Reliability of optimal control strategies for photochemical air pollution

This study illustrates how consideration of modeling uncertainties can affe ct optimal control strategies for urban ozone. Control strategies are inves tigated for illustrative cases of air parcel trajectories ending at Azusa, CA, and Riverside, CA, on August 28, 1987. The control strategies are desig ned to achieve a specified air quality target with a given reliability, con sidering uncertainties in the California Institute of Technology's trajecto ry model and its inputs, including uncertainties in emissions and in the SA PRC-97 chemical mechanism. A decoupled stochastic optimization scheme is us ed to solve the chance-constrained programming;problem, Least-cost control strategies derived using nominal model inputs and parameter Values have low reliability for some target O-3 concentrations when uncertainties are take n into account. For the case considered, reducing Volatile organic compound (VOC) emissions from motor vehicles is identified as the least-cost approa ch to meeting O-3 targets at Azusa. However, the optimal control strategies for Riverside depend on the target O-3 concentrations and the level of rel iability required. Consideration of model uncertainty is found to shift the focus from VOC controls to nitrogen oxide controls for the Riverside traje ctory.