Enabling Sep 13, 2016 Low Carbon Communiessustainability.illinois.edu/wp-content/uploads/2016/12/...1 Enabling Low Carbon Communies The roles of smart planning tools and place-based

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EnablingLowCarbonCommuni1es

Therolesofsmartplanningtoolsandplace-basedsolu1ons

ChrisJones,Ph.D.Director,CoolClimateNetworkProgramChair,BECCConferenceUniv.ofCalifornia,Berkeley

ISEEEnergy2030Sep13,2016

WeiM,Nelson,J.H,GreenblaQ,J.B.,Mileva,A.,Johnston,J.,Ting,M.,Jones,C.M.,Yang,C.,McMahon,J.E.,Kammen,D.M.,Deepcarbonreduc-onsinCaliforniarequireelectrifica-onandintegra-onacrosseconomicsectors.EnvironmentalResearchLeQers(8)014038

Mee1ngCalifornia’s2050GHGreduc1ontarget

0"

100"

200"

300"

400"

500"

600"

700"

GHG#Em

ission

s#[Mt#C

O2eq]#

Increased)Efficiency:"por&olio"of"measures"in""buildings,"transporta5on,"and"industry;""electricity"decoupling"

Low1GHG)Electricity:"low:GHG"loading"order,"renewable"energy,"fossil"fuels"with""carbon"capture"and"storage,"nuclear"

Hea6ng)Electrifica6on:"water"and""space"hea5ng"in"buildings,"some"industrial"processes"

Vehicle)Electrifica6on:"plug:in"hybrid"and"ba>ery""electric"vehicles,"including"cars,"trucks,"buses"and"trains"

Low)1GHG)Biofuels:"cellulosic"ethanol"and"advanced"biofuels""

Conserva6on:"less"driving,""more"reuse"and"recycling"

2050##Reference##

Case#

2050##Compliant##

Case#

############Policy#Landscape#"""""""Long"term"targets"needed"""""""Long"term"targets"and""""""""accelerated"implementa:on""""""""needed"""""""No"enabling"policy"framework""""""""

43%"

27%"

16%"

36%"

35%"16%"

2

Mee#ngCalifornia’s80%GHGReduc#onTargetby2050

GeneralizedLearningCurve

GeneralizedLearningCurve

2020203020402050


ElectricityDemandunder80%GHGReduc#onScenario

Spheres of influence

6 A Socio-Ecological Model of Human Behavior Adapted from Bronfenbrenner’s Ecological Framework for Human Development

PublicPolicy

Communi1es

Organiza1ons

Interpersonal

Individual

motor fuel (direct)

air travel

vehicle mfg

natural gas snack food

meat

dairy

fruits & veg.

furniture & appliances

clothing

health care

motor fuel production

auto. maintenan.

electricity production

fuel production

w ater / w aste

construction

grains / bakery

entertainment

medicalpersonal care

personalentertainment

charitymisc.

education

-

2

4

6

8

10

12

14

16

18

Transportation Housing Food Goods Services

mt C

O2e

/yr

motor fuel (direct)

air travel

vehicle mfg


meat

dairy

fruits & veg.


clothing

health care


auto. maintenan.


energy indirect

w ater / w aste

construction

grains / bakery

entertainment



charitymisc.

education

-

2

4

6

8

10

12

14

16

18


mt C

O2e

/yr

Carbon footprint of average U.S. household 50 metric tons carbon dioxide equivalents (CO2e) per year

Source: coolclimate.berkeley.edu Jones & Kammen (2011)

7

-

2

4

6

8

10

12

14

16

18


mt C

O2e

/yr

Carbon footprint of average global household 10 metric tons carbon dioxide equivalents (CO2e) per year

8


-

2

4

6

8

10

12

14

16

18


mt C

O2e

/yr

Average global household under climate stabilization 2 metric tons carbon dioxide equivalents (CO2e) per year

9


motor fuel (direct)

air travel

vehicle mfg


meat

dairy

fruits & veg.


clothing

health care


auto. maintenan.


fuel production

w ater / w aste

construction

grains / bakery

entertainment



charitymisc.

education

-

2

4

6

8

10

12

14

16

18


mt C

O2e

/yr

motor fuel (direct)

air travel

vehicle mfg


meat

dairy

fruits & veg.


clothing

health care


auto. maintenan.


energy indirect

w ater / w aste

construction

grains / bakery

entertainment



charitymisc.

education

-

2

4

6

8

10

12

14

16

18


mt C

O2e

/yr

Carbon footprint of average U.S. household 50 metric tons carbon dioxide equivalents (CO2e) per year

10


motor fuel (direct)

air travel

vehicle mfg


meat

dairy

fruits & veg.


clothing

health care


auto. maintenan.


