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Uncertainties influencing dynamic evaluation of ozone trends

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Presentation on theme: "Uncertainties influencing dynamic evaluation of ozone trends"— Presentation transcript:

1 Uncertainties influencing dynamic evaluation of ozone trends
Wei Zhou and Daniel Cohan Rice University 10th Annual CMAS Conference October 26, 2011

2 Emission reduction leads to the improvement of air quality
US EPA,2010

3 Objectives Evaluate the performance of air quality model in modeling air quality trend - identify the direction and magnitude of trend - characterize the spatial feature Investigate the impact of uncertain parameters on modeling O3 trend - Meteorology - Emission estimate and trend - Chemical reactions

4 Modeling summer ozone change from 2002 to 2006
Substantial emission reduction and O3 decrease Consistent modeling systems for both years Observational data for modeling evaluation

5 Emission trend from 2002 to 2006 Year Elevated emission (ktons) Ground emission Total 2002 1324 2193 3517 2006 930 2012 2942 Difference( ) -29.8% -8.3% -16.3% Elevated emission: Electrical Generating Units (EGUs) and Non-EGUs Ground emission: mobile, non-road, and other sources Elevated emission: greater reduction and relatively low uncertainty Ground emission: less reduction and higher uncertainty

6 Metrics to evaluate ozone change
Difference of concentration (DIF) = C(2006)-C(2002) -Negative: downward trend -Positive: upward trend 95th percentile of cumulatively distributed 8hr O3 concentration Daily maximum 8hr O3 averaged over the episode

7 Comparison of NOx change between model and observation
DIF_OBS_NOx DIF_NOx(ppb) DIF_MOD_NOx

8 Comparison of O3 change between model and observation
DIF_O3(ppb) DIF_OBS_O3 DIF_MOD_O3

9 No clear correlation between ozone trend and temperature variability
DIF_TEMP= daily maximum temperature in daily maximum temperature in 2002

10 Evaluating modeled NOx and O3 trend in large urban areas

11 Improvement of modeled O3 trend by adjusting NOx emission
NOx Adjustment factor= 1-OBS_NOx/MOD_NOx Atlanta Chicago Houston New York Pittsburgh Philadelphia 2002 0.14 -0.09 -0.3 -0.26 0.3 -0.05 2006 0.20 -0.20 -0.28 -0.11

12 Uncertain parameters affecting the simulation of O3 trend
NOx emission - emission estimate - emission reduction trend VOC emission Chemical reaction - photolysis rates - reaction rate (e.g. OH+NO2->HNO3)

13 Perturbing uncertain parameters to improve the simulation of O3 trend
Decrease NOx estimate Increase NOx reduction trend Decrease VOC emission Increase photolysis rates Decrease the reaction rate of OH+NO2-> HNO3

14 Conclusion Model generally captures the direction of O3 change but significantly underestimates the magnitude of O3 decrease Adjusting NOx emission improves the modeling of O3 downward trend but the O3 decreases remain underestimated Modeled O3 trend can be modestly improved by perturbing uncertainty in NOx emission and trend, VOC emission, photolysis and chemical reactions

15 Acknowledgement National Science Foundation CAREER Award #0847386
Sergey Napelenok of US EPA US EPA Air Quality System(AQS)

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