[PPT] - Air Quality Simulations for the San Joaquin Valley Michael J. PowerPoint Presentation

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Air Quality Simulations for the San Joaquin Valley

Michael J. Kleeman Department of Civil and Environmental Engineering UC Davis

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Emissions Modeling System for California S Fully Source- Oriented: Separate emissions inventories for target categories Select target sources based on sources based on the emissions profile they are p y assigned

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Basecase Emissions

PM10 (μg/m2/day) NOx (ppm*m/day) (μg y) (pp y) Crustal Diesel Food

0.45

C usta ese

od

0.2 0.25 0.3 0.35 0.4

ssions Rate

Mobile Em issions

0.05 0.1 0.15 1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139

Em is

Model Day

NOx ROG

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PM2 5 OC + EC PM2.5 OC + EC

Black lines = measurements Blue circles = predictions Red Shading – Mid 50% Quantile within 10km of monitor Diurnal pattern predicted correctly at urban sites Peak values at urban sites show bl t i ll reasonable agreement, especially considering the sharp gradients Rural Angiola predictions are low

Source: Q Ying J Lu P Allen P Livingstone A Kaduwela and M

Rural Angiola predictions are low. Where is the EC+OC coming from?

Source: Q. Ying, J. Lu, P. Allen, P. Livingstone, A. Kaduwela, and M. Kleeman “Modeling Air Quality During the California Regional PM10/PM2.5 Air Quality Study (CRPAQS) Using the UCD/CIT Source- Oriented Air Quality Model – Part I. Base Case Model Results.”, Atmos. Env., in press, 2008.

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Grid Model vs. CMB Source Apportionment

Angiola

**D t d f **Dust sources removed from grid model

Fresno Fresno

**Dust sources removed from grid model

Source: Q. Ying, J. Lu, A. Kaduwela, and M. Kleeman “Modeling Air Quality During the California Regional PM10/PM2.5 Air Quality Study (CRPAQS) Using the UCD/CIT Source-Oriented Air Quality Model – Part II. Regional Source Apportionment of Primary Airborne Particulate Matter.”, Atmos. Env., in press, 2008.

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Predicted (open squares)

80 100 120 (µg m-3)

and Observed OC (solid diamonds) using CACM

20 40 60 OA Concentration 35 12/15 12/16 12/17 12/18 12/26 12/27 12/28 1/4 1/5 1/6 1/7

a.) Fresno

15 20 25 30 ncentration (µg m-3) 5 10 12/15 12/16 12/17 12/18 12/26 12/27 12/28 1/4 1/5 1/6 1/7 OA Con

b ) A i l

60 80 100 (µg m-3)

b.) Angiola

20 40 60 OA Concentration 12/15 12/16 12/17 12/18 12/26 12/27 12/28 1/4 1/5 1/6 1/7

c.) Bakersfield

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PM2.5 Nitrate, Ammonium, Sulfate

Source: Q. Ying, J. Lu, P. Allen, P. Livingstone, A. Kaduwela, and M. Kleeman “Modeling Air Quality During the California Regional PM10/PM2.5 Air Quality Study (CRPAQS) Using the UCD/CIT Source-Oriented Air Quality Model – Part I. Base Case Model Results.”, Atmos. Env., in press, 2008.

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Regional EC g Source Contributions Contributions

Source: Q. Ying, J. Lu, A. Kaduwela, and M. Kleeman “Modeling Air Quality During the California Regional PM10/PM2.5 Air Quality Study (CRPAQS) Using the UCD/CIT Source-Oriented Air Quality Model – Part II. Regional Source Apportionment of Primary Airborne Particulate Matter.”, Atmos. Env., in press, 2008.

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Regional OC g Source Contributions Contributions

Source: Q. Ying, J. Lu, A. Kaduwela, and M. Kleeman “Modeling Air Quality During the California Regional PM10/PM2.5 Air Quality Study (CRPAQS) Using the UCD/CIT Source-Oriented Air Quality Model – Part II. Regional Source Apportionment of Primary Airborne Particulate Matter.”, Atmos. Env., in press, 2008.

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Regional Nit t Nitrate Source Contributions

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Regional NH4+ Source Contributions

Source: Q. Ying, J. Lu, A. Kaduwela, and M. Kleeman “Modeling Air Quality During the California Regional PM10/PM2.5 Air Quality Study (CRPAQS) Using the UCD/CIT Source-Oriented Air Quality Model – Part III. Regional Source Apportionment of Secondary and Total Airborne PM2.5 and PM0.1.”, Atmos. Env., in press, 2008.