical data lack these shortcomingsand are based on estimatespertinent to the entire state The second baseline ultimately was selected because it uses the same method that this study uses to generate apredicted value for office building water use (see below) meaning that discrepanciesbetweenthe two due to methodological differences would be minimized This baseline also has the lowest estimates of the three options enablingthis studytoerr on the side of conservatism in comparisons between baseline predicted and measured values for water use

Predicted water use

Values for predicted water use were derived from the 2010 California GreenBuilding Standards Code (the ldquoCalGreenrdquo code in Title 24 Part 11)and the 2010 California Plumbing Code These codes were selectedbecause at the time most of the buildings under studywere certified under LEED-EBOMthese codes represented the statersquos official standard of how a new green buildingin Californiashould performBecause the LEED-EBOM data ongreen buildingperformance available tothe research team did not include information on precisely what actions building designers and managers tookto achieve water use performance it was not possible to directly predict the water usage expected from thoseactions Instead the research team could onlycompare the water use expected from compliance with the statersquos green building code for new construction ndash reflecting the prevailing expectations of how a state-of-the-art green buildingshould perform ndash with the actual performance of these existingbuildings beingcertifiedas green but not subject to the official state green building standards in question

The CalGreen code containsstandardsforthe indoorfixturesand fittingsto be used in new green commercial office buildings as well as information on the flow rates durations ofusage and frequency of usage for each Whencombined with plumbing code standardsforoccupant loadfactors (ie employees per square foot) these were usedtogenerate estimates of anticipated water useper squarefoot for indoor usage as shown in Table4

Tableamp4ampPredictedampindoorampwaterampuseampfromamp2010ampCalGreenampandampCAampPlumbingampCodes (Relevant)fixtures)and)characteristics)only)

Fixture Flow(rate( Duration Daily(uses Fixture(water(use Occupant(load Fixture(water(use galmin galcycle galflush (min flush all male female (galoccupantworkday (sfoccupant) (galtsfworkday galsfyr

Lavatory(faucets 05 025 3 04 200 188 05 Kitchen(faucets 22 4 1 88 200 4400 114 Metering(faucets 025 025 3 02 200 094 02 Water(closets 16 1 1 3 64 200 3200 83 Urinals 1 1 2 20 200 1000 26

Totalampindoor 8881 231

CalGreen alsocontains information that enables a prediction of irrigation water usage whencombined with the California Department of Water Resourcesrsquo (DWR 2010) data on

7

evapotranspiration rates for various municipalities around thestate(seeTable5) Foreach of the major metropolitan regions usedin this study the selected evapotranspiration ratewas that of the largest city within the regionexcept in the Bay Area where Oakland was used because it represents a reasonable climatic average betweenthe Bay Arearsquos two major office cores in San FranciscoandSan JoseSilicon Valley The evapotranspirationrate for Redding was selected to represent the rest-of-California region since most coastal areas arewithin one of the other regions and yet the largest cities in the Central Valley (eg FresnoBakersfield) are too hot anddrytoreflect anyaveragingfrom the northern andmountain regionsof the state

The research team then used the method inDWR (2010) to calculate Estimated Total Water Use (ETWU)persquare footfor landscaping for each ofthese five citiesassuming an average plant factor of 06 (in the middle of the possible range)the default irrigation efficiency(71) and noldquospecial landscape areardquo such as vegetable gardens or areasirrigated with recycled waterThe ETWU was initially calculated per square foot of irrigated area The research team then converted this tobe expressed per square foot of building area(toensure comparabilitywith other results) usingthe ratioof averageirrigated area to average building area (034) found among the 72 commercial officebuildings surveyed by Dziegielewski (2000)

Tableamp5ampPredictedampirrigationampusageampfromampCalGreenampcode

Sac$metro (Sacramento)

Bay$Area (Oakland)

LA$metro (LA)

SD$metro (SD)

Rest$of$CA (Redding)

Evapotranspiration$rate$(inyr) Estimated$Total$Water$Use$(galirrigated$sfyr) Estimated$Total$Water$Use$(galbuilding$sfyr)

519 272 92

418 219 74

501 262 89

465 244 83

488 256 87

Sources$2010$California$Green$Building$Standards$Code$Section$53041

DWR$2010$Water$Budget$Workbook$Beta$Version$101

CalGreen does not contain any standards for cooling towers sothe baseline value for cooling tower usage was used as the predicted value as well Predicted whole-building water use is simply the sumof indoor irrigation and cooling tower usage4

Measured water use

The 2008 and 2009 LEED-EBOM rating systemsenable applicantsto seek optional credits for metering water use (WEc11)for sub-metering atleastone sub-system (WEc12)and for achieving performance standards for indoor usage (WEc2) andor irrigation usage(WEc3)The research team used the information on total building water usage and building square footage to expressall usage on a per-square-foot basis Buildings with water usages

4 Process water (ie water usedto create products or runmechanical processes) is negligible inoffice buildings

8

settings(hence with high irrigation demand per building square foot) relative to thepopulationof California office buildings as a whole

The Gleick et al (2003) baselines though not as directly based onempirical data lack these shortcomingsand are based on estimatespertinent to the entire state The second baseline ultimately was selected because it uses the same method that this study uses to generate apredicted value for office building water use (see below) meaning that discrepanciesbetweenthe two due to methodological differences would be minimized This baseline also has the lowest estimates of the three options enablingthis studytoerr on the side of conservatism in comparisons between baseline predicted and measured values for water use

Predicted water use

Values for predicted water use were derived from the 2010 California GreenBuilding Standards Code (the ldquoCalGreenrdquo code in Title 24 Part 11)and the 2010 California Plumbing Code These codes were selectedbecause at the time most of the buildings under studywere certified under LEED-EBOMthese codes represented the statersquos official standard of how a new green buildingin Californiashould performBecause the LEED-EBOM data ongreen buildingperformance available tothe research team did not include information on precisely what actions building designers and managers tookto achieve water use performance it was not possible to directly predict the water usage expected from thoseactions Instead the research team could onlycompare the water use expected from compliance with the statersquos green building code for new construction ndash reflecting the prevailing expectations of how a state-of-the-art green buildingshould perform ndash with the actual performance of these existingbuildings beingcertifiedas green but not subject to the official state green building standards in question

The CalGreen code containsstandardsforthe indoorfixturesand fittingsto be used in new green commercial office buildings as well as information on the flow rates durations ofusage and frequency of usage for each Whencombined with plumbing code standardsforoccupant loadfactors (ie employees per square foot) these were usedtogenerate estimates of anticipated water useper squarefoot for indoor usage as shown in Table4

Tableamp4ampPredictedampindoorampwaterampuseampfromamp2010ampCalGreenampandampCAampPlumbingampCodes (Relevant)fixtures)and)characteristics)only)

Fixture Flow(rate( Duration Daily(uses Fixture(water(use Occupant(load Fixture(water(use galmin galcycle galflush (min flush all male female (galoccupantworkday (sfoccupant) (galtsfworkday galsfyr

Lavatory(faucets 05 025 3 04 200 188 05 Kitchen(faucets 22 4 1 88 200 4400 114 Metering(faucets 025 025 3 02 200 094 02 Water(closets 16 1 1 3 64 200 3200 83 Urinals 1 1 2 20 200 1000 26

Totalampindoor 8881 231

CalGreen alsocontains information that enables a prediction of irrigation water usage whencombined with the California Department of Water Resourcesrsquo (DWR 2010) data on

7

evapotranspiration rates for various municipalities around thestate(seeTable5) Foreach of the major metropolitan regions usedin this study the selected evapotranspiration ratewas that of the largest city within the regionexcept in the Bay Area where Oakland was used because it represents a reasonable climatic average betweenthe Bay Arearsquos two major office cores in San FranciscoandSan JoseSilicon Valley The evapotranspirationrate for Redding was selected to represent the rest-of-California region since most coastal areas arewithin one of the other regions and yet the largest cities in the Central Valley (eg FresnoBakersfield) are too hot anddrytoreflect anyaveragingfrom the northern andmountain regionsof the state

The research team then used the method inDWR (2010) to calculate Estimated Total Water Use (ETWU)persquare footfor landscaping for each ofthese five citiesassuming an average plant factor of 06 (in the middle of the possible range)the default irrigation efficiency(71) and noldquospecial landscape areardquo such as vegetable gardens or areasirrigated with recycled waterThe ETWU was initially calculated per square foot of irrigated area The research team then converted this tobe expressed per square foot of building area(toensure comparabilitywith other results) usingthe ratioof averageirrigated area to average building area (034) found among the 72 commercial officebuildings surveyed by Dziegielewski (2000)

Tableamp5ampPredictedampirrigationampusageampfromampCalGreenampcode

Sac$metro (Sacramento)

Bay$Area (Oakland)

LA$metro (LA)

SD$metro (SD)

Rest$of$CA (Redding)

Evapotranspiration$rate$(inyr) Estimated$Total$Water$Use$(galirrigated$sfyr) Estimated$Total$Water$Use$(galbuilding$sfyr)

519 272 92

418 219 74

501 262 89

465 244 83

488 256 87

Sources$2010$California$Green$Building$Standards$Code$Section$53041

DWR$2010$Water$Budget$Workbook$Beta$Version$101

CalGreen does not contain any standards for cooling towers sothe baseline value for cooling tower usage was used as the predicted value as well Predicted whole-building water use is simply the sumof indoor irrigation and cooling tower usage4

Measured water use

The 2008 and 2009 LEED-EBOM rating systemsenable applicantsto seek optional credits for metering water use (WEc11)for sub-metering atleastone sub-system (WEc12)and for achieving performance standards for indoor usage (WEc2) andor irrigation usage(WEc3)The research team used the information on total building water usage and building square footage to expressall usage on a per-square-foot basis Buildings with water usages

4 Process water (ie water usedto create products or runmechanical processes) is negligible inoffice buildings

8

evapotranspiration rates for various municipalities around thestate(seeTable5) Foreach of the major metropolitan regions usedin this study the selected evapotranspiration ratewas that of the largest city within the regionexcept in the Bay Area where Oakland was used because it represents a reasonable climatic average betweenthe Bay Arearsquos two major office cores in San FranciscoandSan JoseSilicon Valley The evapotranspirationrate for Redding was selected to represent the rest-of-California region since most coastal areas arewithin one of the other regions and yet the largest cities in the Central Valley (eg FresnoBakersfield) are too hot anddrytoreflect anyaveragingfrom the northern andmountain regionsof the state

The research team then used the method inDWR (2010) to calculate Estimated Total Water Use (ETWU)persquare footfor landscaping for each ofthese five citiesassuming an average plant factor of 06 (in the middle of the possible range)the default irrigation efficiency(71) and noldquospecial landscape areardquo such as vegetable gardens or areasirrigated with recycled waterThe ETWU was initially calculated per square foot of irrigated area The research team then converted this tobe expressed per square foot of building area(toensure comparabilitywith other results) usingthe ratioof averageirrigated area to average building area (034) found among the 72 commercial officebuildings surveyed by Dziegielewski (2000)

Tableamp5ampPredictedampirrigationampusageampfromampCalGreenampcode

Sac$metro (Sacramento)

Bay$Area (Oakland)

LA$metro (LA)

SD$metro (SD)

Rest$of$CA (Redding)

Evapotranspiration$rate$(inyr) Estimated$Total$Water$Use$(galirrigated$sfyr) Estimated$Total$Water$Use$(galbuilding$sfyr)

519 272 92

418 219 74

501 262 89

465 244 83

488 256 87

Sources$2010$California$Green$Building$Standards$Code$Section$53041

DWR$2010$Water$Budget$Workbook$Beta$Version$101

CalGreen does not contain any standards for cooling towers sothe baseline value for cooling tower usage was used as the predicted value as well Predicted whole-building water use is simply the sumof indoor irrigation and cooling tower usage4

Measured water use

The 2008 and 2009 LEED-EBOM rating systemsenable applicantsto seek optional credits for metering water use (WEc11)for sub-metering atleastone sub-system (WEc12)and for achieving performance standards for indoor usage (WEc2) andor irrigation usage(WEc3)The research team used the information on total building water usage and building square footage to expressall usage on a per-square-foot basis Buildings with water usages

4 Process water (ie water usedto create products or runmechanical processes) is negligible inoffice buildings

8

above 1000 gallons per square foot were excluded from the subsequent analysis becausethis is an implausibly high usage rate thatsuggests an error in reporting on the partof the LEED applicant (suchas reportingin gallons insteadof the requested kilogallons for example) In addition anybuilding record in which thereported usage forany sub-meteredsystem was larger than the total building usage was also excluded from the analysis sincethis also suggests areportingerror

Buildings seeking thesub-metering credit are not required to sub-meter all of the sub-systemsin the building to earn the credit and no building did so Thus even among thesub-metered buildings the dataset does not include direct measurement of indoorirrigation andcoolingtower usage in the same buildings In addition virtuallynoapplicantschose to sub-meter indoor usage but approximately half chose to sub-meter irrigation andmore than half (not necessarily the same half) chose to sub-meter cooling towerusage The calculation of measured water usage values therefore proceeded in the following steps

1 Calculate the average total building usage for all buildings not excludedfor reporting errors

2 Calculate the average irrigation usage for buildings sub-metering irrigation usage 3 Calculate the average cooling tower usage for buildings sub-metering cooling tower

usage 4 Impute the average indoor usage by subtracting the irrigation average and the

cooling tower average from the whole-building average and 5 Break these results down by region

Step 5 revealed that for three of the regions (Sacramento San Diego and Rest-of-California)there were notenough records to enablereporting of reliableresults Hence only data for the state as a whole and for the Bay Area andLos Angeles regions is reported

LEED-EBOM alsoincludes twooptional credits for achievingspecified water use efficiencylevels (compared to the LEED baseline) for indoor usage and for irrigation usage Only five buildings inthe dataset earned thecredit for irrigation efficiency too small a number to form the basis for any analysis The 71 buildings that earned the indoor efficiency credit however allow for aninteresting supplemental analysis onthe effectiveness of this performance credit inincentivizing water use efficiency The researchteam therefore compared the indoor irrigation and cooling tower water usage for these high-performingbuildings (derived by the same five steps described immediately above) with that of the 115buildings inthe dataset that metered water usage but did not seekeither of the performance credits

Greenhouse gas intensity of water

The final component of the analysis was to estimate the GHGintensity of the water used (or not used) by these buildings This involved estimating the energy intensity of the water in questionandthenestimating the GHG intensity of that energy The energy intensity of the water varies significantly acrossthe state requiring the research team to estimate thesevalues for each of the five regions separately

Estimating the energy intensity of water requires making assumptions about the exactsource of the waterin question While all of the major regions of the state draw from a varietyof water sources this studyfollowed previous precedent for water-energystudies

9

(CEC 2006)and used a marginal-water approach to analyzing the energy intensity ofavoided water use In other words it assumes that as water is conserved the energyexpenditures avoidedwill be those associated with the lastwater added to the supply as opposedtothe average water in the supply This distinction is significant since the lastwater added is often the mostenergy-intense

For the LA andSan Diegoregions the marginal water is assumed to be State Water Projectimports from the East Branchamong the most energy-intense water supplies in the state The Sacramento regionis water-rich and reliesalmost exclusively on localized surface water supplies The Bay Area water portfolio is more complicated with the major citiesrelying on waterof very different origins(San FranciscorsquosHetch Hetchy system the East Bay Municipal Utility Districtrsquos Mokelumne Aqueduct system and the State Water Project for San Jose and much ofSilicon Valley) A regional weighted averageof theenergyintensity ofthese sources was created to represent the marginal water for the Bay AreaFor the rest of the state energyintensitytypical of Central Coast andSan Joaquin Valleygroundwater extraction was used since these are the major populationareas of the state not includedinthe other regions andgroundwater pumping inthese areas is likely to be cut back before any reductions in use of surface supplies

The energy intensities associated with thesemarginal water supplies presented in Table6 are drawnfrom informationinCAPCOA (2010) and amore recent studyof the energyintensity ofwater in the LA region by Blanco et al (2012) These sourcesinclude estimatesof the energyusedtodeliver water to the building for use and for indoor use include the energycost of wastewater treatment but do not include any estimate of the energyinvolved in heating the water for use inside the buildingTo incorporate this factorthe research team applied the energy intensity of water heating identified by NRDC (2004)in an in-depthanalysis of SanDiegorsquos water supply (20562 kWhMG)and assumed that 25 of indoor water use in office buildings is subject toheating

Estimationof the GHGintensity of energyalso took a marginal (as opposed to average) approach assumingthat the GHGintensity of the energyconsumption avoided would bethatof the ldquolastelectronsrdquo added to the electricity supply notthe average of the entire supply In previousresearch describedinMozingoandArens (2013) ARB recommendedthe use of a statewide GHG intensity for marginal electricity of 0000270 MTkWh For the Sacramentoregion the average GHG intensityof the entire electricitysupply is used because it is lower thanthe statewide marginal electricity estimate (E32010)

10

Tableamp6ampampEnergyampandampGHGampintensitiesampforampregionalampmarginalampwaterampsupplies

Region

BayArea

Sacmetro

SDmetro

LAmetro

Restofstate

Assumedorigin

StateWaterProject HetchHetchy

Mokelumne

Weightedaverage

Localintrabasin

StateWaterProject(East) StateWaterProject(East) Groundwater

Quantity

(TAF)

188

265

365

Energyintensityofwater

Outdoor Indoor (kWhMG) (kWhMG)

2817 9869

1383 8435

1543 8595

1784 8835

1503 8555

3459 10511

3459 10511

2279 9331

GHGintensofenergy

(MTkWh)

0000270

0000270

0000270

0000270

0000233

0000270

0000270

0000270

GHGintensityofwater

Outdoor Indoor (MTgal) (MTgal)

0000000761 000000266 0000000373 000000228 0000000417 000000232 0000000482 000000239 0000000350 000000199 0000000934 000000284 0000000934 000000284 0000000615 000000252

SourceforwaterenergyintensitiesCAPCOA(2010)TableWSWZ31p345Blancoetal(2012)forStateWaterProject SourceformarginalGHGintensitiesofenergyARBpersonalcommunicationSacramentomarginalintensityfromE3(2010) SourceforHetchHetchyandMokelumnediversionquantityhttpwwwaquaforniacom

SourceforwaterheatingenergyintensityincorporatedinindoorestimateNRDC(2004)

These GHGintensities for water were thenapplied to all baseline predicted and measuredwater use for the buildings in each of the regions to generate the findings discussed in theResults chapter Waste

The two-step processforcalculating the GHGco-benefits of waste reductionefforts inoffice buildings includes a determinationof baseline predicted and measured waste diversionrates and the GHG emissions associated with landfilled waste The former relied on data collected by CalRecycleand theUSGBC whilethelatter involves theequations at theheart of ARBrsquos Landfill Emissions Model tool

Baseline waste diversion rates

CalRecycle has collectedsolid waste data over the past twodecades but thefocus of this data has beenondiversionanddisposal rates for entire jurisdictions andthe landfills within them After 2007 CalRecycle started to measure per-capita disposal rates as ameans to measure program implementation by jurisdiction but this data blends wastegeneration from all sources within the jurisdiction and does not distinguish between wastegeneration rates from different buildingtypes

CalRecycle publishedWaste Characterizations Reports in 1999 2004 2006and2008 thatlook beyond waste streams in jurisdictions at statewide practices The reports from 1999 2004and2008all characterize the materials disposedat waste facilities throughout theState derived from commercial residential and self-haul waste streams The 2006 Statewide Waste Characterization Reporthoweverexamines diversion and disposal practices by key industry groups After consultation with multiple experts at CalRecycleand elsewhere the research team determined that this report contained the bestavailable data for establishment of baseline values Regional studies conducted inLos Angeles and

11

(CEC 2006)and used a marginal-water approach to analyzing the energy intensity ofavoided water use In other words it assumes that as water is conserved the energyexpenditures avoidedwill be those associated with the lastwater added to the supply as opposedtothe average water in the supply This distinction is significant since the lastwater added is often the mostenergy-intense

For the LA andSan Diegoregions the marginal water is assumed to be State Water Projectimports from the East Branchamong the most energy-intense water supplies in the state The Sacramento regionis water-rich and reliesalmost exclusively on localized surface water supplies The Bay Area water portfolio is more complicated with the major citiesrelying on waterof very different origins(San FranciscorsquosHetch Hetchy system the East Bay Municipal Utility Districtrsquos Mokelumne Aqueduct system and the State Water Project for San Jose and much ofSilicon Valley) A regional weighted averageof theenergyintensity ofthese sources was created to represent the marginal water for the Bay AreaFor the rest of the state energyintensitytypical of Central Coast andSan Joaquin Valleygroundwater extraction was used since these are the major populationareas of the state not includedinthe other regions andgroundwater pumping inthese areas is likely to be cut back before any reductions in use of surface supplies

The energy intensities associated with thesemarginal water supplies presented in Table6 are drawnfrom informationinCAPCOA (2010) and amore recent studyof the energyintensity ofwater in the LA region by Blanco et al (2012) These sourcesinclude estimatesof the energyusedtodeliver water to the building for use and for indoor use include the energycost of wastewater treatment but do not include any estimate of the energyinvolved in heating the water for use inside the buildingTo incorporate this factorthe research team applied the energy intensity of water heating identified by NRDC (2004)in an in-depthanalysis of SanDiegorsquos water supply (20562 kWhMG)and assumed that 25 of indoor water use in office buildings is subject toheating

Estimationof the GHGintensity of energyalso took a marginal (as opposed to average) approach assumingthat the GHGintensity of the energyconsumption avoided would bethatof the ldquolastelectronsrdquo added to the electricity supply notthe average of the entire supply In previousresearch describedinMozingoandArens (2013) ARB recommendedthe use of a statewide GHG intensity for marginal electricity of 0000270 MTkWh For the Sacramentoregion the average GHG intensityof the entire electricitysupply is used because it is lower thanthe statewide marginal electricity estimate (E32010)

10

Tableamp6ampampEnergyampandampGHGampintensitiesampforampregionalampmarginalampwaterampsupplies

Region

BayArea

Sacmetro

SDmetro

LAmetro

Restofstate

Assumedorigin

StateWaterProject HetchHetchy

Mokelumne

Weightedaverage

Localintrabasin

StateWaterProject(East) StateWaterProject(East) Groundwater

Quantity

(TAF)

188

265

365

Energyintensityofwater

Outdoor Indoor (kWhMG) (kWhMG)

2817 9869

1383 8435

1543 8595

1784 8835

1503 8555

3459 10511

3459 10511

2279 9331

GHGintensofenergy

(MTkWh)

0000270

0000270

0000270

0000270

0000233

0000270

0000270

0000270

GHGintensityofwater

Outdoor Indoor (MTgal) (MTgal)

0000000761 000000266 0000000373 000000228 0000000417 000000232 0000000482 000000239 0000000350 000000199 0000000934 000000284 0000000934 000000284 0000000615 000000252

SourceforwaterenergyintensitiesCAPCOA(2010)TableWSWZ31p345Blancoetal(2012)forStateWaterProject SourceformarginalGHGintensitiesofenergyARBpersonalcommunicationSacramentomarginalintensityfromE3(2010) SourceforHetchHetchyandMokelumnediversionquantityhttpwwwaquaforniacom

SourceforwaterheatingenergyintensityincorporatedinindoorestimateNRDC(2004)

These GHGintensities for water were thenapplied to all baseline predicted and measuredwater use for the buildings in each of the regions to generate the findings discussed in theResults chapter Waste

The two-step processforcalculating the GHGco-benefits of waste reductionefforts inoffice buildings includes a determinationof baseline predicted and measured waste diversionrates and the GHG emissions associated with landfilled waste The former relied on data collected by CalRecycleand theUSGBC whilethelatter involves theequations at theheart of ARBrsquos Landfill Emissions Model tool

Baseline waste diversion rates

CalRecycle has collectedsolid waste data over the past twodecades but thefocus of this data has beenondiversionanddisposal rates for entire jurisdictions andthe landfills within them After 2007 CalRecycle started to measure per-capita disposal rates as ameans to measure program implementation by jurisdiction but this data blends wastegeneration from all sources within the jurisdiction and does not distinguish between wastegeneration rates from different buildingtypes

CalRecycle publishedWaste Characterizations Reports in 1999 2004 2006and2008 thatlook beyond waste streams in jurisdictions at statewide practices The reports from 1999 2004and2008all characterize the materials disposedat waste facilities throughout theState derived from commercial residential and self-haul waste streams The 2006 Statewide Waste Characterization Reporthoweverexamines diversion and disposal practices by key industry groups After consultation with multiple experts at CalRecycleand elsewhere the research team determined that this report contained the bestavailable data for establishment of baseline values Regional studies conducted inLos Angeles and

11

Tableamp6ampampEnergyampandampGHGampintensitiesampforampregionalampmarginalampwaterampsupplies

Region

BayArea

Sacmetro

SDmetro

LAmetro

Restofstate

Assumedorigin

StateWaterProject HetchHetchy

Mokelumne

Weightedaverage

Localintrabasin

StateWaterProject(East) StateWaterProject(East) Groundwater

Quantity

(TAF)

188

265

365

Energyintensityofwater

Outdoor Indoor (kWhMG) (kWhMG)

2817 9869

1383 8435

1543 8595

1784 8835

1503 8555

3459 10511

3459 10511

2279 9331

GHGintensofenergy

(MTkWh)

0000270

0000270

0000270

0000270

0000233

0000270

0000270

0000270

GHGintensityofwater

Outdoor Indoor (MTgal) (MTgal)

0000000761 000000266 0000000373 000000228 0000000417 000000232 0000000482 000000239 0000000350 000000199 0000000934 000000284 0000000934 000000284 0000000615 000000252

SourceforwaterenergyintensitiesCAPCOA(2010)TableWSWZ31p345Blancoetal(2012)forStateWaterProject SourceformarginalGHGintensitiesofenergyARBpersonalcommunicationSacramentomarginalintensityfromE3(2010) SourceforHetchHetchyandMokelumnediversionquantityhttpwwwaquaforniacom

SourceforwaterheatingenergyintensityincorporatedinindoorestimateNRDC(2004)

These GHGintensities for water were thenapplied to all baseline predicted and measuredwater use for the buildings in each of the regions to generate the findings discussed in theResults chapter Waste

The two-step processforcalculating the GHGco-benefits of waste reductionefforts inoffice buildings includes a determinationof baseline predicted and measured waste diversionrates and the GHG emissions associated with landfilled waste The former relied on data collected by CalRecycleand theUSGBC whilethelatter involves theequations at theheart of ARBrsquos Landfill Emissions Model tool

Baseline waste diversion rates

CalRecycle has collectedsolid waste data over the past twodecades but thefocus of this data has beenondiversionanddisposal rates for entire jurisdictions andthe landfills within them After 2007 CalRecycle started to measure per-capita disposal rates as ameans to measure program implementation by jurisdiction but this data blends wastegeneration from all sources within the jurisdiction and does not distinguish between wastegeneration rates from different buildingtypes

CalRecycle publishedWaste Characterizations Reports in 1999 2004 2006and2008 thatlook beyond waste streams in jurisdictions at statewide practices The reports from 1999 2004and2008all characterize the materials disposedat waste facilities throughout theState derived from commercial residential and self-haul waste streams The 2006 Statewide Waste Characterization Reporthoweverexamines diversion and disposal practices by key industry groups After consultation with multiple experts at CalRecycleand elsewhere the research team determined that this report contained the bestavailable data for establishment of baseline values Regional studies conducted inLos Angeles and

11

Easily

Dlvertlble 47

7 Other Disposed

324

Disposed Potentially Dlvertlble

14

Alameda County report data by Standard Industrial Classification (SIC)codes and not by building types

The 2006 Statewide Waste Characterization study categorizesindustry groupsby building types and contains a specificcategory for large office buildings The regional samples fromthis category for the statewide study were not large enough to form the basis for regionallyspecific baseline valuesso the research team relied instead upon one statewide baseline valuederived from thefollowingdatapoints

bull Waste generated by large office buildings 1998 pounds1000 square feet bull Waste diverted by large office buildings 132 pounds1000 square feet

Hencethe baseline diversion rate for commercial office buildings in California is 7 (see Figure 1)and the generation rate is rounded to one ton per 1000square feet

Figure 1 Diverted and divertible waste material inCA large office buildings 2005 (From CalRecycle 2006)

Predicted waste diversion rates

CAPCOA (2010) provides a method for calculating emissions associated with building wastegeneration and utilizes CalRecyclersquos 2006Statewide Waste Characterization Study forannual diversion rates but it does not provide any additional waste diversion rate to serveas the basis for apredicted valueFurthermoreit acknowledges the complications involved with determining default waste diversionvalues stating that ldquono literature references exist which provide default valuesforpercent of waste divertedrdquo (CAPCOA 2010 392) CalGreen alsomakes nomention of any anticipated waste diversion rate for non-residential buildingsduring operation

In the absence of an established prediction methodology the research team used the policygoals embodied in state law At the time that the buildings in our dataset were applyingfor LEED-EBOM certification the leading solid waste management law in the state (AB341) mandated a50 solid waste diversion rate on ajurisdictional basiswith a goal of 75

12

waste diversion statewide by 2020 AB341 was subsequently updated inJuly 2012shortlyafter the date of LEED certification of most of the buildings in the dataset to extend the50 target to commercial solid waste Hence at the time these buildings were applying for LEEDcertification 50 was considered an appropriate goal for green buildings to achieve buthadnot yet beenmandatedinstate law (whichwouldmake it a new baseline) In addition the 2006 Waste Characterization Study found that while only seven percent ofoffice building waste was being diverted at that timeanother 47 was ldquoeasily divertiblerdquo (see Figure 1) For these reasons a50 diversion rate was adopted as a reasonable predicted valuefor the operations of certifiedgreen buildings

Measured waste diversion rates

Over 200 measured values for building waste diversion rates were collected from the LEED-EBOM buildings The MRc6credit requiresan audit of the buildingrsquos entire ongoingconsumables waste stream conducted during a performance period selected by theapplicantThe data can be collected and reported in weight (pounds or tons) or volume (gallons) and are reported as suchWaste data reported by volume instead ofweight was converted using the material-specific conversion factorsfound at a standard online conversion calculator (httpwwwaqua-calccomcalculatevolume-to-weight)

The total quantities of waste measured could have beenused to determine a waste generation rate in addition toadiversion rate except that there was noinformation in the recordson how long the waste had been accumulating at the measurement point before theperiod of measurement For this reasonit became apparent uponexaminationof the data that the mostmeaningful data from the samples would come from the diversion percentagesas opposed to quantities The overall measured value diversion rate was therefore determinedby taking the simple average of every buildingrsquos waste diversion rate

GHGintensity of landfilled waste

The leading toolwith which to quantify the GHG emissions associatedwithwaste diversionin California is the Landfill Emissions Tool Version 13 which implements themathematically exact first-order decaymodel of the 2006IPCCguidelines for landfills In consultation with subject expertsat ARBthe research team adapted the calculations underlying the landfill model for use onoffice building waste streamsespecially the following formula (shown in expanded form here forclarity of explanation)foruse atlandfills that have methane collection systems

MTCO2e MT of waste =(ANDOC x05 x 133x 25)x ((075 x 001)+ (025 x 09))

Where

bull ANDOC = the percentage of waste material thatis anaerobically degradable carbon bull 05=the proportion of ANDOCthat converts tomethane (CH4) bull 133=the ratioof methane tocarbon (C) bull 25 =the conversion factor toconvert methane quantity intoCO2-equivalent bull 075=the proportion of methane captured by the collectionsystem bull 001=the proportion of capturedmethane that escapes from the collection system bull 025=the proportion of uncapturedmethane that escapes throughthe soil bull 09=the proportion of the uncapturedmethane that is not oxidizedin thesoil

13

waste diversion statewide by 2020 AB341 was subsequently updated inJuly 2012shortlyafter the date of LEED certification of most of the buildings in the dataset to extend the50 target to commercial solid waste Hence at the time these buildings were applying for LEEDcertification 50 was considered an appropriate goal for green buildings to achieve buthadnot yet beenmandatedinstate law (whichwouldmake it a new baseline) In addition the 2006 Waste Characterization Study found that while only seven percent ofoffice building waste was being diverted at that timeanother 47 was ldquoeasily divertiblerdquo (see Figure 1) For these reasons a50 diversion rate was adopted as a reasonable predicted valuefor the operations of certifiedgreen buildings

Measured waste diversion rates

Over 200 measured values for building waste diversion rates were collected from the LEED-EBOM buildings The MRc6credit requiresan audit of the buildingrsquos entire ongoingconsumables waste stream conducted during a performance period selected by theapplicantThe data can be collected and reported in weight (pounds or tons) or volume (gallons) and are reported as suchWaste data reported by volume instead ofweight was converted using the material-specific conversion factorsfound at a standard online conversion calculator (httpwwwaqua-calccomcalculatevolume-to-weight)

The total quantities of waste measured could have beenused to determine a waste generation rate in addition toadiversion rate except that there was noinformation in the recordson how long the waste had been accumulating at the measurement point before theperiod of measurement For this reasonit became apparent uponexaminationof the data that the mostmeaningful data from the samples would come from the diversion percentagesas opposed to quantities The overall measured value diversion rate was therefore determinedby taking the simple average of every buildingrsquos waste diversion rate

GHGintensity of landfilled waste

The leading toolwith which to quantify the GHG emissions associatedwithwaste diversionin California is the Landfill Emissions Tool Version 13 which implements themathematically exact first-order decaymodel of the 2006IPCCguidelines for landfills In consultation with subject expertsat ARBthe research team adapted the calculations underlying the landfill model for use onoffice building waste streamsespecially the following formula (shown in expanded form here forclarity of explanation)foruse atlandfills that have methane collection systems

MTCO2e MT of waste =(ANDOC x05 x 133x 25)x ((075 x 001)+ (025 x 09))

Where

bull ANDOC = the percentage of waste material thatis anaerobically degradable carbon bull 05=the proportion of ANDOCthat converts tomethane (CH4) bull 133=the ratioof methane tocarbon (C) bull 25 =the conversion factor toconvert methane quantity intoCO2-equivalent bull 075=the proportion of methane captured by the collectionsystem bull 001=the proportion of capturedmethane that escapes from the collection system bull 025=the proportion of uncapturedmethane that escapes throughthe soil bull 09=the proportion of the uncapturedmethane that is not oxidizedin thesoil

13

This involved selecting values for the proportionof Anaerobically Degradable Carbon(ANDOC)in the office building waste stream From the trends displayedin the measuredwaste values (see Figure 4)it was determined that the majority of waste being sent to landfill(disposed) from office buildings is on average comprised of70 wet waste (largely food) and 30 paper Using these percentages the research team was able to calculate aunique weighted ANDOC percentage applicable to all office building waste streams inCalifornia That ANDOCvalue was then used inthe above formula that determines the amount of methane (CH4) emissions per metric ton ofwaste for landfills with gas collection systems Though gascollection systemsare not universally employed by landfills inCalifornia they are present in the large majority of landfills servicing the metropolitan areaswhere green building are concentrated (CalRecycle 2013) so theirpresence was assumed for purposes ofthese calculations Landfills also emit carbon dioxide but these emissions are not considered byARB tobe an anthropogenic emissions source subject toemissions control efforts and are therefore ignored here

Transportation

The analysis of transportationusage centered onthe metric known as average vehicleridership (AVR) essentially the ratio between the numberof office buildingoccupants andthe number of cars ittakes to bring them to the building on a typical day Because the measured transportation data available fromtheUSGBC reports on building AVR theresearch team developed original methodsforcalculating baseline and predicted AVR forthe five regions being analyzed

Baseline transportation usage

The maindata source for the transportationbaselines is the American Community Survey (ACS)conducted annually by the US Census Bureauwhich gathers data on means of transportation to work (Table B08301)and compiles those data on a county-by-county basis and on aone-year three-year or five-year timespanGiven thatthe LEED-EBOM green buildings in our dataset were certified between 2008 and 2012 we chose to examinefive-year countytransportation data compiled over those years for each county within ourmetropolitan regions

The boundaries of our four metropolitan regions follow those of the respectiveMetropolitan Planning Organizations (MPOs) the Southern California Association ofGovernments (SCAG) the Bay Area Metropolitan Transportation Commission andAssociation of Bay Area Governments (MTCABAG) the SacramentoAreaCouncil of Governments (SACOG) and the San Diego Association of Governments (SANDAG) Each of these MPOs contains only whole counties and because they form geographical units usedfor regionaltransportation planning are sufficiently representative of the actual commute-shedsof buildingsin ourdataset The countiesinvolvedare namedinTable 7 The values for the ldquorest-of-staterdquoregion were derived by removing the effects of thefour major regions from the statewide totals reportedinthe ACS througha simple algebraic equation

14

Tableamp7ampampCountiesampincludedampinampmajorampCAampmetropolitanampplanningamporganizations

MTC$(Bay$Area)

Alameda Contra$Costa

Marin Napa

San$Francisco San$Mateo Santa$Clara Solano Sonoma

SCAG$(LA) SACOG$(Sacramento) SANDAG$(SD)

Imperial El$Dorado San$Diego Los$Angeles Placer Orange Sacramento Riverside Sutter

San$Bernardino Yolo Ventura Yuba

The ACS data estimate the total number of commuters for drive-alone 2-personcarpools 3-personcarpools 4-personcarpools 5 or 6-personcarpools 7-personor more carpools public transportation bus or trolleybus streetcar or trolleycar subwayor elevated railroad ferryboat taxicab motorcycle bicycle walking othermeans and ldquoworked at homerdquo for every county A sample of this data for Alameda County California is shown in Table 8

Table 8 Sample AmericanCommunity Survey commute datafor AlamedaCounty 2008-2012 ( ofcommuters using each mode)

Total 693960

Car truck or van 527826

Drove alone 454660

Carpooled 73166

In 2-personcarpool 54162

In 3-personcarpool 13176

In 4-personcarpool 3583

In 5- or 6-personcarpool 1155

In 7-or-more-personcarpool 1090

Public transportation (excluding taxicab) 82417

Bus or trolley bus 31062

Streetcar or trolley car (carro publico in Puerto Rico) 1056

Subway or elevated 42900

Railroad 6412

Ferryboat 987

Taxicab 301

Motorcycle 2050

Bicycle 11945

Walked 26202

Other means 6872

Worked at home 36347

15

To calculate the baseline AVR for eachregion the categorical totals were summedtogether across the different counties in order tofind

bull The total number of commuters inthe region($) bull The total number of vehicle users (car truck or van) driving alone () bull The estimated number of vehicles (car truck or van) used for carpooling()

The estimated number of vehicles used for carpoolingVCPis calculation by simply dividingthe number of commuters who carpooled by the size of the carpool (eg the number ofcarpoolers in two-personcarpools divided by two the number of carpoolers in three-personcarpools divided by three etc)then summing the estimated number of vehicles across the carpool categoryThe ldquo5 or 6-personrdquo carpool category was assumed to carry 55 people per carpool and the ldquo7-or-more-person carpoolrdquo categorywas assumedtocarry75people per carpool

The regional AVR is defined as the adjusted total number of vehicles divided by the total ofall commuters for aregion For eachregion we calculated the baseline AVR as follows

$ = ℎ ( + )

Table 9 shows the baseline AVRs for the five major regions

Tableamp9ampampBaselineampaverageampvehicleampridershipamp(AVR)ampforampmajorampCAampregions

Commuters Vehicles AVR

Bay3Area 33333333 3400199 3333333333 2444789 139 LA3metro 33333333 7886161 3333333333 6271379 126 Sacramento3metro 33333333333 984449 3333333333333 792260 124 SD3metro 33333333 1431134 3333333333 1152142 124 Rest3of3state 33333311810893 3333333333 9116305 129

Predicted transportationusage

Predictionof transportationusage was performedbasedupon the location of the buildings in the study dataset LEED-EBOM does not require the reporting of any other buildingcharacteristics or management strategies such as the amount and allocation of parkingspaces that might influence commute AVRs and therefore GHGemissions

