Determining Alternative Futures - Urban Development Effects on Air

Quality

Julide Kahyaoglu-Koracin and Darko Koracin

May 2007

Zagreb, Croatia

Objectives

•Evaluate the impact of the four alternative futures on air quality in Southwest California

•Develop a modeling system to integrate projected land use patterns with atmospheric emissions and secondary pollutants, meteorology and dispersion, and transportation

•Provide an assessment of the likelihood that San Diego County will violate various Federal and California Standards

Framework for the assessment of air quality using an alternative futures methodology (Mouat et al., 2004)

Total Emissions

BiogenicEmissions

Area SourceEmissions

AirQuality

ProcessModels

ExistingConditions

AirChemistry

MobileSource

Emissions

FutureAir

Quality

PotentialFutureConditions

PotentialFutureConditions

ExistingConditions

&Policies

ExistingConditions

&Policies

ExistingLand Cover

And Infrastructure

AvailableLand

&Policies

AvailableLand

&Policies

Change inPopulation

Values & Views

Change inPopulationChange inPopulation

Values & ViewsValues & Views

FutureLand Cover

AndInfrastructure

XX

YY

AirQuality

ImpactonFutureConditions

ImpactonFutureConditions

Total Emissions

Future Total Emissions

Species of interestPrimary Pollutants:CONOx

SO2

PM2.5 , PM10

VOCs

Secondary PollutantsO3

PM2.5

 Current non-attainment designations for

San Diego County

PollutantAveraging Time Federal Standard

California State Standard

O3 1-hr Maintenance area Non-attainment

O3 8-hr Non-attainment Not applicable

PM10 Annual Attainment Non-Attainment

PM2.5 Annual Non-attainment Not yet designated

Major commuting zones and associated work centers

Orange and Los Angeles Counties

Riverside County

San Diego

County (West)

San Diego

County (NE)

San Diego County

(SE) 

Orange and Los Angeles Counties

97% 2% 1% 0% 0%

Riverside County 25% 72% 2% 1% 0%

San Diego County (West)

1% 1% 97% 1% 0%

San Diego County (Northeast)

1% 1% 86% 12% 0%

San Diego County (Southeast)

1% 1% 93% 4% 1%

Transportation modeling: Percentage of commuters traveling from

home (rows) to work centers (columns)

Total NOx Base Case Emissions

(Shearer et al., 2004)

Species CO NOx SO2 TOG (VOC) PM

Source Area Mobile Area Mobile Area Mobile Area Mobile Area Mobile

2003 6.92 1817.14 2.63 220.21 0.029 12.08 82.47 193.79 287.08 6.06

Coastal Future: 500 k 7.25 1968.83 3.26 233.00 0.033 12.16 87.84 207.62 287.16 6.99

change 0.26 151.69 0.63 12.80 0.004 0.08 5.37 13.82 0.08 0.93

1,000 k 7.50 2152.46 3.89 247.27 0.037 12.27 93.21 220.32 287.24 8.04

change 0.51 335.32 1.26 27.07 0.008 0.19 10.74 26.53 0.17 1.98

Example of emissions estimates (tons/day) for existing conditions and the Coastal Future

  2003 Coastal NorthernReg. Low Density

Three Centers

CO 1817.14 2152.46 2165.20 2145.28 2144.09

Change 335.32 348.06 328.14 326.95

NOx 220.21 247.27 249.21 247.33 247.00

Change 27.06 29.00 27.12 26.79

SO2 12.08 12.27 12.27 12.26 12.26

Change 0.19 0.20 0.19 0.19

TOG (VOC)

193.79 220.32 222.44 223.89 221.36

Change 26.53 28.65 30.10 27.57

PM 6.06 8.04 8.26 8.38 8.14

Change 1.98 2.20 2.32 2.08

Mobile source emissions estimates (tons/day) for existing conditions and the Alternative Futures

NOx emissions by source category

Area Mobile

Stationary Biogenic

NOx emissions by scenario with 1,000k new residents

Coastal Northern

RegionalLow Density

ThreeCenters

MM5 generated one-hour average temperature, wind, and sea-level pressure for July 10, 2003, 10AM -> CAMx

-118.4 -118 -117.6 -117.2 -116.8 -116.4 -116 -115.6

Peak O zone (ppb) Base C ase - Ju ly 10

32.2

32.4

32.6

32.8

33

33.2

33.4

33.6

33.8

34

34.2

0

10

20

30

40

50

60

70

80

90

100

110

120

130

140

150

160

170

180

190

200

Maximum O3 for July 10, 2003

O3 difference distributions by

scenario for 1,000k new residents

Coastal Northern

RegionalLow Density

ThreeCenters

PM2.5 difference distribution by

scenario for 1,000k new residents

 

Coastal Northern

RegionalLow Density

ThreeCenters

Simulations July 7 July 8 July 9 July 10 July 11

Max O3

Diff. Max O3

Diff. Max O3

Diff. Max O3

Diff. Max O3

Diff.

Base Case 115 - 132 - 129 - 135 - 121 -

Coastal Future (1,000k)

128 13 134 2 136 7 143 8 128 7

Northern Future (1,000k)

138 23 134 2 142 13 146 11 133 12

Regional Low Density Future (1,000k)

150 35 134 2 142 13 146 11 137 16

Three Centers Futures (1,000k)

139 24 134 2 141 12 146 11 134 13

Predicted maximum ozone (ppb) values for five simulations and episode days

Summary

The addition of 500k or 1,000k residents to the study area appears to have a greater overall impact on air quality than does their distribution.

Nevertheless the resultant differences in human activity influence air quality.

The project developed a modeling system to predict air quality based on changes in land use patterns resulting from development and growth

• The system coupled land-use predictions with transportation, emissions, meteorology, dispersion, and transportation models.

• This tool can allow potential users to evaluate and assess other “least likely impacts” stemming from the impacts of future growth.

Summary (cont.)

Summary (cont.)

•The area will continue to be in violation of the annual Federal PM2.5 and California 1-hour O3

standards, and is likely to be in violation of the annual California PM2.5 and Federal 1-hour O3 standards.

•Regulators should focus on reducing primary PM2.5