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001050288 1001_ $$0P:(DE-HGF)0$$aWang, Hantao$$b0$$eCorresponding author
001050288 245__ $$aIntercomparison of global ground-level ozone datasets for health-relevant metrics
001050288 260__ $$aKatlenburg-Lindau$$bEGU$$c2025
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001050288 520__ $$aGround-level ozone is a significant air pollutant that detrimentally affects human health and agriculture. Global ground-level ozone concentrations have been estimated using chemical reanalyses, geostatistical methods, and machine learning, but these datasets have not been compared systematically. We compare six global ground-level ozone datasets (three chemical reanalyses, two machine learning, one geostatistics) relative to observations and against one another, for the ozone season daily maximum 8 h average mixing ratio, for 2006 to 2016. Comparing with global ground-level observations, most datasets overestimate ozone, particularly at lower observed concentrations. In 2016, across all stations, grid-to-grid R2 ranges from 0.50 to 0.75 and RMSE 4.25 to 12.22 ppb. Agreement with observed distributions is reduced at ozone concentrations above 50 ppb. Results show significant differences among datasets in global average ozone, as large as 5–10 ppb, multi-year trends, and regional distributions. For example, in Europe, the two chemical reanalyses show an increasing trend while other datasets show no increase. Among the six datasets, the share of population exposed to over 50 ppb varies from 61 % [28 %, 94 %] to 99 % [62 %, 100 %] in East Asia, 17 % [4 %, 72 %] to 88 % [53 %, 99 %] in North America, and 9 % [0 %, 58 %] to 76 % [22 %, 96 %] in Europe (2006–2016 average). Although sharing some of the same input data, we found important differences, likely from variations in approaches, resolution, and other input data, highlighting the importance of continued research on global ozone distributions. These discrepancies are large enough to impact assessments of health impacts and other applications.
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001050288 7001_ $$00000-0002-1466-4655$$aMiyazaki, Kazuyuki$$b1
001050288 7001_ $$0P:(DE-HGF)0$$aSun, Haitong Zhe$$b2
001050288 7001_ $$00000-0002-3766-9838$$aQu, Zhen$$b3
001050288 7001_ $$00000-0002-2748-9550$$aLiu, Xiang$$b4
001050288 7001_ $$00000-0003-0603-5389$$aInness, Antje$$b5
001050288 7001_ $$0P:(DE-Juel1)6952$$aSchultz, Martin$$b6
001050288 7001_ $$0P:(DE-Juel1)16212$$aSchröder, Sabine$$b7
001050288 7001_ $$00000-0003-3145-4024$$aSerre, Marc$$b8
001050288 7001_ $$00000-0001-5652-4987$$aWest, J. Jason$$b9
001050288 770__ $$aTOAR-II Community Special Issue
001050288 773__ $$0PERI:(DE-600)2069847-1$$a10.5194/acp-25-15969-2025$$gVol. 25, no. 22, p. 15969 - 15990$$n22$$p15969 - 15990$$tAtmospheric chemistry and physics$$v25$$x1680-7316$$y2025
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