Preprints
https://doi.org/10.5194/egusphere-2024-3310
https://doi.org/10.5194/egusphere-2024-3310
21 Nov 2024
 | 21 Nov 2024
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

Evaluating spatiotemporal variations and exposure risk of ground-level ozone concentrations across China from 2000 to 2020 using satellite-derived high-resolution data

Qingqing He, Jingru Cao, Pablo E. Saide, Tong Ye, and Weihang Wang

Abstract. Understanding the spatiotemporal characteristics of long- and short-term exposure to ground ozone is crucial for improving environmental management and health studies. However, such studies have been constrained by the availability of high-resolution data. To address this, we characterized ground-level ozone variations and exposure risks across multiple spatial (pixel, county, region, and national) and temporal (daily, monthly, seasonal, and annual) scales using daily 1-km ozone data from 2000 to 2020, derived from satellite LST data via a machine-learning method. The model provided reliable estimates, validated through rigorous cross-validation and direct comparison with external ground-level measurements. Our long-term estimates revealed seasonal shifts in high-exposure ozone centers: spring in eastern China, summer in the North China Plain (NCP), and autumn in the Pearl River Delta (PRD). A non-monotonous trend was observed, with ozone levels rising from 2001–2007 at a rate of 0.47 μg/m3/year, declining after 2008 (-0.58 μg/m3/year), and increasing significantly from 2016–2020 (1.16 μg/m3/year), accompanied by regional and seasonal fluctuations. Notably, ozone levels increased by 0.63 μg/m3/year in summer in the NCP during the second phase, and by 6.38 μg/m3/year in autumn in the PRD during the third phase. Exposure levels over 100 μg/m3 have shifted from June to May, and levels exceeding 160 μg/m3 were primarily seen in the NCP, showing an expanding trend. Our day-to-day analysis highlights the influence of meteorological factors on extreme events. These findings emphasize the need for stronger mitigation efforts.

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Qingqing He, Jingru Cao, Pablo E. Saide, Tong Ye, and Weihang Wang

Status: open (until 02 Jan 2025)

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Qingqing He, Jingru Cao, Pablo E. Saide, Tong Ye, and Weihang Wang
Qingqing He, Jingru Cao, Pablo E. Saide, Tong Ye, and Weihang Wang
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Short summary
We explored variations in ground ozone and exposure risk hotspots across China (2000–2020) at multiple spatiotemporal scales using a high-resolution dataset derived from satellite LST via a machine-learning hindcast framework. The dataset was validated using cross-validation and external measurements. A non-monotonous trend emerged, with turning points around 2007 and 2015, showing regional variation. Ozone levels >100 μg/m3 shifted from June to May, while levels >160 μg/m3 expanded in the NCP.