fuel production

w ater / w aste

construction

grains / bakery

entertainment



charitymisc.

education

-

2

4

6

8

10

12

14

16

18


mt C

O2e

/yr

Previous studies: •  Fuel processing •  Fuel transport/storage •  Power plant construction Our study: •  Procurement •  Full supply chain LCA

energyindirect

motor fuel (direct)

air travel

vehicle mfg


meat

dairy

fruits & veg.


clothing

health care


auto. maintenan.


energy indirect

w ater / w aste

construction grains / bakery

entertainmentmedical

personal care

personal

entertainmentcharitymisc.

education

-

2

4

6

8

10

12

14

16

18


mt C

O2e

/yr

Carbon footprint of average California household 47 metric tons CO2e per year

11


motor fuel (direct)

air travel

vehicle mfg


meat

dairy

fruits & veg.


clothing

health care


auto. maintenan.


energy indirect

w ater / w aste

construction

grains / bakery


personal care


charitymisc.

education

-

2

4

6

8

10

12

14

16

18


mt C

O2e

/yr

Carbon footprint of average St. Louis household 49 metric tons CO2e per year

12


motor fuel (direct)

air travel

vehicle mfg

natural gas snack foodmeatdairy

fruits & veg.


clothing health care


auto. maintenan.


energy indirectw ater / w asteconstruction

grains / bakery

entertainmentmedicalpersonal carepersonalentertainmentcharitymisc.education

-

5

10

15

20

25


mt C

O2e

/yr

1-person CA household: $10k/yr Carbon footprint: 16 tCO2e/yr

13


motor fuel (direct)

air travel

vehicle mfg

natural gas snack foodmeatdairy

fruits & veg.


clothing health care


auto. maintenan.


energy indirectw ater / w asteconstruction

grains / bakeryentertainment



charitymisc.education

-

5

10

15

20

25


mt C

O2e

/yr


14


motor fuel (direct)

air travel

vehicle mfg


meatdairy

fruits & veg.


clothing

health care


auto. maintenan.


energy indirectw ater / w aste

construction

grains / bakery entertainmentmedical

personal care


charitymisc.

education

-

5

10

15

20

25


mt C

O2e

/yr


15


motor fuel (direct)

air travel

vehicle mfg


meat

dairy

fruits & veg.


clothing

health care


auto. maintenan.


energy indirectw ater / w aste

constructiongrains / bakery


personal care


charitymisc.

education

-

5

10

15

20

25


mt C

O2e

/yr


16


motor fuel (direct)

air travel

vehicle mfg


meat

dairy

fruits & veg.


clothing

health care


auto. maintenan.


energy indirect

w ater / w aste

construction grains / bakery


personal care


charitymisc.

education

-

5

10

15

20

25


mt C

O2e

/yr


17


motor fuel (direct)

air travel

vehicle mfg


meat

dairy

fruits & veg.


clothing

health care


auto. maintenan.


energy indirect

w ater / w aste

construction

grains / bakery

entertainmentmedicalpersonal care


charitymisc.

education

-

5

10

15

20

25


mt C

O2e

/yr

4-person St. Louis household: $70k/yr Carbon footprint: 64 tCO2e/yr

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TypicalCaliforniaSchool

But,doesinforma1onchangebehavior?

PublicPolicy

Communi1es

Organiza1ons

Interpersonal

Individual

CoolCalifornia Challenge

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Sponsored by:

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Theore#calFounda#onforCompe##ons:Whydotheywork?1.  Compara#veFeedback:letpeopleknowhowwelltheyaredoingvs.peers

2.  Norms:provideinforma1ononwhatothersaredoingandexpectedbehavior

3.  Collabora#on&Compe##on:fostercollabora1onwithingroupstomeetgoals;friendlycompe11onbetweenout-groups

4.  SocialDiffusion:spreadadop1onthroughexis1ngsocialnetworks

5.  Gamifica#on:earningpointsforsmalltasksand“levelingup”increasesenjoymentoftakingac1ons

6.  Incen#ves:recogni1onandtangiblerewardsprovideposi1vefeedbackforaccomplishments

7.  Visibility:Visibleac1onsaremoremo1va1ngthaninvisibleac1ons

8.  Self-efficacy:byworkingtogetherpeoplefeelliketheycanmakemeaningfulcontribu1onstoaddressclimatechange

Vine,E.,andJones,C.M.(2015)

Electricityconsump1onoftreatmentvs.controlgroupTotalsavings=14%

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!"!!

!100!!

!200!!

!300!!

!400!!

!500!!

!600!!

!700!!

Marchl2012!

April2012!

May2012!

June2012!

July2012!

August2012!

September2012!

October2012!

November2012!

December2012!

January2013!

