Extreme ozone events: Tail behavior of the surface ozone distribution over the U.S. (March 2016)

• Record Type: Journal Article
• Authors: Phalitnonkiat, Pakawat; Sun, Wenxiu; Grigoriu, Mircea Dan; Hess, Peter; Samorodnitsky, Gennady
• Is Part Of: Atmospheric environment. Volume 128(2016)
• Page Start: 134
• Page End: 146
• Publication Date: 2016-03
• Subjects: Extremes -- EVT -- Hill estimator -- GPD -- Ozone -- Air pollution; Air -- Pollution -- Periodicals; Air -- Pollution -- Meteorological aspects -- Periodicals; 551.51
• DOI: 10.1016/j.atmosenv.2015.12.047
• Languages: English
• ISSNs: 1352-2310

Abstract

Abstract: The ground level ozone concentration over the continental United States is analyzed from the point of view of modern Extreme Value Theory using ozone data from the Clean Air Status and Trends Network (CASTNET) at 25 measurement sites. At each site the data is analyzed separately for two time periods (1992–2002 and 2003–2013) approximately separated by the NOX SIP call. The Generalized Pareto Distribution is fit to extremes of the ozone concentration by using a combination of maximum likelihood estimates (MLEs) and Hill estimates. The data is appropriately transformed prior to extreme value analysis and data in the right tail is separated from that in the middle part of the distribution. This analysis is compared to current approaches by using synthetic data. Under a variety of conditions the procedure using the MLE approach is likely to underestimate the tail of the distribution. The analysis of the CASTNET ozone data shows that at some locations the ozone probability distribution is not exponentially bounded, and thus can be characterized as heavy tailed, and that at other locations this distribution is not heavy and is bounded to the right so that the ozone concentration is bounded for any return period. The tails of the distribution of ozone concentration become heavier following the NOX SIP call at most of the sites with heavy tails prior to this call. Highlights: Analyze the concentration of ozone using extreme value theory. Transform the data to get rid of inter- and intra-annual effects. Generate synthetic data to compare and verify the methods used. Calculate upper limits (if applicable) and 20-year return levels of ozone. NOx SIP call decreases the mean but increases shape parameter of the distribution.