AVRis fundamentally a measure of mode share ie the proportion of commuters usingvarious transportation modes and not of vehicle miles traveled(VMT) Fortunately CAPCOA (2010) provides an equationshown in Figure 2 for predicting railtransit mode share based upon the proximity of buildingsto rail stations and thisequation can be used to adjustregional baseline AVRs to reflectthe AVR thatthis particular setof buildings based ontheir locations ldquoshouldrdquobeachieving This process makes noadjustment for bus

16

transit bicycling walking or other non-automobile modesFor this reason the predictedAVRs resulting from this method can be thought of as conservative ie closer to the regionalbaseline thanwouldbe expectedif all non-automobile modes were included in the analysis

Figure 2 Equations for calculating transit mode share as afunctionof distance of destination totransit

Distance to transit Transit mode share calculation equation (where x =distance of project to transit)

0ndash 05miles -50x +38 05to 3miles -44x +152 gt3miles noimpact

The research team identified the distance of each building inthe study dataset to the nearest rail stationusing Google Maps The distance betweenthe building and the rail station wasdefined asthe walking distance overthe street network and wasdetermined by activatingGoogle Mapsrsquo pedestrian walkingdirections function which indicates the totalwalking distance between two identified points The predictedrail transit mode share was then calculated for each building using the appropriate componentof the CAPCOA equation and the predicted rail transitmode shares for all buildings in a given region were then averaged

For eachregion the averaged predicted rail mode share was then used to modify thebaseline regional AVR For purposes of calculating AVR all non-automobile trips are equivalent becausetheydeliver a building occupant to thesitewithout theuseof a car Thethree components that matter for the calculation of AVRtherefore are the use of single-occupancyautomobiles the use of carpools andthe use of all other modes combined The third of these components was modified to reflect the additional rail trips predicted for thisset of buildings and the othertwo categoriesreduced proportionally to create a new AVR This method assumes thatthe additional rail commute trips will displace carpool trips atthe same rate thatthey displace single-occupancyvehicle trips The mathematical process by which this AVR adjustment was performedusing the Sacramento region as an example is illustrated in Figure 3 The predicted AVRs are incorporated into Table 17

17

r-

( )

( )

Figure 3 Process for calculating predicted regional AVR(Sacramento example)

Method labels values Notes and formula

Census data

Drove alone 0752

Carpooled 0049

All other 0200 ℎ

Rail (all forms) 0007

$ Included in

Sum of Census ldquostreet car or trolleycarrdquo ldquosubwayor elevatedrdquoand ldquorailroadrdquocategories

Carpool size 241

=

ℎ ℎ minus ℎ minus ℎ

CAPCOA Predicted rail 0197 Derived from dataset using formulas in Figure 2

Increase in rail 0190 Difference between ldquopredicted railrdquo and ldquorailrdquo categories

All other (predicted) 0321

ℎ Sum of ldquoall otherrdquo accounted with theldquorailrdquo increased number

Drove alone (predicted)

0587

Ratioof ldquodrove alonerdquo relative toldquocarpooledrdquo accountedwithldquoall other (predicted)rdquo increased value

= (1 minus ) lowast ( + )

Carpooled(predicted) 0092

Ratioof ldquocarpooledrdquo relative toldquodrove alonerdquo accountedwithldquoall other (predicted)rdquo increased value

= (1 minus ) lowast ( + )

Predicted AVR 1599 ℎ + +

+

Measured transportation usage

The measured data for this research are based onthe LEED-EBOM 2008and2009submittal data for the Sustainable Sites credit4 (SSc4)credit For each of the buildings considered the database provides the points for the SSc4credit which is associated with a percentage of

18

reduction in conventional trips Tables 10 and 11 provide the scales for the 2008 and 2009versions respectively of LEED-EBOM

Tables 10 and 11 Distribution of points for the SSc4 credit in LEED-EBOM versions 2008and2009

Demonstrated reduction in conventional

Points

commuting trips 10 1 25 2 50 3 75 4

Demonstrated reduction in conventional

Points

commuting trips 10 3

1375 4 1750 5 2125 6 25 7

3125 8 375 9 4375 10 50 11

5625 12 6250 13 6875 14 75 15

Table10 LEED EBOM v 2008 Table11 LEED EBOM v 2009

The ldquodemonstrated percentage reductioninconventional commutingrdquo used inthe LEED reporting isequivalent to the improvement in the reported AVR valuecompared totheLEED baseline of 10 (ie everyonecommutes bysingle-occupancyautomobiles)As a resultthe percentage reductions canbe directly converted to AVR values ie a 10 reduction of conventional tripswill resultsin an AVR of 11a20 reduction will result in an AVR of 12 and soon

Because only binned data are available the team assumed that each building actuallydemonstrateda percentage reductiononaverage 25 above the lower thresholdof the binprovided by the LEED rating system (see Table 12) Apossible alternative would be toassume that the actual AVRs are clustered around the midpoint of the range (ie 50 abovethe lower threshold)but the research team elected not to assume this for two reasonsFirst given the point-based incentives to reach each threshold it seemed more likely thatthe AVRs are notevenly distributed throughout each bin rangebut areinstead likelyclustered in the lower half of each bin range Second given the high GHG-intensity oftransportation the research team felt it important to be conservative inany assumptions about buildingperformance relative tobaseline and predicted values since small differences inassumptions couldresult inestimates of large but potentially illusory GHGsavings

19

Table 12 Assumed measured AVRs for each LEED-EBOM point binrsquos lower threshold

Demonstrated reduction in Assumedmeasured conventional AVR

commuting trips 10 1125

1375 1171875 1750 121875 2125 1265625 25 13125

3125 1390625 375 146875 4375 1546875 50 1625

5625 1703125 6250 178125 6875 1859375 75 19375

These measured AVR values were thenaveraged across buildings withineach regionto create a measured AVR value for the LEED-EBOM buildings withineach region that can be compared to the baseline and predicted AVRs

GHGintensity of transportation

The GHGintensity of each mode of travel expressed as pounds of CO2e emitted perpassenger mile traveled was obtained from the individual emissions calculator attravelmattersorgdeveloped by the Center for Neighborhood Technology for the Federal Transit Administration(Feigonet al 2003)This tool enables users to determine the per-mile emissions resulting fromtravel by various modes in locations aroundthe country including California Though they are state-specific the coefficientsare now overten yearsoldandtherefore donot reflect the gradual de-carbonization of fuel stocks resulting from the statersquosLow Carbon Fuel StandardandRenewable Portfolio Standard

For baselinevalues theGHG intensityof each regionrsquos AVR was determined bycreating anaverage of the GHG intensities of the modes used weighted by the proportion that eachmode was used in that region This yielded a GHG intensity for eachAVR expressedin pounds of CO2eper milecommuted This was then converted into metric tons of CO2eper 1000square feet per year of office buildingbyassumingatypical occupant loadingof 5occupants per 1000square feet (drawn from the 2010California Plumbing Code) atypicalcommuting distance of 12 miles each way or 24 miles per occupant per day (drawn fromfindings on average commute distance in ARB2012a and 2012b) and a typical workyearof 260days The same method was used for predicted AVRs except that theGHG intensityof the extra predicted rail trips was represented by the arithmetic average of the GHGintensities ofthe various rail modes (streetcar or trolley car subway or elevated and railroad)denominated in the ACS data

20

Tableamp7ampampCountiesampincludedampinampmajorampCAampmetropolitanampplanningamporganizations

MTC$(Bay$Area)

Alameda Contra$Costa

Marin Napa

San$Francisco San$Mateo Santa$Clara Solano Sonoma

SCAG$(LA) SACOG$(Sacramento) SANDAG$(SD)

Imperial El$Dorado San$Diego Los$Angeles Placer Orange Sacramento Riverside Sutter

San$Bernardino Yolo Ventura Yuba

The ACS data estimate the total number of commuters for drive-alone 2-personcarpools 3-personcarpools 4-personcarpools 5 or 6-personcarpools 7-personor more carpools public transportation bus or trolleybus streetcar or trolleycar subwayor elevated railroad ferryboat taxicab motorcycle bicycle walking othermeans and ldquoworked at homerdquo for every county A sample of this data for Alameda County California is shown in Table 8

Table 8 Sample AmericanCommunity Survey commute datafor AlamedaCounty 2008-2012 ( ofcommuters using each mode)

Total 693960

Car truck or van 527826

Drove alone 454660

Carpooled 73166

In 2-personcarpool 54162

In 3-personcarpool 13176

In 4-personcarpool 3583

In 5- or 6-personcarpool 1155

In 7-or-more-personcarpool 1090

Public transportation (excluding taxicab) 82417

Bus or trolley bus 31062

Streetcar or trolley car (carro publico in Puerto Rico) 1056

Subway or elevated 42900

Railroad 6412

Ferryboat 987

Taxicab 301

Motorcycle 2050

Bicycle 11945

Walked 26202

Other means 6872

Worked at home 36347

15

To calculate the baseline AVR for eachregion the categorical totals were summedtogether across the different counties in order tofind

bull The total number of commuters inthe region($) bull The total number of vehicle users (car truck or van) driving alone () bull The estimated number of vehicles (car truck or van) used for carpooling()

The estimated number of vehicles used for carpoolingVCPis calculation by simply dividingthe number of commuters who carpooled by the size of the carpool (eg the number ofcarpoolers in two-personcarpools divided by two the number of carpoolers in three-personcarpools divided by three etc)then summing the estimated number of vehicles across the carpool categoryThe ldquo5 or 6-personrdquo carpool category was assumed to carry 55 people per carpool and the ldquo7-or-more-person carpoolrdquo categorywas assumedtocarry75people per carpool

The regional AVR is defined as the adjusted total number of vehicles divided by the total ofall commuters for aregion For eachregion we calculated the baseline AVR as follows

$ = ℎ ( + )

Table 9 shows the baseline AVRs for the five major regions

Tableamp9ampampBaselineampaverageampvehicleampridershipamp(AVR)ampforampmajorampCAampregions

Commuters Vehicles AVR

Bay3Area 33333333 3400199 3333333333 2444789 139 LA3metro 33333333 7886161 3333333333 6271379 126 Sacramento3metro 33333333333 984449 3333333333333 792260 124 SD3metro 33333333 1431134 3333333333 1152142 124 Rest3of3state 33333311810893 3333333333 9116305 129

Predicted transportationusage

Predictionof transportationusage was performedbasedupon the location of the buildings in the study dataset LEED-EBOM does not require the reporting of any other buildingcharacteristics or management strategies such as the amount and allocation of parkingspaces that might influence commute AVRs and therefore GHGemissions

AVRis fundamentally a measure of mode share ie the proportion of commuters usingvarious transportation modes and not of vehicle miles traveled(VMT) Fortunately CAPCOA (2010) provides an equationshown in Figure 2 for predicting railtransit mode share based upon the proximity of buildingsto rail stations and thisequation can be used to adjustregional baseline AVRs to reflectthe AVR thatthis particular setof buildings based ontheir locations ldquoshouldrdquobeachieving This process makes noadjustment for bus

16

transit bicycling walking or other non-automobile modesFor this reason the predictedAVRs resulting from this method can be thought of as conservative ie closer to the regionalbaseline thanwouldbe expectedif all non-automobile modes were included in the analysis

Figure 2 Equations for calculating transit mode share as afunctionof distance of destination totransit

Distance to transit Transit mode share calculation equation (where x =distance of project to transit)

0ndash 05miles -50x +38 05to 3miles -44x +152 gt3miles noimpact

The research team identified the distance of each building inthe study dataset to the nearest rail stationusing Google Maps The distance betweenthe building and the rail station wasdefined asthe walking distance overthe street network and wasdetermined by activatingGoogle Mapsrsquo pedestrian walkingdirections function which indicates the totalwalking distance between two identified points The predictedrail transit mode share was then calculated for each building using the appropriate componentof the CAPCOA equation and the predicted rail transitmode shares for all buildings in a given region were then averaged

For eachregion the averaged predicted rail mode share was then used to modify thebaseline regional AVR For purposes of calculating AVR all non-automobile trips are equivalent becausetheydeliver a building occupant to thesitewithout theuseof a car Thethree components that matter for the calculation of AVRtherefore are the use of single-occupancyautomobiles the use of carpools andthe use of all other modes combined The third of these components was modified to reflect the additional rail trips predicted for thisset of buildings and the othertwo categoriesreduced proportionally to create a new AVR This method assumes thatthe additional rail commute trips will displace carpool trips atthe same rate thatthey displace single-occupancyvehicle trips The mathematical process by which this AVR adjustment was performedusing the Sacramento region as an example is illustrated in Figure 3 The predicted AVRs are incorporated into Table 17

17

r-

( )

( )

Figure 3 Process for calculating predicted regional AVR(Sacramento example)

Method labels values Notes and formula

Census data

Drove alone 0752

Carpooled 0049

All other 0200 ℎ

Rail (all forms) 0007

$ Included in

Sum of Census ldquostreet car or trolleycarrdquo ldquosubwayor elevatedrdquoand ldquorailroadrdquocategories

Carpool size 241

=

ℎ ℎ minus ℎ minus ℎ

CAPCOA Predicted rail 0197 Derived from dataset using formulas in Figure 2

Increase in rail 0190 Difference between ldquopredicted railrdquo and ldquorailrdquo categories

All other (predicted) 0321

ℎ Sum of ldquoall otherrdquo accounted with theldquorailrdquo increased number

Drove alone (predicted)

0587

Ratioof ldquodrove alonerdquo relative toldquocarpooledrdquo accountedwithldquoall other (predicted)rdquo increased value

= (1 minus ) lowast ( + )

Carpooled(predicted) 0092

Ratioof ldquocarpooledrdquo relative toldquodrove alonerdquo accountedwithldquoall other (predicted)rdquo increased value

= (1 minus ) lowast ( + )

Predicted AVR 1599 ℎ + +

+

Measured transportation usage

The measured data for this research are based onthe LEED-EBOM 2008and2009submittal data for the Sustainable Sites credit4 (SSc4)credit For each of the buildings considered the database provides the points for the SSc4credit which is associated with a percentage of

18

reduction in conventional trips Tables 10 and 11 provide the scales for the 2008 and 2009versions respectively of LEED-EBOM

Tables 10 and 11 Distribution of points for the SSc4 credit in LEED-EBOM versions 2008and2009

Demonstrated reduction in conventional

Points

commuting trips 10 1 25 2 50 3 75 4

Demonstrated reduction in conventional

Points

commuting trips 10 3

1375 4 1750 5 2125 6 25 7

3125 8 375 9 4375 10 50 11

5625 12 6250 13 6875 14 75 15

Table10 LEED EBOM v 2008 Table11 LEED EBOM v 2009

The ldquodemonstrated percentage reductioninconventional commutingrdquo used inthe LEED reporting isequivalent to the improvement in the reported AVR valuecompared totheLEED baseline of 10 (ie everyonecommutes bysingle-occupancyautomobiles)As a resultthe percentage reductions canbe directly converted to AVR values ie a 10 reduction of conventional tripswill resultsin an AVR of 11a20 reduction will result in an AVR of 12 and soon

Because only binned data are available the team assumed that each building actuallydemonstrateda percentage reductiononaverage 25 above the lower thresholdof the binprovided by the LEED rating system (see Table 12) Apossible alternative would be toassume that the actual AVRs are clustered around the midpoint of the range (ie 50 abovethe lower threshold)but the research team elected not to assume this for two reasonsFirst given the point-based incentives to reach each threshold it seemed more likely thatthe AVRs are notevenly distributed throughout each bin rangebut areinstead likelyclustered in the lower half of each bin range Second given the high GHG-intensity oftransportation the research team felt it important to be conservative inany assumptions about buildingperformance relative tobaseline and predicted values since small differences inassumptions couldresult inestimates of large but potentially illusory GHGsavings

19

Table 12 Assumed measured AVRs for each LEED-EBOM point binrsquos lower threshold

Demonstrated reduction in Assumedmeasured conventional AVR

commuting trips 10 1125

1375 1171875 1750 121875 2125 1265625 25 13125

3125 1390625 375 146875 4375 1546875 50 1625

5625 1703125 6250 178125 6875 1859375 75 19375

These measured AVR values were thenaveraged across buildings withineach regionto create a measured AVR value for the LEED-EBOM buildings withineach region that can be compared to the baseline and predicted AVRs

GHGintensity of transportation

The GHGintensity of each mode of travel expressed as pounds of CO2e emitted perpassenger mile traveled was obtained from the individual emissions calculator attravelmattersorgdeveloped by the Center for Neighborhood Technology for the Federal Transit Administration(Feigonet al 2003)This tool enables users to determine the per-mile emissions resulting fromtravel by various modes in locations aroundthe country including California Though they are state-specific the coefficientsare now overten yearsoldandtherefore donot reflect the gradual de-carbonization of fuel stocks resulting from the statersquosLow Carbon Fuel StandardandRenewable Portfolio Standard

For baselinevalues theGHG intensityof each regionrsquos AVR was determined bycreating anaverage of the GHG intensities of the modes used weighted by the proportion that eachmode was used in that region This yielded a GHG intensity for eachAVR expressedin pounds of CO2eper milecommuted This was then converted into metric tons of CO2eper 1000square feet per year of office buildingbyassumingatypical occupant loadingof 5occupants per 1000square feet (drawn from the 2010California Plumbing Code) atypicalcommuting distance of 12 miles each way or 24 miles per occupant per day (drawn fromfindings on average commute distance in ARB2012a and 2012b) and a typical workyearof 260days The same method was used for predicted AVRs except that theGHG intensityof the extra predicted rail trips was represented by the arithmetic average of the GHGintensities ofthe various rail modes (streetcar or trolley car subway or elevated and railroad)denominated in the ACS data

20

To calculate the baseline AVR for eachregion the categorical totals were summedtogether across the different counties in order tofind

bull The total number of commuters inthe region($) bull The total number of vehicle users (car truck or van) driving alone () bull The estimated number of vehicles (car truck or van) used for carpooling()

The estimated number of vehicles used for carpoolingVCPis calculation by simply dividingthe number of commuters who carpooled by the size of the carpool (eg the number ofcarpoolers in two-personcarpools divided by two the number of carpoolers in three-personcarpools divided by three etc)then summing the estimated number of vehicles across the carpool categoryThe ldquo5 or 6-personrdquo carpool category was assumed to carry 55 people per carpool and the ldquo7-or-more-person carpoolrdquo categorywas assumedtocarry75people per carpool

The regional AVR is defined as the adjusted total number of vehicles divided by the total ofall commuters for aregion For eachregion we calculated the baseline AVR as follows

$ = ℎ ( + )

Table 9 shows the baseline AVRs for the five major regions

Tableamp9ampampBaselineampaverageampvehicleampridershipamp(AVR)ampforampmajorampCAampregions

Commuters Vehicles AVR

Bay3Area 33333333 3400199 3333333333 2444789 139 LA3metro 33333333 7886161 3333333333 6271379 126 Sacramento3metro 33333333333 984449 3333333333333 792260 124 SD3metro 33333333 1431134 3333333333 1152142 124 Rest3of3state 33333311810893 3333333333 9116305 129

Predicted transportationusage

Predictionof transportationusage was performedbasedupon the location of the buildings in the study dataset LEED-EBOM does not require the reporting of any other buildingcharacteristics or management strategies such as the amount and allocation of parkingspaces that might influence commute AVRs and therefore GHGemissions

AVRis fundamentally a measure of mode share ie the proportion of commuters usingvarious transportation modes and not of vehicle miles traveled(VMT) Fortunately CAPCOA (2010) provides an equationshown in Figure 2 for predicting railtransit mode share based upon the proximity of buildingsto rail stations and thisequation can be used to adjustregional baseline AVRs to reflectthe AVR thatthis particular setof buildings based ontheir locations ldquoshouldrdquobeachieving This process makes noadjustment for bus

16

transit bicycling walking or other non-automobile modesFor this reason the predictedAVRs resulting from this method can be thought of as conservative ie closer to the regionalbaseline thanwouldbe expectedif all non-automobile modes were included in the analysis

Figure 2 Equations for calculating transit mode share as afunctionof distance of destination totransit

Distance to transit Transit mode share calculation equation (where x =distance of project to transit)

0ndash 05miles -50x +38 05to 3miles -44x +152 gt3miles noimpact

The research team identified the distance of each building inthe study dataset to the nearest rail stationusing Google Maps The distance betweenthe building and the rail station wasdefined asthe walking distance overthe street network and wasdetermined by activatingGoogle Mapsrsquo pedestrian walkingdirections function which indicates the totalwalking distance between two identified points The predictedrail transit mode share was then calculated for each building using the appropriate componentof the CAPCOA equation and the predicted rail transitmode shares for all buildings in a given region were then averaged

For eachregion the averaged predicted rail mode share was then used to modify thebaseline regional AVR For purposes of calculating AVR all non-automobile trips are equivalent becausetheydeliver a building occupant to thesitewithout theuseof a car Thethree components that matter for the calculation of AVRtherefore are the use of single-occupancyautomobiles the use of carpools andthe use of all other modes combined The third of these components was modified to reflect the additional rail trips predicted for thisset of buildings and the othertwo categoriesreduced proportionally to create a new AVR This method assumes thatthe additional rail commute trips will displace carpool trips atthe same rate thatthey displace single-occupancyvehicle trips The mathematical process by which this AVR adjustment was performedusing the Sacramento region as an example is illustrated in Figure 3 The predicted AVRs are incorporated into Table 17

17

r-

( )

( )

Figure 3 Process for calculating predicted regional AVR(Sacramento example)

Method labels values Notes and formula

Census data

Drove alone 0752

Carpooled 0049

All other 0200 ℎ

Rail (all forms) 0007

$ Included in

Sum of Census ldquostreet car or trolleycarrdquo ldquosubwayor elevatedrdquoand ldquorailroadrdquocategories

Carpool size 241

=

ℎ ℎ minus ℎ minus ℎ

CAPCOA Predicted rail 0197 Derived from dataset using formulas in Figure 2

Increase in rail 0190 Difference between ldquopredicted railrdquo and ldquorailrdquo categories

All other (predicted) 0321

ℎ Sum of ldquoall otherrdquo accounted with theldquorailrdquo increased number

Drove alone (predicted)

0587

Ratioof ldquodrove alonerdquo relative toldquocarpooledrdquo accountedwithldquoall other (predicted)rdquo increased value

= (1 minus ) lowast ( + )

Carpooled(predicted) 0092

Ratioof ldquocarpooledrdquo relative toldquodrove alonerdquo accountedwithldquoall other (predicted)rdquo increased value

= (1 minus ) lowast ( + )

Predicted AVR 1599 ℎ + +

+

Measured transportation usage

The measured data for this research are based onthe LEED-EBOM 2008and2009submittal data for the Sustainable Sites credit4 (SSc4)credit For each of the buildings considered the database provides the points for the SSc4credit which is associated with a percentage of

18

reduction in conventional trips Tables 10 and 11 provide the scales for the 2008 and 2009versions respectively of LEED-EBOM

Tables 10 and 11 Distribution of points for the SSc4 credit in LEED-EBOM versions 2008and2009

Demonstrated reduction in conventional

Points

commuting trips 10 1 25 2 50 3 75 4

Demonstrated reduction in conventional

Points

commuting trips 10 3

1375 4 1750 5 2125 6 25 7

3125 8 375 9 4375 10 50 11

5625 12 6250 13 6875 14 75 15

Table10 LEED EBOM v 2008 Table11 LEED EBOM v 2009

The ldquodemonstrated percentage reductioninconventional commutingrdquo used inthe LEED reporting isequivalent to the improvement in the reported AVR valuecompared totheLEED baseline of 10 (ie everyonecommutes bysingle-occupancyautomobiles)As a resultthe percentage reductions canbe directly converted to AVR values ie a 10 reduction of conventional tripswill resultsin an AVR of 11a20 reduction will result in an AVR of 12 and soon

Because only binned data are available the team assumed that each building actuallydemonstrateda percentage reductiononaverage 25 above the lower thresholdof the binprovided by the LEED rating system (see Table 12) Apossible alternative would be toassume that the actual AVRs are clustered around the midpoint of the range (ie 50 abovethe lower threshold)but the research team elected not to assume this for two reasonsFirst given the point-based incentives to reach each threshold it seemed more likely thatthe AVRs are notevenly distributed throughout each bin rangebut areinstead likelyclustered in the lower half of each bin range Second given the high GHG-intensity oftransportation the research team felt it important to be conservative inany assumptions about buildingperformance relative tobaseline and predicted values since small differences inassumptions couldresult inestimates of large but potentially illusory GHGsavings

19

Table 12 Assumed measured AVRs for each LEED-EBOM point binrsquos lower threshold

Demonstrated reduction in Assumedmeasured conventional AVR

commuting trips 10 1125

1375 1171875 1750 121875 2125 1265625 25 13125

3125 1390625 375 146875 4375 1546875 50 1625

5625 1703125 6250 178125 6875 1859375 75 19375

These measured AVR values were thenaveraged across buildings withineach regionto create a measured AVR value for the LEED-EBOM buildings withineach region that can be compared to the baseline and predicted AVRs

GHGintensity of transportation

The GHGintensity of each mode of travel expressed as pounds of CO2e emitted perpassenger mile traveled was obtained from the individual emissions calculator attravelmattersorgdeveloped by the Center for Neighborhood Technology for the Federal Transit Administration(Feigonet al 2003)This tool enables users to determine the per-mile emissions resulting fromtravel by various modes in locations aroundthe country including California Though they are state-specific the coefficientsare now overten yearsoldandtherefore donot reflect the gradual de-carbonization of fuel stocks resulting from the statersquosLow Carbon Fuel StandardandRenewable Portfolio Standard

For baselinevalues theGHG intensityof each regionrsquos AVR was determined bycreating anaverage of the GHG intensities of the modes used weighted by the proportion that eachmode was used in that region This yielded a GHG intensity for eachAVR expressedin pounds of CO2eper milecommuted This was then converted into metric tons of CO2eper 1000square feet per year of office buildingbyassumingatypical occupant loadingof 5occupants per 1000square feet (drawn from the 2010California Plumbing Code) atypicalcommuting distance of 12 miles each way or 24 miles per occupant per day (drawn fromfindings on average commute distance in ARB2012a and 2012b) and a typical workyearof 260days The same method was used for predicted AVRs except that theGHG intensityof the extra predicted rail trips was represented by the arithmetic average of the GHGintensities ofthe various rail modes (streetcar or trolley car subway or elevated and railroad)denominated in the ACS data

20

transit bicycling walking or other non-automobile modesFor this reason the predictedAVRs resulting from this method can be thought of as conservative ie closer to the regionalbaseline thanwouldbe expectedif all non-automobile modes were included in the analysis

Figure 2 Equations for calculating transit mode share as afunctionof distance of destination totransit

Distance to transit Transit mode share calculation equation (where x =distance of project to transit)

0ndash 05miles -50x +38 05to 3miles -44x +152 gt3miles noimpact

The research team identified the distance of each building inthe study dataset to the nearest rail stationusing Google Maps The distance betweenthe building and the rail station wasdefined asthe walking distance overthe street network and wasdetermined by activatingGoogle Mapsrsquo pedestrian walkingdirections function which indicates the totalwalking distance between two identified points The predictedrail transit mode share was then calculated for each building using the appropriate componentof the CAPCOA equation and the predicted rail transitmode shares for all buildings in a given region were then averaged

For eachregion the averaged predicted rail mode share was then used to modify thebaseline regional AVR For purposes of calculating AVR all non-automobile trips are equivalent becausetheydeliver a building occupant to thesitewithout theuseof a car Thethree components that matter for the calculation of AVRtherefore are the use of single-occupancyautomobiles the use of carpools andthe use of all other modes combined The third of these components was modified to reflect the additional rail trips predicted for thisset of buildings and the othertwo categoriesreduced proportionally to create a new AVR This method assumes thatthe additional rail commute trips will displace carpool trips atthe same rate thatthey displace single-occupancyvehicle trips The mathematical process by which this AVR adjustment was performedusing the Sacramento region as an example is illustrated in Figure 3 The predicted AVRs are incorporated into Table 17

17

r-

( )

( )

Figure 3 Process for calculating predicted regional AVR(Sacramento example)

Method labels values Notes and formula

Census data

Drove alone 0752

Carpooled 0049

All other 0200 ℎ

Rail (all forms) 0007

$ Included in

Sum of Census ldquostreet car or trolleycarrdquo ldquosubwayor elevatedrdquoand ldquorailroadrdquocategories

Carpool size 241

=

ℎ ℎ minus ℎ minus ℎ

CAPCOA Predicted rail 0197 Derived from dataset using formulas in Figure 2

Increase in rail 0190 Difference between ldquopredicted railrdquo and ldquorailrdquo categories

All other (predicted) 0321

ℎ Sum of ldquoall otherrdquo accounted with theldquorailrdquo increased number

Drove alone (predicted)

0587

Ratioof ldquodrove alonerdquo relative toldquocarpooledrdquo accountedwithldquoall other (predicted)rdquo increased value

= (1 minus ) lowast ( + )

Carpooled(predicted) 0092

Ratioof ldquocarpooledrdquo relative toldquodrove alonerdquo accountedwithldquoall other (predicted)rdquo increased value

= (1 minus ) lowast ( + )

Predicted AVR 1599 ℎ + +

+

Measured transportation usage

The measured data for this research are based onthe LEED-EBOM 2008and2009submittal data for the Sustainable Sites credit4 (SSc4)credit For each of the buildings considered the database provides the points for the SSc4credit which is associated with a percentage of

18

reduction in conventional trips Tables 10 and 11 provide the scales for the 2008 and 2009versions respectively of LEED-EBOM

Tables 10 and 11 Distribution of points for the SSc4 credit in LEED-EBOM versions 2008and2009

Demonstrated reduction in conventional

Points

commuting trips 10 1 25 2 50 3 75 4

Demonstrated reduction in conventional

Points

commuting trips 10 3

1375 4 1750 5 2125 6 25 7

3125 8 375 9 4375 10 50 11

5625 12 6250 13 6875 14 75 15

Table10 LEED EBOM v 2008 Table11 LEED EBOM v 2009

The ldquodemonstrated percentage reductioninconventional commutingrdquo used inthe LEED reporting isequivalent to the improvement in the reported AVR valuecompared totheLEED baseline of 10 (ie everyonecommutes bysingle-occupancyautomobiles)As a resultthe percentage reductions canbe directly converted to AVR values ie a 10 reduction of conventional tripswill resultsin an AVR of 11a20 reduction will result in an AVR of 12 and soon

Because only binned data are available the team assumed that each building actuallydemonstrateda percentage reductiononaverage 25 above the lower thresholdof the binprovided by the LEED rating system (see Table 12) Apossible alternative would be toassume that the actual AVRs are clustered around the midpoint of the range (ie 50 abovethe lower threshold)but the research team elected not to assume this for two reasonsFirst given the point-based incentives to reach each threshold it seemed more likely thatthe AVRs are notevenly distributed throughout each bin rangebut areinstead likelyclustered in the lower half of each bin range Second given the high GHG-intensity oftransportation the research team felt it important to be conservative inany assumptions about buildingperformance relative tobaseline and predicted values since small differences inassumptions couldresult inestimates of large but potentially illusory GHGsavings

19

Table 12 Assumed measured AVRs for each LEED-EBOM point binrsquos lower threshold

Demonstrated reduction in Assumedmeasured conventional AVR

commuting trips 10 1125

1375 1171875 1750 121875 2125 1265625 25 13125

3125 1390625 375 146875 4375 1546875 50 1625

5625 1703125 6250 178125 6875 1859375 75 19375

These measured AVR values were thenaveraged across buildings withineach regionto create a measured AVR value for the LEED-EBOM buildings withineach region that can be compared to the baseline and predicted AVRs

GHGintensity of transportation

The GHGintensity of each mode of travel expressed as pounds of CO2e emitted perpassenger mile traveled was obtained from the individual emissions calculator attravelmattersorgdeveloped by the Center for Neighborhood Technology for the Federal Transit Administration(Feigonet al 2003)This tool enables users to determine the per-mile emissions resulting fromtravel by various modes in locations aroundthe country including California Though they are state-specific the coefficientsare now overten yearsoldandtherefore donot reflect the gradual de-carbonization of fuel stocks resulting from the statersquosLow Carbon Fuel StandardandRenewable Portfolio Standard

For baselinevalues theGHG intensityof each regionrsquos AVR was determined bycreating anaverage of the GHG intensities of the modes used weighted by the proportion that eachmode was used in that region This yielded a GHG intensity for eachAVR expressedin pounds of CO2eper milecommuted This was then converted into metric tons of CO2eper 1000square feet per year of office buildingbyassumingatypical occupant loadingof 5occupants per 1000square feet (drawn from the 2010California Plumbing Code) atypicalcommuting distance of 12 miles each way or 24 miles per occupant per day (drawn fromfindings on average commute distance in ARB2012a and 2012b) and a typical workyearof 260days The same method was used for predicted AVRs except that theGHG intensityof the extra predicted rail trips was represented by the arithmetic average of the GHGintensities ofthe various rail modes (streetcar or trolley car subway or elevated and railroad)denominated in the ACS data

20

r-

( )

( )

Figure 3 Process for calculating predicted regional AVR(Sacramento example)

Method labels values Notes and formula

Census data

Drove alone 0752

Carpooled 0049

All other 0200 ℎ

Rail (all forms) 0007

$ Included in

Sum of Census ldquostreet car or trolleycarrdquo ldquosubwayor elevatedrdquoand ldquorailroadrdquocategories

Carpool size 241

=

ℎ ℎ minus ℎ minus ℎ

CAPCOA Predicted rail 0197 Derived from dataset using formulas in Figure 2

Increase in rail 0190 Difference between ldquopredicted railrdquo and ldquorailrdquo categories

All other (predicted) 0321

ℎ Sum of ldquoall otherrdquo accounted with theldquorailrdquo increased number

Drove alone (predicted)

0587

Ratioof ldquodrove alonerdquo relative toldquocarpooledrdquo accountedwithldquoall other (predicted)rdquo increased value

= (1 minus ) lowast ( + )

Carpooled(predicted) 0092

Ratioof ldquocarpooledrdquo relative toldquodrove alonerdquo accountedwithldquoall other (predicted)rdquo increased value

= (1 minus ) lowast ( + )

Predicted AVR 1599 ℎ + +

+

Measured transportation usage

The measured data for this research are based onthe LEED-EBOM 2008and2009submittal data for the Sustainable Sites credit4 (SSc4)credit For each of the buildings considered the database provides the points for the SSc4credit which is associated with a percentage of

18

reduction in conventional trips Tables 10 and 11 provide the scales for the 2008 and 2009versions respectively of LEED-EBOM

Tables 10 and 11 Distribution of points for the SSc4 credit in LEED-EBOM versions 2008and2009

Demonstrated reduction in conventional

Points

commuting trips 10 1 25 2 50 3 75 4

Demonstrated reduction in conventional

Points

commuting trips 10 3

1375 4 1750 5 2125 6 25 7

3125 8 375 9 4375 10 50 11

5625 12 6250 13 6875 14 75 15

Table10 LEED EBOM v 2008 Table11 LEED EBOM v 2009

The ldquodemonstrated percentage reductioninconventional commutingrdquo used inthe LEED reporting isequivalent to the improvement in the reported AVR valuecompared totheLEED baseline of 10 (ie everyonecommutes bysingle-occupancyautomobiles)As a resultthe percentage reductions canbe directly converted to AVR values ie a 10 reduction of conventional tripswill resultsin an AVR of 11a20 reduction will result in an AVR of 12 and soon

Because only binned data are available the team assumed that each building actuallydemonstrateda percentage reductiononaverage 25 above the lower thresholdof the binprovided by the LEED rating system (see Table 12) Apossible alternative would be toassume that the actual AVRs are clustered around the midpoint of the range (ie 50 abovethe lower threshold)but the research team elected not to assume this for two reasonsFirst given the point-based incentives to reach each threshold it seemed more likely thatthe AVRs are notevenly distributed throughout each bin rangebut areinstead likelyclustered in the lower half of each bin range Second given the high GHG-intensity oftransportation the research team felt it important to be conservative inany assumptions about buildingperformance relative tobaseline and predicted values since small differences inassumptions couldresult inestimates of large but potentially illusory GHGsavings

19

Table 12 Assumed measured AVRs for each LEED-EBOM point binrsquos lower threshold

Demonstrated reduction in Assumedmeasured conventional AVR

commuting trips 10 1125

1375 1171875 1750 121875 2125 1265625 25 13125

3125 1390625 375 146875 4375 1546875 50 1625

5625 1703125 6250 178125 6875 1859375 75 19375

These measured AVR values were thenaveraged across buildings withineach regionto create a measured AVR value for the LEED-EBOM buildings withineach region that can be compared to the baseline and predicted AVRs

GHGintensity of transportation

The GHGintensity of each mode of travel expressed as pounds of CO2e emitted perpassenger mile traveled was obtained from the individual emissions calculator attravelmattersorgdeveloped by the Center for Neighborhood Technology for the Federal Transit Administration(Feigonet al 2003)This tool enables users to determine the per-mile emissions resulting fromtravel by various modes in locations aroundthe country including California Though they are state-specific the coefficientsare now overten yearsoldandtherefore donot reflect the gradual de-carbonization of fuel stocks resulting from the statersquosLow Carbon Fuel StandardandRenewable Portfolio Standard

For baselinevalues theGHG intensityof each regionrsquos AVR was determined bycreating anaverage of the GHG intensities of the modes used weighted by the proportion that eachmode was used in that region This yielded a GHG intensity for eachAVR expressedin pounds of CO2eper milecommuted This was then converted into metric tons of CO2eper 1000square feet per year of office buildingbyassumingatypical occupant loadingof 5occupants per 1000square feet (drawn from the 2010California Plumbing Code) atypicalcommuting distance of 12 miles each way or 24 miles per occupant per day (drawn fromfindings on average commute distance in ARB2012a and 2012b) and a typical workyearof 260days The same method was used for predicted AVRs except that theGHG intensityof the extra predicted rail trips was represented by the arithmetic average of the GHGintensities ofthe various rail modes (streetcar or trolley car subway or elevated and railroad)denominated in the ACS data

20

reduction in conventional trips Tables 10 and 11 provide the scales for the 2008 and 2009versions respectively of LEED-EBOM

Tables 10 and 11 Distribution of points for the SSc4 credit in LEED-EBOM versions 2008and2009

Demonstrated reduction in conventional

Points

commuting trips 10 1 25 2 50 3 75 4

Demonstrated reduction in conventional

Points

commuting trips 10 3

1375 4 1750 5 2125 6 25 7

3125 8 375 9 4375 10 50 11

5625 12 6250 13 6875 14 75 15

Table10 LEED EBOM v 2008 Table11 LEED EBOM v 2009

The ldquodemonstrated percentage reductioninconventional commutingrdquo used inthe LEED reporting isequivalent to the improvement in the reported AVR valuecompared totheLEED baseline of 10 (ie everyonecommutes bysingle-occupancyautomobiles)As a resultthe percentage reductions canbe directly converted to AVR values ie a 10 reduction of conventional tripswill resultsin an AVR of 11a20 reduction will result in an AVR of 12 and soon

Because only binned data are available the team assumed that each building actuallydemonstrateda percentage reductiononaverage 25 above the lower thresholdof the binprovided by the LEED rating system (see Table 12) Apossible alternative would be toassume that the actual AVRs are clustered around the midpoint of the range (ie 50 abovethe lower threshold)but the research team elected not to assume this for two reasonsFirst given the point-based incentives to reach each threshold it seemed more likely thatthe AVRs are notevenly distributed throughout each bin rangebut areinstead likelyclustered in the lower half of each bin range Second given the high GHG-intensity oftransportation the research team felt it important to be conservative inany assumptions about buildingperformance relative tobaseline and predicted values since small differences inassumptions couldresult inestimates of large but potentially illusory GHGsavings

19

Table 12 Assumed measured AVRs for each LEED-EBOM point binrsquos lower threshold

Demonstrated reduction in Assumedmeasured conventional AVR

commuting trips 10 1125

1375 1171875 1750 121875 2125 1265625 25 13125

3125 1390625 375 146875 4375 1546875 50 1625

5625 1703125 6250 178125 6875 1859375 75 19375

These measured AVR values were thenaveraged across buildings withineach regionto create a measured AVR value for the LEED-EBOM buildings withineach region that can be compared to the baseline and predicted AVRs