February2013!

March2013!

April2013!

kWh!

CONTROL'

TREATMENT'

Source:JonesandKammen(2014)

Davis is the “Coolest California City” 2014

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Riverside is the “Coolest California City” 2015

ARBBoardMemberBarbaraRiordan,RiversideMayorRustyBailey,ARBBoardMemberJudyMitchell,&ARBChairmanMaryD.Nichols

Claremont is the “Coolest California City” 2016

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PrimaryMo1va1onstoPar1cipatebyDemographics

Highlights

•  20,000students,staffandfacultyat10campuses(5%oftotalpop.)•  >100,000stories&25,000photossubmiQed•  >$1Minenergysavings•  Cost:$100,000

“Iusedtobescaredoftakingthebusonlybecauseofthescheduleandrunninglate.Buttakingitwithagroupoffriendsmakesiteasier!”

“Meandmyfriendshavestartedcarpoolingwheneverwegooff-campusforfoodorshopping.Wealsohavestartedridingbikes(whichishardinthecoldweather),butwemanage!”

“Alwayswearinglongsleeves,sweaters,andjacketswhenit'scold.”

“AllofmyroommateshaveLEDlamps.Thatwasoneofthethingsthatallofusbondedover.Wetrytoconserveasmuchenergyaspossible.”

Spheres of influence

38 A Socio-Ecological Model of Human Behavior Adapted from Bronfenbrenner’s Ecological Framework for Human Development

PublicPolicy

Communi1es

Organiza1ons

Interpersonal

Individual

39Source:JonesandKammen(2014)Env.Sci&Tech.

HouseholdcarbonfootprintsinEastCoastMetropolitanAreas

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CBEIProducts

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•  Inventorytables&graphsatregional,county,andcityscale•  MapsshowingGHGfootprintatfine-grainedlocalscale

metric tons CO2e / household

Motor Vehicle Fuel

HouseholdGHGEmissionsfromTransporta#onbyBlockGroup

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!70!!

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MOSS!BEA

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SANTA

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SF! SAN!MATEO! SANTA!CLARA!

metric!tons!CO2e!!per!hou

seho

ld!

San!Francisco!&!South!Bay!CiUes!"!Average!Household!Carbon!Footprint!

Services!

Goods!

Food!

Housing!

TransportaUon!

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MajorLessons&Recommenda#ons•  GHGreduc1onopportuni1esvarygreatlybyloca1on,demographics,sector

•  Behaviorchangeatscalecanbecost-effec1ve….ornot(enablingsorwarecanhelp)

•  Localgovernmentsshouldincorporateconsump1on-basedinventories&percapitatargets

•  80%GHGreduc1onfromconsump1onperspec1venotpossible–perhaps50%max

•  ThemixofGHGmi1ga1onopportuni1esdependsonstrengthoftarget

•  FoodbecomeslargestsourceofGHGemissionsunderaggressiveGHGmi1ga1on

•  Pop.densifica1ongenerallynoteffec1veinsuburbs;focusonurbancores&controlsprawl

•  Nearcompleteelectrifica1onofvehiclesandhea1ngneededtomeet80%reduc1ontarget

•  MethodscalestoallU.S.ci1es,coun1esandstates

Citedreferences:

Vine, Edward L., and Christopher M. Jones. "Competition, carbon, and conservation: Assessing the energy savings potential of energy efficiency competitions." Energy Research & Social Science 19 (2016): 158-176.

Christopher M. Jones and Daniel M. Kammen. A Consumption-Based Greenhouse Gas Inventory of San Francisco Bay Area Neighborhoods, Cities and Counties: Prioritizing Climate Action for Different Locations. Report prepared for the Bay Area Air Quality Management District. December 15, 2015.

Christopher M. Jones and Daniel M. Kammen. The CoolCalifornia Challenge: A Pilot Inter-City Household Carbon Footprint Reduction. Report prepared for the California Air Resources Board under contract 10-325. November 2014. 90 pages.

Christopher M. Jones and Daniel M. Kammen, Spatial Distribution of U.S. Household Carbon Footprints Reveals Suburbanization Undermines Greenhouse Gas Benefits of Urban Population Density. Environ. Sci. Technol., 2014, 48 (2), pp 895–902.

Christopher M. Jones and Daniel M. Kammen, Quantifying Carbon Footprint Reduction Opportunities for U.S. Households and Communities. Environ. Sci. Technol., 2011, 45 (9), pp 4088–4095


Thankyou

[email protected]

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Mo1va1onClimatechangeistheresultofcountlessdailyac1onsbybillionsofpeople,embeddedincomplexeconomic,socialandculturalsystems.Howcanhumanitymassivelyscaleuptheadop1onofawiderangeoflowcarbontechnologiesandprac1cestoverydiversepopula-ons,eachwiththeirownvalues,mo1va1ons,barriers,opportuni1es,abili1esandcompe1ngpriori1es.

