Title: | Improved Estimation of Trends in U.S. Ozone Concentrations Adjusted for Interannual Variability in Meteorological Conditions |
Author(s): | Wells B; Dolwick P; Eder B; Evangelista M; Foley K; Mannshardt E; Misenis C; Weishampel A; |
Address: | "United States Environmental Protection Agency, Research Triangle Park, NC. North Carolina State University, Raleigh, NC" |
DOI: | 10.1016/j.atmosenv.2021.118234 |
ISSN/ISBN: | 1352-2310 (Print) 1352-2310 (Linking) |
Abstract: | "Daily maximum 8-hour average (MDA8) ozone (O(3)) 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 O(3) concentrations for meteorological effects using various statistical and mathematical methods in order to get a better estimate of the long-term changes in O(3) concentrations due to changes in precursor emissions such as nitrogen oxides (NO(X)) 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 O(3) 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 90(th) and 98(th) percentiles of the distribution of MDA8 O(3) concentrations, allowing for a better understanding of the effects of local meteorology on peak O(3) levels in addition to seasonal average concentrations. The revised method is used to adjust trends in the May to September mean, 90(th) percentile, and 98(th) percentile MDA8 O(3) 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 O(3) 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 O(3) National Ambient Air Quality Standards (NAAQS)" |
Keywords: | meteorology ozone quantile regression statistics trends variable selection; |
Notes: | "PubMed-not-MEDLINEWells, Benjamin Dolwick, Pat Eder, Brian Evangelista, Mark Foley, Kristen Mannshardt, Elizabeth Misenis, Chris Weishampel, Anthony eng EPA999999/ImEPA/Intramural EPA/ England 2021/03/30 Atmos Environ (1994). 2021 Mar 1; 248:118234. doi: 10.1016/j.atmosenv.2021.118234" |