GHGintensity of transportation

The GHGintensity of each mode of travel expressed as pounds of CO2e emitted perpassenger mile traveled was obtained from the individual emissions calculator attravelmattersorgdeveloped by the Center for Neighborhood Technology for the Federal Transit Administration(Feigonet al 2003)This tool enables users to determine the per-mile emissions resulting fromtravel by various modes in locations aroundthe country including California Though they are state-specific the coefficientsare now overten yearsoldandtherefore donot reflect the gradual de-carbonization of fuel stocks resulting from the statersquosLow Carbon Fuel StandardandRenewable Portfolio Standard

For baselinevalues theGHG intensityof each regionrsquos AVR was determined bycreating anaverage of the GHG intensities of the modes used weighted by the proportion that eachmode was used in that region This yielded a GHG intensity for eachAVR expressedin pounds of CO2eper milecommuted This was then converted into metric tons of CO2eper 1000square feet per year of office buildingbyassumingatypical occupant loadingof 5occupants per 1000square feet (drawn from the 2010California Plumbing Code) atypicalcommuting distance of 12 miles each way or 24 miles per occupant per day (drawn fromfindings on average commute distance in ARB2012a and 2012b) and a typical workyearof 260days The same method was used for predicted AVRs except that theGHG intensityof the extra predicted rail trips was represented by the arithmetic average of the GHGintensities ofthe various rail modes (streetcar or trolley car subway or elevated and railroad)denominated in the ACS data

20

Table 12 Assumed measured AVRs for each LEED-EBOM point binrsquos lower threshold

Demonstrated reduction in Assumedmeasured conventional AVR

commuting trips 10 1125

1375 1171875 1750 121875 2125 1265625 25 13125

3125 1390625 375 146875 4375 1546875 50 1625

5625 1703125 6250 178125 6875 1859375 75 19375

These measured AVR values were thenaveraged across buildings withineach regionto create a measured AVR value for the LEED-EBOM buildings withineach region that can be compared to the baseline and predicted AVRs

GHGintensity of transportation

The GHGintensity of each mode of travel expressed as pounds of CO2e emitted perpassenger mile traveled was obtained from the individual emissions calculator attravelmattersorgdeveloped by the Center for Neighborhood Technology for the Federal Transit Administration(Feigonet al 2003)This tool enables users to determine the per-mile emissions resulting fromtravel by various modes in locations aroundthe country including California Though they are state-specific the coefficientsare now overten yearsoldandtherefore donot reflect the gradual de-carbonization of fuel stocks resulting from the statersquosLow Carbon Fuel StandardandRenewable Portfolio Standard

For baselinevalues theGHG intensityof each regionrsquos AVR was determined bycreating anaverage of the GHG intensities of the modes used weighted by the proportion that eachmode was used in that region This yielded a GHG intensity for eachAVR expressedin pounds of CO2eper milecommuted This was then converted into metric tons of CO2eper 1000square feet per year of office buildingbyassumingatypical occupant loadingof 5occupants per 1000square feet (drawn from the 2010California Plumbing Code) atypicalcommuting distance of 12 miles each way or 24 miles per occupant per day (drawn fromfindings on average commute distance in ARB2012a and 2012b) and a typical workyearof 260days The same method was used for predicted AVRs except that theGHG intensityof the extra predicted rail trips was represented by the arithmetic average of the GHGintensities ofthe various rail modes (streetcar or trolley car subway or elevated and railroad)denominated in the ACS data

20

For measuredAVR data the methodwas somewhat different because the measureddatadoes not containany breakdownof the means of transportationtoworkfor eachbuilding All non-automobile trips are equivalent with respect to AVRbut do not have the same GHGfootprint so it is necessary to assume something about the proportion ofnon-automobile trips taken by various modes (rail bus bicyclingwalkingetc) Because the measured AVRs are fairly similar to the baseline AVRs and there is noother reasonto assume dramatic differences inthe selectionof travel modes the researchteam assumedthat the proportional distributionof non-automobile trips in the measured AVR was the same as theACS data that formed the basis for the baseline AVR With respect to car drivers theresearch team also assumed that the relative proportionsof people driving alone andcarpooling are the same for the measured AVR as for the baseline AVRs

After adjusting the number of employees driving alone or carpooling and keeping thedistributionfor the other means of transportations identical tothe baseline AVR the GHG emissions in metric tons of CO2eper 1000 squarefeet per year was calculated with thesame method used forthe baseline and predicted AVRs

21

Results

The resultsof ouranalysisare shown in Tables13to 19The results for all three resource areas are expressed in units of metric tons of carbon dioxide-equivalent per 1000 squarefeet ofcommercialoffice space per year (MTCO2e1000sfyr) This normalization enablescomparison of the three resource areas to one another and also facilitates expression of theresultsin termsof the emissionssavingsachievable per office building types or per the entirecommercial officebuilding stock of California

Water

Table 13 showswaterresultsforindoorusage irrigation usage and cooling towerusage independently as well as whole-building usage (which is the sum of these) Two regionsthe Bay Area and Los Angeles have enough buildings in the sample to enable them to beexamined independentlyof theset as a whole The191 LEED-EBOM buildings inthe dataset ingeneral show noteworthy reductions of water usage from bothbaseline andpredicted valuesTotal building usage for the entire dataset was measured at 485galsfyr about 55 below the baseline of 1082galsfyr andabout 27 below the predicted value of 666 galsfyrThe GHG emissions improvements vary from the usage improvements because the GHG intensity ofwater varies both regionally and depending onthe use of the water (indoor usage includes energy expenditure for heating and sewagetreatment whereas outdoor usage does not) The GHG emissions reductions for total building water usage are 50 comparedtobaseline and13compared to predictionNotably these values are substantially better for 63 buildings in the LA region than for the89buildings inthe Bay Area where water-related GHG emissions are actually 16higher for the measured values than the predicted values

For indoor use measured values for BayArea LEED-EBOM buildings (295 galsfyr)exceed the predicted value of 231galsfyrand as a result pull the statewide result up to 235 galsfyr alsoabove the predicted value Indoor usage in the LA EBOM buildings bycontrast is considerably lower at only 142galsfyr

Irrigation usage for both predicted and measured values is considerably lower than thebaseline of 311 galsfyr (Irrigationvalues are expressed per square foot of building ratherthan persquare foot ofirrigated area to maintain comparability with indoor and cooling tower usage) Measured irrigation usage among Los Angeles EBOM buildings exceeds thepredicted valueof 89 galsfyr while both Bay Area EBOM buildings and thedataset as a whole used 106 galsfyr for irrigation as compared to predicted values of 81and 86 galsfyr respectively

Cooling tower usage in bothregions andstatewide is alsoconsiderably lower than the baseline and predicted value of 349 galsfyr The 43 LA-region buildingsin the dataset measuring cooling tower use reported only 54 galsfyr 85 below baseline andprediction while Bay Area EBOM buildings were at 233 galsfyr still 33 below baselineand prediction This over-performance incooling tower usage relative toprediction outweighs the under-performance inindoor and irrigationusage to yield total building measured values that are better than prediction

The water results also include analysis of the effect of the EBOM performance credit forextra-efficient indoor water usage (see Table 14)The 71 buildingsachieving thiscredit

22

Tableamp13ampWaterampU

sageampandampAssociatedampGHGampEmissionsampinampCAampCertifiedampGreenampO

fficeampBuildings

N

Baseline Predicted

Measured

Waterampuse

GHGampemissions

Waterampuse

GHGampemissions

Waterampuse

GHGampemissions

galsfyr ampM

TampCO2e1000sfyr

galsfyr ampM

TampCO2e1000sfyr

galsfyr ampM

TampCO2e1000sfyr

Usageampim

provements

Base0Measure

Pred0Measure

Indoorampusage 191

421 0106

231 0058

235 Bay$Area

89 421

0100 231

0055 295

LA$region 63

421 0119

231 0066

142

Irrigationampusage 95

311 0021

86 0006

106 Bay$Area

35 311

0015 81

0004 106

LA$region 37

311 0029

89 0008

131

Coolingamptowerampusage

117 349

0023 349

0023 144

Bay$Area 61

349 0017

349 0017

233 LA$region

43 349

0033 349

0033 54

Totalampbuildingampusage 191

1082 0149

666 0086

485 Bay$Area

89 1082

0132 661

0075 634

LA$region 63

1082 0181

669 0106

327

Tableamp14ampampAnalysisampofampBuildingsampEarningampLEED9EBOMampW

aterampPerformanceampCredit

IndoorampPerfampCreditamp(W2)ampBldgs

Non9PerfampCreditampBldgs

N

Wateruse

GHGemissions

N

Wateruse

GHGemissions

galsfyr M

TCO2e1000sfyr

galsfyr M

TCO2e1000sfyr

Indoorusage 71

123 0019

115 304

0048

Irrigationusage 35

74 0012

55 125

0020

Coolingtowerusage

39 115

0018 75

163 0025

Totalampbuildingampusage 71

312 0046

115 592

0092

Bay$Area 34

363 0050

55 802

0110

Los$Angeles 20

162 0029

41 406

0071

0060 0070 0040

0008 0005 0012

0008 0011 0005

0075 0087 0058

GHGampimprovem

ents Base0M

easure Pred0M

easure

43

03

30

327

66

39

62

033

67

325

59

350

0 65

3

35

3 85

50

13

34

316

68

45

44

30

66

66

66

58

59

33

85

55

41

70

02

328

39

023

331

347

59

33

85

27

4

51

UsageampIm

provements

Nonperf2Perf

Pred2Perf

60

47

41

14

29

67

47

53

55

45

60

76

GHGampImprovem

ents Nonperf2Perf

Pred2Perf

60

67

40

40

28

22

50

53

55

33

59

80

Results

The resultsof ouranalysisare shown in Tables13to 19The results for all three resource areas are expressed in units of metric tons of carbon dioxide-equivalent per 1000 squarefeet ofcommercialoffice space per year (MTCO2e1000sfyr) This normalization enablescomparison of the three resource areas to one another and also facilitates expression of theresultsin termsof the emissionssavingsachievable per office building types or per the entirecommercial officebuilding stock of California

Water

Table 13 showswaterresultsforindoorusage irrigation usage and cooling towerusage independently as well as whole-building usage (which is the sum of these) Two regionsthe Bay Area and Los Angeles have enough buildings in the sample to enable them to beexamined independentlyof theset as a whole The191 LEED-EBOM buildings inthe dataset ingeneral show noteworthy reductions of water usage from bothbaseline andpredicted valuesTotal building usage for the entire dataset was measured at 485galsfyr about 55 below the baseline of 1082galsfyr andabout 27 below the predicted value of 666 galsfyrThe GHG emissions improvements vary from the usage improvements because the GHG intensity ofwater varies both regionally and depending onthe use of the water (indoor usage includes energy expenditure for heating and sewagetreatment whereas outdoor usage does not) The GHG emissions reductions for total building water usage are 50 comparedtobaseline and13compared to predictionNotably these values are substantially better for 63 buildings in the LA region than for the89buildings inthe Bay Area where water-related GHG emissions are actually 16higher for the measured values than the predicted values

For indoor use measured values for BayArea LEED-EBOM buildings (295 galsfyr)exceed the predicted value of 231galsfyrand as a result pull the statewide result up to 235 galsfyr alsoabove the predicted value Indoor usage in the LA EBOM buildings bycontrast is considerably lower at only 142galsfyr

Irrigation usage for both predicted and measured values is considerably lower than thebaseline of 311 galsfyr (Irrigationvalues are expressed per square foot of building ratherthan persquare foot ofirrigated area to maintain comparability with indoor and cooling tower usage) Measured irrigation usage among Los Angeles EBOM buildings exceeds thepredicted valueof 89 galsfyr while both Bay Area EBOM buildings and thedataset as a whole used 106 galsfyr for irrigation as compared to predicted values of 81and 86 galsfyr respectively

Cooling tower usage in bothregions andstatewide is alsoconsiderably lower than the baseline and predicted value of 349 galsfyr The 43 LA-region buildingsin the dataset measuring cooling tower use reported only 54 galsfyr 85 below baseline andprediction while Bay Area EBOM buildings were at 233 galsfyr still 33 below baselineand prediction This over-performance incooling tower usage relative toprediction outweighs the under-performance inindoor and irrigationusage to yield total building measured values that are better than prediction

The water results also include analysis of the effect of the EBOM performance credit forextra-efficient indoor water usage (see Table 14)The 71 buildingsachieving thiscredit

22

Tableamp13ampWaterampU

sageampandampAssociatedampGHGampEmissionsampinampCAampCertifiedampGreenampO

fficeampBuildings

N

Baseline Predicted

Measured

Waterampuse

GHGampemissions

Waterampuse

GHGampemissions

Waterampuse

GHGampemissions

galsfyr ampM

TampCO2e1000sfyr

galsfyr ampM

TampCO2e1000sfyr

galsfyr ampM

TampCO2e1000sfyr

Usageampim

provements

Base0Measure

Pred0Measure

Indoorampusage 191

421 0106

231 0058

235 Bay$Area

89 421

0100 231

0055 295

LA$region 63

421 0119

231 0066

142

Irrigationampusage 95

311 0021

86 0006

106 Bay$Area

35 311

0015 81

0004 106

LA$region 37

311 0029

89 0008

131

Coolingamptowerampusage

117 349

0023 349

0023 144

Bay$Area 61

349 0017

349 0017

233 LA$region

43 349

0033 349

0033 54

Totalampbuildingampusage 191

1082 0149

666 0086

485 Bay$Area

89 1082

0132 661

0075 634

LA$region 63

1082 0181

669 0106

327

Tableamp14ampampAnalysisampofampBuildingsampEarningampLEED9EBOMampW

aterampPerformanceampCredit

IndoorampPerfampCreditamp(W2)ampBldgs

Non9PerfampCreditampBldgs

N

Wateruse

GHGemissions

N

Wateruse

GHGemissions

galsfyr M

TCO2e1000sfyr

galsfyr M

TCO2e1000sfyr

Indoorusage 71

123 0019

115 304

0048

Irrigationusage 35

74 0012

55 125

0020

Coolingtowerusage

39 115

0018 75

163 0025

Totalampbuildingampusage 71

312 0046

115 592

0092

Bay$Area 34

363 0050

55 802

0110

Los$Angeles 20

162 0029

41 406

0071

0060 0070 0040

0008 0005 0012

0008 0011 0005

0075 0087 0058

GHGampimprovem

ents Base0M

easure Pred0M

easure

43

03

30

327

66

39

62

033

67

325

59

350

0 65

3

35

3 85

50

13

34

316

68

45

44

30

66

66

66

58

59

33

85

55

41

70

02

328

39

023

331

347

59

33

85

27

4

51

UsageampIm

provements

Nonperf2Perf

Pred2Perf

60

47

41

14

29

67

47

53

55

45

60

76

GHGampImprovem

ents Nonperf2Perf

Pred2Perf

60

67

40

40

28

22

50

53

55

33

59

80

Tableamp13ampWaterampU

sageampandampAssociatedampGHGampEmissionsampinampCAampCertifiedampGreenampO

fficeampBuildings

N

Baseline Predicted

Measured

Waterampuse

GHGampemissions

Waterampuse

GHGampemissions

Waterampuse

GHGampemissions

galsfyr ampM

TampCO2e1000sfyr

galsfyr ampM

TampCO2e1000sfyr

galsfyr ampM

TampCO2e1000sfyr

Usageampim

provements

Base0Measure

Pred0Measure

Indoorampusage 191

421 0106

231 0058

235 Bay$Area

89 421

0100 231

0055 295

LA$region 63

421 0119

231 0066

142

Irrigationampusage 95

311 0021

86 0006

106 Bay$Area

35 311

0015 81

0004 106

LA$region 37

311 0029

89 0008

131

Coolingamptowerampusage

117 349

0023 349

0023 144

Bay$Area 61

349 0017

349 0017

233 LA$region

43 349

0033 349

0033 54

Totalampbuildingampusage 191

1082 0149

666 0086

485 Bay$Area

89 1082

0132 661

0075 634

LA$region 63

1082 0181

669 0106

327

Tableamp14ampampAnalysisampofampBuildingsampEarningampLEED9EBOMampW

aterampPerformanceampCredit

IndoorampPerfampCreditamp(W2)ampBldgs

Non9PerfampCreditampBldgs

N

Wateruse

GHGemissions

N

Wateruse

GHGemissions

galsfyr M

TCO2e1000sfyr

galsfyr M

TCO2e1000sfyr

Indoorusage 71

123 0019

115 304

0048

Irrigationusage 35

74 0012

55 125

0020

Coolingtowerusage

39 115

0018 75

163 0025

Totalampbuildingampusage 71

312 0046

115 592

0092

Bay$Area 34

363 0050

55 802

0110

Los$Angeles 20

162 0029

41 406

0071

0060 0070 0040

0008 0005 0012

0008 0011 0005

0075 0087 0058

GHGampimprovem

ents Base0M

easure Pred0M

easure

43

03

30

327

66

39

62

033

67

325

59

350

0 65

3

35

3 85

50

13

34

316

68

45

44

30

66

66

66

58

59

33

85

55

41

70

02

328

39

023

331

347

59

33

85

27

4

51

UsageampIm

provements

Nonperf2Perf

Pred2Perf

60

47

41

14

29

67

47

53

55

45

60

76

GHGampImprovem

ents Nonperf2Perf

Pred2Perf

60

67

40

40

28

22

50

53

55

33

59

80

Tableamp15ampSolidampW

asteampDisposalampRatesampandampAssociatedampGHGampEmissionsampinampCAampCertifiedampGreenampO

fficeampBuildings

N

Totalampbuildingampusage 233

Bay$Area 105

LA$region 74

Baseline Diversion

Disposal GHGem

issions

MTCO

2e1000sfyr

7

93

0079 7

93

0079

7

93

0079

Predicted Diversion

Disposal GHGem

issions

MTCO

2e1000sfyr

50

50

0043 50

50

0043

50

50

0043

Measured

Diversion Disposal

GHGemissions

MTCO

2e1000sfyr

52

48

0041 53

47

0040

53

47

0040

Usageampim

provements

Base1Measure

Pred1Measure

48

4

49

6

49

6

GHGampimprovem

ents Base1M

easure Pred1M

easure

48

4

49

6

49

6

Tableamp16ampampAnalysisampofampBuildingsampEarningampLEED9EBOMampSolidampW

asteampPerformanceampCredit

WasteampPerfamp(M

Rc7)ampBuildings Non9PerfampCreditampBldgs

UsageampIm

provements

GHGampImprovem

ents N

Diversion

Disposal GHGem

issions N

Diversion

Disposal GHGem

issions Nonperf2Perf

Pred2Perf Nonperf2Perf

Pred2Perf

MTCO

2e1000sfyr M

TCO2e1000sfyr

Totalampbuildingampusage 144

65

35

0030 84

39

61

0052 43

30

43

30

used 312galsfyr animprovement of 47 over the 115EBOM buildings that didnot earnthe credit As would be expected these improvements were most pronouncedfor indoor usage (60) but are also sizable for irrigationand cooling tower usage (41 and 29respectively) Notably the EBOM rating systems of 2008and2009onlyawarded points for reductionsof upto 30 for indoor usage compared to the minimum level that all certifiedEBOM buildings are required to achieve Hence the observed performance gap betweenbuildings earning the indoor efficiency credit and those not earning it is considerably largerthan one would expect from the EBOM rating system itself

Comparing Tables 14 and 13 it is noteworthy that the EBOM buildings not earning theindoor performance credit underperform the predicted valuefor indoor usage(304 galsfyr compared to231 galsfyr) but still outperform the baseline value of421 galsfyrThey alsounderperform the predicted irrigation usage(125 galsfyr compared to 86 galsfyr)but because they substantially outperform the predicted value for cooling tower usage the total building usage for these buildings is still betterthan prediction (592 galsfyr compared to666 galsfyr)and significantly better than the baseline of 1082 galsfyr

Waste

Table 15 showsdetailedresultsforwaste diversion ratesforthe statewide EBOM dataset as well as the BayArea and LA regions Asnoted in the methodssection the baseline predicted and measured values inquestionare the diversion ratesforsolid waste (ie thepercentage of solid waste sent to landfill as opposed to recycling or compost) assuming agiven rate of generation of solid waste (1998 pounds1000sfyr) Hence higher diversionratesare betterfrom the point of view of GHG emissions

Statewide the EBOM buildings achieve adiversionrate of 52 compared to the baseline rate of 7and predicted rateof 50 BecausetheGHG impact is calculated from the disposal rate (the inverse of the diversionrate) these figures represent a 48 and4 improvement over baseline and prediction respectivelyThe EBOM buildings of the Bay Area and LAregionshappen to achieve the same diversionrate of 53 approximately the same asthe state asa whole

The LEED-EBOM rating system alsocontains aperformance credit for improved wastediversion rates thatrequires among other things that50 of ldquoongoing consumablesrdquo (as opposedtoconstruction waste or other forms of solidwaste) bereused recycled or composted equivalent to a diversion rate of 50The buildings earning this credit actuallyachieved diversionrates of 65 comparedto39for the EBOM buildings not earning the credit (see Table 16) As with the performance credit for water the observed performance of buildings achievingthis credit exceeds what one would expect from the EBOM ratingsystem itself In addition even the buildings notseeking theperformancecredit significantly outperform the baseline diversion rate of 7

Transportation

The detailed results of the transportation analysis are shown in Table 17As noted previously the unit of analysis is Average Vehicle Rideship(AVR) essentially a ratio of the number of employees ina givenoffice building andthe number of cars it takes to bring

25

Tableamp17ampTransporta

tionampRatesampa

ndampAsso

ciatedampGHGampEmissio

nsampin

ampCAampCertifie

dampGreenampOffice

ampBuild

ings

N

Totalampbuild

ingampusage

196

Bay$Area 99

LA$region 54

Baselin

e AVR

GHGampemissions

ampMTampCO

2e1000sfyr

132

1360

139 1317

126 1411

Predicte

d AVR

GHGampemissions

ampMTampCO

2e1000sfyr

154

1220

160 1192

141 1288

Measured

AVR GHGampem

issions ampM

TampCO2e1000sfyr

140

1299

151 1217

128 1386

UsageampIm

provements

BaseMeasure

PredMeasure

5

H11

8

36

2

310

GHGampIm

provements

BaseMeasure

PredMeasure

5

H6

8

32

2

38

Tableamp18ampSummaryampofampGHGampEm

issionsampRatesampfromampW

aterampWasteampandampTransportationampinampCAampCertifiedampGreenampO

fficeampBuildings

N

Baseline Predicted

Measured

HiFPerformance

GHGemissions

GHGemissions

GHGemissions

GHGemissions

MTCO

2e1000sfyr M

TCO2e1000sfyr

MTCO

2e1000sfyr M

TCO2e1000sfyr

Water

191 0149

0086 0075

0046 Waste

233 0079

0043 0041

0030 Transportation

196 13605

12204 12988

Operationalenergy(forcom

parison) 5289

GHGampImprovem

ents BaseM

easure PredM

easure BaseHiPerf

50

13

69

48

4

62

5

6

Tableamp17ampTransporta

tionampRatesampa

ndampAsso

ciatedampGHGampEmissio

nsampin

ampCAampCertifie

dampGreenampOffice

ampBuild

ings

N

Totalampbuild

ingampusage

196

Bay$Area 99

LA$region 54

Baselin

e AVR

GHGampemissions

ampMTampCO

2e1000sfyr

132

1360

139 1317

126 1411

Predicte

d AVR

GHGampemissions

ampMTampCO

2e1000sfyr

154

1220

160 1192

141 1288

Measured

AVR GHGampem

issions ampM

TampCO2e1000sfyr

140

1299

151 1217

128 1386

UsageampIm

provements

BaseMeasure

PredMeasure

5

H11

8

36

2

310

GHGampIm

provements

BaseMeasure

PredMeasure

5

H6

8

32

2

38

Tableamp18ampSummaryampofampGHGampEm

issionsampRatesampfromampW

aterampWasteampandampTransportationampinampCAampCertifiedampGreenampO

fficeampBuildings

N

Baseline Predicted

Measured

HiFPerformance

GHGemissions

GHGemissions

GHGemissions

GHGemissions

MTCO

2e1000sfyr M

TCO2e1000sfyr

MTCO

2e1000sfyr M

TCO2e1000sfyr

Water

191 0149

0086 0075

0046 Waste

233 0079

0043 0041

0030 Transportation

196 13605

12204 12988

Operationalenergy(forcom

parison) 5289

GHGampImprovem

ents BaseM

easure PredM

easure BaseHiPerf

50

13

69

48

4

62

5

6

them to work on a given workday A higher AVR indicates a higher employeendashto-car ratio with lower GHG impacts

The measured AVR value for the EBOM dataset as a whole is 140 a 5 improvement overthe baseline of 132 but 11 below (worse than)the predicted AVR of 154 generated byobservingthe distance torail transit for eachbuildingandapplyingthe CAPCOA formulafor mode share (see methodssection fordetail) The GHGemissions impacts of these buildingsrsquo transportation patterns were only6below (worse than) prediction however given theregional distribution of the mode shifts

The measured AVR value for Bay Area EBOM buildings is 1518 above the baseline and 6 below prediction(2 below for GHGs) For the LA region measured AVR for the EBOMbuildings was 2 above baseline but 10 below prediction (8 below for GHGs) There is no additional credit inLEED-EBOM for transportation behavior beyond the one from whichthis AVR data was drawn so no supplementary analysis akin to that performed for waterand waste performance credits was possible

Table 18 shows a summary of the statewide results from all three resource areas A baseline values for operational energy derived from the CaliforniaCommercial End-Use Study(CEUS) is shown forthe sake of comparison (Itron 2006) This figure was derived by applyingthe same estimate of the statewide marginal GHG intensity of electricitydescribedin the water methods section as well as the EPA (2014) estimatefor theGHG intensityof natural gas to the per-square-foot energy consumption data compiled by CEUS forCalifornia office buildings

Total emissions comparisons

Table 19 showsthe levelsof GHG emissionsand potential emissionssavingsthat might be expected from typical commercial officebuildings of various sizesand Californiarsquos office building stockas a whole from these three resource areas These comparisons relyon an implicit assumption that all commercial office buildingsas a whole could attainperformance comparable to the LEED-EBOM buildings studied here While not all existing buildings could meet such standards individuallyothers could significantly exceed them under the right code requirements This extrapolationis meant simply to illustrate theapproximate potential of the commercial office building sector to avoid GHG emissions fromthese three resource areas and tooffer insight intothe role that commercial office buildingscould play in GHG control efforts in California (See the discussion section below formore detail)

The 2006 CEUS study sample selectedtobe statistically representative of Californiarsquos office building stock had an average building size of 12968 sf A building that size using typicalconstruction could be expected to trigger emissions of 193 MTCO2eyr from water use 103 MTCO2e yr from solid waste 17642 MTCO2eyr from transportation A LEED-EBOM building of that size however wouldreap emissions savings of 096 MTCO2e yr from water use efficiency 050 MTCO2e yr from solid waste and 800 MTCO2e yr from transportation compared to that typical construction

The emissions levels expected from office buildings ofvarious sizes scale upward linearly Potential savings from a large urbanhigh-rise office building of 500000 sf(about 32 stories) would be 3700 MTCO2e yr from water 1913 MTCO2e yr from solid waste and

27

Tableamp19ampSummaryampofampGHGampEm

issionsampCo8BenefitsampfromampW

aterampWasteampandampTransportationampinampCAampO

fficeampBuildings

AllfiguresinMTCO

2eyr

Baseline

Predicted Measured

Hi8Performance

Emissions

Emissions

Emissions

Emissions

PotentialampGHGampImprovem

ents Base5M

easure Pred5M

easure Base5HiPerf

Averageampofficeampbuilding(12968sf)

Water

Waste

Transportation

193

112

097

060

103

055

053

039

17642 15826

16843

096 014

134 050

002 064

800 (1017)

Largeampofficeampbuilding(100000sf)

Water

Waste

Transportation

1490

860

750

460

791

425

408

298 136045

122038 129878

740 110

1030 383

017 493

6167 (7841)

High8riseampofficeampbuilding(500000sf~32stories)

Water

Waste

Transportation

7450 4300

3750 2300

3953 2125

2040 1488

680226 610189

649392

3700 550

5150 1913

085 2465

30835 (39203)

AllampCAampofficeampbuildings(114billionsf)

Water

Waste

Transportation Total

16986000 9804000

8550000 5244000

9011700 4845000

4651200 3391500

1550915925 1391230364

1480613250 ampampampampampampampamp1576913625

ampampampampampampampamp1405879364 ampampampampampampampamp1493814450

ampampampampampampampamp1489248750

8436000 1254000

11742000 4360500

193800 5620200

70302675 (89382886)

ampampampampampamp83099175 ampampampampamp(87935086)

ampampampampampamp87664875

Tableamp19ampSummaryampofampGHGampEm

issionsampCo8BenefitsampfromampW

aterampWasteampandampTransportationampinampCAampO

fficeampBuildings

AllfiguresinMTCO

2eyr

Baseline

Predicted Measured

Hi8Performance

Emissions

Emissions

Emissions

Emissions

PotentialampGHGampImprovem

ents Base5M

easure Pred5M

easure Base5HiPerf

Averageampofficeampbuilding(12968sf)

Water

Waste

Transportation

193

112

097

060

103

055

053

039

17642 15826

16843

096 014

134 050

002 064

800 (1017)

Largeampofficeampbuilding(100000sf)

Water

Waste

Transportation

1490

860

750

460

791

425

408

298 136045

122038 129878

740 110

1030 383

017 493

6167 (7841)

High8riseampofficeampbuilding(500000sf~32stories)

Water

Waste

Transportation

7450 4300

3750 2300

3953 2125

2040 1488

680226 610189

649392

3700 550

5150 1913

085 2465

30835 (39203)

AllampCAampofficeampbuildings(114billionsf)

Water

Waste

Transportation Total

16986000 9804000

8550000 5244000

9011700 4845000

4651200 3391500

1550915925 1391230364

1480613250 ampampampampampampampamp1576913625

ampampampampampampampamp1405879364 ampampampampampampampamp1493814450

ampampampampampampampamp1489248750

8436000 1254000

11742000 4360500

193800 5620200

70302675 (89382886)

ampampampampampamp83099175 ampampampampamp(87935086)

ampampampampampamp87664875

30835MTCO2e yr from transportation when comparing LEED-EBOM certification totypical construction

The areaof Californiacovered bythe CEUSsurveycontains about 102billionsf of commercial office space (Itron 2006)The survey covered electric utility service areas that containall of the important office markets inthe state withthe notable exceptionof the service area of the LA Department of Waterand Powerndash essentiallytheCityof Los Angeles plus portions of a few neighboring cities Drawing uponeconomic reports prepared bythecommercial real estate company CBRE (2014) the City of Los Angeles is estimated tocontain about 120 million sf of office space Thus the state of California as a whole is estimated to contain approximately114 billion sf of office space

Typical constructionof that square footage triggers about 0170 million megatons (MMT)of CO2eyear from water use 0090 MMTCO2eyear from solid waste and 15509 MMTCO2e yr from transportation Savings relative tobaseline from LEED-EBOM certification ofthe entireCalifornia officebuilding stockif it performed identically to the buildings studied here would be about 0084 MMTCO2e yr from wateruse 0044 MMTCO2e yr fromsolid waste and 0703 MMTCO2e yr from transportationfor a total of about 0831 MMTCO2e yr Stock-wide achievement of the water use and solid waste diversion ratesof the buildings earning additional performancecredits under LEED-EBOM would boost the total potential emissions savings to about 0877 MMTCO2e yr

29

Discussion

These results show that greenbuilding certificationwith respect to water waste andtransportation does indeed produce important GHG co-benefits relative to baseline levelsreflecting typical office construction Water usage and waste diversion performance inparticular is significantly improved by greenbuilding certification relative to baselineeven amongbuildings that donot seek additional performance-based credits withinthe EBOM rating system In general the certified green buildingsapproximately match theperformance predicted for them for waste and indoor water usage (on astatewide basis) but fall short of predicted performance for irrigationwater usage and transportation

Water

In general EBOM buildings are achieving very significantwater savings relativeto baseline and this is true even though theresearch team selected the most conservative of three possible baselines (see methods section)Bay Area LEED-EBOM buildings are significantlyunderperforming the predicted values for both indoor (-28) andirrigation(-31) usagewhile LA region buildings are underperforming for irrigation (-47) The LEED-EBOM buildings are shown to be saving considerable water (27overall) relative to predicted valuesbut this is entirely due to dramatic over-performance incooling tower usage where there was no basis upon which to create a predicted value thatdiffered from baseline

The LA region buildings perform much more efficientlythan the Bay Area buildings withrespect to indoor usage but less efficiently with respect to irrigation usageThis finding is consistent with the general observation thatSouthern California water districts and municipalities have invested heavily in indoor water use efficiency due towater supply reliability challengesbut as yet have not made comparable investments in outdoor water use efficiency

Cooling tower performance in the LEED-EBOM buildings is dramatically better than bothbaseline and predicted values (the same inthis case) especially inthe LA region Itis possible that this reflects a geographical bias inthe LEED-EBOM building sample which is disproportionately composedof buildings locatedinthe most temperate parts of the innerBay Area and coastal southern California where cooling demand is lower than in inlandparts of the state It may alsomean that these buildings have identified some wayof avoidingmajor coolingtower water use that future LEED-EBOM and CalGreenversions could seek to incentivize The buildings inthis sample received no credit in LEED-EBOM for anylevel of coolingtower performance onlyfor sub-metering this usage

As noted above irrigation usage isexpressed perbuilding square footnot per square foot of irrigated areaOne consequence of this is that the measuredvalues of irrigation usage may be influenced by the factthatLEED-EBOM buildings are likely disproportionately located in denser urbansettings where parcels are smaller and therefore overall irrigation needs lowerthan the typical California office building Nonetheless they still fall shortof the usage predicted by modeling of the CalGreenirrigationstandards though both represent substantial waterand GHG savings compared to baselineUnlike indoor and cooling tower usage irrigation usage could theoretically be brought tonear zero through a combination of xeriscaping sitingof buildings in urban settings where there is verylittle landscaped space and the use of captured stormwater or other highlylocalized alternative supplies Hence

30

the more than 20 of total water use thatirrigation still represents even for theEBOM buildings could be an area of significant future water and GHG savings

The indoor performance credit available in EBOM (W2) appears to be having adisproportionately large effect on water usage for those buildings that chose to obtain itThe difference betweenthe measured usage of the credited buildings versus the non-credited is much larger than the EBOM credit itself rewards and the gap is by far the largestin the indoor usage imputed from the overall building usageas it should be ifthe credit is indeed the motivating factor for these improvements But there are also majorimprovements in irrigation and cooling tower usage compared to non-credited buildings aswell as to predicted valuessuggesting that buildings committed to efficiency find ways to save everywhere This across-the-board over-performance due to a single performancecredit suggests that embedding rewards for extraefficiencywithin buildingsmay be a worthwhile policy initiative Both predicted indoor and irrigation usage are derived fromCalGreen 2010 The water usage rates measuredfor the buildings seeking the extraperformance credit compared to predicted values suggest that there is significant latitudefor further improvement in future editions ofCalGreen

From the point of view of per-gallon GHG savings indoorusage isthe best place for codes and standards tofocus since this water use is more GHG-intense than other uses due to water heating and wastewater treatment requirements In addition thiswater is harder to displace withreclaimed water or capturedstormwater eachof whichare potentially applicable toirrigation and coolingtowers and maybe significantlyless GHG-intense than utility-deliveredwater treatedtopotable standards

Waste

Solid waste diversion performance by the EBOM buildings only marginally exceedspredicted levels (52compared to a 50prediction) but significantly exceeds the much lower diversion ratesof baseline buildings The GHG intensity of solid waste issignificantly lower than that ofwater or transportation however so even this large percentageimprovement relative to baseline isresulting in comparatively little emissions reduction benefit

As with water usage the performance credit available in the LEED-EBOM rating system appears tobe effective in stimulatingdisproportionatelylarge performance improvementThe buildings earning that credit are required by EBOM to achieve a 50 diversion rate butinstead are achieving a 65 diversionrate (as comparedto39for the buildings not seeking the credit) Both the waterand waste performance credit resultssuggest that once building operators begina conscious effort to reduce resource use they are able to exceedthe stated goals on a routine basis The waste results may be even more significantin this regard given that recycling and otherwaste diversion require ongoing effort by buildingmanagers and potentially occupants whereas water use efficiency gains may be ldquohard-wiredrdquo into the building by one-time decisions aboutplumbing fixtures and fittings landscaping patterns and cooling tower design

Data on the composition of the waste streams (see Figure 4) showsthat a large amount ofthe undiverted waste is wetwaste This suggests thatadditional composting capacity will

31

I I l

I I

I I

r Metals

Mixed

Paper

Cardboard

Glass

Plastics

WetW

aste

LandscapeWaste

Other

PERCENT W

ASTE DISPO

SED

PERCENT W

ASTE DIVERTED

Metals

Mixed Paper

Cardboard

Glass

Plastics

Wet W

aste

Landscape Waste

Other

‐10000

‐8000

‐6000

‐4000

‐2000

000

2000

4000

6000

8000

10000

Discussion

These results show that greenbuilding certificationwith respect to water waste andtransportation does indeed produce important GHG co-benefits relative to baseline levelsreflecting typical office construction Water usage and waste diversion performance inparticular is significantly improved by greenbuilding certification relative to baselineeven amongbuildings that donot seek additional performance-based credits withinthe EBOM rating system In general the certified green buildingsapproximately match theperformance predicted for them for waste and indoor water usage (on astatewide basis) but fall short of predicted performance for irrigationwater usage and transportation

Water

In general EBOM buildings are achieving very significantwater savings relativeto baseline and this is true even though theresearch team selected the most conservative of three possible baselines (see methods section)Bay Area LEED-EBOM buildings are significantlyunderperforming the predicted values for both indoor (-28) andirrigation(-31) usagewhile LA region buildings are underperforming for irrigation (-47) The LEED-EBOM buildings are shown to be saving considerable water (27overall) relative to predicted valuesbut this is entirely due to dramatic over-performance incooling tower usage where there was no basis upon which to create a predicted value thatdiffered from baseline

The LA region buildings perform much more efficientlythan the Bay Area buildings withrespect to indoor usage but less efficiently with respect to irrigation usageThis finding is consistent with the general observation thatSouthern California water districts and municipalities have invested heavily in indoor water use efficiency due towater supply reliability challengesbut as yet have not made comparable investments in outdoor water use efficiency

Cooling tower performance in the LEED-EBOM buildings is dramatically better than bothbaseline and predicted values (the same inthis case) especially inthe LA region Itis possible that this reflects a geographical bias inthe LEED-EBOM building sample which is disproportionately composedof buildings locatedinthe most temperate parts of the innerBay Area and coastal southern California where cooling demand is lower than in inlandparts of the state It may alsomean that these buildings have identified some wayof avoidingmajor coolingtower water use that future LEED-EBOM and CalGreenversions could seek to incentivize The buildings inthis sample received no credit in LEED-EBOM for anylevel of coolingtower performance onlyfor sub-metering this usage

As noted above irrigation usage isexpressed perbuilding square footnot per square foot of irrigated areaOne consequence of this is that the measuredvalues of irrigation usage may be influenced by the factthatLEED-EBOM buildings are likely disproportionately located in denser urbansettings where parcels are smaller and therefore overall irrigation needs lowerthan the typical California office building Nonetheless they still fall shortof the usage predicted by modeling of the CalGreenirrigationstandards though both represent substantial waterand GHG savings compared to baselineUnlike indoor and cooling tower usage irrigation usage could theoretically be brought tonear zero through a combination of xeriscaping sitingof buildings in urban settings where there is verylittle landscaped space and the use of captured stormwater or other highlylocalized alternative supplies Hence

30

the more than 20 of total water use thatirrigation still represents even for theEBOM buildings could be an area of significant future water and GHG savings