CoolClimateVisionSmartToolsforaCoolerPlanet

Acceleratethetransi1ontoacleanenergyeconomythroughsmartgreenhousegasdecision-makingtoolsandprogramsSmarttoolsandprograms:•  ProduceSMARTrecommenda1ons(specific,measurable,achievable,relevant,1me-bound)•  Mo1vatebehaviorchange(e.g.,feedback,norms,messaging,socialdiffusion…)•  Arvullydesigned(user-friendly,aesthe1callypleasing)•  Responsivetouserinput(engaging,learning)•  Tailoredtospecificaudience(smartdefaults)

PublicPolicy

Communi1es

Organiza1ons

Interpersonal

Individual

Modeledvs.ActualResultShowsEfficiencyofEachLoca#on(policy+behavior)

R²=0.61

0

3000

6000

9000

12000

15000

- 3,000 6,000 9,000 12,000 15,000

kWhpe

rhou

seho

ld(P

G&E)

kWhperhousehold(CoolClimateModel)

AveragekWhperhouseholdbyzipcodeCoolClimatevs.PG&Edata(2013-14)

AMeasureofTechnicalPoten#alforEnergyEfficiency(electricityonly)?

R²=0.61

0

3000

6000

9000

12000

15000

- 3,000 6,000 9,000 12,000 15,000

kWhpe

rhou

seho

ld(P

G&E)



TechnicalPoten1al:~30%atmeanusage

AMeasureofAchievablePoten#alforEnergyEfficiency(electricityonly)?

R²=0.61

0

3000

6000

9000

12000

15000

- 3,000 6,000 9,000 12,000 15,000

kWhpe

rhou

seho

ld(P

G&E)



AchievablePoten1al(1SD):~20%atmeanusage

• CBEIis~35%largerthanproduc1on-basedinventory• GHGfootprintisgenerallylowerinurbancoreareas-smallerhomes,lowervehicleownershiprate,beQertransit

• Varia1onbetweenblockgroups:ra1oof7to1• Varia1onwithin(largeci1es):ra1oof4or5to1• Varia1onbetweenci1es:ra1oof3to1•  Lessvaria1onbetweencoun1es:-averageannualGHGfootprintrangesfrom39to49metrictonsperhousehold

BayAreaGHGFootprint

58

Natural Gas

tCO2e / household

A. Electricity

B. Natural Gas

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Largevaria1oninsizeandcomposi#onofGHGfootprintCoolClimateNetworkmodelincludes30+factorsBut6factorsaccountfor92%ofvaria1oninGHGfootprint:•  vehicleownershiprate•  householdincome•  householdsize(#people)•  sizeofhome(squarefootageofdwellingunit)•  carbonintensityofelectricity•  popula1ondensityofneighborhood

KeyFactors

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TopPolicyRecommenda#ons

1.  IncorporateCBEIinClimateAc1onPlans2.  Urbaninfill:directfuturedevelopmenttoareaswithlowGHGs3.  Promoteelectricvehicles(especiallyinhigh-VMTareas)4.  Promotehealthydiets(e.g.,schoolprograms,meatlessMondays)5.  Requireelectrichea1nginnewhomes6.  Promotesustainableconsump1on:shirfromgoodstolocalservices7.  Promoteefficienthomesize:e.g.,taxincen1vesforsmallerhomes8.  Behaviorchangeprograms(e.g.,energyreduc1oncompe11ons)9.  Promotelow-carbonprocurementdecisionsinlocalbusinesses10. Adopt50%by2050percapitaconsump1on-basedGHGtarget

CBEIMethodology•  Expenditureprofilesforaveragehouseholdineachofthe~4,700

CensusblockgroupsinBayArea–thenscaleup•  Localinputdata:

•  Electricity&naturalgas(byzipcode…modifiedtoblockgroup)•  Other:pubictransit,fueleconomy,recycing/compos1ng•  Censusdata&weather

•  Modelingusingna1onalhouseholdsurveys(BayArearespondents)•  ConsumerExpendituresSurvey•  Na1onalHouseholdTravelSurvey•  Residen1alEnergyConsump1onSurvey

•  Life-cycleGHGemissionfactorsforthe“Kyoto6”setofGHGs-IndirectEmissions:ComprehensiveEnvironmentalDataArchive-BayArea-specificemissionsfactors(water,LCSF) 62

Documents

Enabling Sep 13, 2016 Low Carbon Communiessustainability.illinois.edu/wp-content/uploads/2016/12/...1 Enabling Low Carbon Communies The roles of smart planning tools and place-based