ABSTRACT
Daily maximum 8-hour average (MDA8) ozone (O3) concentrations are well-known to be influenced by local meteorological conditions, which vary across both daily and seasonal temporal scales. Previous studies have adjusted long-term trends in O3 concentrations for meteorological effects using various statistical and mathematical methods in order to get a better estimate of the long-term changes in O3 concentrations due to changes in precursor emissions such as nitrogen oxides (NOX) and volatile organic compounds (VOCs). In this work, the authors present improvements to the current method used by the United States Environmental Protection Agency (US EPA) to adjust O3 trends for meteorological influences by making refinements to the input data sources and by allowing the underlying statistical model to vary locally using a variable selection procedure. The current method is also expanded by using a quantile regression model to adjust trends in the 90th and 98th percentiles of the distribution of MDA8 O3 concentrations, allowing for a better understanding of the effects of local meteorology on peak O3 levels in addition to seasonal average concentrations. The revised method is used to adjust trends in the May to September mean, 90th percentile, and 98th percentile MDA8 O3 concentrations at over 700 monitoring sites in the U.S. for years 2000 to 2016. The utilization of variable selection and quantile regression allow for a more in-depth understanding of how weather conditions affect O3 levels in the U.S. This represents a fundamental advancement in our ability to understand how interannual variability in weather conditions in the U.S. may impact attainment of the O3 National Ambient Air Quality Standards (NAAQS).