The indoor performance credit available in EBOM (W2) appears to be having adisproportionately large effect on water usage for those buildings that chose to obtain itThe difference betweenthe measured usage of the credited buildings versus the non-credited is much larger than the EBOM credit itself rewards and the gap is by far the largestin the indoor usage imputed from the overall building usageas it should be ifthe credit is indeed the motivating factor for these improvements But there are also majorimprovements in irrigation and cooling tower usage compared to non-credited buildings aswell as to predicted valuessuggesting that buildings committed to efficiency find ways to save everywhere This across-the-board over-performance due to a single performancecredit suggests that embedding rewards for extraefficiencywithin buildingsmay be a worthwhile policy initiative Both predicted indoor and irrigation usage are derived fromCalGreen 2010 The water usage rates measuredfor the buildings seeking the extraperformance credit compared to predicted values suggest that there is significant latitudefor further improvement in future editions ofCalGreen

From the point of view of per-gallon GHG savings indoorusage isthe best place for codes and standards tofocus since this water use is more GHG-intense than other uses due to water heating and wastewater treatment requirements In addition thiswater is harder to displace withreclaimed water or capturedstormwater eachof whichare potentially applicable toirrigation and coolingtowers and maybe significantlyless GHG-intense than utility-deliveredwater treatedtopotable standards

Waste

Solid waste diversion performance by the EBOM buildings only marginally exceedspredicted levels (52compared to a 50prediction) but significantly exceeds the much lower diversion ratesof baseline buildings The GHG intensity of solid waste issignificantly lower than that ofwater or transportation however so even this large percentageimprovement relative to baseline isresulting in comparatively little emissions reduction benefit

As with water usage the performance credit available in the LEED-EBOM rating system appears tobe effective in stimulatingdisproportionatelylarge performance improvementThe buildings earning that credit are required by EBOM to achieve a 50 diversion rate butinstead are achieving a 65 diversionrate (as comparedto39for the buildings not seeking the credit) Both the waterand waste performance credit resultssuggest that once building operators begina conscious effort to reduce resource use they are able to exceedthe stated goals on a routine basis The waste results may be even more significantin this regard given that recycling and otherwaste diversion require ongoing effort by buildingmanagers and potentially occupants whereas water use efficiency gains may be ldquohard-wiredrdquo into the building by one-time decisions aboutplumbing fixtures and fittings landscaping patterns and cooling tower design

Data on the composition of the waste streams (see Figure 4) showsthat a large amount ofthe undiverted waste is wetwaste This suggests thatadditional composting capacity will

31

I I l

I I

I I

r Metals

Mixed

Paper

Cardboard

Glass

Plastics

WetW

aste

LandscapeWaste

Other

PERCENT W

ASTE DISPO

SED

PERCENT W

ASTE DIVERTED

Metals

Mixed Paper

Cardboard

Glass

Plastics

Wet W

aste

Landscape Waste

Other

‐10000

‐8000

‐6000

‐4000

‐2000

000

2000

4000

6000

8000

10000

the more than 20 of total water use thatirrigation still represents even for theEBOM buildings could be an area of significant future water and GHG savings

The indoor performance credit available in EBOM (W2) appears to be having adisproportionately large effect on water usage for those buildings that chose to obtain itThe difference betweenthe measured usage of the credited buildings versus the non-credited is much larger than the EBOM credit itself rewards and the gap is by far the largestin the indoor usage imputed from the overall building usageas it should be ifthe credit is indeed the motivating factor for these improvements But there are also majorimprovements in irrigation and cooling tower usage compared to non-credited buildings aswell as to predicted valuessuggesting that buildings committed to efficiency find ways to save everywhere This across-the-board over-performance due to a single performancecredit suggests that embedding rewards for extraefficiencywithin buildingsmay be a worthwhile policy initiative Both predicted indoor and irrigation usage are derived fromCalGreen 2010 The water usage rates measuredfor the buildings seeking the extraperformance credit compared to predicted values suggest that there is significant latitudefor further improvement in future editions ofCalGreen

From the point of view of per-gallon GHG savings indoorusage isthe best place for codes and standards tofocus since this water use is more GHG-intense than other uses due to water heating and wastewater treatment requirements In addition thiswater is harder to displace withreclaimed water or capturedstormwater eachof whichare potentially applicable toirrigation and coolingtowers and maybe significantlyless GHG-intense than utility-deliveredwater treatedtopotable standards

Waste

Solid waste diversion performance by the EBOM buildings only marginally exceedspredicted levels (52compared to a 50prediction) but significantly exceeds the much lower diversion ratesof baseline buildings The GHG intensity of solid waste issignificantly lower than that ofwater or transportation however so even this large percentageimprovement relative to baseline isresulting in comparatively little emissions reduction benefit

As with water usage the performance credit available in the LEED-EBOM rating system appears tobe effective in stimulatingdisproportionatelylarge performance improvementThe buildings earning that credit are required by EBOM to achieve a 50 diversion rate butinstead are achieving a 65 diversionrate (as comparedto39for the buildings not seeking the credit) Both the waterand waste performance credit resultssuggest that once building operators begina conscious effort to reduce resource use they are able to exceedthe stated goals on a routine basis The waste results may be even more significantin this regard given that recycling and otherwaste diversion require ongoing effort by buildingmanagers and potentially occupants whereas water use efficiency gains may be ldquohard-wiredrdquo into the building by one-time decisions aboutplumbing fixtures and fittings landscaping patterns and cooling tower design

Data on the composition of the waste streams (see Figure 4) showsthat a large amount ofthe undiverted waste is wetwaste This suggests thatadditional composting capacity will

31

I I l

I I

I I

r Metals

Mixed

Paper

Cardboard

Glass

Plastics

WetW

aste

LandscapeWaste

Other

PERCENT W

ASTE DISPO

SED

PERCENT W

ASTE DIVERTED

Metals

Mixed Paper

Cardboard

Glass

Plastics

Wet W

aste

Landscape Waste

Other

‐10000

‐8000

‐6000

‐4000

‐2000

000

2000

4000

6000

8000

10000

I I l

I I

I I

r Metals

Mixed

Paper

Cardboard

Glass

Plastics

WetW

aste

LandscapeWaste

Other

PERCENT W

ASTE DISPO

SED

PERCENT W

ASTE DIVERTED

Metals

Mixed Paper

Cardboard

Glass

Plastics

Wet W

aste

Landscape Waste

Other

‐10000

‐8000

‐6000

‐4000

‐2000

000

2000

4000

6000

8000

10000

be important to further improving diversion rates Thisisdoubly so since wet wastegenerates more methane than other types of waste once disposed in landfills Thoughbuilding occupant behavior is critical to any effort to reduce disposal to landfills buildingcodes could stimulate additional improvements by requiring office buildings to installthree-binsystems (recycling composting and landfill streams) andcontract withthe relevant waste-hauling services Measures of this kindmay be necessary for the state tomeet its current goal of 75 diversion (25 disposal) at the municipal level Notably even the EBOM buildings earning the extraperformance credit are currentlyfallingshort of that goal with 65 diversion (35 disposal)

Transportation

The GHGintensity of transportationto and from office buildings greatly exceeds that ofwater and waste so improved performance in this areais essential tosignificantlyreducingassociated GHG emissions Indeed even though the EBOM buildings report onlya5 improvement over baseline in their transportation performance theassociated GHG savingsare far larger than that ofthe water and waste sectors combined It is worth noting thatthis finding likely would be significantly different for some otherkindsof commercial buildings such aswarehouses which have many fewer occupants (and hence lesstransportation need)but may have proportionally higher water usage and solid wastegeneration per building

The character of the data is important to its interpretation The baseline values represent the average vehicle ridership (AVR)of the region as awholewith the implication being that aldquotypicalrdquo office buildingwould have the same AVR The prediction formulais based solelyuponthe locationof the building specifically the effect that its distance to a rail stopis predicted to have onthe proportionof occupants using rail (including subway light rail commuter rail and heavy rail) totravel towork The EBOM ratingsystemfor its partrequiresnothing otherthan the measurement of a buildingrsquosAVR hence there isno information on what ifany additional strategies to improvetransportation sustainabilitythese buildings may be employing

In thatsense itis perhaps unsurprising thatthe measured values do notdeviate dramatically from the predicted values The prediction formula appears tobe over-predicting non-automobile usage especially outside of the BayAreawhich has the most mature commuter rail systemsin California and the most transit-supportive land use context The dramaticexpansion of the LA Metro system notwithstanding the necessity ofand perhaps cultural dispositiontoward automobile usage insouthernCalifornia appears still to be apowerful force shaping transportation behavior These conclusions are true even though theprediction method used herelikelyunderstates theproportion of non-automobile commute travelin transit-friendly locations (since it is based entirely onpredictions of rail mode share)

Other green building rating systems such as LEED for New Construction include specificstrategiesthat building designersand managerscan undertake toreduce transportationenergyuseand GHGs such as parking policies pre-tax transitfare withholdings from paychecks and shuttle bus programs Evaluationof the GHGco-benefits of these strategies will have to await another study but it is worthnotingthat the literature on commutingbehavior strongly supports the assertionthat the proximity of the trip destination(inthis

33

case the office building) to transit is avery important factor shaping the likelihood to usenon-automobile modes (Ewing et al 2008)

Itis also worth noting thatthe GHG emissions consequences of commutes to office buildingsare more directly dependent uponaverage vehicle miles traveled(VMT) per occupant thanthey are on the AVR Previous research by the USGBC (Pykeet al 2014) has found that officedistricts with similar land use and transportation sustainability characteristicssuch as the PleasantonOffice Parks andEast Palo Alto Office Parkinthe Bay Area may nonetheless have quite different average commutedistances for officeworkers and hencequitedifferent GHGimpacts from commuting even if themodesplits areidentical That study alsopresents evidence that the occupants of LEED-EBOM buildings may be more willing to usetransitfor long-distance commutes than other commuters These dynamics are not captured by an AVR-based approach or bythe prediction methods employedin this studyand subsequent research should explore this issue in greater depth

To a large extent sustainabletransportation is synonymouswith compact land use patternsthatcluster both origins and destinations around transit (orso close to one anotherthatwalking and bicycling become viable options)In that sense the finding thatthe location of EBOM buildings alone cangenerate transportationGHG savings of approximately 5 relative to baseline isuseful confirmation of the value of compact development especially given the veryhigh GHG intensityof transportation for office buildings Perhaps notcoincidentally these GHG savings are similar to those sought on a regional level by SB 375which seeks to reduce transportation-related GHG emissionsby enabling morenon-automobile travel within Californiarsquos eighteen urban regions

There is also evidence that people generallycommutelonger distances for high-wage jobs of the sort often foundin LEED-EBOM buildings and that these long commutes may bemore difficult to carry out through transit (Pyke 2014) If so this would introduce an extra impediment to LEED-EBOM buildings relative toboth the baseline and prediction estimation methods used here

As noted above transportation is so GHG-intense that even these seemingly marginalpercentage gains meana much larger absolute reductioninGHG emissions for the state Just the 5 improvementover baseline statewide would translate to about07 MMT of CO2eavoided whereas a55improvement in water use translates to barely one-tenth the GHG savings (about008 MMTCO2eavoided)

General

In interpreting these results itis important to recall the characteristics ofthe EBOM dataset thatis the basis of the measured values Because itis focused on improving the operations of already-existing buildings rather than thedesign characteristics of new construction (as other LEED rating systemsand much of CalGreen are) these resultshave direct implications for the retrofitof the existing California office building stock ndash over one billion square feet of space These findings support the idea that greenbuilding rating systems such asLEED-EBOM canperform effectively inmeeting the expectations of state policy makers for GHGemissions reductions

Itis worth bearing in mind thatthe LEED-EBOM office buildings included inthis dataset are relatively early adoptersthat differ in important ways from the office building stock as a

34

whole LEED-EBOM office buildings as a group are more concentrated incentral cities thanothers whichhas particular implications for the extrapolation of transportation findingsCentral-city office space offers access to more alternative transportation modes than doessuburban space but average commute distancesndash which have large effects on transportation-related GHG emissionsndash can vary significantly from one office core to another (Pyke et al 2014) andthere is noguarantee that central-city locations necessarily play host to shorter commutes For water onthe other hand more suburbanoffice buildings will generally be sited onlarger parcels requiring more irrigationevenif standardsfor indoor use are the same While this may lead one to conclude that suburban office buildings wouldnotperform as well as urban ones even if certified as green underLEED-EBOM it also suggests that there may be evenmore potential room for improvement than these findings suggest

Adherence to CalGreen became mandatory for new construction (notexisting buildings) in California on January 1 2014 CalGreen contains requirements toinstall water fixtures andfittings that meet certain performance standards but it doesnot contain any mandatory provisions requiring achievement of a givenlevel of water consumptionor waste diversion and provisions encouragingbuildinglocation within short distances of transit stops are voluntaryin the2013 version of thecode As CalGreen takes effect and is updated in thefuture it willgradually improve the baseline performance ofthe commercialbuilding stock in California to which green retrofits ofexisting buildings (what LEED-EBOM certifies) are compared but this transformation ofthe building stock will be slow and should not affect short-range expectationsforthe emissionsavoidance available from retrofit of existing buildings

The AB 32 Scoping Plan(ARB 2008) includes a greenbuilding strategy that identifies a GHG reduction potential of 26 MMTCO2eyr from green buildings as a whole 75 MMTCO2eyr of which is attributed to existing commercial buildings (notjustoffice buildings)This total was derived from projections that one-third of an anticipated 705 billion square feet of California commercial building space couldbe retrofittedtoLEED-EBOM standards by 2020 (CAT 2008) The results of the presentstudy cannotbe directly related to thisestimated total for the following reasons

bull ARBrsquos avoided emissions estimates include potential savings fromoperational energyefficiencyimprovements but do not includetransportation

bull ARBrsquos avoided emissions estimates for solid waste involve construction and demolitionwaste not the solidwaste generatedfrom building operations as assessed here

bull ARBrsquos avoided emissions estimates encompass all commercial buildings ndash including verydisparateuses such as hotels educational buildings restaurant and warehouses ndash not only office buildings

Nonetheless there are points of comparisonthat allow us to assess whether the two estimates aregenerallyconsistent with one another The only directly comparable estimates arein water whereCAT (2008) identified from then-current research aGHG emissions factor of 385 MTCO2eper million gallons substantially higherthan the GHG intensities of water derivedfrom more recent sources for this report (see Table 20)

35

Tableamp20ampComparativeampGHGampIntensitiesampofampWater

MTCO2emillion-gal

n Outdoor Indoor Whole-building-avg

CAT-(2008) Statewide 3850

Present-study Bay-Area

Los-Angeles

Sacramento

San-Diego

RestNofNstate

89

63

22

11

6

0482

0934

0350

0934

0615

2386

2838

1993

2838

2520

1368

1761

1494

1832

2449

The assumedbaseline water usage inthe CAT (2008) report is 20295galsfyr almost double the baseline of 1082galsfyr usedinthis reportbut the CAT baseline applies to all commercial buildings many of which (such as restaurants and hotels) have higher waterdemandper square foot thanoffice buildingsRetrofits of existing non-residential buildingswere predicted by CAT (2008) to save 4059 galsfyrvery close to the difference between baseline and predicted values inthe present study (416 galsfyr) Thus despite the large difference inbaseline values the predicted savingsare comparablein terms of water quantity per square footAs noted however the LEEDEBOM office buildings have infact performed better thanpredicted ndash measured water usage is actually 597 galsfyr below baseline

The CAT(2008)study assumesthat one-third of commercial space could be retrofitted toLEED-EBOM standards by 2020 or about 233 billionsquare feet If this square footage ofcommercial space saved water at the same rates as the LEED-EBOM commercial office buildings inthis study it would result inavoidance of about 0147 MMTCO2eyr TheCAT study doesnot explicitly state what proportion of the overall 75 MMTCO2eyr emissions savingsisexpected from waterefficiency asopposed to operational energy efficiency orconstruction and demolition waste reduction However the study presumes a 25 reduction in both waterand energy use within commercial building

Table 18 shows that typical commercial office space in California (the baseline values)triggers about 35 times more GHG emissions per square foot from operational energyuse than from water use5so the vast majority of the anticipated 75MMTCO2eyr fromcommercial buildings would have to come from operational energy which is not analyzed inthis report Thus while the two studies differin too many waysto permit direct comparison it can be said that the current studyrsquos results for potential water-related emissions reduction in office buildingswhile they appear small are not necessarily inconsistent with ARBrsquos CAT-derivedoverall goals for GHG savings from the commercial building sector

5 This ratio likely varies considerably among other kinds of commercial buildings

36

Notably the GHG intensity of electricity assumed for the CAT study (0442 MTCO2eMWh) is also higher than that used in this report (0270 MTCO2eMWh) It is possiblethat someof this discrepancy is because the present study used a marginal-electricityapproach whilethe CAT study does notspecify whether itused a marginal or portfolio-average approach More importantly however GHGintensities of electricity have dropped throughoutCalifornia since the CAT study wasdone in 2008 due to the implementation of theRenewable Portfolio Standard (RPS) This progress will continue at least through 2020under the RPS and likely beyond if the cap-and-trade system or successor legislation to AB32stimulates further de-carbonization of the electricity supply As the electricity system is de-carbonized however building-levelefficiency measures willavoid fewer GHG emissions than they would with a ldquodirtierrdquo electricity supply ARBrsquos goal to reduce 26MMTCO2eyr through green building measures and 75 MMTCO2eyr from existing commercial buildingswhich are based on GHG intensity estimates dating from 2008 may therefore needto be revisited to accountfor the drop in GHG intensity of electricity (and by extension water)6

The current study also shows however that a 25 reductioninwater use may be too modest agoal given the much larger usage reductions achieved bycurrent LEED-EBOM buildings especially those seeking the high-performance credit

The apparent effectiveness of additional performance credits instimulating over-performance inwater and waste efficiency is instructive for the formulation of buildingcodes for new construction not just retrofits In a sense the buildings earning these creditsover-performed the predictions of LEED-EBOM itself suggesting that performance-basedcredits in codes and rating systems for new construction could do the same LEED-EBOM was intentionally designed to try to stimulate improvements in underlying codes andstandards and these resultssuggest that continuing updatesof LEED-EBOM could continue to drive market transformation code updates and over-performance byexemplarybuildings (even relativeto updated standards and codes) LEED v4 released too recently toproduce data for this study contains mandatory provisions for water metering and wasteaudits (as opposed tooptional credits) and strengthens the standards in other ways Previous researchby USGBC (Pyke et al 2011) has shownthat averagecredit achievement and associatedGHG co-benefits under LEED for New Construction(not existing buildings)has risen even as the standard has been strengthened with periodic updates

With respect to water use LEED for New Construction (LEED-ND) andCalGreenbothrequire the installation of plumbing fittingsand fixturesthat are expected to achieve a certain water usage rate Indeed this is all it is possible to require at the point ofconstruction since actual usage will only occur after the certification (orcode compliance)has beenachieved The questionis what actual usage rates could be expected from theseplumbing installations Though the character of our data prevented us from answering thisquestiondirectly the results from LEED-EBOMwhich alsorequires minimum fixture and fitting standards (not identicalto those of LEED-NC or CalGreen) but also awards credits formeasurement of actual performance and achievement of specific performance rates is atleast encouraging to the conclusions that new constructioncould over-perform its plumbing ldquopredictionsrdquo

Itcould be argued thatthere is a self-selection biasin these results The buildingsthat chose to seek the water performance credit may have done so knowing that they were

6 This is related to the reasonwhy the greenbuilding targets were not included inthe overall emissions reduction targetsin AB 32 forfearof double-counting the same emissions reduction

37

alreadyperforming verywell and could thereforegain credit points easilywith littleor no extra effort It seems unlikely however that that could fullyexplain such largeover-performance across a set of 71 buildings

With respect to solid waste codes and ratingsystems for new construction are limited torequiring the provision of recycling andorcomposting binsand waste handling facilities LEED-EBOM office buildings that measuredtheir waste diversion ratesbut did not earn the performance credit failed to meet the 50 diversion rate threshold derived from state lawinstead achieving only a 39diversion rate If thisperformance istypical of buildingsrequired to include recycling binsbut not seeking any performance standard it suggeststhat rating systemsand codesfornew construction will need to escalate theirrequirementsin order to meet even a50 threshold much less the 75 diversion ratesthat are sought on astatewide level in the future

For bothwater andwaste the prediction methods produced bytheCalifornia Pollution Control Officers Association (CAPCOA 2010) provide methods for determining the GHGemissions from given levels of water and wasteperformance but theydo not providemethods for predicting the overall water and waste performance levels of a building basedon the specific management strategies that theypursue In that sense prediction of waterand waste performance levels of new construction based on the requirements of codeandor ratingsystems will have tobesimilar to thoseused in this study(ie modeling thewater usage rates based on characteristics of plumbing fixtures and fittings and identifying arough diversion rate target derived from state law andorCalGreen)

For transportation there are morespecific prediction methods available in CAPCOA (2010) thatproject the performance of buildings based onbuilding characteristics mostly having to do with parkingand also building locationThis study used the CAPCOA prediction method that predicts rail mode share based on a buildingrsquosdistance to rail stationsto create the predicted values for transportation AVR Since LEED-EBOM does not require or request buildings to report uponthe strategies that they are pursuing to achieve a givenAVR level but instead only to report onthat AVR level this study does notgenerate any insight even indirectly into the efficacy ofparking management on transportation-related GHG emissions However theCAPCOA prediction method for rail transit useappears tobe overlyldquooptimisticrdquo in predicting more transit-influenced AVRbased on location when deployedusing this studyrsquos method The locationof office buildings (andcommercial buildings generally) is anissue that canonly be addressed systematically through generalplans and zoning codes not through building codes but it is highly important inshaping the transportation behavior of occupants

Studying non-green-certified commercial buildings

Certifiedgreen office buildings are still a very small fraction ofthe overall commercial building stock and state GHG control policies must concernthemselves with all buildings whether certified ldquogreenrdquo or not Many non-certified commercial buildings may alsoperform as well or better than certified greenbuildings especially with respect to transportation which is by far the mostimportantsource of GHG emissions in this context Anon-certified office building if it is located near transit may trigger fewer GHG emissionsthan a certified green office building farther from transit evenif the latter greatly outperforms it on water andwaste management Likewise individual non-certified

38

buildings could excel inwater or waste management without adherence to any givenrating system

To set policies codes and standards intended to reduce emissions from all commercialbuildings additional informationonthe performance of these non-certified buildings will therefore be necessary Currently information on building performance in general is scarceand there is very little transparency in the commercial office building sector in particularLEED itself is anotable advance in this regard andwithout improvedtransparencygenerally it is difficult toimagine substantial improvement in buildingperformance across the entire construction and building managementindustry

Two major surveys of commercial buildings already exist and are conducted ona periodic basis the federal Commercial Building Energy ConsumptionSurvey (CBECS)and the California-wide Commercial End-Use Study (CEUS) These studies are focused on measuring operational energy consumption but given their reach and the fact that theysample the commercial building population in waysthat permit statistical inference to the entirebuilding stock they are likely the most effective vehiclesforgathering information on water waste and transportation performance

The CBECS has alreadyincorporated questions about water useThis was done in the surveyrsquos2007 edition but none of the surveyrsquos data was ever released due to errors in the sampling methodology The 2013 edition data from which are scheduled to be released in 2014 will containinformationontotal building water usage building size and will distinguishbetweenindoor irrigation and cooling tower though notprocess water use(which is not a factor in the present study but is potentially important for other kinds ofcommercial buildings)

Neither survey currently contains any questions pertaining to solid waste management To be of greatest use measurements of solid waste output should be conducted over aspecified reporting period (perhapstwo weeks) and occur at apoint in the year where building occupancy is expectedto be typical (ie notsummerorthe holiday season) This would allowinsight into rates of waste generationnot only the rates of disposal and diversionof the waste generatedLEED-EBOMrsquos reporting format currently allows respondentsto define the period of measurement themselves limiting the ability to analyzewaste generation rates The surveys shouldalsoseek to acquire information on existence ofrecycling andorcomposting facilities both in the workspace and in the collection point in the building

Transportationmeasurement through surveys ismore challenging and can take one of two paths VMT-based or AVR-based reporting This study used the latter for baseline andpredicted values because the measured data used AVRand it may be more appropriate for destination-side measurement since operators of existing buildings cannot be expected to influence the distance thatoccupants commute only (to some degree)the transportation mode that they choose to commuteStudies of new construction where buildinglocation is to some extentdiscretionaryon thepart of thebuilders maydiffer in this regard Importantly using AVR asthe study metric limits researchers to assuming averagecommute lengths rather than acquiring empirical building-specific data on commutelengthswhich can vary in surprising waysfrom first-glance expectations (Pyke 2014)In addition most of the existing transportation research literature does not use AVRwhich reducesthe ability to leverage otherresearch findingsin the analysisof the data

39

AVRinformation could be obtained by either a survey of occupants (either for one day orpreferably aperiod of days) or it could be estimated in most situations bycountingcars in the parking garagelot Although the latter streamlinesthe survey processconsiderably and avoids the needtocontact occupants it will also be the least accurate inthe cases where AVR is highest ie dense urban cores where office buildings may not provide all theirown parking and therefore countingcars could make AVR look even higher than itactually isIf reducing the data-gathering burdenonthe survey respondents is a high priority thenthere could be a two-tier system where only buildings thatdo notprovide all their own parking are required to survey the occupants (otherwise they cancount cars inthe parking lot)

Another downside is that car-counting does not capture people being dropped off byanother driver who does not park at the building The error this would introduce is fairly minimal because this practice rarely accountsformore than a very small percentage of commuters AVR baseline and predicted values could be generated for virtuallyanylocation in the US using the present studyrsquos method Even for locations outside of the metropolitanregions for which the relevant census information iscompiled routinely baseline and predicted AVRs canbe imputed from other geographical scales of census data though areaswithout regionally compiled censusinformation have small enough populations thattransitusage for commuting is likely nearly negligible

In VMT-based analysisestablishment of the baseline would alsoemployregionalcommuting information from the census multiplied by average commute distance To make use of CAPCOA predictionmethods the survey would have to generate detailedinformation on parkingpolicies primarily (including bike parking)as well as policies pertaining to fleet vehicles (if any) Measured datawould havetocomefrom surveydatathat asks occupants directly about their commute modes andthe distance of their automobile commutes as well as usage of fleet vehicles (if any) This is inherently more difficult thana survey limited to askingquestions of a single building managerThe advantages are that VMT is more directly relatedtoGHG emissions than AVR there would be improved analytical insightabout the effect of buildingstrategies on transportation behavior and related GHG emissions and therewould bemuch greater opportunityto leverageexisting research findings on transportation behavior in the analysis

40

Conclusion

This research quantifies for the first time the GHGco-benefits associated with water wasteand transportation aspects of certified green commercial office buildings in California It finds that these buildings do infact achieve significant GHG emissions reductions relative totypical non-green office buildings ndash about 38for water 48for waste and 5for transportation In terms of absolute emissions however savings in transportation dwarfthose of the other sectors because transportationis more than 90 times as GHG-intense per square foot of buildingspace as water use and over 170 times as GHG-intense per squarefoot as solid waste among baseline valuesOverallconversion of the entire stock ofexisting California officebuildings to theperformancestandards achieved bythecertified green office buildings would avoid emissions of about 0831 MMTCO2e per year

Furthermore additional performance incentives for water andwaste within the green rating systemswere found to be effectivein stimulating further resourceuseand emissions reductions These performance improvementswere actually largerthan what isrequired to achieve the extracredits in the LEED-EBOM system suggesting that such incentives may be worth more than ldquoface valuerdquo This finding has particular significance for standards for newconstruction and suggests that incentivizing higher efficiency standards could prompt aldquovirtuouslooprdquowhere buildersseek additional efficiencies beyond code requirements

The three resource areas differed significantly intheir performance relative to predictions for green building performance With respect to GHG emissions the certifiedbuildings performed better thanpredicted on water use (13) slightly better than predicted onwaste diversion (4) and worse than predicted on transportation (-6) The latter is a significant finding given the GHG intensity of transportation and suggeststhat the CAPCOA formula for calculating railmodeshares based on proximityto rail stations mayover-estimateactual rail ridership outcomes Thewidedivergencebetween predicted andmeasured values for water use likewise suggests that efforts should be made to improvewater use prediction methods especially with respect to cooling toweruse

Finally additional insights intocommercial office buildingperformance couldbe gainedbyinserting basic questions on water waste and transportation usage into the CEUS or CBECSsurveys which currently focus onoperational energy use Systematic collection ofperformance data of non-certified commercial office buildings would enable deeper analysisinto the effectiveness ofspecific building design strategies such as parking policiesplacement of recycling andcomposting bins andwater-efficient landscaping in securing GHGemissions reduction co-benefits The findings of this report suggest that importantadditional efficiencies and GHG co-benefits are available inall three resource areas as indeed they must be if the state is tomeet its long-range GHG emissionsgoals

41

Recommendations

The findings of this report imply a number of recommendations for future researchfuture climate policy initiatives and future updates to building standards

Addresstransportation behavior through CalGreen and other building standardsto the greatest possible extentTransportation is so GHG-intense that even small percentageimprovements over baseline such as those reported here can avoid substantial quantitiesof GHG emissions Indeed commercial office buildings stimulate more than twice as muchGHGemission through induced transportation than they do through their own operational energyconsumption (see Table 18)yet operational energy is the subject of detailed code requirementsand standardswhile transportation islargely assumed to be beyond the reach of buildingstandards Locatingbuildings in transit-accessible areas in particular is soimpactful to GHG emissions and so fundamental to facilitating non-automobiletransportation thatitmay be worth more to GHG control efforts (from commercialoffice buildings) than all other foreseeable improvements to green buildingstandards combined Itshould be given an emphasis within CalGreen and other building standards relatedto commercial construction commensurate with that importance

Improve prediction methods for future analysis ofgreen building performanceCAPCOA guidance on the quantification of GHG emissions should be revised and expanded to includemore direct methods for assessing the GHG emissions expected fromspecific water and waste-related building strategies(asopposed to usage levels) especially those related to irrigation and cooling towers In addition the formula for estimating railmode shares from the distance to rail stations should be updated with further research when feasible andultimately expanded to include bus bicycle walking and other non-automobile modes

Improve the information base for assessing regional transportation baselinesThe method for identifying transportation baselines used in this study relied on regional-scale data thatlikely oversimplifies the commuting dynamics ofparticular office cores Recent work byUSGBC (Pyke et al 2014) draws upon aggregated cellular data to establish morefine-grained characterizations of typical commutingpatterns in specific neighborhoods of office buildings Future research inthis veincould establish much more accurate neighborhood-scale baselinesagainst which the transportation behavior of green office building occupantscould be compared Such research might also enable the incorporation of otherdemographic factors that influence commuting behavior andmay co-vary with green building occupancy and enable greaterinsight into commute distances(and by extension vehiclemiles traveled)

Future CalGreen updates shouldsignificantly strengthen plumbing standardsThe predictions for greenbuilding water use were derived from the fixture and fitting standards in the 2010editionof the CalGreencode Giventhat the LEED-EBOM buildings outperformedthese predictions by 27 it appears that significant additional strengtheningof these standards is feasible andjustifiable

Future CalGreen updates should require placement of composting collection facilities within commercial office buildingsAccording to the date shown in Figure 4 a large proportion ofthe un-divertedwaste leaving commercial office buildings and entering landfills is ldquowet wasterdquo ndash ie food and other organic waste that is highin carbon content andtherefore arelatively potent source of methane in landfills Introduction of compost collection facilities

42

would enable this waste to be diverted from landfills far more effectively improvingdiversion rates avoiding unnecessary GHG emissions and creating compost for re-use orresale The current CalGreenrequirement (Section54101) requires provisionof ldquoreadily accessible areasrdquo for the ldquodepositing storage and collectionrdquo of recyclables but does not explicitlyincludeanysuch requirement for compostablematerials

Include questions related to water waste and transportation in the CBECS andor CEUS surveysAs noted in the discussioninsertion of a small number of simple questions in these surveyswould greatly expand the information base foranalysisof GHG co-benefits innon-certified commercial buildings CBECS has already incorporated water questions in its 2013 edition Collection of high-quality transportationdata may involve requiring buildingmanagers to issue surveys to occupants but given the importance of transportation to theoverall GHG emissions footprint of commercial office buildings and the general paucity ofdestination-side commuting data it isworth the extra effort

Encourage information-sharing on operational performance of buildingsThis research was made possible by USGBCrsquos unilateral commitment to share information about projectperformance as part of LEEDrsquos stated goal of market transformation Evenif CBECS and CEUS are revisedas recommendedabove there will still be a needfor muchmore information on the operational performance ofcommercial buildings whether certified as ldquogreenrdquoornot Data sharing and collection should be institutionalized particularly for anyperformance domainthat is claimed to produce public benefit or is cited as evidence ofcompliance with laws and regulations such as AB 32 Building codes including CalGreen could require publicoperational data-sharing aspart of a post-occupancyinspection process Local building permits whether for greenor non-green buildings could alsobe made conditional on commitment to share post-occupancydata subject tolater inspection by local building officials

Expand emphasis on existingbuildings instate and localclimate planning effortsBuilding energyefficiencyand GHG control efforts havehistoricallytended to emphasizecreation of standardsfornew construction asa meansof saving energy and GHGs While thisisgraduallychangingwith the passage of AB 758 and other efforts toestablish standards for renovations the existing building sectorremainsunder-emphasized in climateplanning generally More than one billion square feet of commercial office space alreadyexists in Californiaand bringing this space up to performance standards typical of certified green building would save over 083 MMTCO2e per year Considerably larger improvements beyond that are possible giventhe water and waste performance levels achieved by thehigh-performance buildings in this dataset and given the very large latentpotential for reduction of transportation-related emissionsthrough transit-friendly building siting decisions Itshould also be borne in mind thatthe figures reported in this study are foroffice buildings only additional large savings can be expectedfrom efforts toreduce waterwaste and transportation usage associated with other types of commercial buildings

43

References

American Community Survey 2008-2012 Table B08301 for various counties named in Table 7

ARB[AirResourcesBoard] 2014First Update tothe Climate Change Scoping Plan Building on the FrameworkSacramento ARB

ARB[Air Resources Board] 2008 Climate Change Scoping Plan A Framework for ChangeSacramento RB

ARB[Air Resources Board] 2012a Technical Evaluationof the Greenhouse Gas EmissionReduction Quantification for the Sacramento Area Council of Governmentsrsquo SB375 Sustainable Communities StrategySacramento ARB

ARB[Air Resources Board] 2012b ARBDetermination on Apple CampusMemorandum to Governorrsquos Office of Planning and ResearchSacramento ARB

Blanco H J Newell L Stott and M Alberti 2012 Water Supply Scarcity in Southern California Assessing Water District-Level StrategiesLos Angeles USC Center for Sustainable Cities

California Building Standards Commission 2010 CaliforniaGreen Building Standards Code 2010Title 24Part 11

California Building Standards Commission 2010 CaliforniaPlumbing Code2010

California Department of Water Resources 2010 Water Budget WorkbookVersion 101

CalRecycle 2013 Landfilling of WasteMemorandum downloaded from httparbcagovccwastelandfillingofwastepdf

CalRecycle [fka California IntegratedWaste Management Board] 2006 Targeted Statewide Waste Characterization Study Waste Disposal andDiversion Findings for SelectedIndustry GroupsReport to the Board by Cascadia Consulting Group Sacramento CA IWMB

CAPCOA [California Air Pollution Control Officers Association] 2010 Quantifying Greenhouse Gas Mitigation Measures A Resource for Local Government to Assess Emission Reductions from Greenhouse Gas Mitigation MeasuresSacramento CAPCOA

CAT [Climate Action Team] 2008 Green Building Sector Subgroup Scoping Plan Measure Development and Cost AnalysisSacramento CAT

CBRE 2014 Greater Los Angeles Office MarketViewQuarter 22014

CEC[California EnergyCommission] 2006 Refining Estimates of Water-Related Energy Use in CaliforniaCEC 500-2006-118

Dziegielewski Benedykt et al 2000 Commercial andInstitutional EndUses of WaterDenver American Water Works Association Research Foundation

44

case the office building) to transit is avery important factor shaping the likelihood to usenon-automobile modes (Ewing et al 2008)

Itis also worth noting thatthe GHG emissions consequences of commutes to office buildingsare more directly dependent uponaverage vehicle miles traveled(VMT) per occupant thanthey are on the AVR Previous research by the USGBC (Pykeet al 2014) has found that officedistricts with similar land use and transportation sustainability characteristicssuch as the PleasantonOffice Parks andEast Palo Alto Office Parkinthe Bay Area may nonetheless have quite different average commutedistances for officeworkers and hencequitedifferent GHGimpacts from commuting even if themodesplits areidentical That study alsopresents evidence that the occupants of LEED-EBOM buildings may be more willing to usetransitfor long-distance commutes than other commuters These dynamics are not captured by an AVR-based approach or bythe prediction methods employedin this studyand subsequent research should explore this issue in greater depth

To a large extent sustainabletransportation is synonymouswith compact land use patternsthatcluster both origins and destinations around transit (orso close to one anotherthatwalking and bicycling become viable options)In that sense the finding thatthe location of EBOM buildings alone cangenerate transportationGHG savings of approximately 5 relative to baseline isuseful confirmation of the value of compact development especially given the veryhigh GHG intensityof transportation for office buildings Perhaps notcoincidentally these GHG savings are similar to those sought on a regional level by SB 375which seeks to reduce transportation-related GHG emissionsby enabling morenon-automobile travel within Californiarsquos eighteen urban regions

There is also evidence that people generallycommutelonger distances for high-wage jobs of the sort often foundin LEED-EBOM buildings and that these long commutes may bemore difficult to carry out through transit (Pyke 2014) If so this would introduce an extra impediment to LEED-EBOM buildings relative toboth the baseline and prediction estimation methods used here

As noted above transportation is so GHG-intense that even these seemingly marginalpercentage gains meana much larger absolute reductioninGHG emissions for the state Just the 5 improvementover baseline statewide would translate to about07 MMT of CO2eavoided whereas a55improvement in water use translates to barely one-tenth the GHG savings (about008 MMTCO2eavoided)

General

In interpreting these results itis important to recall the characteristics ofthe EBOM dataset thatis the basis of the measured values Because itis focused on improving the operations of already-existing buildings rather than thedesign characteristics of new construction (as other LEED rating systemsand much of CalGreen are) these resultshave direct implications for the retrofitof the existing California office building stock ndash over one billion square feet of space These findings support the idea that greenbuilding rating systems such asLEED-EBOM canperform effectively inmeeting the expectations of state policy makers for GHGemissions reductions

Itis worth bearing in mind thatthe LEED-EBOM office buildings included inthis dataset are relatively early adoptersthat differ in important ways from the office building stock as a

34

whole LEED-EBOM office buildings as a group are more concentrated incentral cities thanothers whichhas particular implications for the extrapolation of transportation findingsCentral-city office space offers access to more alternative transportation modes than doessuburban space but average commute distancesndash which have large effects on transportation-related GHG emissionsndash can vary significantly from one office core to another (Pyke et al 2014) andthere is noguarantee that central-city locations necessarily play host to shorter commutes For water onthe other hand more suburbanoffice buildings will generally be sited onlarger parcels requiring more irrigationevenif standardsfor indoor use are the same While this may lead one to conclude that suburban office buildings wouldnotperform as well as urban ones even if certified as green underLEED-EBOM it also suggests that there may be evenmore potential room for improvement than these findings suggest

Adherence to CalGreen became mandatory for new construction (notexisting buildings) in California on January 1 2014 CalGreen contains requirements toinstall water fixtures andfittings that meet certain performance standards but it doesnot contain any mandatory provisions requiring achievement of a givenlevel of water consumptionor waste diversion and provisions encouragingbuildinglocation within short distances of transit stops are voluntaryin the2013 version of thecode As CalGreen takes effect and is updated in thefuture it willgradually improve the baseline performance ofthe commercialbuilding stock in California to which green retrofits ofexisting buildings (what LEED-EBOM certifies) are compared but this transformation ofthe building stock will be slow and should not affect short-range expectationsforthe emissionsavoidance available from retrofit of existing buildings

