Adjoint sensitivity analysis of ozone formation under different types of synoptic events

California's San Joaquin Valley suffers from serious ozone air pollution problems due to its unique geography as well as diverse emission sources from both local and upwind areas. Mesoscale flows directly influence spatial distributions of ozone and ozone limiting reagents, and change the source-receptor relationships. Synoptic systems that interact with mesoscale meteorology give rise to different types of ozone episodes. As climate change may modify the strengths and occurrence frequencies of synoptic systems, understanding the variability in ozone levels and their sensitivities to emission sources under different types of synoptic events is therefore important to anticipating changes in future chemical regimes of ozone pollution and ozone control strategies.

While past modeling studies have investigated ozone-to-precursor sensitivities in relation to meteorology conditions, most of them rely on forward simulations of ozone responses to a collective change in precursor emissions. These practices cannot distinguish the relative importance of emissions of different locations or times, which also vary with meteorology. This study aims to map influential emissions to population weighted 8 h maximum ozone in the San Joaquin Valley and to characterize their spatiotemporal heterogeneity across four representative synoptic events determined from cluster analysis over a summer season. We use an adjoint tool coupled to EPA's chemical transport model (CMAQ). The adjoint tool enables efficient calculation of ozone sensitivities to large numbers of model parameters such that influential precursor emissions can be resolved at high spatial resolution. We will delineate areas of influence in space and time and determine variabilities in ozone sensitivities to limiting reagents across different flow and temperature regimes. Our results will enhance the understanding of the underlying physicochemical processes that connect ozone air pollution to various modes of variability in meteorology.