ESSDD Earth System Science Data Discussions ESSDD Earth Syst. Sci. Data Discuss. 1866-3591 Göttingen, Germany 10.5194/essd-2022-187 Reconstructed daily ground-level O<sub>3</sub> in China over 2005&ndash;2021 for climatological, ecological, and health research Zhou Chenhong 1 9 Wang Fan 2 9 Guo Yike 1 Liu Cheng https://orcid.org/0000-0002-3759-9219 3 Ji Dongsheng https://orcid.org/0000-0002-7889-4417 4 Wang Yuesi 4 Xu Xiaobin https://orcid.org/0000-0003-4321-9267 5 Lu Xiao https://orcid.org/0000-0002-5989-0912 6 Wang Yan 7 Carmichael Gregory 8 Gao Meng https://orcid.org/0000-0002-8657-3541 2 Department of Computer Science, Faculty of Science, Hong Kong Baptist University, Hong Kong SAR, China Department of Geography, Faculty of Social Sciences, Hong Kong Baptist University, Hong Kong SAR, China Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, 230026, Anhui Province, China State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China State Key Laboratory of Severe Weather & Key Laboratory for Atmospheric Chemistry of China Meteorological Administration, Chinese Academy of Meteorological Sciences, Beijing, 100081, China School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, 519082, Guangdong Province, China Department of Ocean Science, The Hong Kong University of Science and Technology, Hong Kong, Hong Kong SAR, China Department of Chemical and Biochemical Engineering, University of Iowa, Iowa City, IA 52242, USA These authors contributed equally to this work. Research Grants Council, University Grants Committee HKBU22201820 HKBU12202021 National Natural Science Foundation of China 42005084 07 06 2022 2022 1 21 Copyright: © 2022 Chenhong Zhou et al. 2022 This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/ This article is available from https://essd.copernicus.org/preprints/essd-2022-187/ The full text article is available as a PDF file from https://essd.copernicus.org/preprints/essd-2022-187/essd-2022-187.pdf

<p>Accompanied by the continuous declines of PM<sub>2.5</sub>, O<sub>3</sub> pollution has become increasingly prominent and has been targeted by the Government of China to protect climate, ecosystem, and human health. Although satellite retrievals of column O<sub>3</sub> have been operated for decades and nationwide monitoring of ground-level O<sub>3</sub> has been offered since 2013 in China, climatological variability of ground-level O<sub>3</sub> remains unknown, which impedes understanding of the long-term driver and impacts of O<sub>3</sub> pollution in China. Here we develop an eXtreme Gradient Boosting (XGBoost) model integrating high-resolution meteorological data, satellite retrievals of trace gases, etc. to provide reconstructed daily ground-level O<sub>3</sub> over 2005&ndash;2021 in China. Model validation confirms the robustness of this dataset, with R<sup>2</sup> of 0.89 for sample-based cross-validation. The accuracy of the long-term variations has also been confirmed with independent historical observations covering the same period from urban, rural and background sites. Our dataset covers the long time period of 2005&ndash;2021 with 0.1&deg;&times;0.1&deg; gap-free grids, which can facilitate climatological, ecological, and health research. The dataset is freely available at Zenodo (<a href="https://zenodo.org/record/6507706#.Yo8hKujP13g" target="_blank" rel="noopener">https://zenodo.org/record/6507706#.Yo8hKujP13g</a>; Zhou, 2022).</p>