The AB 32 Scoping Plan(ARB 2008) includes a greenbuilding strategy that identifies a GHG reduction potential of 26 MMTCO2eyr from green buildings as a whole 75 MMTCO2eyr of which is attributed to existing commercial buildings (notjustoffice buildings)This total was derived from projections that one-third of an anticipated 705 billion square feet of California commercial building space couldbe retrofittedtoLEED-EBOM standards by 2020 (CAT 2008) The results of the presentstudy cannotbe directly related to thisestimated total for the following reasons

bull ARBrsquos avoided emissions estimates include potential savings fromoperational energyefficiencyimprovements but do not includetransportation

bull ARBrsquos avoided emissions estimates for solid waste involve construction and demolitionwaste not the solidwaste generatedfrom building operations as assessed here

bull ARBrsquos avoided emissions estimates encompass all commercial buildings ndash including verydisparateuses such as hotels educational buildings restaurant and warehouses ndash not only office buildings

Nonetheless there are points of comparisonthat allow us to assess whether the two estimates aregenerallyconsistent with one another The only directly comparable estimates arein water whereCAT (2008) identified from then-current research aGHG emissions factor of 385 MTCO2eper million gallons substantially higherthan the GHG intensities of water derivedfrom more recent sources for this report (see Table 20)

35

Tableamp20ampComparativeampGHGampIntensitiesampofampWater

MTCO2emillion-gal

n Outdoor Indoor Whole-building-avg

CAT-(2008) Statewide 3850

Present-study Bay-Area

Los-Angeles

Sacramento

San-Diego

RestNofNstate

89

63

22

11

6

0482

0934

0350

0934

0615

2386

2838

1993

2838

2520

1368

1761

1494

1832

2449

The assumedbaseline water usage inthe CAT (2008) report is 20295galsfyr almost double the baseline of 1082galsfyr usedinthis reportbut the CAT baseline applies to all commercial buildings many of which (such as restaurants and hotels) have higher waterdemandper square foot thanoffice buildingsRetrofits of existing non-residential buildingswere predicted by CAT (2008) to save 4059 galsfyrvery close to the difference between baseline and predicted values inthe present study (416 galsfyr) Thus despite the large difference inbaseline values the predicted savingsare comparablein terms of water quantity per square footAs noted however the LEEDEBOM office buildings have infact performed better thanpredicted ndash measured water usage is actually 597 galsfyr below baseline

The CAT(2008)study assumesthat one-third of commercial space could be retrofitted toLEED-EBOM standards by 2020 or about 233 billionsquare feet If this square footage ofcommercial space saved water at the same rates as the LEED-EBOM commercial office buildings inthis study it would result inavoidance of about 0147 MMTCO2eyr TheCAT study doesnot explicitly state what proportion of the overall 75 MMTCO2eyr emissions savingsisexpected from waterefficiency asopposed to operational energy efficiency orconstruction and demolition waste reduction However the study presumes a 25 reduction in both waterand energy use within commercial building

Table 18 shows that typical commercial office space in California (the baseline values)triggers about 35 times more GHG emissions per square foot from operational energyuse than from water use5so the vast majority of the anticipated 75MMTCO2eyr fromcommercial buildings would have to come from operational energy which is not analyzed inthis report Thus while the two studies differin too many waysto permit direct comparison it can be said that the current studyrsquos results for potential water-related emissions reduction in office buildingswhile they appear small are not necessarily inconsistent with ARBrsquos CAT-derivedoverall goals for GHG savings from the commercial building sector

5 This ratio likely varies considerably among other kinds of commercial buildings

36

Notably the GHG intensity of electricity assumed for the CAT study (0442 MTCO2eMWh) is also higher than that used in this report (0270 MTCO2eMWh) It is possiblethat someof this discrepancy is because the present study used a marginal-electricityapproach whilethe CAT study does notspecify whether itused a marginal or portfolio-average approach More importantly however GHGintensities of electricity have dropped throughoutCalifornia since the CAT study wasdone in 2008 due to the implementation of theRenewable Portfolio Standard (RPS) This progress will continue at least through 2020under the RPS and likely beyond if the cap-and-trade system or successor legislation to AB32stimulates further de-carbonization of the electricity supply As the electricity system is de-carbonized however building-levelefficiency measures willavoid fewer GHG emissions than they would with a ldquodirtierrdquo electricity supply ARBrsquos goal to reduce 26MMTCO2eyr through green building measures and 75 MMTCO2eyr from existing commercial buildingswhich are based on GHG intensity estimates dating from 2008 may therefore needto be revisited to accountfor the drop in GHG intensity of electricity (and by extension water)6

The current study also shows however that a 25 reductioninwater use may be too modest agoal given the much larger usage reductions achieved bycurrent LEED-EBOM buildings especially those seeking the high-performance credit

The apparent effectiveness of additional performance credits instimulating over-performance inwater and waste efficiency is instructive for the formulation of buildingcodes for new construction not just retrofits In a sense the buildings earning these creditsover-performed the predictions of LEED-EBOM itself suggesting that performance-basedcredits in codes and rating systems for new construction could do the same LEED-EBOM was intentionally designed to try to stimulate improvements in underlying codes andstandards and these resultssuggest that continuing updatesof LEED-EBOM could continue to drive market transformation code updates and over-performance byexemplarybuildings (even relativeto updated standards and codes) LEED v4 released too recently toproduce data for this study contains mandatory provisions for water metering and wasteaudits (as opposed tooptional credits) and strengthens the standards in other ways Previous researchby USGBC (Pyke et al 2011) has shownthat averagecredit achievement and associatedGHG co-benefits under LEED for New Construction(not existing buildings)has risen even as the standard has been strengthened with periodic updates

With respect to water use LEED for New Construction (LEED-ND) andCalGreenbothrequire the installation of plumbing fittingsand fixturesthat are expected to achieve a certain water usage rate Indeed this is all it is possible to require at the point ofconstruction since actual usage will only occur after the certification (orcode compliance)has beenachieved The questionis what actual usage rates could be expected from theseplumbing installations Though the character of our data prevented us from answering thisquestiondirectly the results from LEED-EBOMwhich alsorequires minimum fixture and fitting standards (not identicalto those of LEED-NC or CalGreen) but also awards credits formeasurement of actual performance and achievement of specific performance rates is atleast encouraging to the conclusions that new constructioncould over-perform its plumbing ldquopredictionsrdquo

Itcould be argued thatthere is a self-selection biasin these results The buildingsthat chose to seek the water performance credit may have done so knowing that they were

6 This is related to the reasonwhy the greenbuilding targets were not included inthe overall emissions reduction targetsin AB 32 forfearof double-counting the same emissions reduction

37

alreadyperforming verywell and could thereforegain credit points easilywith littleor no extra effort It seems unlikely however that that could fullyexplain such largeover-performance across a set of 71 buildings

With respect to solid waste codes and ratingsystems for new construction are limited torequiring the provision of recycling andorcomposting binsand waste handling facilities LEED-EBOM office buildings that measuredtheir waste diversion ratesbut did not earn the performance credit failed to meet the 50 diversion rate threshold derived from state lawinstead achieving only a 39diversion rate If thisperformance istypical of buildingsrequired to include recycling binsbut not seeking any performance standard it suggeststhat rating systemsand codesfornew construction will need to escalate theirrequirementsin order to meet even a50 threshold much less the 75 diversion ratesthat are sought on astatewide level in the future

For bothwater andwaste the prediction methods produced bytheCalifornia Pollution Control Officers Association (CAPCOA 2010) provide methods for determining the GHGemissions from given levels of water and wasteperformance but theydo not providemethods for predicting the overall water and waste performance levels of a building basedon the specific management strategies that theypursue In that sense prediction of waterand waste performance levels of new construction based on the requirements of codeandor ratingsystems will have tobesimilar to thoseused in this study(ie modeling thewater usage rates based on characteristics of plumbing fixtures and fittings and identifying arough diversion rate target derived from state law andorCalGreen)

For transportation there are morespecific prediction methods available in CAPCOA (2010) thatproject the performance of buildings based onbuilding characteristics mostly having to do with parkingand also building locationThis study used the CAPCOA prediction method that predicts rail mode share based on a buildingrsquosdistance to rail stationsto create the predicted values for transportation AVR Since LEED-EBOM does not require or request buildings to report uponthe strategies that they are pursuing to achieve a givenAVR level but instead only to report onthat AVR level this study does notgenerate any insight even indirectly into the efficacy ofparking management on transportation-related GHG emissions However theCAPCOA prediction method for rail transit useappears tobe overlyldquooptimisticrdquo in predicting more transit-influenced AVRbased on location when deployedusing this studyrsquos method The locationof office buildings (andcommercial buildings generally) is anissue that canonly be addressed systematically through generalplans and zoning codes not through building codes but it is highly important inshaping the transportation behavior of occupants

Studying non-green-certified commercial buildings

Certifiedgreen office buildings are still a very small fraction ofthe overall commercial building stock and state GHG control policies must concernthemselves with all buildings whether certified ldquogreenrdquo or not Many non-certified commercial buildings may alsoperform as well or better than certified greenbuildings especially with respect to transportation which is by far the mostimportantsource of GHG emissions in this context Anon-certified office building if it is located near transit may trigger fewer GHG emissionsthan a certified green office building farther from transit evenif the latter greatly outperforms it on water andwaste management Likewise individual non-certified

38

buildings could excel inwater or waste management without adherence to any givenrating system

To set policies codes and standards intended to reduce emissions from all commercialbuildings additional informationonthe performance of these non-certified buildings will therefore be necessary Currently information on building performance in general is scarceand there is very little transparency in the commercial office building sector in particularLEED itself is anotable advance in this regard andwithout improvedtransparencygenerally it is difficult toimagine substantial improvement in buildingperformance across the entire construction and building managementindustry

Two major surveys of commercial buildings already exist and are conducted ona periodic basis the federal Commercial Building Energy ConsumptionSurvey (CBECS)and the California-wide Commercial End-Use Study (CEUS) These studies are focused on measuring operational energy consumption but given their reach and the fact that theysample the commercial building population in waysthat permit statistical inference to the entirebuilding stock they are likely the most effective vehiclesforgathering information on water waste and transportation performance

The CBECS has alreadyincorporated questions about water useThis was done in the surveyrsquos2007 edition but none of the surveyrsquos data was ever released due to errors in the sampling methodology The 2013 edition data from which are scheduled to be released in 2014 will containinformationontotal building water usage building size and will distinguishbetweenindoor irrigation and cooling tower though notprocess water use(which is not a factor in the present study but is potentially important for other kinds ofcommercial buildings)

Neither survey currently contains any questions pertaining to solid waste management To be of greatest use measurements of solid waste output should be conducted over aspecified reporting period (perhapstwo weeks) and occur at apoint in the year where building occupancy is expectedto be typical (ie notsummerorthe holiday season) This would allowinsight into rates of waste generationnot only the rates of disposal and diversionof the waste generatedLEED-EBOMrsquos reporting format currently allows respondentsto define the period of measurement themselves limiting the ability to analyzewaste generation rates The surveys shouldalsoseek to acquire information on existence ofrecycling andorcomposting facilities both in the workspace and in the collection point in the building

Transportationmeasurement through surveys ismore challenging and can take one of two paths VMT-based or AVR-based reporting This study used the latter for baseline andpredicted values because the measured data used AVRand it may be more appropriate for destination-side measurement since operators of existing buildings cannot be expected to influence the distance thatoccupants commute only (to some degree)the transportation mode that they choose to commuteStudies of new construction where buildinglocation is to some extentdiscretionaryon thepart of thebuilders maydiffer in this regard Importantly using AVR asthe study metric limits researchers to assuming averagecommute lengths rather than acquiring empirical building-specific data on commutelengthswhich can vary in surprising waysfrom first-glance expectations (Pyke 2014)In addition most of the existing transportation research literature does not use AVRwhich reducesthe ability to leverage otherresearch findingsin the analysisof the data

39

AVRinformation could be obtained by either a survey of occupants (either for one day orpreferably aperiod of days) or it could be estimated in most situations bycountingcars in the parking garagelot Although the latter streamlinesthe survey processconsiderably and avoids the needtocontact occupants it will also be the least accurate inthe cases where AVR is highest ie dense urban cores where office buildings may not provide all theirown parking and therefore countingcars could make AVR look even higher than itactually isIf reducing the data-gathering burdenonthe survey respondents is a high priority thenthere could be a two-tier system where only buildings thatdo notprovide all their own parking are required to survey the occupants (otherwise they cancount cars inthe parking lot)

Another downside is that car-counting does not capture people being dropped off byanother driver who does not park at the building The error this would introduce is fairly minimal because this practice rarely accountsformore than a very small percentage of commuters AVR baseline and predicted values could be generated for virtuallyanylocation in the US using the present studyrsquos method Even for locations outside of the metropolitanregions for which the relevant census information iscompiled routinely baseline and predicted AVRs canbe imputed from other geographical scales of census data though areaswithout regionally compiled censusinformation have small enough populations thattransitusage for commuting is likely nearly negligible

In VMT-based analysisestablishment of the baseline would alsoemployregionalcommuting information from the census multiplied by average commute distance To make use of CAPCOA predictionmethods the survey would have to generate detailedinformation on parkingpolicies primarily (including bike parking)as well as policies pertaining to fleet vehicles (if any) Measured datawould havetocomefrom surveydatathat asks occupants directly about their commute modes andthe distance of their automobile commutes as well as usage of fleet vehicles (if any) This is inherently more difficult thana survey limited to askingquestions of a single building managerThe advantages are that VMT is more directly relatedtoGHG emissions than AVR there would be improved analytical insightabout the effect of buildingstrategies on transportation behavior and related GHG emissions and therewould bemuch greater opportunityto leverageexisting research findings on transportation behavior in the analysis

40

Conclusion

This research quantifies for the first time the GHGco-benefits associated with water wasteand transportation aspects of certified green commercial office buildings in California It finds that these buildings do infact achieve significant GHG emissions reductions relative totypical non-green office buildings ndash about 38for water 48for waste and 5for transportation In terms of absolute emissions however savings in transportation dwarfthose of the other sectors because transportationis more than 90 times as GHG-intense per square foot of buildingspace as water use and over 170 times as GHG-intense per squarefoot as solid waste among baseline valuesOverallconversion of the entire stock ofexisting California officebuildings to theperformancestandards achieved bythecertified green office buildings would avoid emissions of about 0831 MMTCO2e per year

Furthermore additional performance incentives for water andwaste within the green rating systemswere found to be effectivein stimulating further resourceuseand emissions reductions These performance improvementswere actually largerthan what isrequired to achieve the extracredits in the LEED-EBOM system suggesting that such incentives may be worth more than ldquoface valuerdquo This finding has particular significance for standards for newconstruction and suggests that incentivizing higher efficiency standards could prompt aldquovirtuouslooprdquowhere buildersseek additional efficiencies beyond code requirements

The three resource areas differed significantly intheir performance relative to predictions for green building performance With respect to GHG emissions the certifiedbuildings performed better thanpredicted on water use (13) slightly better than predicted onwaste diversion (4) and worse than predicted on transportation (-6) The latter is a significant finding given the GHG intensity of transportation and suggeststhat the CAPCOA formula for calculating railmodeshares based on proximityto rail stations mayover-estimateactual rail ridership outcomes Thewidedivergencebetween predicted andmeasured values for water use likewise suggests that efforts should be made to improvewater use prediction methods especially with respect to cooling toweruse

Finally additional insights intocommercial office buildingperformance couldbe gainedbyinserting basic questions on water waste and transportation usage into the CEUS or CBECSsurveys which currently focus onoperational energy use Systematic collection ofperformance data of non-certified commercial office buildings would enable deeper analysisinto the effectiveness ofspecific building design strategies such as parking policiesplacement of recycling andcomposting bins andwater-efficient landscaping in securing GHGemissions reduction co-benefits The findings of this report suggest that importantadditional efficiencies and GHG co-benefits are available inall three resource areas as indeed they must be if the state is tomeet its long-range GHG emissionsgoals

41

Recommendations

The findings of this report imply a number of recommendations for future researchfuture climate policy initiatives and future updates to building standards

Addresstransportation behavior through CalGreen and other building standardsto the greatest possible extentTransportation is so GHG-intense that even small percentageimprovements over baseline such as those reported here can avoid substantial quantitiesof GHG emissions Indeed commercial office buildings stimulate more than twice as muchGHGemission through induced transportation than they do through their own operational energyconsumption (see Table 18)yet operational energy is the subject of detailed code requirementsand standardswhile transportation islargely assumed to be beyond the reach of buildingstandards Locatingbuildings in transit-accessible areas in particular is soimpactful to GHG emissions and so fundamental to facilitating non-automobiletransportation thatitmay be worth more to GHG control efforts (from commercialoffice buildings) than all other foreseeable improvements to green buildingstandards combined Itshould be given an emphasis within CalGreen and other building standards relatedto commercial construction commensurate with that importance

Improve prediction methods for future analysis ofgreen building performanceCAPCOA guidance on the quantification of GHG emissions should be revised and expanded to includemore direct methods for assessing the GHG emissions expected fromspecific water and waste-related building strategies(asopposed to usage levels) especially those related to irrigation and cooling towers In addition the formula for estimating railmode shares from the distance to rail stations should be updated with further research when feasible andultimately expanded to include bus bicycle walking and other non-automobile modes

Improve the information base for assessing regional transportation baselinesThe method for identifying transportation baselines used in this study relied on regional-scale data thatlikely oversimplifies the commuting dynamics ofparticular office cores Recent work byUSGBC (Pyke et al 2014) draws upon aggregated cellular data to establish morefine-grained characterizations of typical commutingpatterns in specific neighborhoods of office buildings Future research inthis veincould establish much more accurate neighborhood-scale baselinesagainst which the transportation behavior of green office building occupantscould be compared Such research might also enable the incorporation of otherdemographic factors that influence commuting behavior andmay co-vary with green building occupancy and enable greaterinsight into commute distances(and by extension vehiclemiles traveled)

Future CalGreen updates shouldsignificantly strengthen plumbing standardsThe predictions for greenbuilding water use were derived from the fixture and fitting standards in the 2010editionof the CalGreencode Giventhat the LEED-EBOM buildings outperformedthese predictions by 27 it appears that significant additional strengtheningof these standards is feasible andjustifiable

Future CalGreen updates should require placement of composting collection facilities within commercial office buildingsAccording to the date shown in Figure 4 a large proportion ofthe un-divertedwaste leaving commercial office buildings and entering landfills is ldquowet wasterdquo ndash ie food and other organic waste that is highin carbon content andtherefore arelatively potent source of methane in landfills Introduction of compost collection facilities

42

would enable this waste to be diverted from landfills far more effectively improvingdiversion rates avoiding unnecessary GHG emissions and creating compost for re-use orresale The current CalGreenrequirement (Section54101) requires provisionof ldquoreadily accessible areasrdquo for the ldquodepositing storage and collectionrdquo of recyclables but does not explicitlyincludeanysuch requirement for compostablematerials

Include questions related to water waste and transportation in the CBECS andor CEUS surveysAs noted in the discussioninsertion of a small number of simple questions in these surveyswould greatly expand the information base foranalysisof GHG co-benefits innon-certified commercial buildings CBECS has already incorporated water questions in its 2013 edition Collection of high-quality transportationdata may involve requiring buildingmanagers to issue surveys to occupants but given the importance of transportation to theoverall GHG emissions footprint of commercial office buildings and the general paucity ofdestination-side commuting data it isworth the extra effort

Encourage information-sharing on operational performance of buildingsThis research was made possible by USGBCrsquos unilateral commitment to share information about projectperformance as part of LEEDrsquos stated goal of market transformation Evenif CBECS and CEUS are revisedas recommendedabove there will still be a needfor muchmore information on the operational performance ofcommercial buildings whether certified as ldquogreenrdquoornot Data sharing and collection should be institutionalized particularly for anyperformance domainthat is claimed to produce public benefit or is cited as evidence ofcompliance with laws and regulations such as AB 32 Building codes including CalGreen could require publicoperational data-sharing aspart of a post-occupancyinspection process Local building permits whether for greenor non-green buildings could alsobe made conditional on commitment to share post-occupancydata subject tolater inspection by local building officials

Expand emphasis on existingbuildings instate and localclimate planning effortsBuilding energyefficiencyand GHG control efforts havehistoricallytended to emphasizecreation of standardsfornew construction asa meansof saving energy and GHGs While thisisgraduallychangingwith the passage of AB 758 and other efforts toestablish standards for renovations the existing building sectorremainsunder-emphasized in climateplanning generally More than one billion square feet of commercial office space alreadyexists in Californiaand bringing this space up to performance standards typical of certified green building would save over 083 MMTCO2e per year Considerably larger improvements beyond that are possible giventhe water and waste performance levels achieved by thehigh-performance buildings in this dataset and given the very large latentpotential for reduction of transportation-related emissionsthrough transit-friendly building siting decisions Itshould also be borne in mind thatthe figures reported in this study are foroffice buildings only additional large savings can be expectedfrom efforts toreduce waterwaste and transportation usage associated with other types of commercial buildings

43

References

American Community Survey 2008-2012 Table B08301 for various counties named in Table 7

ARB[AirResourcesBoard] 2014First Update tothe Climate Change Scoping Plan Building on the FrameworkSacramento ARB

ARB[Air Resources Board] 2008 Climate Change Scoping Plan A Framework for ChangeSacramento RB

ARB[Air Resources Board] 2012a Technical Evaluationof the Greenhouse Gas EmissionReduction Quantification for the Sacramento Area Council of Governmentsrsquo SB375 Sustainable Communities StrategySacramento ARB

ARB[Air Resources Board] 2012b ARBDetermination on Apple CampusMemorandum to Governorrsquos Office of Planning and ResearchSacramento ARB

Blanco H J Newell L Stott and M Alberti 2012 Water Supply Scarcity in Southern California Assessing Water District-Level StrategiesLos Angeles USC Center for Sustainable Cities

California Building Standards Commission 2010 CaliforniaGreen Building Standards Code 2010Title 24Part 11

California Building Standards Commission 2010 CaliforniaPlumbing Code2010

California Department of Water Resources 2010 Water Budget WorkbookVersion 101

CalRecycle 2013 Landfilling of WasteMemorandum downloaded from httparbcagovccwastelandfillingofwastepdf

CalRecycle [fka California IntegratedWaste Management Board] 2006 Targeted Statewide Waste Characterization Study Waste Disposal andDiversion Findings for SelectedIndustry GroupsReport to the Board by Cascadia Consulting Group Sacramento CA IWMB

CAPCOA [California Air Pollution Control Officers Association] 2010 Quantifying Greenhouse Gas Mitigation Measures A Resource for Local Government to Assess Emission Reductions from Greenhouse Gas Mitigation MeasuresSacramento CAPCOA

CAT [Climate Action Team] 2008 Green Building Sector Subgroup Scoping Plan Measure Development and Cost AnalysisSacramento CAT

CBRE 2014 Greater Los Angeles Office MarketViewQuarter 22014

CEC[California EnergyCommission] 2006 Refining Estimates of Water-Related Energy Use in CaliforniaCEC 500-2006-118

Dziegielewski Benedykt et al 2000 Commercial andInstitutional EndUses of WaterDenver American Water Works Association Research Foundation

44

whole LEED-EBOM office buildings as a group are more concentrated incentral cities thanothers whichhas particular implications for the extrapolation of transportation findingsCentral-city office space offers access to more alternative transportation modes than doessuburban space but average commute distancesndash which have large effects on transportation-related GHG emissionsndash can vary significantly from one office core to another (Pyke et al 2014) andthere is noguarantee that central-city locations necessarily play host to shorter commutes For water onthe other hand more suburbanoffice buildings will generally be sited onlarger parcels requiring more irrigationevenif standardsfor indoor use are the same While this may lead one to conclude that suburban office buildings wouldnotperform as well as urban ones even if certified as green underLEED-EBOM it also suggests that there may be evenmore potential room for improvement than these findings suggest

Adherence to CalGreen became mandatory for new construction (notexisting buildings) in California on January 1 2014 CalGreen contains requirements toinstall water fixtures andfittings that meet certain performance standards but it doesnot contain any mandatory provisions requiring achievement of a givenlevel of water consumptionor waste diversion and provisions encouragingbuildinglocation within short distances of transit stops are voluntaryin the2013 version of thecode As CalGreen takes effect and is updated in thefuture it willgradually improve the baseline performance ofthe commercialbuilding stock in California to which green retrofits ofexisting buildings (what LEED-EBOM certifies) are compared but this transformation ofthe building stock will be slow and should not affect short-range expectationsforthe emissionsavoidance available from retrofit of existing buildings

The AB 32 Scoping Plan(ARB 2008) includes a greenbuilding strategy that identifies a GHG reduction potential of 26 MMTCO2eyr from green buildings as a whole 75 MMTCO2eyr of which is attributed to existing commercial buildings (notjustoffice buildings)This total was derived from projections that one-third of an anticipated 705 billion square feet of California commercial building space couldbe retrofittedtoLEED-EBOM standards by 2020 (CAT 2008) The results of the presentstudy cannotbe directly related to thisestimated total for the following reasons

bull ARBrsquos avoided emissions estimates include potential savings fromoperational energyefficiencyimprovements but do not includetransportation

bull ARBrsquos avoided emissions estimates for solid waste involve construction and demolitionwaste not the solidwaste generatedfrom building operations as assessed here

bull ARBrsquos avoided emissions estimates encompass all commercial buildings ndash including verydisparateuses such as hotels educational buildings restaurant and warehouses ndash not only office buildings

Nonetheless there are points of comparisonthat allow us to assess whether the two estimates aregenerallyconsistent with one another The only directly comparable estimates arein water whereCAT (2008) identified from then-current research aGHG emissions factor of 385 MTCO2eper million gallons substantially higherthan the GHG intensities of water derivedfrom more recent sources for this report (see Table 20)

35

Tableamp20ampComparativeampGHGampIntensitiesampofampWater

MTCO2emillion-gal

n Outdoor Indoor Whole-building-avg

CAT-(2008) Statewide 3850

Present-study Bay-Area

Los-Angeles

Sacramento

San-Diego

RestNofNstate

89

63

22

11

6

0482

0934

0350

0934

0615

2386

2838

1993

2838

2520

1368

1761

1494

1832

2449

The assumedbaseline water usage inthe CAT (2008) report is 20295galsfyr almost double the baseline of 1082galsfyr usedinthis reportbut the CAT baseline applies to all commercial buildings many of which (such as restaurants and hotels) have higher waterdemandper square foot thanoffice buildingsRetrofits of existing non-residential buildingswere predicted by CAT (2008) to save 4059 galsfyrvery close to the difference between baseline and predicted values inthe present study (416 galsfyr) Thus despite the large difference inbaseline values the predicted savingsare comparablein terms of water quantity per square footAs noted however the LEEDEBOM office buildings have infact performed better thanpredicted ndash measured water usage is actually 597 galsfyr below baseline

The CAT(2008)study assumesthat one-third of commercial space could be retrofitted toLEED-EBOM standards by 2020 or about 233 billionsquare feet If this square footage ofcommercial space saved water at the same rates as the LEED-EBOM commercial office buildings inthis study it would result inavoidance of about 0147 MMTCO2eyr TheCAT study doesnot explicitly state what proportion of the overall 75 MMTCO2eyr emissions savingsisexpected from waterefficiency asopposed to operational energy efficiency orconstruction and demolition waste reduction However the study presumes a 25 reduction in both waterand energy use within commercial building

Table 18 shows that typical commercial office space in California (the baseline values)triggers about 35 times more GHG emissions per square foot from operational energyuse than from water use5so the vast majority of the anticipated 75MMTCO2eyr fromcommercial buildings would have to come from operational energy which is not analyzed inthis report Thus while the two studies differin too many waysto permit direct comparison it can be said that the current studyrsquos results for potential water-related emissions reduction in office buildingswhile they appear small are not necessarily inconsistent with ARBrsquos CAT-derivedoverall goals for GHG savings from the commercial building sector

5 This ratio likely varies considerably among other kinds of commercial buildings

36

Notably the GHG intensity of electricity assumed for the CAT study (0442 MTCO2eMWh) is also higher than that used in this report (0270 MTCO2eMWh) It is possiblethat someof this discrepancy is because the present study used a marginal-electricityapproach whilethe CAT study does notspecify whether itused a marginal or portfolio-average approach More importantly however GHGintensities of electricity have dropped throughoutCalifornia since the CAT study wasdone in 2008 due to the implementation of theRenewable Portfolio Standard (RPS) This progress will continue at least through 2020under the RPS and likely beyond if the cap-and-trade system or successor legislation to AB32stimulates further de-carbonization of the electricity supply As the electricity system is de-carbonized however building-levelefficiency measures willavoid fewer GHG emissions than they would with a ldquodirtierrdquo electricity supply ARBrsquos goal to reduce 26MMTCO2eyr through green building measures and 75 MMTCO2eyr from existing commercial buildingswhich are based on GHG intensity estimates dating from 2008 may therefore needto be revisited to accountfor the drop in GHG intensity of electricity (and by extension water)6

The current study also shows however that a 25 reductioninwater use may be too modest agoal given the much larger usage reductions achieved bycurrent LEED-EBOM buildings especially those seeking the high-performance credit

The apparent effectiveness of additional performance credits instimulating over-performance inwater and waste efficiency is instructive for the formulation of buildingcodes for new construction not just retrofits In a sense the buildings earning these creditsover-performed the predictions of LEED-EBOM itself suggesting that performance-basedcredits in codes and rating systems for new construction could do the same LEED-EBOM was intentionally designed to try to stimulate improvements in underlying codes andstandards and these resultssuggest that continuing updatesof LEED-EBOM could continue to drive market transformation code updates and over-performance byexemplarybuildings (even relativeto updated standards and codes) LEED v4 released too recently toproduce data for this study contains mandatory provisions for water metering and wasteaudits (as opposed tooptional credits) and strengthens the standards in other ways Previous researchby USGBC (Pyke et al 2011) has shownthat averagecredit achievement and associatedGHG co-benefits under LEED for New Construction(not existing buildings)has risen even as the standard has been strengthened with periodic updates

With respect to water use LEED for New Construction (LEED-ND) andCalGreenbothrequire the installation of plumbing fittingsand fixturesthat are expected to achieve a certain water usage rate Indeed this is all it is possible to require at the point ofconstruction since actual usage will only occur after the certification (orcode compliance)has beenachieved The questionis what actual usage rates could be expected from theseplumbing installations Though the character of our data prevented us from answering thisquestiondirectly the results from LEED-EBOMwhich alsorequires minimum fixture and fitting standards (not identicalto those of LEED-NC or CalGreen) but also awards credits formeasurement of actual performance and achievement of specific performance rates is atleast encouraging to the conclusions that new constructioncould over-perform its plumbing ldquopredictionsrdquo

Itcould be argued thatthere is a self-selection biasin these results The buildingsthat chose to seek the water performance credit may have done so knowing that they were

6 This is related to the reasonwhy the greenbuilding targets were not included inthe overall emissions reduction targetsin AB 32 forfearof double-counting the same emissions reduction

37

alreadyperforming verywell and could thereforegain credit points easilywith littleor no extra effort It seems unlikely however that that could fullyexplain such largeover-performance across a set of 71 buildings

With respect to solid waste codes and ratingsystems for new construction are limited torequiring the provision of recycling andorcomposting binsand waste handling facilities LEED-EBOM office buildings that measuredtheir waste diversion ratesbut did not earn the performance credit failed to meet the 50 diversion rate threshold derived from state lawinstead achieving only a 39diversion rate If thisperformance istypical of buildingsrequired to include recycling binsbut not seeking any performance standard it suggeststhat rating systemsand codesfornew construction will need to escalate theirrequirementsin order to meet even a50 threshold much less the 75 diversion ratesthat are sought on astatewide level in the future

For bothwater andwaste the prediction methods produced bytheCalifornia Pollution Control Officers Association (CAPCOA 2010) provide methods for determining the GHGemissions from given levels of water and wasteperformance but theydo not providemethods for predicting the overall water and waste performance levels of a building basedon the specific management strategies that theypursue In that sense prediction of waterand waste performance levels of new construction based on the requirements of codeandor ratingsystems will have tobesimilar to thoseused in this study(ie modeling thewater usage rates based on characteristics of plumbing fixtures and fittings and identifying arough diversion rate target derived from state law andorCalGreen)

For transportation there are morespecific prediction methods available in CAPCOA (2010) thatproject the performance of buildings based onbuilding characteristics mostly having to do with parkingand also building locationThis study used the CAPCOA prediction method that predicts rail mode share based on a buildingrsquosdistance to rail stationsto create the predicted values for transportation AVR Since LEED-EBOM does not require or request buildings to report uponthe strategies that they are pursuing to achieve a givenAVR level but instead only to report onthat AVR level this study does notgenerate any insight even indirectly into the efficacy ofparking management on transportation-related GHG emissions However theCAPCOA prediction method for rail transit useappears tobe overlyldquooptimisticrdquo in predicting more transit-influenced AVRbased on location when deployedusing this studyrsquos method The locationof office buildings (andcommercial buildings generally) is anissue that canonly be addressed systematically through generalplans and zoning codes not through building codes but it is highly important inshaping the transportation behavior of occupants

Studying non-green-certified commercial buildings

Certifiedgreen office buildings are still a very small fraction ofthe overall commercial building stock and state GHG control policies must concernthemselves with all buildings whether certified ldquogreenrdquo or not Many non-certified commercial buildings may alsoperform as well or better than certified greenbuildings especially with respect to transportation which is by far the mostimportantsource of GHG emissions in this context Anon-certified office building if it is located near transit may trigger fewer GHG emissionsthan a certified green office building farther from transit evenif the latter greatly outperforms it on water andwaste management Likewise individual non-certified

38

buildings could excel inwater or waste management without adherence to any givenrating system

To set policies codes and standards intended to reduce emissions from all commercialbuildings additional informationonthe performance of these non-certified buildings will therefore be necessary Currently information on building performance in general is scarceand there is very little transparency in the commercial office building sector in particularLEED itself is anotable advance in this regard andwithout improvedtransparencygenerally it is difficult toimagine substantial improvement in buildingperformance across the entire construction and building managementindustry

Two major surveys of commercial buildings already exist and are conducted ona periodic basis the federal Commercial Building Energy ConsumptionSurvey (CBECS)and the California-wide Commercial End-Use Study (CEUS) These studies are focused on measuring operational energy consumption but given their reach and the fact that theysample the commercial building population in waysthat permit statistical inference to the entirebuilding stock they are likely the most effective vehiclesforgathering information on water waste and transportation performance

The CBECS has alreadyincorporated questions about water useThis was done in the surveyrsquos2007 edition but none of the surveyrsquos data was ever released due to errors in the sampling methodology The 2013 edition data from which are scheduled to be released in 2014 will containinformationontotal building water usage building size and will distinguishbetweenindoor irrigation and cooling tower though notprocess water use(which is not a factor in the present study but is potentially important for other kinds ofcommercial buildings)

Neither survey currently contains any questions pertaining to solid waste management To be of greatest use measurements of solid waste output should be conducted over aspecified reporting period (perhapstwo weeks) and occur at apoint in the year where building occupancy is expectedto be typical (ie notsummerorthe holiday season) This would allowinsight into rates of waste generationnot only the rates of disposal and diversionof the waste generatedLEED-EBOMrsquos reporting format currently allows respondentsto define the period of measurement themselves limiting the ability to analyzewaste generation rates The surveys shouldalsoseek to acquire information on existence ofrecycling andorcomposting facilities both in the workspace and in the collection point in the building

Transportationmeasurement through surveys ismore challenging and can take one of two paths VMT-based or AVR-based reporting This study used the latter for baseline andpredicted values because the measured data used AVRand it may be more appropriate for destination-side measurement since operators of existing buildings cannot be expected to influence the distance thatoccupants commute only (to some degree)the transportation mode that they choose to commuteStudies of new construction where buildinglocation is to some extentdiscretionaryon thepart of thebuilders maydiffer in this regard Importantly using AVR asthe study metric limits researchers to assuming averagecommute lengths rather than acquiring empirical building-specific data on commutelengthswhich can vary in surprising waysfrom first-glance expectations (Pyke 2014)In addition most of the existing transportation research literature does not use AVRwhich reducesthe ability to leverage otherresearch findingsin the analysisof the data

39

AVRinformation could be obtained by either a survey of occupants (either for one day orpreferably aperiod of days) or it could be estimated in most situations bycountingcars in the parking garagelot Although the latter streamlinesthe survey processconsiderably and avoids the needtocontact occupants it will also be the least accurate inthe cases where AVR is highest ie dense urban cores where office buildings may not provide all theirown parking and therefore countingcars could make AVR look even higher than itactually isIf reducing the data-gathering burdenonthe survey respondents is a high priority thenthere could be a two-tier system where only buildings thatdo notprovide all their own parking are required to survey the occupants (otherwise they cancount cars inthe parking lot)

Another downside is that car-counting does not capture people being dropped off byanother driver who does not park at the building The error this would introduce is fairly minimal because this practice rarely accountsformore than a very small percentage of commuters AVR baseline and predicted values could be generated for virtuallyanylocation in the US using the present studyrsquos method Even for locations outside of the metropolitanregions for which the relevant census information iscompiled routinely baseline and predicted AVRs canbe imputed from other geographical scales of census data though areaswithout regionally compiled censusinformation have small enough populations thattransitusage for commuting is likely nearly negligible

In VMT-based analysisestablishment of the baseline would alsoemployregionalcommuting information from the census multiplied by average commute distance To make use of CAPCOA predictionmethods the survey would have to generate detailedinformation on parkingpolicies primarily (including bike parking)as well as policies pertaining to fleet vehicles (if any) Measured datawould havetocomefrom surveydatathat asks occupants directly about their commute modes andthe distance of their automobile commutes as well as usage of fleet vehicles (if any) This is inherently more difficult thana survey limited to askingquestions of a single building managerThe advantages are that VMT is more directly relatedtoGHG emissions than AVR there would be improved analytical insightabout the effect of buildingstrategies on transportation behavior and related GHG emissions and therewould bemuch greater opportunityto leverageexisting research findings on transportation behavior in the analysis

40

Conclusion

This research quantifies for the first time the GHGco-benefits associated with water wasteand transportation aspects of certified green commercial office buildings in California It finds that these buildings do infact achieve significant GHG emissions reductions relative totypical non-green office buildings ndash about 38for water 48for waste and 5for transportation In terms of absolute emissions however savings in transportation dwarfthose of the other sectors because transportationis more than 90 times as GHG-intense per square foot of buildingspace as water use and over 170 times as GHG-intense per squarefoot as solid waste among baseline valuesOverallconversion of the entire stock ofexisting California officebuildings to theperformancestandards achieved bythecertified green office buildings would avoid emissions of about 0831 MMTCO2e per year

Furthermore additional performance incentives for water andwaste within the green rating systemswere found to be effectivein stimulating further resourceuseand emissions reductions These performance improvementswere actually largerthan what isrequired to achieve the extracredits in the LEED-EBOM system suggesting that such incentives may be worth more than ldquoface valuerdquo This finding has particular significance for standards for newconstruction and suggests that incentivizing higher efficiency standards could prompt aldquovirtuouslooprdquowhere buildersseek additional efficiencies beyond code requirements

The three resource areas differed significantly intheir performance relative to predictions for green building performance With respect to GHG emissions the certifiedbuildings performed better thanpredicted on water use (13) slightly better than predicted onwaste diversion (4) and worse than predicted on transportation (-6) The latter is a significant finding given the GHG intensity of transportation and suggeststhat the CAPCOA formula for calculating railmodeshares based on proximityto rail stations mayover-estimateactual rail ridership outcomes Thewidedivergencebetween predicted andmeasured values for water use likewise suggests that efforts should be made to improvewater use prediction methods especially with respect to cooling toweruse

Finally additional insights intocommercial office buildingperformance couldbe gainedbyinserting basic questions on water waste and transportation usage into the CEUS or CBECSsurveys which currently focus onoperational energy use Systematic collection ofperformance data of non-certified commercial office buildings would enable deeper analysisinto the effectiveness ofspecific building design strategies such as parking policiesplacement of recycling andcomposting bins andwater-efficient landscaping in securing GHGemissions reduction co-benefits The findings of this report suggest that importantadditional efficiencies and GHG co-benefits are available inall three resource areas as indeed they must be if the state is tomeet its long-range GHG emissionsgoals

