Preprints
https://doi.org/10.5194/essd-2022-187
https://doi.org/10.5194/essd-2022-187
07 Jun 2022
 | 07 Jun 2022
Status: this discussion paper is a preprint. It has been under review for the journal Earth System Science Data (ESSD). The manuscript was not accepted for further review after discussion.

Reconstructed daily ground-level O3 in China over 2005–2021 for climatological, ecological, and health research

Chenhong Zhou, Fan Wang, Yike Guo, Cheng Liu, Dongsheng Ji, Yuesi Wang, Xiaobin Xu, Xiao Lu, Yan Wang, Gregory Carmichael, and Meng Gao

Abstract. Accompanied by the continuous declines of PM2.5, O3 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 O3 have been operated for decades and nationwide monitoring of ground-level O3 has been offered since 2013 in China, climatological variability of ground-level O3 remains unknown, which impedes understanding of the long-term driver and impacts of O3 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 O3 over 2005–2021 in China. Model validation confirms the robustness of this dataset, with R2 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 2005–2021 with 0.1°×0.1° gap-free grids, which can facilitate climatological, ecological, and health research. The dataset is freely available at Zenodo (https://zenodo.org/record/6507706#.Yo8hKujP13g; Zhou, 2022).

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Chenhong Zhou, Fan Wang, Yike Guo, Cheng Liu, Dongsheng Ji, Yuesi Wang, Xiaobin Xu, Xiao Lu, Yan Wang, Gregory Carmichael, and Meng Gao

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2022-187', Anonymous Referee #1, 27 Jul 2022
  • CEC1: 'Comment on essd-2022-187', David Carlson, 29 Jul 2022
  • EC1: 'Comment on essd-2022-187', Qingxiang Li, 31 Jul 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2022-187', Anonymous Referee #1, 27 Jul 2022
  • CEC1: 'Comment on essd-2022-187', David Carlson, 29 Jul 2022
  • EC1: 'Comment on essd-2022-187', Qingxiang Li, 31 Jul 2022
Chenhong Zhou, Fan Wang, Yike Guo, Cheng Liu, Dongsheng Ji, Yuesi Wang, Xiaobin Xu, Xiao Lu, Yan Wang, Gregory Carmichael, and Meng Gao

Data sets

Reconstructed daily ground-level MDA8 O3 over 2005-2021 in China Chenghong Zhou; Fan Wang; Yike Guo; Gregory R. Carmichael; Cheng Liu; Yan Wang; Meng Gao https://zenodo.org/record/6507706#.YpMbmHZBxLl

Chenhong Zhou, Fan Wang, Yike Guo, Cheng Liu, Dongsheng Ji, Yuesi Wang, Xiaobin Xu, Xiao Lu, Yan Wang, Gregory Carmichael, and Meng Gao

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Short summary
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 O3 over 2005–2021 in China. It can facilitate climatological, ecological, and health research. The dataset is freely available at Zenodo (https://zenodo.org/record/6507706#.Yo8hKujP13g; Zhou, 2022).
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