Assessing attainment likelihood of State Implementation Plans

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Thursday, 21 January 2010: 11:00 AM
B316 (GWCC)
Daniel S. Cohan, Rice University, Houston, TX; and A. Digar

Photochemical modeling to inform State Implementation Plans (SIPs) traditionally has applied bright-line tests to evaluate whether a control package is sufficient to achieve attainment. However, because photochemical models are uncertain and future meteorology is unknowable, future pollutant levels cannot be predicted perfectly and attainment cannot be guaranteed absolutely. Instead, it is more realistic to seek to maximize the likelihood of attainment, subject to practical or budgetary constraints.

Here, we introduce methods for estimating the likelihood of attainment for a SIP control strategy in light of three key uncertainties: future meteorology, photochemical model input parameters, and control measure effectiveness. High-order sensitivity analysis of a photochemical model is applied to compute how uncertainty in input parameters (e.g., emission rates, reaction rates, and boundary conditions) leads to uncertainty in the responsiveness of pollutant concentrations to precursor emissions. Retrospective consideration of 8-hour ozone attainment planning for Atlanta, Georgia, provides a case study for this work, conducted under US EPA STAR grant “Incorporating Uncertainty Analysis into Integrated Air Quality Planning.” The methods are applied to characterize the rate at which additional control measures yield improvements in attainment likelihood.