41

Recommendations

The findings of this report imply a number of recommendations for future researchfuture climate policy initiatives and future updates to building standards

Addresstransportation behavior through CalGreen and other building standardsto the greatest possible extentTransportation is so GHG-intense that even small percentageimprovements over baseline such as those reported here can avoid substantial quantitiesof GHG emissions Indeed commercial office buildings stimulate more than twice as muchGHGemission through induced transportation than they do through their own operational energyconsumption (see Table 18)yet operational energy is the subject of detailed code requirementsand standardswhile transportation islargely assumed to be beyond the reach of buildingstandards Locatingbuildings in transit-accessible areas in particular is soimpactful to GHG emissions and so fundamental to facilitating non-automobiletransportation thatitmay be worth more to GHG control efforts (from commercialoffice buildings) than all other foreseeable improvements to green buildingstandards combined Itshould be given an emphasis within CalGreen and other building standards relatedto commercial construction commensurate with that importance

Improve prediction methods for future analysis ofgreen building performanceCAPCOA guidance on the quantification of GHG emissions should be revised and expanded to includemore direct methods for assessing the GHG emissions expected fromspecific water and waste-related building strategies(asopposed to usage levels) especially those related to irrigation and cooling towers In addition the formula for estimating railmode shares from the distance to rail stations should be updated with further research when feasible andultimately expanded to include bus bicycle walking and other non-automobile modes

Improve the information base for assessing regional transportation baselinesThe method for identifying transportation baselines used in this study relied on regional-scale data thatlikely oversimplifies the commuting dynamics ofparticular office cores Recent work byUSGBC (Pyke et al 2014) draws upon aggregated cellular data to establish morefine-grained characterizations of typical commutingpatterns in specific neighborhoods of office buildings Future research inthis veincould establish much more accurate neighborhood-scale baselinesagainst which the transportation behavior of green office building occupantscould be compared Such research might also enable the incorporation of otherdemographic factors that influence commuting behavior andmay co-vary with green building occupancy and enable greaterinsight into commute distances(and by extension vehiclemiles traveled)

Future CalGreen updates shouldsignificantly strengthen plumbing standardsThe predictions for greenbuilding water use were derived from the fixture and fitting standards in the 2010editionof the CalGreencode Giventhat the LEED-EBOM buildings outperformedthese predictions by 27 it appears that significant additional strengtheningof these standards is feasible andjustifiable

Future CalGreen updates should require placement of composting collection facilities within commercial office buildingsAccording to the date shown in Figure 4 a large proportion ofthe un-divertedwaste leaving commercial office buildings and entering landfills is ldquowet wasterdquo ndash ie food and other organic waste that is highin carbon content andtherefore arelatively potent source of methane in landfills Introduction of compost collection facilities

42

would enable this waste to be diverted from landfills far more effectively improvingdiversion rates avoiding unnecessary GHG emissions and creating compost for re-use orresale The current CalGreenrequirement (Section54101) requires provisionof ldquoreadily accessible areasrdquo for the ldquodepositing storage and collectionrdquo of recyclables but does not explicitlyincludeanysuch requirement for compostablematerials

Include questions related to water waste and transportation in the CBECS andor CEUS surveysAs noted in the discussioninsertion of a small number of simple questions in these surveyswould greatly expand the information base foranalysisof GHG co-benefits innon-certified commercial buildings CBECS has already incorporated water questions in its 2013 edition Collection of high-quality transportationdata may involve requiring buildingmanagers to issue surveys to occupants but given the importance of transportation to theoverall GHG emissions footprint of commercial office buildings and the general paucity ofdestination-side commuting data it isworth the extra effort

Encourage information-sharing on operational performance of buildingsThis research was made possible by USGBCrsquos unilateral commitment to share information about projectperformance as part of LEEDrsquos stated goal of market transformation Evenif CBECS and CEUS are revisedas recommendedabove there will still be a needfor muchmore information on the operational performance ofcommercial buildings whether certified as ldquogreenrdquoornot Data sharing and collection should be institutionalized particularly for anyperformance domainthat is claimed to produce public benefit or is cited as evidence ofcompliance with laws and regulations such as AB 32 Building codes including CalGreen could require publicoperational data-sharing aspart of a post-occupancyinspection process Local building permits whether for greenor non-green buildings could alsobe made conditional on commitment to share post-occupancydata subject tolater inspection by local building officials

Expand emphasis on existingbuildings instate and localclimate planning effortsBuilding energyefficiencyand GHG control efforts havehistoricallytended to emphasizecreation of standardsfornew construction asa meansof saving energy and GHGs While thisisgraduallychangingwith the passage of AB 758 and other efforts toestablish standards for renovations the existing building sectorremainsunder-emphasized in climateplanning generally More than one billion square feet of commercial office space alreadyexists in Californiaand bringing this space up to performance standards typical of certified green building would save over 083 MMTCO2e per year Considerably larger improvements beyond that are possible giventhe water and waste performance levels achieved by thehigh-performance buildings in this dataset and given the very large latentpotential for reduction of transportation-related emissionsthrough transit-friendly building siting decisions Itshould also be borne in mind thatthe figures reported in this study are foroffice buildings only additional large savings can be expectedfrom efforts toreduce waterwaste and transportation usage associated with other types of commercial buildings

43

References

American Community Survey 2008-2012 Table B08301 for various counties named in Table 7

ARB[AirResourcesBoard] 2014First Update tothe Climate Change Scoping Plan Building on the FrameworkSacramento ARB

ARB[Air Resources Board] 2008 Climate Change Scoping Plan A Framework for ChangeSacramento RB

ARB[Air Resources Board] 2012a Technical Evaluationof the Greenhouse Gas EmissionReduction Quantification for the Sacramento Area Council of Governmentsrsquo SB375 Sustainable Communities StrategySacramento ARB

ARB[Air Resources Board] 2012b ARBDetermination on Apple CampusMemorandum to Governorrsquos Office of Planning and ResearchSacramento ARB

Blanco H J Newell L Stott and M Alberti 2012 Water Supply Scarcity in Southern California Assessing Water District-Level StrategiesLos Angeles USC Center for Sustainable Cities

California Building Standards Commission 2010 CaliforniaGreen Building Standards Code 2010Title 24Part 11

California Building Standards Commission 2010 CaliforniaPlumbing Code2010

California Department of Water Resources 2010 Water Budget WorkbookVersion 101

CalRecycle 2013 Landfilling of WasteMemorandum downloaded from httparbcagovccwastelandfillingofwastepdf

CalRecycle [fka California IntegratedWaste Management Board] 2006 Targeted Statewide Waste Characterization Study Waste Disposal andDiversion Findings for SelectedIndustry GroupsReport to the Board by Cascadia Consulting Group Sacramento CA IWMB

CAPCOA [California Air Pollution Control Officers Association] 2010 Quantifying Greenhouse Gas Mitigation Measures A Resource for Local Government to Assess Emission Reductions from Greenhouse Gas Mitigation MeasuresSacramento CAPCOA

CAT [Climate Action Team] 2008 Green Building Sector Subgroup Scoping Plan Measure Development and Cost AnalysisSacramento CAT

CBRE 2014 Greater Los Angeles Office MarketViewQuarter 22014

CEC[California EnergyCommission] 2006 Refining Estimates of Water-Related Energy Use in CaliforniaCEC 500-2006-118

Dziegielewski Benedykt et al 2000 Commercial andInstitutional EndUses of WaterDenver American Water Works Association Research Foundation

44

Tableamp20ampComparativeampGHGampIntensitiesampofampWater

MTCO2emillion-gal

n Outdoor Indoor Whole-building-avg

CAT-(2008) Statewide 3850

Present-study Bay-Area

Los-Angeles

Sacramento

San-Diego

RestNofNstate

89

63

22

11

6

0482

0934

0350

0934

0615

2386

2838

1993

2838

2520

1368

1761

1494

1832

2449

The assumedbaseline water usage inthe CAT (2008) report is 20295galsfyr almost double the baseline of 1082galsfyr usedinthis reportbut the CAT baseline applies to all commercial buildings many of which (such as restaurants and hotels) have higher waterdemandper square foot thanoffice buildingsRetrofits of existing non-residential buildingswere predicted by CAT (2008) to save 4059 galsfyrvery close to the difference between baseline and predicted values inthe present study (416 galsfyr) Thus despite the large difference inbaseline values the predicted savingsare comparablein terms of water quantity per square footAs noted however the LEEDEBOM office buildings have infact performed better thanpredicted ndash measured water usage is actually 597 galsfyr below baseline

The CAT(2008)study assumesthat one-third of commercial space could be retrofitted toLEED-EBOM standards by 2020 or about 233 billionsquare feet If this square footage ofcommercial space saved water at the same rates as the LEED-EBOM commercial office buildings inthis study it would result inavoidance of about 0147 MMTCO2eyr TheCAT study doesnot explicitly state what proportion of the overall 75 MMTCO2eyr emissions savingsisexpected from waterefficiency asopposed to operational energy efficiency orconstruction and demolition waste reduction However the study presumes a 25 reduction in both waterand energy use within commercial building

Table 18 shows that typical commercial office space in California (the baseline values)triggers about 35 times more GHG emissions per square foot from operational energyuse than from water use5so the vast majority of the anticipated 75MMTCO2eyr fromcommercial buildings would have to come from operational energy which is not analyzed inthis report Thus while the two studies differin too many waysto permit direct comparison it can be said that the current studyrsquos results for potential water-related emissions reduction in office buildingswhile they appear small are not necessarily inconsistent with ARBrsquos CAT-derivedoverall goals for GHG savings from the commercial building sector

5 This ratio likely varies considerably among other kinds of commercial buildings

36

Notably the GHG intensity of electricity assumed for the CAT study (0442 MTCO2eMWh) is also higher than that used in this report (0270 MTCO2eMWh) It is possiblethat someof this discrepancy is because the present study used a marginal-electricityapproach whilethe CAT study does notspecify whether itused a marginal or portfolio-average approach More importantly however GHGintensities of electricity have dropped throughoutCalifornia since the CAT study wasdone in 2008 due to the implementation of theRenewable Portfolio Standard (RPS) This progress will continue at least through 2020under the RPS and likely beyond if the cap-and-trade system or successor legislation to AB32stimulates further de-carbonization of the electricity supply As the electricity system is de-carbonized however building-levelefficiency measures willavoid fewer GHG emissions than they would with a ldquodirtierrdquo electricity supply ARBrsquos goal to reduce 26MMTCO2eyr through green building measures and 75 MMTCO2eyr from existing commercial buildingswhich are based on GHG intensity estimates dating from 2008 may therefore needto be revisited to accountfor the drop in GHG intensity of electricity (and by extension water)6

The current study also shows however that a 25 reductioninwater use may be too modest agoal given the much larger usage reductions achieved bycurrent LEED-EBOM buildings especially those seeking the high-performance credit

The apparent effectiveness of additional performance credits instimulating over-performance inwater and waste efficiency is instructive for the formulation of buildingcodes for new construction not just retrofits In a sense the buildings earning these creditsover-performed the predictions of LEED-EBOM itself suggesting that performance-basedcredits in codes and rating systems for new construction could do the same LEED-EBOM was intentionally designed to try to stimulate improvements in underlying codes andstandards and these resultssuggest that continuing updatesof LEED-EBOM could continue to drive market transformation code updates and over-performance byexemplarybuildings (even relativeto updated standards and codes) LEED v4 released too recently toproduce data for this study contains mandatory provisions for water metering and wasteaudits (as opposed tooptional credits) and strengthens the standards in other ways Previous researchby USGBC (Pyke et al 2011) has shownthat averagecredit achievement and associatedGHG co-benefits under LEED for New Construction(not existing buildings)has risen even as the standard has been strengthened with periodic updates

With respect to water use LEED for New Construction (LEED-ND) andCalGreenbothrequire the installation of plumbing fittingsand fixturesthat are expected to achieve a certain water usage rate Indeed this is all it is possible to require at the point ofconstruction since actual usage will only occur after the certification (orcode compliance)has beenachieved The questionis what actual usage rates could be expected from theseplumbing installations Though the character of our data prevented us from answering thisquestiondirectly the results from LEED-EBOMwhich alsorequires minimum fixture and fitting standards (not identicalto those of LEED-NC or CalGreen) but also awards credits formeasurement of actual performance and achievement of specific performance rates is atleast encouraging to the conclusions that new constructioncould over-perform its plumbing ldquopredictionsrdquo

Itcould be argued thatthere is a self-selection biasin these results The buildingsthat chose to seek the water performance credit may have done so knowing that they were

6 This is related to the reasonwhy the greenbuilding targets were not included inthe overall emissions reduction targetsin AB 32 forfearof double-counting the same emissions reduction

37

alreadyperforming verywell and could thereforegain credit points easilywith littleor no extra effort It seems unlikely however that that could fullyexplain such largeover-performance across a set of 71 buildings

With respect to solid waste codes and ratingsystems for new construction are limited torequiring the provision of recycling andorcomposting binsand waste handling facilities LEED-EBOM office buildings that measuredtheir waste diversion ratesbut did not earn the performance credit failed to meet the 50 diversion rate threshold derived from state lawinstead achieving only a 39diversion rate If thisperformance istypical of buildingsrequired to include recycling binsbut not seeking any performance standard it suggeststhat rating systemsand codesfornew construction will need to escalate theirrequirementsin order to meet even a50 threshold much less the 75 diversion ratesthat are sought on astatewide level in the future

For bothwater andwaste the prediction methods produced bytheCalifornia Pollution Control Officers Association (CAPCOA 2010) provide methods for determining the GHGemissions from given levels of water and wasteperformance but theydo not providemethods for predicting the overall water and waste performance levels of a building basedon the specific management strategies that theypursue In that sense prediction of waterand waste performance levels of new construction based on the requirements of codeandor ratingsystems will have tobesimilar to thoseused in this study(ie modeling thewater usage rates based on characteristics of plumbing fixtures and fittings and identifying arough diversion rate target derived from state law andorCalGreen)

For transportation there are morespecific prediction methods available in CAPCOA (2010) thatproject the performance of buildings based onbuilding characteristics mostly having to do with parkingand also building locationThis study used the CAPCOA prediction method that predicts rail mode share based on a buildingrsquosdistance to rail stationsto create the predicted values for transportation AVR Since LEED-EBOM does not require or request buildings to report uponthe strategies that they are pursuing to achieve a givenAVR level but instead only to report onthat AVR level this study does notgenerate any insight even indirectly into the efficacy ofparking management on transportation-related GHG emissions However theCAPCOA prediction method for rail transit useappears tobe overlyldquooptimisticrdquo in predicting more transit-influenced AVRbased on location when deployedusing this studyrsquos method The locationof office buildings (andcommercial buildings generally) is anissue that canonly be addressed systematically through generalplans and zoning codes not through building codes but it is highly important inshaping the transportation behavior of occupants

Studying non-green-certified commercial buildings

Certifiedgreen office buildings are still a very small fraction ofthe overall commercial building stock and state GHG control policies must concernthemselves with all buildings whether certified ldquogreenrdquo or not Many non-certified commercial buildings may alsoperform as well or better than certified greenbuildings especially with respect to transportation which is by far the mostimportantsource of GHG emissions in this context Anon-certified office building if it is located near transit may trigger fewer GHG emissionsthan a certified green office building farther from transit evenif the latter greatly outperforms it on water andwaste management Likewise individual non-certified

38

buildings could excel inwater or waste management without adherence to any givenrating system

To set policies codes and standards intended to reduce emissions from all commercialbuildings additional informationonthe performance of these non-certified buildings will therefore be necessary Currently information on building performance in general is scarceand there is very little transparency in the commercial office building sector in particularLEED itself is anotable advance in this regard andwithout improvedtransparencygenerally it is difficult toimagine substantial improvement in buildingperformance across the entire construction and building managementindustry

Two major surveys of commercial buildings already exist and are conducted ona periodic basis the federal Commercial Building Energy ConsumptionSurvey (CBECS)and the California-wide Commercial End-Use Study (CEUS) These studies are focused on measuring operational energy consumption but given their reach and the fact that theysample the commercial building population in waysthat permit statistical inference to the entirebuilding stock they are likely the most effective vehiclesforgathering information on water waste and transportation performance

The CBECS has alreadyincorporated questions about water useThis was done in the surveyrsquos2007 edition but none of the surveyrsquos data was ever released due to errors in the sampling methodology The 2013 edition data from which are scheduled to be released in 2014 will containinformationontotal building water usage building size and will distinguishbetweenindoor irrigation and cooling tower though notprocess water use(which is not a factor in the present study but is potentially important for other kinds ofcommercial buildings)

Neither survey currently contains any questions pertaining to solid waste management To be of greatest use measurements of solid waste output should be conducted over aspecified reporting period (perhapstwo weeks) and occur at apoint in the year where building occupancy is expectedto be typical (ie notsummerorthe holiday season) This would allowinsight into rates of waste generationnot only the rates of disposal and diversionof the waste generatedLEED-EBOMrsquos reporting format currently allows respondentsto define the period of measurement themselves limiting the ability to analyzewaste generation rates The surveys shouldalsoseek to acquire information on existence ofrecycling andorcomposting facilities both in the workspace and in the collection point in the building

Transportationmeasurement through surveys ismore challenging and can take one of two paths VMT-based or AVR-based reporting This study used the latter for baseline andpredicted values because the measured data used AVRand it may be more appropriate for destination-side measurement since operators of existing buildings cannot be expected to influence the distance thatoccupants commute only (to some degree)the transportation mode that they choose to commuteStudies of new construction where buildinglocation is to some extentdiscretionaryon thepart of thebuilders maydiffer in this regard Importantly using AVR asthe study metric limits researchers to assuming averagecommute lengths rather than acquiring empirical building-specific data on commutelengthswhich can vary in surprising waysfrom first-glance expectations (Pyke 2014)In addition most of the existing transportation research literature does not use AVRwhich reducesthe ability to leverage otherresearch findingsin the analysisof the data

39

AVRinformation could be obtained by either a survey of occupants (either for one day orpreferably aperiod of days) or it could be estimated in most situations bycountingcars in the parking garagelot Although the latter streamlinesthe survey processconsiderably and avoids the needtocontact occupants it will also be the least accurate inthe cases where AVR is highest ie dense urban cores where office buildings may not provide all theirown parking and therefore countingcars could make AVR look even higher than itactually isIf reducing the data-gathering burdenonthe survey respondents is a high priority thenthere could be a two-tier system where only buildings thatdo notprovide all their own parking are required to survey the occupants (otherwise they cancount cars inthe parking lot)

Another downside is that car-counting does not capture people being dropped off byanother driver who does not park at the building The error this would introduce is fairly minimal because this practice rarely accountsformore than a very small percentage of commuters AVR baseline and predicted values could be generated for virtuallyanylocation in the US using the present studyrsquos method Even for locations outside of the metropolitanregions for which the relevant census information iscompiled routinely baseline and predicted AVRs canbe imputed from other geographical scales of census data though areaswithout regionally compiled censusinformation have small enough populations thattransitusage for commuting is likely nearly negligible

In VMT-based analysisestablishment of the baseline would alsoemployregionalcommuting information from the census multiplied by average commute distance To make use of CAPCOA predictionmethods the survey would have to generate detailedinformation on parkingpolicies primarily (including bike parking)as well as policies pertaining to fleet vehicles (if any) Measured datawould havetocomefrom surveydatathat asks occupants directly about their commute modes andthe distance of their automobile commutes as well as usage of fleet vehicles (if any) This is inherently more difficult thana survey limited to askingquestions of a single building managerThe advantages are that VMT is more directly relatedtoGHG emissions than AVR there would be improved analytical insightabout the effect of buildingstrategies on transportation behavior and related GHG emissions and therewould bemuch greater opportunityto leverageexisting research findings on transportation behavior in the analysis

40

Conclusion

This research quantifies for the first time the GHGco-benefits associated with water wasteand transportation aspects of certified green commercial office buildings in California It finds that these buildings do infact achieve significant GHG emissions reductions relative totypical non-green office buildings ndash about 38for water 48for waste and 5for transportation In terms of absolute emissions however savings in transportation dwarfthose of the other sectors because transportationis more than 90 times as GHG-intense per square foot of buildingspace as water use and over 170 times as GHG-intense per squarefoot as solid waste among baseline valuesOverallconversion of the entire stock ofexisting California officebuildings to theperformancestandards achieved bythecertified green office buildings would avoid emissions of about 0831 MMTCO2e per year

Furthermore additional performance incentives for water andwaste within the green rating systemswere found to be effectivein stimulating further resourceuseand emissions reductions These performance improvementswere actually largerthan what isrequired to achieve the extracredits in the LEED-EBOM system suggesting that such incentives may be worth more than ldquoface valuerdquo This finding has particular significance for standards for newconstruction and suggests that incentivizing higher efficiency standards could prompt aldquovirtuouslooprdquowhere buildersseek additional efficiencies beyond code requirements

The three resource areas differed significantly intheir performance relative to predictions for green building performance With respect to GHG emissions the certifiedbuildings performed better thanpredicted on water use (13) slightly better than predicted onwaste diversion (4) and worse than predicted on transportation (-6) The latter is a significant finding given the GHG intensity of transportation and suggeststhat the CAPCOA formula for calculating railmodeshares based on proximityto rail stations mayover-estimateactual rail ridership outcomes Thewidedivergencebetween predicted andmeasured values for water use likewise suggests that efforts should be made to improvewater use prediction methods especially with respect to cooling toweruse

Finally additional insights intocommercial office buildingperformance couldbe gainedbyinserting basic questions on water waste and transportation usage into the CEUS or CBECSsurveys which currently focus onoperational energy use Systematic collection ofperformance data of non-certified commercial office buildings would enable deeper analysisinto the effectiveness ofspecific building design strategies such as parking policiesplacement of recycling andcomposting bins andwater-efficient landscaping in securing GHGemissions reduction co-benefits The findings of this report suggest that importantadditional efficiencies and GHG co-benefits are available inall three resource areas as indeed they must be if the state is tomeet its long-range GHG emissionsgoals

41

Recommendations

The findings of this report imply a number of recommendations for future researchfuture climate policy initiatives and future updates to building standards

Addresstransportation behavior through CalGreen and other building standardsto the greatest possible extentTransportation is so GHG-intense that even small percentageimprovements over baseline such as those reported here can avoid substantial quantitiesof GHG emissions Indeed commercial office buildings stimulate more than twice as muchGHGemission through induced transportation than they do through their own operational energyconsumption (see Table 18)yet operational energy is the subject of detailed code requirementsand standardswhile transportation islargely assumed to be beyond the reach of buildingstandards Locatingbuildings in transit-accessible areas in particular is soimpactful to GHG emissions and so fundamental to facilitating non-automobiletransportation thatitmay be worth more to GHG control efforts (from commercialoffice buildings) than all other foreseeable improvements to green buildingstandards combined Itshould be given an emphasis within CalGreen and other building standards relatedto commercial construction commensurate with that importance

Improve prediction methods for future analysis ofgreen building performanceCAPCOA guidance on the quantification of GHG emissions should be revised and expanded to includemore direct methods for assessing the GHG emissions expected fromspecific water and waste-related building strategies(asopposed to usage levels) especially those related to irrigation and cooling towers In addition the formula for estimating railmode shares from the distance to rail stations should be updated with further research when feasible andultimately expanded to include bus bicycle walking and other non-automobile modes

Improve the information base for assessing regional transportation baselinesThe method for identifying transportation baselines used in this study relied on regional-scale data thatlikely oversimplifies the commuting dynamics ofparticular office cores Recent work byUSGBC (Pyke et al 2014) draws upon aggregated cellular data to establish morefine-grained characterizations of typical commutingpatterns in specific neighborhoods of office buildings Future research inthis veincould establish much more accurate neighborhood-scale baselinesagainst which the transportation behavior of green office building occupantscould be compared Such research might also enable the incorporation of otherdemographic factors that influence commuting behavior andmay co-vary with green building occupancy and enable greaterinsight into commute distances(and by extension vehiclemiles traveled)

Future CalGreen updates shouldsignificantly strengthen plumbing standardsThe predictions for greenbuilding water use were derived from the fixture and fitting standards in the 2010editionof the CalGreencode Giventhat the LEED-EBOM buildings outperformedthese predictions by 27 it appears that significant additional strengtheningof these standards is feasible andjustifiable

Future CalGreen updates should require placement of composting collection facilities within commercial office buildingsAccording to the date shown in Figure 4 a large proportion ofthe un-divertedwaste leaving commercial office buildings and entering landfills is ldquowet wasterdquo ndash ie food and other organic waste that is highin carbon content andtherefore arelatively potent source of methane in landfills Introduction of compost collection facilities

42

would enable this waste to be diverted from landfills far more effectively improvingdiversion rates avoiding unnecessary GHG emissions and creating compost for re-use orresale The current CalGreenrequirement (Section54101) requires provisionof ldquoreadily accessible areasrdquo for the ldquodepositing storage and collectionrdquo of recyclables but does not explicitlyincludeanysuch requirement for compostablematerials

Include questions related to water waste and transportation in the CBECS andor CEUS surveysAs noted in the discussioninsertion of a small number of simple questions in these surveyswould greatly expand the information base foranalysisof GHG co-benefits innon-certified commercial buildings CBECS has already incorporated water questions in its 2013 edition Collection of high-quality transportationdata may involve requiring buildingmanagers to issue surveys to occupants but given the importance of transportation to theoverall GHG emissions footprint of commercial office buildings and the general paucity ofdestination-side commuting data it isworth the extra effort

Encourage information-sharing on operational performance of buildingsThis research was made possible by USGBCrsquos unilateral commitment to share information about projectperformance as part of LEEDrsquos stated goal of market transformation Evenif CBECS and CEUS are revisedas recommendedabove there will still be a needfor muchmore information on the operational performance ofcommercial buildings whether certified as ldquogreenrdquoornot Data sharing and collection should be institutionalized particularly for anyperformance domainthat is claimed to produce public benefit or is cited as evidence ofcompliance with laws and regulations such as AB 32 Building codes including CalGreen could require publicoperational data-sharing aspart of a post-occupancyinspection process Local building permits whether for greenor non-green buildings could alsobe made conditional on commitment to share post-occupancydata subject tolater inspection by local building officials

Expand emphasis on existingbuildings instate and localclimate planning effortsBuilding energyefficiencyand GHG control efforts havehistoricallytended to emphasizecreation of standardsfornew construction asa meansof saving energy and GHGs While thisisgraduallychangingwith the passage of AB 758 and other efforts toestablish standards for renovations the existing building sectorremainsunder-emphasized in climateplanning generally More than one billion square feet of commercial office space alreadyexists in Californiaand bringing this space up to performance standards typical of certified green building would save over 083 MMTCO2e per year Considerably larger improvements beyond that are possible giventhe water and waste performance levels achieved by thehigh-performance buildings in this dataset and given the very large latentpotential for reduction of transportation-related emissionsthrough transit-friendly building siting decisions Itshould also be borne in mind thatthe figures reported in this study are foroffice buildings only additional large savings can be expectedfrom efforts toreduce waterwaste and transportation usage associated with other types of commercial buildings

43

References

American Community Survey 2008-2012 Table B08301 for various counties named in Table 7

ARB[AirResourcesBoard] 2014First Update tothe Climate Change Scoping Plan Building on the FrameworkSacramento ARB

ARB[Air Resources Board] 2008 Climate Change Scoping Plan A Framework for ChangeSacramento RB

ARB[Air Resources Board] 2012a Technical Evaluationof the Greenhouse Gas EmissionReduction Quantification for the Sacramento Area Council of Governmentsrsquo SB375 Sustainable Communities StrategySacramento ARB

ARB[Air Resources Board] 2012b ARBDetermination on Apple CampusMemorandum to Governorrsquos Office of Planning and ResearchSacramento ARB

Blanco H J Newell L Stott and M Alberti 2012 Water Supply Scarcity in Southern California Assessing Water District-Level StrategiesLos Angeles USC Center for Sustainable Cities

California Building Standards Commission 2010 CaliforniaGreen Building Standards Code 2010Title 24Part 11

California Building Standards Commission 2010 CaliforniaPlumbing Code2010

California Department of Water Resources 2010 Water Budget WorkbookVersion 101

CalRecycle 2013 Landfilling of WasteMemorandum downloaded from httparbcagovccwastelandfillingofwastepdf

CalRecycle [fka California IntegratedWaste Management Board] 2006 Targeted Statewide Waste Characterization Study Waste Disposal andDiversion Findings for SelectedIndustry GroupsReport to the Board by Cascadia Consulting Group Sacramento CA IWMB

CAPCOA [California Air Pollution Control Officers Association] 2010 Quantifying Greenhouse Gas Mitigation Measures A Resource for Local Government to Assess Emission Reductions from Greenhouse Gas Mitigation MeasuresSacramento CAPCOA

CAT [Climate Action Team] 2008 Green Building Sector Subgroup Scoping Plan Measure Development and Cost AnalysisSacramento CAT

CBRE 2014 Greater Los Angeles Office MarketViewQuarter 22014

CEC[California EnergyCommission] 2006 Refining Estimates of Water-Related Energy Use in CaliforniaCEC 500-2006-118

Dziegielewski Benedykt et al 2000 Commercial andInstitutional EndUses of WaterDenver American Water Works Association Research Foundation

44

Notably the GHG intensity of electricity assumed for the CAT study (0442 MTCO2eMWh) is also higher than that used in this report (0270 MTCO2eMWh) It is possiblethat someof this discrepancy is because the present study used a marginal-electricityapproach whilethe CAT study does notspecify whether itused a marginal or portfolio-average approach More importantly however GHGintensities of electricity have dropped throughoutCalifornia since the CAT study wasdone in 2008 due to the implementation of theRenewable Portfolio Standard (RPS) This progress will continue at least through 2020under the RPS and likely beyond if the cap-and-trade system or successor legislation to AB32stimulates further de-carbonization of the electricity supply As the electricity system is de-carbonized however building-levelefficiency measures willavoid fewer GHG emissions than they would with a ldquodirtierrdquo electricity supply ARBrsquos goal to reduce 26MMTCO2eyr through green building measures and 75 MMTCO2eyr from existing commercial buildingswhich are based on GHG intensity estimates dating from 2008 may therefore needto be revisited to accountfor the drop in GHG intensity of electricity (and by extension water)6

The current study also shows however that a 25 reductioninwater use may be too modest agoal given the much larger usage reductions achieved bycurrent LEED-EBOM buildings especially those seeking the high-performance credit

The apparent effectiveness of additional performance credits instimulating over-performance inwater and waste efficiency is instructive for the formulation of buildingcodes for new construction not just retrofits In a sense the buildings earning these creditsover-performed the predictions of LEED-EBOM itself suggesting that performance-basedcredits in codes and rating systems for new construction could do the same LEED-EBOM was intentionally designed to try to stimulate improvements in underlying codes andstandards and these resultssuggest that continuing updatesof LEED-EBOM could continue to drive market transformation code updates and over-performance byexemplarybuildings (even relativeto updated standards and codes) LEED v4 released too recently toproduce data for this study contains mandatory provisions for water metering and wasteaudits (as opposed tooptional credits) and strengthens the standards in other ways Previous researchby USGBC (Pyke et al 2011) has shownthat averagecredit achievement and associatedGHG co-benefits under LEED for New Construction(not existing buildings)has risen even as the standard has been strengthened with periodic updates

With respect to water use LEED for New Construction (LEED-ND) andCalGreenbothrequire the installation of plumbing fittingsand fixturesthat are expected to achieve a certain water usage rate Indeed this is all it is possible to require at the point ofconstruction since actual usage will only occur after the certification (orcode compliance)has beenachieved The questionis what actual usage rates could be expected from theseplumbing installations Though the character of our data prevented us from answering thisquestiondirectly the results from LEED-EBOMwhich alsorequires minimum fixture and fitting standards (not identicalto those of LEED-NC or CalGreen) but also awards credits formeasurement of actual performance and achievement of specific performance rates is atleast encouraging to the conclusions that new constructioncould over-perform its plumbing ldquopredictionsrdquo

Itcould be argued thatthere is a self-selection biasin these results The buildingsthat chose to seek the water performance credit may have done so knowing that they were

6 This is related to the reasonwhy the greenbuilding targets were not included inthe overall emissions reduction targetsin AB 32 forfearof double-counting the same emissions reduction

37

alreadyperforming verywell and could thereforegain credit points easilywith littleor no extra effort It seems unlikely however that that could fullyexplain such largeover-performance across a set of 71 buildings

With respect to solid waste codes and ratingsystems for new construction are limited torequiring the provision of recycling andorcomposting binsand waste handling facilities LEED-EBOM office buildings that measuredtheir waste diversion ratesbut did not earn the performance credit failed to meet the 50 diversion rate threshold derived from state lawinstead achieving only a 39diversion rate If thisperformance istypical of buildingsrequired to include recycling binsbut not seeking any performance standard it suggeststhat rating systemsand codesfornew construction will need to escalate theirrequirementsin order to meet even a50 threshold much less the 75 diversion ratesthat are sought on astatewide level in the future

For bothwater andwaste the prediction methods produced bytheCalifornia Pollution Control Officers Association (CAPCOA 2010) provide methods for determining the GHGemissions from given levels of water and wasteperformance but theydo not providemethods for predicting the overall water and waste performance levels of a building basedon the specific management strategies that theypursue In that sense prediction of waterand waste performance levels of new construction based on the requirements of codeandor ratingsystems will have tobesimilar to thoseused in this study(ie modeling thewater usage rates based on characteristics of plumbing fixtures and fittings and identifying arough diversion rate target derived from state law andorCalGreen)

For transportation there are morespecific prediction methods available in CAPCOA (2010) thatproject the performance of buildings based onbuilding characteristics mostly having to do with parkingand also building locationThis study used the CAPCOA prediction method that predicts rail mode share based on a buildingrsquosdistance to rail stationsto create the predicted values for transportation AVR Since LEED-EBOM does not require or request buildings to report uponthe strategies that they are pursuing to achieve a givenAVR level but instead only to report onthat AVR level this study does notgenerate any insight even indirectly into the efficacy ofparking management on transportation-related GHG emissions However theCAPCOA prediction method for rail transit useappears tobe overlyldquooptimisticrdquo in predicting more transit-influenced AVRbased on location when deployedusing this studyrsquos method The locationof office buildings (andcommercial buildings generally) is anissue that canonly be addressed systematically through generalplans and zoning codes not through building codes but it is highly important inshaping the transportation behavior of occupants

Studying non-green-certified commercial buildings

Certifiedgreen office buildings are still a very small fraction ofthe overall commercial building stock and state GHG control policies must concernthemselves with all buildings whether certified ldquogreenrdquo or not Many non-certified commercial buildings may alsoperform as well or better than certified greenbuildings especially with respect to transportation which is by far the mostimportantsource of GHG emissions in this context Anon-certified office building if it is located near transit may trigger fewer GHG emissionsthan a certified green office building farther from transit evenif the latter greatly outperforms it on water andwaste management Likewise individual non-certified

38

buildings could excel inwater or waste management without adherence to any givenrating system

To set policies codes and standards intended to reduce emissions from all commercialbuildings additional informationonthe performance of these non-certified buildings will therefore be necessary Currently information on building performance in general is scarceand there is very little transparency in the commercial office building sector in particularLEED itself is anotable advance in this regard andwithout improvedtransparencygenerally it is difficult toimagine substantial improvement in buildingperformance across the entire construction and building managementindustry

Two major surveys of commercial buildings already exist and are conducted ona periodic basis the federal Commercial Building Energy ConsumptionSurvey (CBECS)and the California-wide Commercial End-Use Study (CEUS) These studies are focused on measuring operational energy consumption but given their reach and the fact that theysample the commercial building population in waysthat permit statistical inference to the entirebuilding stock they are likely the most effective vehiclesforgathering information on water waste and transportation performance

The CBECS has alreadyincorporated questions about water useThis was done in the surveyrsquos2007 edition but none of the surveyrsquos data was ever released due to errors in the sampling methodology The 2013 edition data from which are scheduled to be released in 2014 will containinformationontotal building water usage building size and will distinguishbetweenindoor irrigation and cooling tower though notprocess water use(which is not a factor in the present study but is potentially important for other kinds ofcommercial buildings)

Neither survey currently contains any questions pertaining to solid waste management To be of greatest use measurements of solid waste output should be conducted over aspecified reporting period (perhapstwo weeks) and occur at apoint in the year where building occupancy is expectedto be typical (ie notsummerorthe holiday season) This would allowinsight into rates of waste generationnot only the rates of disposal and diversionof the waste generatedLEED-EBOMrsquos reporting format currently allows respondentsto define the period of measurement themselves limiting the ability to analyzewaste generation rates The surveys shouldalsoseek to acquire information on existence ofrecycling andorcomposting facilities both in the workspace and in the collection point in the building

Transportationmeasurement through surveys ismore challenging and can take one of two paths VMT-based or AVR-based reporting This study used the latter for baseline andpredicted values because the measured data used AVRand it may be more appropriate for destination-side measurement since operators of existing buildings cannot be expected to influence the distance thatoccupants commute only (to some degree)the transportation mode that they choose to commuteStudies of new construction where buildinglocation is to some extentdiscretionaryon thepart of thebuilders maydiffer in this regard Importantly using AVR asthe study metric limits researchers to assuming averagecommute lengths rather than acquiring empirical building-specific data on commutelengthswhich can vary in surprising waysfrom first-glance expectations (Pyke 2014)In addition most of the existing transportation research literature does not use AVRwhich reducesthe ability to leverage otherresearch findingsin the analysisof the data

39

AVRinformation could be obtained by either a survey of occupants (either for one day orpreferably aperiod of days) or it could be estimated in most situations bycountingcars in the parking garagelot Although the latter streamlinesthe survey processconsiderably and avoids the needtocontact occupants it will also be the least accurate inthe cases where AVR is highest ie dense urban cores where office buildings may not provide all theirown parking and therefore countingcars could make AVR look even higher than itactually isIf reducing the data-gathering burdenonthe survey respondents is a high priority thenthere could be a two-tier system where only buildings thatdo notprovide all their own parking are required to survey the occupants (otherwise they cancount cars inthe parking lot)

Another downside is that car-counting does not capture people being dropped off byanother driver who does not park at the building The error this would introduce is fairly minimal because this practice rarely accountsformore than a very small percentage of commuters AVR baseline and predicted values could be generated for virtuallyanylocation in the US using the present studyrsquos method Even for locations outside of the metropolitanregions for which the relevant census information iscompiled routinely baseline and predicted AVRs canbe imputed from other geographical scales of census data though areaswithout regionally compiled censusinformation have small enough populations thattransitusage for commuting is likely nearly negligible

In VMT-based analysisestablishment of the baseline would alsoemployregionalcommuting information from the census multiplied by average commute distance To make use of CAPCOA predictionmethods the survey would have to generate detailedinformation on parkingpolicies primarily (including bike parking)as well as policies pertaining to fleet vehicles (if any) Measured datawould havetocomefrom surveydatathat asks occupants directly about their commute modes andthe distance of their automobile commutes as well as usage of fleet vehicles (if any) This is inherently more difficult thana survey limited to askingquestions of a single building managerThe advantages are that VMT is more directly relatedtoGHG emissions than AVR there would be improved analytical insightabout the effect of buildingstrategies on transportation behavior and related GHG emissions and therewould bemuch greater opportunityto leverageexisting research findings on transportation behavior in the analysis

40

Conclusion

This research quantifies for the first time the GHGco-benefits associated with water wasteand transportation aspects of certified green commercial office buildings in California It finds that these buildings do infact achieve significant GHG emissions reductions relative totypical non-green office buildings ndash about 38for water 48for waste and 5for transportation In terms of absolute emissions however savings in transportation dwarfthose of the other sectors because transportationis more than 90 times as GHG-intense per square foot of buildingspace as water use and over 170 times as GHG-intense per squarefoot as solid waste among baseline valuesOverallconversion of the entire stock ofexisting California officebuildings to theperformancestandards achieved bythecertified green office buildings would avoid emissions of about 0831 MMTCO2e per year

