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Project Number:
 
10-008
Title:
 
Factors Influencing Ozone-Precursor Response in Texas Attainment Modeling
Lead PI:
 
Daniel Cohan
Institution(s) Represented:
 
Rice University- Daniel Cohan, ENVIRON- Greg Yarwood
AQRP Project Manager:
 
Elena McDonald-Buller
TCEQ Project Liaison:
 
Jim Smith
Awarded Amount:
 
$178,796.00

Executive Summary- Project 10-008
Factors Influencing Ozone-Precursor Response in Texas Attainment Modeling
 
This project aims to characterize how various model inputs and formulations influence predictions of ozone-precursor response in Texas ozone attainment modeling episodes. Bayesian inference is being used to consider model performance for alternate structural and parametric scenarios to develop probabilistic representations of ozone response to emissions. The expected outcomes of this research are to improve understanding of how various factors (anthropogenic and biogenic emission rates, chemical mechanisms, photolysis rates, boundary conditions, and dry deposition schemes) influence ozone response predictions; to help prioritize future improvements to Texas SIP modeling; and to demonstrate how probabilistic analyses via an ensemble approach can supplement deterministic estimates of ozone response.

Work Plan:
 
     
Technical Report(s):
 
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Publications & Citations
Digar, A., D.S. Cohan, X. Xiao, K.M. Foley, B. Koo, and G. Yarwood (2013). Constraining ozone-precursor responsiveness using ambient measurements. Journal of Geophysical Research, 118(2), 1005-1019, doi:10.1029/2012JD018100.