Spatial and Temporal Representation of Ozone Precursors and Ozone Production in Air Quality Models

As air quality in the Eastern United States has improved, determining the root cause of air pollution episodes has become more challenging. This not only impacts the ability to reliably forecast pollution episodes but also the development of regulations that will lead to further reductions in ozone and its precursors, such as NO_x and volatile organic compounds (VOCs). Policy makers rely on air quality models such as CMAQ and CAMx to test realistic attainment strategies that will lead to further improvements in air quality. A necessary condition is that these models should sufficiently represent the actual chemistry, emissions, and meteorology leading to pollution events. Here, we use ground-based, aircraft, and satellite observations to test the spatial and temporal representation of NO_x, VOCs, and ozone production in air quality model simulations using recent versions of the Carbon Bond chemical mechanism. Our primary focus is years 2011 and 2016, designated as “baseline” by state and federal agencies. Baseline years are used by regulatory agencies to determine the relative change in surface ozone, based on anticipated and theoretical pollution control strategies, for future years. For the baseline years, relatively accurate emissions inventories and meteorological fields prepared by the EPA, state and regional agencies have or are being developed for use in preparation of state implementation planning. This works builds upon the wealth of similar research performed by our group through a multi-decadal collaboration with the Maryland Department of the Environment which has led to significant improvements in prior regulatory model platforms. The implications for policy development and future observational needs will be discussed.