Furthermore additional performance incentives for water andwaste within the green rating systemswere found to be effectivein stimulating further resourceuseand emissions reductions These performance improvementswere actually largerthan what isrequired to achieve the extracredits in the LEED-EBOM system suggesting that such incentives may be worth more than ldquoface valuerdquo This finding has particular significance for standards for newconstruction and suggests that incentivizing higher efficiency standards could prompt aldquovirtuouslooprdquowhere buildersseek additional efficiencies beyond code requirements

The three resource areas differed significantly intheir performance relative to predictions for green building performance With respect to GHG emissions the certifiedbuildings performed better thanpredicted on water use (13) slightly better than predicted onwaste diversion (4) and worse than predicted on transportation (-6) The latter is a significant finding given the GHG intensity of transportation and suggeststhat the CAPCOA formula for calculating railmodeshares based on proximityto rail stations mayover-estimateactual rail ridership outcomes Thewidedivergencebetween predicted andmeasured values for water use likewise suggests that efforts should be made to improvewater use prediction methods especially with respect to cooling toweruse

Finally additional insights intocommercial office buildingperformance couldbe gainedbyinserting basic questions on water waste and transportation usage into the CEUS or CBECSsurveys which currently focus onoperational energy use Systematic collection ofperformance data of non-certified commercial office buildings would enable deeper analysisinto the effectiveness ofspecific building design strategies such as parking policiesplacement of recycling andcomposting bins andwater-efficient landscaping in securing GHGemissions reduction co-benefits The findings of this report suggest that importantadditional efficiencies and GHG co-benefits are available inall three resource areas as indeed they must be if the state is tomeet its long-range GHG emissionsgoals

41

Recommendations

The findings of this report imply a number of recommendations for future researchfuture climate policy initiatives and future updates to building standards

Addresstransportation behavior through CalGreen and other building standardsto the greatest possible extentTransportation is so GHG-intense that even small percentageimprovements over baseline such as those reported here can avoid substantial quantitiesof GHG emissions Indeed commercial office buildings stimulate more than twice as muchGHGemission through induced transportation than they do through their own operational energyconsumption (see Table 18)yet operational energy is the subject of detailed code requirementsand standardswhile transportation islargely assumed to be beyond the reach of buildingstandards Locatingbuildings in transit-accessible areas in particular is soimpactful to GHG emissions and so fundamental to facilitating non-automobiletransportation thatitmay be worth more to GHG control efforts (from commercialoffice buildings) than all other foreseeable improvements to green buildingstandards combined Itshould be given an emphasis within CalGreen and other building standards relatedto commercial construction commensurate with that importance

Improve prediction methods for future analysis ofgreen building performanceCAPCOA guidance on the quantification of GHG emissions should be revised and expanded to includemore direct methods for assessing the GHG emissions expected fromspecific water and waste-related building strategies(asopposed to usage levels) especially those related to irrigation and cooling towers In addition the formula for estimating railmode shares from the distance to rail stations should be updated with further research when feasible andultimately expanded to include bus bicycle walking and other non-automobile modes

Improve the information base for assessing regional transportation baselinesThe method for identifying transportation baselines used in this study relied on regional-scale data thatlikely oversimplifies the commuting dynamics ofparticular office cores Recent work byUSGBC (Pyke et al 2014) draws upon aggregated cellular data to establish morefine-grained characterizations of typical commutingpatterns in specific neighborhoods of office buildings Future research inthis veincould establish much more accurate neighborhood-scale baselinesagainst which the transportation behavior of green office building occupantscould be compared Such research might also enable the incorporation of otherdemographic factors that influence commuting behavior andmay co-vary with green building occupancy and enable greaterinsight into commute distances(and by extension vehiclemiles traveled)

Future CalGreen updates shouldsignificantly strengthen plumbing standardsThe predictions for greenbuilding water use were derived from the fixture and fitting standards in the 2010editionof the CalGreencode Giventhat the LEED-EBOM buildings outperformedthese predictions by 27 it appears that significant additional strengtheningof these standards is feasible andjustifiable

Future CalGreen updates should require placement of composting collection facilities within commercial office buildingsAccording to the date shown in Figure 4 a large proportion ofthe un-divertedwaste leaving commercial office buildings and entering landfills is ldquowet wasterdquo ndash ie food and other organic waste that is highin carbon content andtherefore arelatively potent source of methane in landfills Introduction of compost collection facilities

42

would enable this waste to be diverted from landfills far more effectively improvingdiversion rates avoiding unnecessary GHG emissions and creating compost for re-use orresale The current CalGreenrequirement (Section54101) requires provisionof ldquoreadily accessible areasrdquo for the ldquodepositing storage and collectionrdquo of recyclables but does not explicitlyincludeanysuch requirement for compostablematerials

Include questions related to water waste and transportation in the CBECS andor CEUS surveysAs noted in the discussioninsertion of a small number of simple questions in these surveyswould greatly expand the information base foranalysisof GHG co-benefits innon-certified commercial buildings CBECS has already incorporated water questions in its 2013 edition Collection of high-quality transportationdata may involve requiring buildingmanagers to issue surveys to occupants but given the importance of transportation to theoverall GHG emissions footprint of commercial office buildings and the general paucity ofdestination-side commuting data it isworth the extra effort

Encourage information-sharing on operational performance of buildingsThis research was made possible by USGBCrsquos unilateral commitment to share information about projectperformance as part of LEEDrsquos stated goal of market transformation Evenif CBECS and CEUS are revisedas recommendedabove there will still be a needfor muchmore information on the operational performance ofcommercial buildings whether certified as ldquogreenrdquoornot Data sharing and collection should be institutionalized particularly for anyperformance domainthat is claimed to produce public benefit or is cited as evidence ofcompliance with laws and regulations such as AB 32 Building codes including CalGreen could require publicoperational data-sharing aspart of a post-occupancyinspection process Local building permits whether for greenor non-green buildings could alsobe made conditional on commitment to share post-occupancydata subject tolater inspection by local building officials

Expand emphasis on existingbuildings instate and localclimate planning effortsBuilding energyefficiencyand GHG control efforts havehistoricallytended to emphasizecreation of standardsfornew construction asa meansof saving energy and GHGs While thisisgraduallychangingwith the passage of AB 758 and other efforts toestablish standards for renovations the existing building sectorremainsunder-emphasized in climateplanning generally More than one billion square feet of commercial office space alreadyexists in Californiaand bringing this space up to performance standards typical of certified green building would save over 083 MMTCO2e per year Considerably larger improvements beyond that are possible giventhe water and waste performance levels achieved by thehigh-performance buildings in this dataset and given the very large latentpotential for reduction of transportation-related emissionsthrough transit-friendly building siting decisions Itshould also be borne in mind thatthe figures reported in this study are foroffice buildings only additional large savings can be expectedfrom efforts toreduce waterwaste and transportation usage associated with other types of commercial buildings

43

References

American Community Survey 2008-2012 Table B08301 for various counties named in Table 7

ARB[AirResourcesBoard] 2014First Update tothe Climate Change Scoping Plan Building on the FrameworkSacramento ARB

ARB[Air Resources Board] 2008 Climate Change Scoping Plan A Framework for ChangeSacramento RB

ARB[Air Resources Board] 2012a Technical Evaluationof the Greenhouse Gas EmissionReduction Quantification for the Sacramento Area Council of Governmentsrsquo SB375 Sustainable Communities StrategySacramento ARB

ARB[Air Resources Board] 2012b ARBDetermination on Apple CampusMemorandum to Governorrsquos Office of Planning and ResearchSacramento ARB

Blanco H J Newell L Stott and M Alberti 2012 Water Supply Scarcity in Southern California Assessing Water District-Level StrategiesLos Angeles USC Center for Sustainable Cities

California Building Standards Commission 2010 CaliforniaGreen Building Standards Code 2010Title 24Part 11

California Building Standards Commission 2010 CaliforniaPlumbing Code2010

California Department of Water Resources 2010 Water Budget WorkbookVersion 101

CalRecycle 2013 Landfilling of WasteMemorandum downloaded from httparbcagovccwastelandfillingofwastepdf

CalRecycle [fka California IntegratedWaste Management Board] 2006 Targeted Statewide Waste Characterization Study Waste Disposal andDiversion Findings for SelectedIndustry GroupsReport to the Board by Cascadia Consulting Group Sacramento CA IWMB

CAPCOA [California Air Pollution Control Officers Association] 2010 Quantifying Greenhouse Gas Mitigation Measures A Resource for Local Government to Assess Emission Reductions from Greenhouse Gas Mitigation MeasuresSacramento CAPCOA

CAT [Climate Action Team] 2008 Green Building Sector Subgroup Scoping Plan Measure Development and Cost AnalysisSacramento CAT

CBRE 2014 Greater Los Angeles Office MarketViewQuarter 22014

CEC[California EnergyCommission] 2006 Refining Estimates of Water-Related Energy Use in CaliforniaCEC 500-2006-118

Dziegielewski Benedykt et al 2000 Commercial andInstitutional EndUses of WaterDenver American Water Works Association Research Foundation

44

alreadyperforming verywell and could thereforegain credit points easilywith littleor no extra effort It seems unlikely however that that could fullyexplain such largeover-performance across a set of 71 buildings

With respect to solid waste codes and ratingsystems for new construction are limited torequiring the provision of recycling andorcomposting binsand waste handling facilities LEED-EBOM office buildings that measuredtheir waste diversion ratesbut did not earn the performance credit failed to meet the 50 diversion rate threshold derived from state lawinstead achieving only a 39diversion rate If thisperformance istypical of buildingsrequired to include recycling binsbut not seeking any performance standard it suggeststhat rating systemsand codesfornew construction will need to escalate theirrequirementsin order to meet even a50 threshold much less the 75 diversion ratesthat are sought on astatewide level in the future

For bothwater andwaste the prediction methods produced bytheCalifornia Pollution Control Officers Association (CAPCOA 2010) provide methods for determining the GHGemissions from given levels of water and wasteperformance but theydo not providemethods for predicting the overall water and waste performance levels of a building basedon the specific management strategies that theypursue In that sense prediction of waterand waste performance levels of new construction based on the requirements of codeandor ratingsystems will have tobesimilar to thoseused in this study(ie modeling thewater usage rates based on characteristics of plumbing fixtures and fittings and identifying arough diversion rate target derived from state law andorCalGreen)

For transportation there are morespecific prediction methods available in CAPCOA (2010) thatproject the performance of buildings based onbuilding characteristics mostly having to do with parkingand also building locationThis study used the CAPCOA prediction method that predicts rail mode share based on a buildingrsquosdistance to rail stationsto create the predicted values for transportation AVR Since LEED-EBOM does not require or request buildings to report uponthe strategies that they are pursuing to achieve a givenAVR level but instead only to report onthat AVR level this study does notgenerate any insight even indirectly into the efficacy ofparking management on transportation-related GHG emissions However theCAPCOA prediction method for rail transit useappears tobe overlyldquooptimisticrdquo in predicting more transit-influenced AVRbased on location when deployedusing this studyrsquos method The locationof office buildings (andcommercial buildings generally) is anissue that canonly be addressed systematically through generalplans and zoning codes not through building codes but it is highly important inshaping the transportation behavior of occupants

Studying non-green-certified commercial buildings

Certifiedgreen office buildings are still a very small fraction ofthe overall commercial building stock and state GHG control policies must concernthemselves with all buildings whether certified ldquogreenrdquo or not Many non-certified commercial buildings may alsoperform as well or better than certified greenbuildings especially with respect to transportation which is by far the mostimportantsource of GHG emissions in this context Anon-certified office building if it is located near transit may trigger fewer GHG emissionsthan a certified green office building farther from transit evenif the latter greatly outperforms it on water andwaste management Likewise individual non-certified

38

buildings could excel inwater or waste management without adherence to any givenrating system

To set policies codes and standards intended to reduce emissions from all commercialbuildings additional informationonthe performance of these non-certified buildings will therefore be necessary Currently information on building performance in general is scarceand there is very little transparency in the commercial office building sector in particularLEED itself is anotable advance in this regard andwithout improvedtransparencygenerally it is difficult toimagine substantial improvement in buildingperformance across the entire construction and building managementindustry

Two major surveys of commercial buildings already exist and are conducted ona periodic basis the federal Commercial Building Energy ConsumptionSurvey (CBECS)and the California-wide Commercial End-Use Study (CEUS) These studies are focused on measuring operational energy consumption but given their reach and the fact that theysample the commercial building population in waysthat permit statistical inference to the entirebuilding stock they are likely the most effective vehiclesforgathering information on water waste and transportation performance

The CBECS has alreadyincorporated questions about water useThis was done in the surveyrsquos2007 edition but none of the surveyrsquos data was ever released due to errors in the sampling methodology The 2013 edition data from which are scheduled to be released in 2014 will containinformationontotal building water usage building size and will distinguishbetweenindoor irrigation and cooling tower though notprocess water use(which is not a factor in the present study but is potentially important for other kinds ofcommercial buildings)

Neither survey currently contains any questions pertaining to solid waste management To be of greatest use measurements of solid waste output should be conducted over aspecified reporting period (perhapstwo weeks) and occur at apoint in the year where building occupancy is expectedto be typical (ie notsummerorthe holiday season) This would allowinsight into rates of waste generationnot only the rates of disposal and diversionof the waste generatedLEED-EBOMrsquos reporting format currently allows respondentsto define the period of measurement themselves limiting the ability to analyzewaste generation rates The surveys shouldalsoseek to acquire information on existence ofrecycling andorcomposting facilities both in the workspace and in the collection point in the building

Transportationmeasurement through surveys ismore challenging and can take one of two paths VMT-based or AVR-based reporting This study used the latter for baseline andpredicted values because the measured data used AVRand it may be more appropriate for destination-side measurement since operators of existing buildings cannot be expected to influence the distance thatoccupants commute only (to some degree)the transportation mode that they choose to commuteStudies of new construction where buildinglocation is to some extentdiscretionaryon thepart of thebuilders maydiffer in this regard Importantly using AVR asthe study metric limits researchers to assuming averagecommute lengths rather than acquiring empirical building-specific data on commutelengthswhich can vary in surprising waysfrom first-glance expectations (Pyke 2014)In addition most of the existing transportation research literature does not use AVRwhich reducesthe ability to leverage otherresearch findingsin the analysisof the data

39

AVRinformation could be obtained by either a survey of occupants (either for one day orpreferably aperiod of days) or it could be estimated in most situations bycountingcars in the parking garagelot Although the latter streamlinesthe survey processconsiderably and avoids the needtocontact occupants it will also be the least accurate inthe cases where AVR is highest ie dense urban cores where office buildings may not provide all theirown parking and therefore countingcars could make AVR look even higher than itactually isIf reducing the data-gathering burdenonthe survey respondents is a high priority thenthere could be a two-tier system where only buildings thatdo notprovide all their own parking are required to survey the occupants (otherwise they cancount cars inthe parking lot)

Another downside is that car-counting does not capture people being dropped off byanother driver who does not park at the building The error this would introduce is fairly minimal because this practice rarely accountsformore than a very small percentage of commuters AVR baseline and predicted values could be generated for virtuallyanylocation in the US using the present studyrsquos method Even for locations outside of the metropolitanregions for which the relevant census information iscompiled routinely baseline and predicted AVRs canbe imputed from other geographical scales of census data though areaswithout regionally compiled censusinformation have small enough populations thattransitusage for commuting is likely nearly negligible

In VMT-based analysisestablishment of the baseline would alsoemployregionalcommuting information from the census multiplied by average commute distance To make use of CAPCOA predictionmethods the survey would have to generate detailedinformation on parkingpolicies primarily (including bike parking)as well as policies pertaining to fleet vehicles (if any) Measured datawould havetocomefrom surveydatathat asks occupants directly about their commute modes andthe distance of their automobile commutes as well as usage of fleet vehicles (if any) This is inherently more difficult thana survey limited to askingquestions of a single building managerThe advantages are that VMT is more directly relatedtoGHG emissions than AVR there would be improved analytical insightabout the effect of buildingstrategies on transportation behavior and related GHG emissions and therewould bemuch greater opportunityto leverageexisting research findings on transportation behavior in the analysis

40

Conclusion

This research quantifies for the first time the GHGco-benefits associated with water wasteand transportation aspects of certified green commercial office buildings in California It finds that these buildings do infact achieve significant GHG emissions reductions relative totypical non-green office buildings ndash about 38for water 48for waste and 5for transportation In terms of absolute emissions however savings in transportation dwarfthose of the other sectors because transportationis more than 90 times as GHG-intense per square foot of buildingspace as water use and over 170 times as GHG-intense per squarefoot as solid waste among baseline valuesOverallconversion of the entire stock ofexisting California officebuildings to theperformancestandards achieved bythecertified green office buildings would avoid emissions of about 0831 MMTCO2e per year

Furthermore additional performance incentives for water andwaste within the green rating systemswere found to be effectivein stimulating further resourceuseand emissions reductions These performance improvementswere actually largerthan what isrequired to achieve the extracredits in the LEED-EBOM system suggesting that such incentives may be worth more than ldquoface valuerdquo This finding has particular significance for standards for newconstruction and suggests that incentivizing higher efficiency standards could prompt aldquovirtuouslooprdquowhere buildersseek additional efficiencies beyond code requirements

The three resource areas differed significantly intheir performance relative to predictions for green building performance With respect to GHG emissions the certifiedbuildings performed better thanpredicted on water use (13) slightly better than predicted onwaste diversion (4) and worse than predicted on transportation (-6) The latter is a significant finding given the GHG intensity of transportation and suggeststhat the CAPCOA formula for calculating railmodeshares based on proximityto rail stations mayover-estimateactual rail ridership outcomes Thewidedivergencebetween predicted andmeasured values for water use likewise suggests that efforts should be made to improvewater use prediction methods especially with respect to cooling toweruse

Finally additional insights intocommercial office buildingperformance couldbe gainedbyinserting basic questions on water waste and transportation usage into the CEUS or CBECSsurveys which currently focus onoperational energy use Systematic collection ofperformance data of non-certified commercial office buildings would enable deeper analysisinto the effectiveness ofspecific building design strategies such as parking policiesplacement of recycling andcomposting bins andwater-efficient landscaping in securing GHGemissions reduction co-benefits The findings of this report suggest that importantadditional efficiencies and GHG co-benefits are available inall three resource areas as indeed they must be if the state is tomeet its long-range GHG emissionsgoals

41

Recommendations

The findings of this report imply a number of recommendations for future researchfuture climate policy initiatives and future updates to building standards

Addresstransportation behavior through CalGreen and other building standardsto the greatest possible extentTransportation is so GHG-intense that even small percentageimprovements over baseline such as those reported here can avoid substantial quantitiesof GHG emissions Indeed commercial office buildings stimulate more than twice as muchGHGemission through induced transportation than they do through their own operational energyconsumption (see Table 18)yet operational energy is the subject of detailed code requirementsand standardswhile transportation islargely assumed to be beyond the reach of buildingstandards Locatingbuildings in transit-accessible areas in particular is soimpactful to GHG emissions and so fundamental to facilitating non-automobiletransportation thatitmay be worth more to GHG control efforts (from commercialoffice buildings) than all other foreseeable improvements to green buildingstandards combined Itshould be given an emphasis within CalGreen and other building standards relatedto commercial construction commensurate with that importance

Improve prediction methods for future analysis ofgreen building performanceCAPCOA guidance on the quantification of GHG emissions should be revised and expanded to includemore direct methods for assessing the GHG emissions expected fromspecific water and waste-related building strategies(asopposed to usage levels) especially those related to irrigation and cooling towers In addition the formula for estimating railmode shares from the distance to rail stations should be updated with further research when feasible andultimately expanded to include bus bicycle walking and other non-automobile modes

Improve the information base for assessing regional transportation baselinesThe method for identifying transportation baselines used in this study relied on regional-scale data thatlikely oversimplifies the commuting dynamics ofparticular office cores Recent work byUSGBC (Pyke et al 2014) draws upon aggregated cellular data to establish morefine-grained characterizations of typical commutingpatterns in specific neighborhoods of office buildings Future research inthis veincould establish much more accurate neighborhood-scale baselinesagainst which the transportation behavior of green office building occupantscould be compared Such research might also enable the incorporation of otherdemographic factors that influence commuting behavior andmay co-vary with green building occupancy and enable greaterinsight into commute distances(and by extension vehiclemiles traveled)

Future CalGreen updates shouldsignificantly strengthen plumbing standardsThe predictions for greenbuilding water use were derived from the fixture and fitting standards in the 2010editionof the CalGreencode Giventhat the LEED-EBOM buildings outperformedthese predictions by 27 it appears that significant additional strengtheningof these standards is feasible andjustifiable

Future CalGreen updates should require placement of composting collection facilities within commercial office buildingsAccording to the date shown in Figure 4 a large proportion ofthe un-divertedwaste leaving commercial office buildings and entering landfills is ldquowet wasterdquo ndash ie food and other organic waste that is highin carbon content andtherefore arelatively potent source of methane in landfills Introduction of compost collection facilities

42

would enable this waste to be diverted from landfills far more effectively improvingdiversion rates avoiding unnecessary GHG emissions and creating compost for re-use orresale The current CalGreenrequirement (Section54101) requires provisionof ldquoreadily accessible areasrdquo for the ldquodepositing storage and collectionrdquo of recyclables but does not explicitlyincludeanysuch requirement for compostablematerials

Include questions related to water waste and transportation in the CBECS andor CEUS surveysAs noted in the discussioninsertion of a small number of simple questions in these surveyswould greatly expand the information base foranalysisof GHG co-benefits innon-certified commercial buildings CBECS has already incorporated water questions in its 2013 edition Collection of high-quality transportationdata may involve requiring buildingmanagers to issue surveys to occupants but given the importance of transportation to theoverall GHG emissions footprint of commercial office buildings and the general paucity ofdestination-side commuting data it isworth the extra effort

Encourage information-sharing on operational performance of buildingsThis research was made possible by USGBCrsquos unilateral commitment to share information about projectperformance as part of LEEDrsquos stated goal of market transformation Evenif CBECS and CEUS are revisedas recommendedabove there will still be a needfor muchmore information on the operational performance ofcommercial buildings whether certified as ldquogreenrdquoornot Data sharing and collection should be institutionalized particularly for anyperformance domainthat is claimed to produce public benefit or is cited as evidence ofcompliance with laws and regulations such as AB 32 Building codes including CalGreen could require publicoperational data-sharing aspart of a post-occupancyinspection process Local building permits whether for greenor non-green buildings could alsobe made conditional on commitment to share post-occupancydata subject tolater inspection by local building officials

Expand emphasis on existingbuildings instate and localclimate planning effortsBuilding energyefficiencyand GHG control efforts havehistoricallytended to emphasizecreation of standardsfornew construction asa meansof saving energy and GHGs While thisisgraduallychangingwith the passage of AB 758 and other efforts toestablish standards for renovations the existing building sectorremainsunder-emphasized in climateplanning generally More than one billion square feet of commercial office space alreadyexists in Californiaand bringing this space up to performance standards typical of certified green building would save over 083 MMTCO2e per year Considerably larger improvements beyond that are possible giventhe water and waste performance levels achieved by thehigh-performance buildings in this dataset and given the very large latentpotential for reduction of transportation-related emissionsthrough transit-friendly building siting decisions Itshould also be borne in mind thatthe figures reported in this study are foroffice buildings only additional large savings can be expectedfrom efforts toreduce waterwaste and transportation usage associated with other types of commercial buildings

43

References

American Community Survey 2008-2012 Table B08301 for various counties named in Table 7

ARB[AirResourcesBoard] 2014First Update tothe Climate Change Scoping Plan Building on the FrameworkSacramento ARB

ARB[Air Resources Board] 2008 Climate Change Scoping Plan A Framework for ChangeSacramento RB

ARB[Air Resources Board] 2012a Technical Evaluationof the Greenhouse Gas EmissionReduction Quantification for the Sacramento Area Council of Governmentsrsquo SB375 Sustainable Communities StrategySacramento ARB

ARB[Air Resources Board] 2012b ARBDetermination on Apple CampusMemorandum to Governorrsquos Office of Planning and ResearchSacramento ARB

Blanco H J Newell L Stott and M Alberti 2012 Water Supply Scarcity in Southern California Assessing Water District-Level StrategiesLos Angeles USC Center for Sustainable Cities

California Building Standards Commission 2010 CaliforniaGreen Building Standards Code 2010Title 24Part 11

California Building Standards Commission 2010 CaliforniaPlumbing Code2010

California Department of Water Resources 2010 Water Budget WorkbookVersion 101

CalRecycle 2013 Landfilling of WasteMemorandum downloaded from httparbcagovccwastelandfillingofwastepdf

CalRecycle [fka California IntegratedWaste Management Board] 2006 Targeted Statewide Waste Characterization Study Waste Disposal andDiversion Findings for SelectedIndustry GroupsReport to the Board by Cascadia Consulting Group Sacramento CA IWMB

CAPCOA [California Air Pollution Control Officers Association] 2010 Quantifying Greenhouse Gas Mitigation Measures A Resource for Local Government to Assess Emission Reductions from Greenhouse Gas Mitigation MeasuresSacramento CAPCOA

CAT [Climate Action Team] 2008 Green Building Sector Subgroup Scoping Plan Measure Development and Cost AnalysisSacramento CAT

CBRE 2014 Greater Los Angeles Office MarketViewQuarter 22014

CEC[California EnergyCommission] 2006 Refining Estimates of Water-Related Energy Use in CaliforniaCEC 500-2006-118

Dziegielewski Benedykt et al 2000 Commercial andInstitutional EndUses of WaterDenver American Water Works Association Research Foundation

44

buildings could excel inwater or waste management without adherence to any givenrating system

To set policies codes and standards intended to reduce emissions from all commercialbuildings additional informationonthe performance of these non-certified buildings will therefore be necessary Currently information on building performance in general is scarceand there is very little transparency in the commercial office building sector in particularLEED itself is anotable advance in this regard andwithout improvedtransparencygenerally it is difficult toimagine substantial improvement in buildingperformance across the entire construction and building managementindustry

Two major surveys of commercial buildings already exist and are conducted ona periodic basis the federal Commercial Building Energy ConsumptionSurvey (CBECS)and the California-wide Commercial End-Use Study (CEUS) These studies are focused on measuring operational energy consumption but given their reach and the fact that theysample the commercial building population in waysthat permit statistical inference to the entirebuilding stock they are likely the most effective vehiclesforgathering information on water waste and transportation performance

The CBECS has alreadyincorporated questions about water useThis was done in the surveyrsquos2007 edition but none of the surveyrsquos data was ever released due to errors in the sampling methodology The 2013 edition data from which are scheduled to be released in 2014 will containinformationontotal building water usage building size and will distinguishbetweenindoor irrigation and cooling tower though notprocess water use(which is not a factor in the present study but is potentially important for other kinds ofcommercial buildings)

Neither survey currently contains any questions pertaining to solid waste management To be of greatest use measurements of solid waste output should be conducted over aspecified reporting period (perhapstwo weeks) and occur at apoint in the year where building occupancy is expectedto be typical (ie notsummerorthe holiday season) This would allowinsight into rates of waste generationnot only the rates of disposal and diversionof the waste generatedLEED-EBOMrsquos reporting format currently allows respondentsto define the period of measurement themselves limiting the ability to analyzewaste generation rates The surveys shouldalsoseek to acquire information on existence ofrecycling andorcomposting facilities both in the workspace and in the collection point in the building

Transportationmeasurement through surveys ismore challenging and can take one of two paths VMT-based or AVR-based reporting This study used the latter for baseline andpredicted values because the measured data used AVRand it may be more appropriate for destination-side measurement since operators of existing buildings cannot be expected to influence the distance thatoccupants commute only (to some degree)the transportation mode that they choose to commuteStudies of new construction where buildinglocation is to some extentdiscretionaryon thepart of thebuilders maydiffer in this regard Importantly using AVR asthe study metric limits researchers to assuming averagecommute lengths rather than acquiring empirical building-specific data on commutelengthswhich can vary in surprising waysfrom first-glance expectations (Pyke 2014)In addition most of the existing transportation research literature does not use AVRwhich reducesthe ability to leverage otherresearch findingsin the analysisof the data

39

AVRinformation could be obtained by either a survey of occupants (either for one day orpreferably aperiod of days) or it could be estimated in most situations bycountingcars in the parking garagelot Although the latter streamlinesthe survey processconsiderably and avoids the needtocontact occupants it will also be the least accurate inthe cases where AVR is highest ie dense urban cores where office buildings may not provide all theirown parking and therefore countingcars could make AVR look even higher than itactually isIf reducing the data-gathering burdenonthe survey respondents is a high priority thenthere could be a two-tier system where only buildings thatdo notprovide all their own parking are required to survey the occupants (otherwise they cancount cars inthe parking lot)

Another downside is that car-counting does not capture people being dropped off byanother driver who does not park at the building The error this would introduce is fairly minimal because this practice rarely accountsformore than a very small percentage of commuters AVR baseline and predicted values could be generated for virtuallyanylocation in the US using the present studyrsquos method Even for locations outside of the metropolitanregions for which the relevant census information iscompiled routinely baseline and predicted AVRs canbe imputed from other geographical scales of census data though areaswithout regionally compiled censusinformation have small enough populations thattransitusage for commuting is likely nearly negligible

In VMT-based analysisestablishment of the baseline would alsoemployregionalcommuting information from the census multiplied by average commute distance To make use of CAPCOA predictionmethods the survey would have to generate detailedinformation on parkingpolicies primarily (including bike parking)as well as policies pertaining to fleet vehicles (if any) Measured datawould havetocomefrom surveydatathat asks occupants directly about their commute modes andthe distance of their automobile commutes as well as usage of fleet vehicles (if any) This is inherently more difficult thana survey limited to askingquestions of a single building managerThe advantages are that VMT is more directly relatedtoGHG emissions than AVR there would be improved analytical insightabout the effect of buildingstrategies on transportation behavior and related GHG emissions and therewould bemuch greater opportunityto leverageexisting research findings on transportation behavior in the analysis

40

Conclusion

This research quantifies for the first time the GHGco-benefits associated with water wasteand transportation aspects of certified green commercial office buildings in California It finds that these buildings do infact achieve significant GHG emissions reductions relative totypical non-green office buildings ndash about 38for water 48for waste and 5for transportation In terms of absolute emissions however savings in transportation dwarfthose of the other sectors because transportationis more than 90 times as GHG-intense per square foot of buildingspace as water use and over 170 times as GHG-intense per squarefoot as solid waste among baseline valuesOverallconversion of the entire stock ofexisting California officebuildings to theperformancestandards achieved bythecertified green office buildings would avoid emissions of about 0831 MMTCO2e per year

Furthermore additional performance incentives for water andwaste within the green rating systemswere found to be effectivein stimulating further resourceuseand emissions reductions These performance improvementswere actually largerthan what isrequired to achieve the extracredits in the LEED-EBOM system suggesting that such incentives may be worth more than ldquoface valuerdquo This finding has particular significance for standards for newconstruction and suggests that incentivizing higher efficiency standards could prompt aldquovirtuouslooprdquowhere buildersseek additional efficiencies beyond code requirements

The three resource areas differed significantly intheir performance relative to predictions for green building performance With respect to GHG emissions the certifiedbuildings performed better thanpredicted on water use (13) slightly better than predicted onwaste diversion (4) and worse than predicted on transportation (-6) The latter is a significant finding given the GHG intensity of transportation and suggeststhat the CAPCOA formula for calculating railmodeshares based on proximityto rail stations mayover-estimateactual rail ridership outcomes Thewidedivergencebetween predicted andmeasured values for water use likewise suggests that efforts should be made to improvewater use prediction methods especially with respect to cooling toweruse

Finally additional insights intocommercial office buildingperformance couldbe gainedbyinserting basic questions on water waste and transportation usage into the CEUS or CBECSsurveys which currently focus onoperational energy use Systematic collection ofperformance data of non-certified commercial office buildings would enable deeper analysisinto the effectiveness ofspecific building design strategies such as parking policiesplacement of recycling andcomposting bins andwater-efficient landscaping in securing GHGemissions reduction co-benefits The findings of this report suggest that importantadditional efficiencies and GHG co-benefits are available inall three resource areas as indeed they must be if the state is tomeet its long-range GHG emissionsgoals

41

Recommendations

The findings of this report imply a number of recommendations for future researchfuture climate policy initiatives and future updates to building standards

Addresstransportation behavior through CalGreen and other building standardsto the greatest possible extentTransportation is so GHG-intense that even small percentageimprovements over baseline such as those reported here can avoid substantial quantitiesof GHG emissions Indeed commercial office buildings stimulate more than twice as muchGHGemission through induced transportation than they do through their own operational energyconsumption (see Table 18)yet operational energy is the subject of detailed code requirementsand standardswhile transportation islargely assumed to be beyond the reach of buildingstandards Locatingbuildings in transit-accessible areas in particular is soimpactful to GHG emissions and so fundamental to facilitating non-automobiletransportation thatitmay be worth more to GHG control efforts (from commercialoffice buildings) than all other foreseeable improvements to green buildingstandards combined Itshould be given an emphasis within CalGreen and other building standards relatedto commercial construction commensurate with that importance

Improve prediction methods for future analysis ofgreen building performanceCAPCOA guidance on the quantification of GHG emissions should be revised and expanded to includemore direct methods for assessing the GHG emissions expected fromspecific water and waste-related building strategies(asopposed to usage levels) especially those related to irrigation and cooling towers In addition the formula for estimating railmode shares from the distance to rail stations should be updated with further research when feasible andultimately expanded to include bus bicycle walking and other non-automobile modes

Improve the information base for assessing regional transportation baselinesThe method for identifying transportation baselines used in this study relied on regional-scale data thatlikely oversimplifies the commuting dynamics ofparticular office cores Recent work byUSGBC (Pyke et al 2014) draws upon aggregated cellular data to establish morefine-grained characterizations of typical commutingpatterns in specific neighborhoods of office buildings Future research inthis veincould establish much more accurate neighborhood-scale baselinesagainst which the transportation behavior of green office building occupantscould be compared Such research might also enable the incorporation of otherdemographic factors that influence commuting behavior andmay co-vary with green building occupancy and enable greaterinsight into commute distances(and by extension vehiclemiles traveled)

Future CalGreen updates shouldsignificantly strengthen plumbing standardsThe predictions for greenbuilding water use were derived from the fixture and fitting standards in the 2010editionof the CalGreencode Giventhat the LEED-EBOM buildings outperformedthese predictions by 27 it appears that significant additional strengtheningof these standards is feasible andjustifiable

Future CalGreen updates should require placement of composting collection facilities within commercial office buildingsAccording to the date shown in Figure 4 a large proportion ofthe un-divertedwaste leaving commercial office buildings and entering landfills is ldquowet wasterdquo ndash ie food and other organic waste that is highin carbon content andtherefore arelatively potent source of methane in landfills Introduction of compost collection facilities

42

would enable this waste to be diverted from landfills far more effectively improvingdiversion rates avoiding unnecessary GHG emissions and creating compost for re-use orresale The current CalGreenrequirement (Section54101) requires provisionof ldquoreadily accessible areasrdquo for the ldquodepositing storage and collectionrdquo of recyclables but does not explicitlyincludeanysuch requirement for compostablematerials

Include questions related to water waste and transportation in the CBECS andor CEUS surveysAs noted in the discussioninsertion of a small number of simple questions in these surveyswould greatly expand the information base foranalysisof GHG co-benefits innon-certified commercial buildings CBECS has already incorporated water questions in its 2013 edition Collection of high-quality transportationdata may involve requiring buildingmanagers to issue surveys to occupants but given the importance of transportation to theoverall GHG emissions footprint of commercial office buildings and the general paucity ofdestination-side commuting data it isworth the extra effort

Encourage information-sharing on operational performance of buildingsThis research was made possible by USGBCrsquos unilateral commitment to share information about projectperformance as part of LEEDrsquos stated goal of market transformation Evenif CBECS and CEUS are revisedas recommendedabove there will still be a needfor muchmore information on the operational performance ofcommercial buildings whether certified as ldquogreenrdquoornot Data sharing and collection should be institutionalized particularly for anyperformance domainthat is claimed to produce public benefit or is cited as evidence ofcompliance with laws and regulations such as AB 32 Building codes including CalGreen could require publicoperational data-sharing aspart of a post-occupancyinspection process Local building permits whether for greenor non-green buildings could alsobe made conditional on commitment to share post-occupancydata subject tolater inspection by local building officials

Expand emphasis on existingbuildings instate and localclimate planning effortsBuilding energyefficiencyand GHG control efforts havehistoricallytended to emphasizecreation of standardsfornew construction asa meansof saving energy and GHGs While thisisgraduallychangingwith the passage of AB 758 and other efforts toestablish standards for renovations the existing building sectorremainsunder-emphasized in climateplanning generally More than one billion square feet of commercial office space alreadyexists in Californiaand bringing this space up to performance standards typical of certified green building would save over 083 MMTCO2e per year Considerably larger improvements beyond that are possible giventhe water and waste performance levels achieved by thehigh-performance buildings in this dataset and given the very large latentpotential for reduction of transportation-related emissionsthrough transit-friendly building siting decisions Itshould also be borne in mind thatthe figures reported in this study are foroffice buildings only additional large savings can be expectedfrom efforts toreduce waterwaste and transportation usage associated with other types of commercial buildings

43

References

American Community Survey 2008-2012 Table B08301 for various counties named in Table 7

ARB[AirResourcesBoard] 2014First Update tothe Climate Change Scoping Plan Building on the FrameworkSacramento ARB

ARB[Air Resources Board] 2008 Climate Change Scoping Plan A Framework for ChangeSacramento RB

ARB[Air Resources Board] 2012a Technical Evaluationof the Greenhouse Gas EmissionReduction Quantification for the Sacramento Area Council of Governmentsrsquo SB375 Sustainable Communities StrategySacramento ARB

ARB[Air Resources Board] 2012b ARBDetermination on Apple CampusMemorandum to Governorrsquos Office of Planning and ResearchSacramento ARB

Blanco H J Newell L Stott and M Alberti 2012 Water Supply Scarcity in Southern California Assessing Water District-Level StrategiesLos Angeles USC Center for Sustainable Cities

California Building Standards Commission 2010 CaliforniaGreen Building Standards Code 2010Title 24Part 11

California Building Standards Commission 2010 CaliforniaPlumbing Code2010

California Department of Water Resources 2010 Water Budget WorkbookVersion 101

CalRecycle 2013 Landfilling of WasteMemorandum downloaded from httparbcagovccwastelandfillingofwastepdf

CalRecycle [fka California IntegratedWaste Management Board] 2006 Targeted Statewide Waste Characterization Study Waste Disposal andDiversion Findings for SelectedIndustry GroupsReport to the Board by Cascadia Consulting Group Sacramento CA IWMB

CAPCOA [California Air Pollution Control Officers Association] 2010 Quantifying Greenhouse Gas Mitigation Measures A Resource for Local Government to Assess Emission Reductions from Greenhouse Gas Mitigation MeasuresSacramento CAPCOA

CAT [Climate Action Team] 2008 Green Building Sector Subgroup Scoping Plan Measure Development and Cost AnalysisSacramento CAT

CBRE 2014 Greater Los Angeles Office MarketViewQuarter 22014

CEC[California EnergyCommission] 2006 Refining Estimates of Water-Related Energy Use in CaliforniaCEC 500-2006-118

Dziegielewski Benedykt et al 2000 Commercial andInstitutional EndUses of WaterDenver American Water Works Association Research Foundation

44

AVRinformation could be obtained by either a survey of occupants (either for one day orpreferably aperiod of days) or it could be estimated in most situations bycountingcars in the parking garagelot Although the latter streamlinesthe survey processconsiderably and avoids the needtocontact occupants it will also be the least accurate inthe cases where AVR is highest ie dense urban cores where office buildings may not provide all theirown parking and therefore countingcars could make AVR look even higher than itactually isIf reducing the data-gathering burdenonthe survey respondents is a high priority thenthere could be a two-tier system where only buildings thatdo notprovide all their own parking are required to survey the occupants (otherwise they cancount cars inthe parking lot)

Another downside is that car-counting does not capture people being dropped off byanother driver who does not park at the building The error this would introduce is fairly minimal because this practice rarely accountsformore than a very small percentage of commuters AVR baseline and predicted values could be generated for virtuallyanylocation in the US using the present studyrsquos method Even for locations outside of the metropolitanregions for which the relevant census information iscompiled routinely baseline and predicted AVRs canbe imputed from other geographical scales of census data though areaswithout regionally compiled censusinformation have small enough populations thattransitusage for commuting is likely nearly negligible

In VMT-based analysisestablishment of the baseline would alsoemployregionalcommuting information from the census multiplied by average commute distance To make use of CAPCOA predictionmethods the survey would have to generate detailedinformation on parkingpolicies primarily (including bike parking)as well as policies pertaining to fleet vehicles (if any) Measured datawould havetocomefrom surveydatathat asks occupants directly about their commute modes andthe distance of their automobile commutes as well as usage of fleet vehicles (if any) This is inherently more difficult thana survey limited to askingquestions of a single building managerThe advantages are that VMT is more directly relatedtoGHG emissions than AVR there would be improved analytical insightabout the effect of buildingstrategies on transportation behavior and related GHG emissions and therewould bemuch greater opportunityto leverageexisting research findings on transportation behavior in the analysis

40

Conclusion

This research quantifies for the first time the GHGco-benefits associated with water wasteand transportation aspects of certified green commercial office buildings in California It finds that these buildings do infact achieve significant GHG emissions reductions relative totypical non-green office buildings ndash about 38for water 48for waste and 5for transportation In terms of absolute emissions however savings in transportation dwarfthose of the other sectors because transportationis more than 90 times as GHG-intense per square foot of buildingspace as water use and over 170 times as GHG-intense per squarefoot as solid waste among baseline valuesOverallconversion of the entire stock ofexisting California officebuildings to theperformancestandards achieved bythecertified green office buildings would avoid emissions of about 0831 MMTCO2e per year

Furthermore additional performance incentives for water andwaste within the green rating systemswere found to be effectivein stimulating further resourceuseand emissions reductions These performance improvementswere actually largerthan what isrequired to achieve the extracredits in the LEED-EBOM system suggesting that such incentives may be worth more than ldquoface valuerdquo This finding has particular significance for standards for newconstruction and suggests that incentivizing higher efficiency standards could prompt aldquovirtuouslooprdquowhere buildersseek additional efficiencies beyond code requirements

The three resource areas differed significantly intheir performance relative to predictions for green building performance With respect to GHG emissions the certifiedbuildings performed better thanpredicted on water use (13) slightly better than predicted onwaste diversion (4) and worse than predicted on transportation (-6) The latter is a significant finding given the GHG intensity of transportation and suggeststhat the CAPCOA formula for calculating railmodeshares based on proximityto rail stations mayover-estimateactual rail ridership outcomes Thewidedivergencebetween predicted andmeasured values for water use likewise suggests that efforts should be made to improvewater use prediction methods especially with respect to cooling toweruse

Finally additional insights intocommercial office buildingperformance couldbe gainedbyinserting basic questions on water waste and transportation usage into the CEUS or CBECSsurveys which currently focus onoperational energy use Systematic collection ofperformance data of non-certified commercial office buildings would enable deeper analysisinto the effectiveness ofspecific building design strategies such as parking policiesplacement of recycling andcomposting bins andwater-efficient landscaping in securing GHGemissions reduction co-benefits The findings of this report suggest that importantadditional efficiencies and GHG co-benefits are available inall three resource areas as indeed they must be if the state is tomeet its long-range GHG emissionsgoals

41

Recommendations

The findings of this report imply a number of recommendations for future researchfuture climate policy initiatives and future updates to building standards

Addresstransportation behavior through CalGreen and other building standardsto the greatest possible extentTransportation is so GHG-intense that even small percentageimprovements over baseline such as those reported here can avoid substantial quantitiesof GHG emissions Indeed commercial office buildings stimulate more than twice as muchGHGemission through induced transportation than they do through their own operational energyconsumption (see Table 18)yet operational energy is the subject of detailed code requirementsand standardswhile transportation islargely assumed to be beyond the reach of buildingstandards Locatingbuildings in transit-accessible areas in particular is soimpactful to GHG emissions and so fundamental to facilitating non-automobiletransportation thatitmay be worth more to GHG control efforts (from commercialoffice buildings) than all other foreseeable improvements to green buildingstandards combined Itshould be given an emphasis within CalGreen and other building standards relatedto commercial construction commensurate with that importance

Improve prediction methods for future analysis ofgreen building performanceCAPCOA guidance on the quantification of GHG emissions should be revised and expanded to includemore direct methods for assessing the GHG emissions expected fromspecific water and waste-related building strategies(asopposed to usage levels) especially those related to irrigation and cooling towers In addition the formula for estimating railmode shares from the distance to rail stations should be updated with further research when feasible andultimately expanded to include bus bicycle walking and other non-automobile modes

Improve the information base for assessing regional transportation baselinesThe method for identifying transportation baselines used in this study relied on regional-scale data thatlikely oversimplifies the commuting dynamics ofparticular office cores Recent work byUSGBC (Pyke et al 2014) draws upon aggregated cellular data to establish morefine-grained characterizations of typical commutingpatterns in specific neighborhoods of office buildings Future research inthis veincould establish much more accurate neighborhood-scale baselinesagainst which the transportation behavior of green office building occupantscould be compared Such research might also enable the incorporation of otherdemographic factors that influence commuting behavior andmay co-vary with green building occupancy and enable greaterinsight into commute distances(and by extension vehiclemiles traveled)

Future CalGreen updates shouldsignificantly strengthen plumbing standardsThe predictions for greenbuilding water use were derived from the fixture and fitting standards in the 2010editionof the CalGreencode Giventhat the LEED-EBOM buildings outperformedthese predictions by 27 it appears that significant additional strengtheningof these standards is feasible andjustifiable

Future CalGreen updates should require placement of composting collection facilities within commercial office buildingsAccording to the date shown in Figure 4 a large proportion ofthe un-divertedwaste leaving commercial office buildings and entering landfills is ldquowet wasterdquo ndash ie food and other organic waste that is highin carbon content andtherefore arelatively potent source of methane in landfills Introduction of compost collection facilities

42

would enable this waste to be diverted from landfills far more effectively improvingdiversion rates avoiding unnecessary GHG emissions and creating compost for re-use orresale The current CalGreenrequirement (Section54101) requires provisionof ldquoreadily accessible areasrdquo for the ldquodepositing storage and collectionrdquo of recyclables but does not explicitlyincludeanysuch requirement for compostablematerials

Include questions related to water waste and transportation in the CBECS andor CEUS surveysAs noted in the discussioninsertion of a small number of simple questions in these surveyswould greatly expand the information base foranalysisof GHG co-benefits innon-certified commercial buildings CBECS has already incorporated water questions in its 2013 edition Collection of high-quality transportationdata may involve requiring buildingmanagers to issue surveys to occupants but given the importance of transportation to theoverall GHG emissions footprint of commercial office buildings and the general paucity ofdestination-side commuting data it isworth the extra effort

Encourage information-sharing on operational performance of buildingsThis research was made possible by USGBCrsquos unilateral commitment to share information about projectperformance as part of LEEDrsquos stated goal of market transformation Evenif CBECS and CEUS are revisedas recommendedabove there will still be a needfor muchmore information on the operational performance ofcommercial buildings whether certified as ldquogreenrdquoornot Data sharing and collection should be institutionalized particularly for anyperformance domainthat is claimed to produce public benefit or is cited as evidence ofcompliance with laws and regulations such as AB 32 Building codes including CalGreen could require publicoperational data-sharing aspart of a post-occupancyinspection process Local building permits whether for greenor non-green buildings could alsobe made conditional on commitment to share post-occupancydata subject tolater inspection by local building officials

Expand emphasis on existingbuildings instate and localclimate planning effortsBuilding energyefficiencyand GHG control efforts havehistoricallytended to emphasizecreation of standardsfornew construction asa meansof saving energy and GHGs While thisisgraduallychangingwith the passage of AB 758 and other efforts toestablish standards for renovations the existing building sectorremainsunder-emphasized in climateplanning generally More than one billion square feet of commercial office space alreadyexists in Californiaand bringing this space up to performance standards typical of certified green building would save over 083 MMTCO2e per year Considerably larger improvements beyond that are possible giventhe water and waste performance levels achieved by thehigh-performance buildings in this dataset and given the very large latentpotential for reduction of transportation-related emissionsthrough transit-friendly building siting decisions Itshould also be borne in mind thatthe figures reported in this study are foroffice buildings only additional large savings can be expectedfrom efforts toreduce waterwaste and transportation usage associated with other types of commercial buildings

43

References

American Community Survey 2008-2012 Table B08301 for various counties named in Table 7

ARB[AirResourcesBoard] 2014First Update tothe Climate Change Scoping Plan Building on the FrameworkSacramento ARB

ARB[Air Resources Board] 2008 Climate Change Scoping Plan A Framework for ChangeSacramento RB

ARB[Air Resources Board] 2012a Technical Evaluationof the Greenhouse Gas EmissionReduction Quantification for the Sacramento Area Council of Governmentsrsquo SB375 Sustainable Communities StrategySacramento ARB

ARB[Air Resources Board] 2012b ARBDetermination on Apple CampusMemorandum to Governorrsquos Office of Planning and ResearchSacramento ARB

Blanco H J Newell L Stott and M Alberti 2012 Water Supply Scarcity in Southern California Assessing Water District-Level StrategiesLos Angeles USC Center for Sustainable Cities

California Building Standards Commission 2010 CaliforniaGreen Building Standards Code 2010Title 24Part 11

California Building Standards Commission 2010 CaliforniaPlumbing Code2010

California Department of Water Resources 2010 Water Budget WorkbookVersion 101

CalRecycle 2013 Landfilling of WasteMemorandum downloaded from httparbcagovccwastelandfillingofwastepdf

CalRecycle [fka California IntegratedWaste Management Board] 2006 Targeted Statewide Waste Characterization Study Waste Disposal andDiversion Findings for SelectedIndustry GroupsReport to the Board by Cascadia Consulting Group Sacramento CA IWMB

CAPCOA [California Air Pollution Control Officers Association] 2010 Quantifying Greenhouse Gas Mitigation Measures A Resource for Local Government to Assess Emission Reductions from Greenhouse Gas Mitigation MeasuresSacramento CAPCOA

CAT [Climate Action Team] 2008 Green Building Sector Subgroup Scoping Plan Measure Development and Cost AnalysisSacramento CAT

CBRE 2014 Greater Los Angeles Office MarketViewQuarter 22014

CEC[California EnergyCommission] 2006 Refining Estimates of Water-Related Energy Use in CaliforniaCEC 500-2006-118

Dziegielewski Benedykt et al 2000 Commercial andInstitutional EndUses of WaterDenver American Water Works Association Research Foundation

44

Conclusion

This research quantifies for the first time the GHGco-benefits associated with water wasteand transportation aspects of certified green commercial office buildings in California It finds that these buildings do infact achieve significant GHG emissions reductions relative totypical non-green office buildings ndash about 38for water 48for waste and 5for transportation In terms of absolute emissions however savings in transportation dwarfthose of the other sectors because transportationis more than 90 times as GHG-intense per square foot of buildingspace as water use and over 170 times as GHG-intense per squarefoot as solid waste among baseline valuesOverallconversion of the entire stock ofexisting California officebuildings to theperformancestandards achieved bythecertified green office buildings would avoid emissions of about 0831 MMTCO2e per year

Furthermore additional performance incentives for water andwaste within the green rating systemswere found to be effectivein stimulating further resourceuseand emissions reductions These performance improvementswere actually largerthan what isrequired to achieve the extracredits in the LEED-EBOM system suggesting that such incentives may be worth more than ldquoface valuerdquo This finding has particular significance for standards for newconstruction and suggests that incentivizing higher efficiency standards could prompt aldquovirtuouslooprdquowhere buildersseek additional efficiencies beyond code requirements

The three resource areas differed significantly intheir performance relative to predictions for green building performance With respect to GHG emissions the certifiedbuildings performed better thanpredicted on water use (13) slightly better than predicted onwaste diversion (4) and worse than predicted on transportation (-6) The latter is a significant finding given the GHG intensity of transportation and suggeststhat the CAPCOA formula for calculating railmodeshares based on proximityto rail stations mayover-estimateactual rail ridership outcomes Thewidedivergencebetween predicted andmeasured values for water use likewise suggests that efforts should be made to improvewater use prediction methods especially with respect to cooling toweruse

Finally additional insights intocommercial office buildingperformance couldbe gainedbyinserting basic questions on water waste and transportation usage into the CEUS or CBECSsurveys which currently focus onoperational energy use Systematic collection ofperformance data of non-certified commercial office buildings would enable deeper analysisinto the effectiveness ofspecific building design strategies such as parking policiesplacement of recycling andcomposting bins andwater-efficient landscaping in securing GHGemissions reduction co-benefits The findings of this report suggest that importantadditional efficiencies and GHG co-benefits are available inall three resource areas as indeed they must be if the state is tomeet its long-range GHG emissionsgoals

41

Recommendations

The findings of this report imply a number of recommendations for future researchfuture climate policy initiatives and future updates to building standards

Addresstransportation behavior through CalGreen and other building standardsto the greatest possible extentTransportation is so GHG-intense that even small percentageimprovements over baseline such as those reported here can avoid substantial quantitiesof GHG emissions Indeed commercial office buildings stimulate more than twice as muchGHGemission through induced transportation than they do through their own operational energyconsumption (see Table 18)yet operational energy is the subject of detailed code requirementsand standardswhile transportation islargely assumed to be beyond the reach of buildingstandards Locatingbuildings in transit-accessible areas in particular is soimpactful to GHG emissions and so fundamental to facilitating non-automobiletransportation thatitmay be worth more to GHG control efforts (from commercialoffice buildings) than all other foreseeable improvements to green buildingstandards combined Itshould be given an emphasis within CalGreen and other building standards relatedto commercial construction commensurate with that importance

Improve prediction methods for future analysis ofgreen building performanceCAPCOA guidance on the quantification of GHG emissions should be revised and expanded to includemore direct methods for assessing the GHG emissions expected fromspecific water and waste-related building strategies(asopposed to usage levels) especially those related to irrigation and cooling towers In addition the formula for estimating railmode shares from the distance to rail stations should be updated with further research when feasible andultimately expanded to include bus bicycle walking and other non-automobile modes

Improve the information base for assessing regional transportation baselinesThe method for identifying transportation baselines used in this study relied on regional-scale data thatlikely oversimplifies the commuting dynamics ofparticular office cores Recent work byUSGBC (Pyke et al 2014) draws upon aggregated cellular data to establish morefine-grained characterizations of typical commutingpatterns in specific neighborhoods of office buildings Future research inthis veincould establish much more accurate neighborhood-scale baselinesagainst which the transportation behavior of green office building occupantscould be compared Such research might also enable the incorporation of otherdemographic factors that influence commuting behavior andmay co-vary with green building occupancy and enable greaterinsight into commute distances(and by extension vehiclemiles traveled)

Future CalGreen updates shouldsignificantly strengthen plumbing standardsThe predictions for greenbuilding water use were derived from the fixture and fitting standards in the 2010editionof the CalGreencode Giventhat the LEED-EBOM buildings outperformedthese predictions by 27 it appears that significant additional strengtheningof these standards is feasible andjustifiable

Future CalGreen updates should require placement of composting collection facilities within commercial office buildingsAccording to the date shown in Figure 4 a large proportion ofthe un-divertedwaste leaving commercial office buildings and entering landfills is ldquowet wasterdquo ndash ie food and other organic waste that is highin carbon content andtherefore arelatively potent source of methane in landfills Introduction of compost collection facilities

42

would enable this waste to be diverted from landfills far more effectively improvingdiversion rates avoiding unnecessary GHG emissions and creating compost for re-use orresale The current CalGreenrequirement (Section54101) requires provisionof ldquoreadily accessible areasrdquo for the ldquodepositing storage and collectionrdquo of recyclables but does not explicitlyincludeanysuch requirement for compostablematerials

Include questions related to water waste and transportation in the CBECS andor CEUS surveysAs noted in the discussioninsertion of a small number of simple questions in these surveyswould greatly expand the information base foranalysisof GHG co-benefits innon-certified commercial buildings CBECS has already incorporated water questions in its 2013 edition Collection of high-quality transportationdata may involve requiring buildingmanagers to issue surveys to occupants but given the importance of transportation to theoverall GHG emissions footprint of commercial office buildings and the general paucity ofdestination-side commuting data it isworth the extra effort

Encourage information-sharing on operational performance of buildingsThis research was made possible by USGBCrsquos unilateral commitment to share information about projectperformance as part of LEEDrsquos stated goal of market transformation Evenif CBECS and CEUS are revisedas recommendedabove there will still be a needfor muchmore information on the operational performance ofcommercial buildings whether certified as ldquogreenrdquoornot Data sharing and collection should be institutionalized particularly for anyperformance domainthat is claimed to produce public benefit or is cited as evidence ofcompliance with laws and regulations such as AB 32 Building codes including CalGreen could require publicoperational data-sharing aspart of a post-occupancyinspection process Local building permits whether for greenor non-green buildings could alsobe made conditional on commitment to share post-occupancydata subject tolater inspection by local building officials

Expand emphasis on existingbuildings instate and localclimate planning effortsBuilding energyefficiencyand GHG control efforts havehistoricallytended to emphasizecreation of standardsfornew construction asa meansof saving energy and GHGs While thisisgraduallychangingwith the passage of AB 758 and other efforts toestablish standards for renovations the existing building sectorremainsunder-emphasized in climateplanning generally More than one billion square feet of commercial office space alreadyexists in Californiaand bringing this space up to performance standards typical of certified green building would save over 083 MMTCO2e per year Considerably larger improvements beyond that are possible giventhe water and waste performance levels achieved by thehigh-performance buildings in this dataset and given the very large latentpotential for reduction of transportation-related emissionsthrough transit-friendly building siting decisions Itshould also be borne in mind thatthe figures reported in this study are foroffice buildings only additional large savings can be expectedfrom efforts toreduce waterwaste and transportation usage associated with other types of commercial buildings

43

References

American Community Survey 2008-2012 Table B08301 for various counties named in Table 7

ARB[AirResourcesBoard] 2014First Update tothe Climate Change Scoping Plan Building on the FrameworkSacramento ARB

ARB[Air Resources Board] 2008 Climate Change Scoping Plan A Framework for ChangeSacramento RB

ARB[Air Resources Board] 2012a Technical Evaluationof the Greenhouse Gas EmissionReduction Quantification for the Sacramento Area Council of Governmentsrsquo SB375 Sustainable Communities StrategySacramento ARB

ARB[Air Resources Board] 2012b ARBDetermination on Apple CampusMemorandum to Governorrsquos Office of Planning and ResearchSacramento ARB

Blanco H J Newell L Stott and M Alberti 2012 Water Supply Scarcity in Southern California Assessing Water District-Level StrategiesLos Angeles USC Center for Sustainable Cities

California Building Standards Commission 2010 CaliforniaGreen Building Standards Code 2010Title 24Part 11

California Building Standards Commission 2010 CaliforniaPlumbing Code2010

California Department of Water Resources 2010 Water Budget WorkbookVersion 101

CalRecycle 2013 Landfilling of WasteMemorandum downloaded from httparbcagovccwastelandfillingofwastepdf

CalRecycle [fka California IntegratedWaste Management Board] 2006 Targeted Statewide Waste Characterization Study Waste Disposal andDiversion Findings for SelectedIndustry GroupsReport to the Board by Cascadia Consulting Group Sacramento CA IWMB

CAPCOA [California Air Pollution Control Officers Association] 2010 Quantifying Greenhouse Gas Mitigation Measures A Resource for Local Government to Assess Emission Reductions from Greenhouse Gas Mitigation MeasuresSacramento CAPCOA

CAT [Climate Action Team] 2008 Green Building Sector Subgroup Scoping Plan Measure Development and Cost AnalysisSacramento CAT

CBRE 2014 Greater Los Angeles Office MarketViewQuarter 22014

CEC[California EnergyCommission] 2006 Refining Estimates of Water-Related Energy Use in CaliforniaCEC 500-2006-118

Dziegielewski Benedykt et al 2000 Commercial andInstitutional EndUses of WaterDenver American Water Works Association Research Foundation

44

Recommendations

The findings of this report imply a number of recommendations for future researchfuture climate policy initiatives and future updates to building standards

Addresstransportation behavior through CalGreen and other building standardsto the greatest possible extentTransportation is so GHG-intense that even small percentageimprovements over baseline such as those reported here can avoid substantial quantitiesof GHG emissions Indeed commercial office buildings stimulate more than twice as muchGHGemission through induced transportation than they do through their own operational energyconsumption (see Table 18)yet operational energy is the subject of detailed code requirementsand standardswhile transportation islargely assumed to be beyond the reach of buildingstandards Locatingbuildings in transit-accessible areas in particular is soimpactful to GHG emissions and so fundamental to facilitating non-automobiletransportation thatitmay be worth more to GHG control efforts (from commercialoffice buildings) than all other foreseeable improvements to green buildingstandards combined Itshould be given an emphasis within CalGreen and other building standards relatedto commercial construction commensurate with that importance

Improve prediction methods for future analysis ofgreen building performanceCAPCOA guidance on the quantification of GHG emissions should be revised and expanded to includemore direct methods for assessing the GHG emissions expected fromspecific water and waste-related building strategies(asopposed to usage levels) especially those related to irrigation and cooling towers In addition the formula for estimating railmode shares from the distance to rail stations should be updated with further research when feasible andultimately expanded to include bus bicycle walking and other non-automobile modes

Improve the information base for assessing regional transportation baselinesThe method for identifying transportation baselines used in this study relied on regional-scale data thatlikely oversimplifies the commuting dynamics ofparticular office cores Recent work byUSGBC (Pyke et al 2014) draws upon aggregated cellular data to establish morefine-grained characterizations of typical commutingpatterns in specific neighborhoods of office buildings Future research inthis veincould establish much more accurate neighborhood-scale baselinesagainst which the transportation behavior of green office building occupantscould be compared Such research might also enable the incorporation of otherdemographic factors that influence commuting behavior andmay co-vary with green building occupancy and enable greaterinsight into commute distances(and by extension vehiclemiles traveled)

Future CalGreen updates shouldsignificantly strengthen plumbing standardsThe predictions for greenbuilding water use were derived from the fixture and fitting standards in the 2010editionof the CalGreencode Giventhat the LEED-EBOM buildings outperformedthese predictions by 27 it appears that significant additional strengtheningof these standards is feasible andjustifiable

Future CalGreen updates should require placement of composting collection facilities within commercial office buildingsAccording to the date shown in Figure 4 a large proportion ofthe un-divertedwaste leaving commercial office buildings and entering landfills is ldquowet wasterdquo ndash ie food and other organic waste that is highin carbon content andtherefore arelatively potent source of methane in landfills Introduction of compost collection facilities

42

would enable this waste to be diverted from landfills far more effectively improvingdiversion rates avoiding unnecessary GHG emissions and creating compost for re-use orresale The current CalGreenrequirement (Section54101) requires provisionof ldquoreadily accessible areasrdquo for the ldquodepositing storage and collectionrdquo of recyclables but does not explicitlyincludeanysuch requirement for compostablematerials

Include questions related to water waste and transportation in the CBECS andor CEUS surveysAs noted in the discussioninsertion of a small number of simple questions in these surveyswould greatly expand the information base foranalysisof GHG co-benefits innon-certified commercial buildings CBECS has already incorporated water questions in its 2013 edition Collection of high-quality transportationdata may involve requiring buildingmanagers to issue surveys to occupants but given the importance of transportation to theoverall GHG emissions footprint of commercial office buildings and the general paucity ofdestination-side commuting data it isworth the extra effort

Encourage information-sharing on operational performance of buildingsThis research was made possible by USGBCrsquos unilateral commitment to share information about projectperformance as part of LEEDrsquos stated goal of market transformation Evenif CBECS and CEUS are revisedas recommendedabove there will still be a needfor muchmore information on the operational performance ofcommercial buildings whether certified as ldquogreenrdquoornot Data sharing and collection should be institutionalized particularly for anyperformance domainthat is claimed to produce public benefit or is cited as evidence ofcompliance with laws and regulations such as AB 32 Building codes including CalGreen could require publicoperational data-sharing aspart of a post-occupancyinspection process Local building permits whether for greenor non-green buildings could alsobe made conditional on commitment to share post-occupancydata subject tolater inspection by local building officials

Expand emphasis on existingbuildings instate and localclimate planning effortsBuilding energyefficiencyand GHG control efforts havehistoricallytended to emphasizecreation of standardsfornew construction asa meansof saving energy and GHGs While thisisgraduallychangingwith the passage of AB 758 and other efforts toestablish standards for renovations the existing building sectorremainsunder-emphasized in climateplanning generally More than one billion square feet of commercial office space alreadyexists in Californiaand bringing this space up to performance standards typical of certified green building would save over 083 MMTCO2e per year Considerably larger improvements beyond that are possible giventhe water and waste performance levels achieved by thehigh-performance buildings in this dataset and given the very large latentpotential for reduction of transportation-related emissionsthrough transit-friendly building siting decisions Itshould also be borne in mind thatthe figures reported in this study are foroffice buildings only additional large savings can be expectedfrom efforts toreduce waterwaste and transportation usage associated with other types of commercial buildings

43

References

American Community Survey 2008-2012 Table B08301 for various counties named in Table 7

ARB[AirResourcesBoard] 2014First Update tothe Climate Change Scoping Plan Building on the FrameworkSacramento ARB

ARB[Air Resources Board] 2008 Climate Change Scoping Plan A Framework for ChangeSacramento RB

ARB[Air Resources Board] 2012a Technical Evaluationof the Greenhouse Gas EmissionReduction Quantification for the Sacramento Area Council of Governmentsrsquo SB375 Sustainable Communities StrategySacramento ARB

ARB[Air Resources Board] 2012b ARBDetermination on Apple CampusMemorandum to Governorrsquos Office of Planning and ResearchSacramento ARB

Blanco H J Newell L Stott and M Alberti 2012 Water Supply Scarcity in Southern California Assessing Water District-Level StrategiesLos Angeles USC Center for Sustainable Cities

California Building Standards Commission 2010 CaliforniaGreen Building Standards Code 2010Title 24Part 11

California Building Standards Commission 2010 CaliforniaPlumbing Code2010

California Department of Water Resources 2010 Water Budget WorkbookVersion 101

CalRecycle 2013 Landfilling of WasteMemorandum downloaded from httparbcagovccwastelandfillingofwastepdf

CalRecycle [fka California IntegratedWaste Management Board] 2006 Targeted Statewide Waste Characterization Study Waste Disposal andDiversion Findings for SelectedIndustry GroupsReport to the Board by Cascadia Consulting Group Sacramento CA IWMB

CAPCOA [California Air Pollution Control Officers Association] 2010 Quantifying Greenhouse Gas Mitigation Measures A Resource for Local Government to Assess Emission Reductions from Greenhouse Gas Mitigation MeasuresSacramento CAPCOA

CAT [Climate Action Team] 2008 Green Building Sector Subgroup Scoping Plan Measure Development and Cost AnalysisSacramento CAT

CBRE 2014 Greater Los Angeles Office MarketViewQuarter 22014

CEC[California EnergyCommission] 2006 Refining Estimates of Water-Related Energy Use in CaliforniaCEC 500-2006-118

Dziegielewski Benedykt et al 2000 Commercial andInstitutional EndUses of WaterDenver American Water Works Association Research Foundation

44

would enable this waste to be diverted from landfills far more effectively improvingdiversion rates avoiding unnecessary GHG emissions and creating compost for re-use orresale The current CalGreenrequirement (Section54101) requires provisionof ldquoreadily accessible areasrdquo for the ldquodepositing storage and collectionrdquo of recyclables but does not explicitlyincludeanysuch requirement for compostablematerials

Include questions related to water waste and transportation in the CBECS andor CEUS surveysAs noted in the discussioninsertion of a small number of simple questions in these surveyswould greatly expand the information base foranalysisof GHG co-benefits innon-certified commercial buildings CBECS has already incorporated water questions in its 2013 edition Collection of high-quality transportationdata may involve requiring buildingmanagers to issue surveys to occupants but given the importance of transportation to theoverall GHG emissions footprint of commercial office buildings and the general paucity ofdestination-side commuting data it isworth the extra effort

Encourage information-sharing on operational performance of buildingsThis research was made possible by USGBCrsquos unilateral commitment to share information about projectperformance as part of LEEDrsquos stated goal of market transformation Evenif CBECS and CEUS are revisedas recommendedabove there will still be a needfor muchmore information on the operational performance ofcommercial buildings whether certified as ldquogreenrdquoornot Data sharing and collection should be institutionalized particularly for anyperformance domainthat is claimed to produce public benefit or is cited as evidence ofcompliance with laws and regulations such as AB 32 Building codes including CalGreen could require publicoperational data-sharing aspart of a post-occupancyinspection process Local building permits whether for greenor non-green buildings could alsobe made conditional on commitment to share post-occupancydata subject tolater inspection by local building officials

Expand emphasis on existingbuildings instate and localclimate planning effortsBuilding energyefficiencyand GHG control efforts havehistoricallytended to emphasizecreation of standardsfornew construction asa meansof saving energy and GHGs While thisisgraduallychangingwith the passage of AB 758 and other efforts toestablish standards for renovations the existing building sectorremainsunder-emphasized in climateplanning generally More than one billion square feet of commercial office space alreadyexists in Californiaand bringing this space up to performance standards typical of certified green building would save over 083 MMTCO2e per year Considerably larger improvements beyond that are possible giventhe water and waste performance levels achieved by thehigh-performance buildings in this dataset and given the very large latentpotential for reduction of transportation-related emissionsthrough transit-friendly building siting decisions Itshould also be borne in mind thatthe figures reported in this study are foroffice buildings only additional large savings can be expectedfrom efforts toreduce waterwaste and transportation usage associated with other types of commercial buildings

43

References

American Community Survey 2008-2012 Table B08301 for various counties named in Table 7

ARB[AirResourcesBoard] 2014First Update tothe Climate Change Scoping Plan Building on the FrameworkSacramento ARB

ARB[Air Resources Board] 2008 Climate Change Scoping Plan A Framework for ChangeSacramento RB

ARB[Air Resources Board] 2012a Technical Evaluationof the Greenhouse Gas EmissionReduction Quantification for the Sacramento Area Council of Governmentsrsquo SB375 Sustainable Communities StrategySacramento ARB

ARB[Air Resources Board] 2012b ARBDetermination on Apple CampusMemorandum to Governorrsquos Office of Planning and ResearchSacramento ARB

Blanco H J Newell L Stott and M Alberti 2012 Water Supply Scarcity in Southern California Assessing Water District-Level StrategiesLos Angeles USC Center for Sustainable Cities

California Building Standards Commission 2010 CaliforniaGreen Building Standards Code 2010Title 24Part 11

California Building Standards Commission 2010 CaliforniaPlumbing Code2010

California Department of Water Resources 2010 Water Budget WorkbookVersion 101

CalRecycle 2013 Landfilling of WasteMemorandum downloaded from httparbcagovccwastelandfillingofwastepdf

CalRecycle [fka California IntegratedWaste Management Board] 2006 Targeted Statewide Waste Characterization Study Waste Disposal andDiversion Findings for SelectedIndustry GroupsReport to the Board by Cascadia Consulting Group Sacramento CA IWMB

CAPCOA [California Air Pollution Control Officers Association] 2010 Quantifying Greenhouse Gas Mitigation Measures A Resource for Local Government to Assess Emission Reductions from Greenhouse Gas Mitigation MeasuresSacramento CAPCOA

CAT [Climate Action Team] 2008 Green Building Sector Subgroup Scoping Plan Measure Development and Cost AnalysisSacramento CAT

CBRE 2014 Greater Los Angeles Office MarketViewQuarter 22014

CEC[California EnergyCommission] 2006 Refining Estimates of Water-Related Energy Use in CaliforniaCEC 500-2006-118

Dziegielewski Benedykt et al 2000 Commercial andInstitutional EndUses of WaterDenver American Water Works Association Research Foundation

44

References

American Community Survey 2008-2012 Table B08301 for various counties named in Table 7

ARB[AirResourcesBoard] 2014First Update tothe Climate Change Scoping Plan Building on the FrameworkSacramento ARB

ARB[Air Resources Board] 2008 Climate Change Scoping Plan A Framework for ChangeSacramento RB

ARB[Air Resources Board] 2012a Technical Evaluationof the Greenhouse Gas EmissionReduction Quantification for the Sacramento Area Council of Governmentsrsquo SB375 Sustainable Communities StrategySacramento ARB

ARB[Air Resources Board] 2012b ARBDetermination on Apple CampusMemorandum to Governorrsquos Office of Planning and ResearchSacramento ARB

Blanco H J Newell L Stott and M Alberti 2012 Water Supply Scarcity in Southern California Assessing Water District-Level StrategiesLos Angeles USC Center for Sustainable Cities

California Building Standards Commission 2010 CaliforniaGreen Building Standards Code 2010Title 24Part 11

California Building Standards Commission 2010 CaliforniaPlumbing Code2010

California Department of Water Resources 2010 Water Budget WorkbookVersion 101

CalRecycle 2013 Landfilling of WasteMemorandum downloaded from httparbcagovccwastelandfillingofwastepdf

CalRecycle [fka California IntegratedWaste Management Board] 2006 Targeted Statewide Waste Characterization Study Waste Disposal andDiversion Findings for SelectedIndustry GroupsReport to the Board by Cascadia Consulting Group Sacramento CA IWMB

CAPCOA [California Air Pollution Control Officers Association] 2010 Quantifying Greenhouse Gas Mitigation Measures A Resource for Local Government to Assess Emission Reductions from Greenhouse Gas Mitigation MeasuresSacramento CAPCOA

CAT [Climate Action Team] 2008 Green Building Sector Subgroup Scoping Plan Measure Development and Cost AnalysisSacramento CAT

CBRE 2014 Greater Los Angeles Office MarketViewQuarter 22014

CEC[California EnergyCommission] 2006 Refining Estimates of Water-Related Energy Use in CaliforniaCEC 500-2006-118

Dziegielewski Benedykt et al 2000 Commercial andInstitutional EndUses of WaterDenver American Water Works Association Research Foundation

44

E32010CPUCGHG Calculator UpdatedReport andRevisedModelhttpwwwethreecompublic_projectscpuc2php

EPA [Environmental ProtectionAgency] 2014 Clean Energy Calculations andReferenceshttpwwwepagovcleanenergyenergy-resourcesrefshtml

Ewing R et al 2008 Growing Cooler The Evidence on Urban Development and Climate ChangeWashingtonDC Urban Land Institute

Feigon S D Hoyt L McNally R Mooney-Bullock S Campbell and D Leach 2003 Travel Matters Mitigating Climate Change with Sustainable Surface TransportationTransit Cooperative ResearchProgram Report 93 Washington DC Transportation ResearchBoard

Gleick Peter et al 2003 Waste Not Want Not The Potential for Urban Water Conservation in CaliforniaOakland Pacific Institute

Itron Inc 2006 CEUSFinal ReportConsultant Report to California Energy Commission for Contract 400-2006-005

Mozingo L and E Arens 2013 Residential Energy Use and GHG Emissions Impacts for Compact LandUse TypesARB Contract 10-323 Berkeley CREC

NRDC [Natural Resources Defense Council] 2004 Energy Down the Drain The Hidden Costs of Californiarsquos Water SupplySan Francisco NRDC

Pyke C L Schewel andR Zhang 2014 Performance-basedmeasures of office commuting Potential applications of aggregated anonymous cellular dataGreen Building Information Gateway (GBIG) Insight Technical Report 14-03

Pyke C J Todd A Rohloff andB Owens 2011 Geographic and temporal patterns in green building practice Apreliminary analysis of data from LEED for New Construction projects in the United StatesPaper presented at Sustainable Buildings 2011

US Census Bureau 2008-2012AmericanCommunity Survey (searchB08301- Means of TransportationTo Work) httpfactfinder2censusgovfacestableservicesjsfpagesproductviewxhtmlpid=ACS_12_5YR_B08301ampprodType=table

USGBC [US Green Building Council] 2009 LEED for Existing Buildings Operations and MaintenanceWashingtonDC USGBC

USGBC [US Green Building Council] 2008 LEED for Existing Buildings Operations andMaintenanceWashingtonDC USGBC

45

Glossary of Abbreviations

AB32 Assembly Bill 32 aka The Global Warming Solutions Actof 2006

ACS American Community Survey ANDOC Anaerobically degradable carbon ARB California Air Resource Board AVR Average vehicle ridership CalGreen California Green Building Standards Code CAPCOA California Air Pollution ControlOfficers Association CBECS Commercial Building Energy Consumption Survey CEC California Energy Commission CEUS California Commercial EndUse Survey CO2e Carbon dioxide equivalent DWR California Department of Water Resources EBMUD East Bay Municipal Utility District GHG Greenhouse gas LA DWP Los Angeles Department of Water andPower LEED Leadership in EnergyandEnvironmental Design green

building rating systems LEED-EBOM Leadership in EnergyandEnvironmental Design for

Existing Buildings Operation and Maintenances greenbuilding rating system

LEED-CI Leadership in EnergyandEnvironmental Design forCommercial Interiors green building rating system

LEED-CS Leadership in EnergyandEnvironmental Design for Core and Shell green buildingratingsystem

LEED-MC Leadership in EnergyandEnvironmental Design for NewConstruction green building rating system

MTCO2e Metric tons of carbon dioxide equivalent MMTCO2e Million metric tons of carbon dioxide equivalent MPOs Metropolitan Planning Organizations MRc6 Materials amp Resources credit 6 in LEED-EBOM v 2008 and

2009requiring a waste stream audit MRc7 Materials amp Resources credit 6 in LEED-EBOM v 2008 and

2009requiring a 50 wastediversion rate MTCABAG Metropolitan Transportation Commission and Association

of BayAreaGovernments (Bay Area) MWD Metropolitan Water District of Southern California PGampE Pacific Gas andElectric SACOG SacramentoAreaCouncil of Governments SANDAG San DiegoAssociation of Governments SCAG Southern CaliforniaAssociation of Governments SDGampE San DiegoGas and Electric SFPUC San FranciscoPublic Utilities Commission SIC Standard Industrial Classification code SMUD Sacramento Municipal Utility District SSc4 Sustainable Sites credit 4 in LEED-EBOM v 2008 and 2009

46

SWP State Water Project USGBC United States Green Building Council VMT Vehicle miles traveled WEc11 Water Efficiency credits 11 in LEED-EBOM v 2008

requiring a water consumption audit (referred to as WEc1option 1in LEED-EBOM 2009)

WEc12 Water Efficiency credits 12 in LEED-EBOM v 2008requiring submetering of watersystems(referred to asWEc1 option 2 in LEED-EBOM 2009)

WEc2 Water Efficiency credit 2 in LEED-EBOM v 2008 and 2009requiring additional plumbing fixture and fitting efficiencyfor indoor use

WEc3 Water Efficiency credit 3 in LEED-EBOM v 2008 and 2009requiring waterefficient landscape irrigation

47

SWP State Water Project USGBC United States Green Building Council VMT Vehicle miles traveled WEc11 Water Efficiency credits 11 in LEED-EBOM v 2008

requiring a water consumption audit (referred to as WEc1option 1in LEED-EBOM 2009)

WEc12 Water Efficiency credits 12 in LEED-EBOM v 2008requiring submetering of watersystems(referred to asWEc1 option 2 in LEED-EBOM 2009)

WEc2 Water Efficiency credit 2 in LEED-EBOM v 2008 and 2009requiring additional plumbing fixture and fitting efficiencyfor indoor use

WEc3 Water Efficiency credit 3 in LEED-EBOM v 2008 and 2009requiring waterefficient landscape irrigation

47