Preprints
https://doi.org/10.5194/acp-2022-716
https://doi.org/10.5194/acp-2022-716
01 Nov 2022
 | 01 Nov 2022
Status: this preprint was under review for the journal ACP but the revision was not accepted.

Assessment of the impacts of cloud chemistry on surface SO2 and sulfate levels in typical regions of China

Jian-yan Lu, Sunling Gong, Chun-hong Zhou, Jian Zhang, Jian-min Chen, and Lei Zhang

Abstract. A regional online chemical weather model WRF/ CUACE (China Meteorological Administration Unified Atmospheric Chemistry Environment) was used to assess the contributions of cloud chemistry to the SO2 and sulfate levels in typical regions in China. By comparing with several time series of in-situ cloud chemical observations on Mountain Tai in Shandong Province of China, the CUACE cloud chemistry scheme was found to well reproduce the cloud processing the consumptions of H2O2, O3 and SO2, and consequently was used in the regional assessment for a heavy pollution episode and monthly average in December 2016. During cloud availability in heavy pollution episode, the sulfate production increases 40–80 % and SO2 reduces over 80 %. During the heavy pollution episode, it is found that the cloud chemistry mainly affects the middle and lower troposphere below 5 km as well as within the boundary layer, and contributes significantly to SO2 reduction and sulfate increase in east-central China. Among the regions of North China Plain (NCP), Yangtze River Delta (YRD) and Sichuan Basin (SCB), the SCB is mostly affected by the cloud chemistry, with the average SO2 abatement up to about 1–15 ppb and sulfate increase up to more than 50 μg m-3, followed by YRD where the contribution of cloud chemistry is still significant, averaging up to 1–3 ppb for SO2 abatement and 5–20 μg/m3 for sulfate increase. The cloud chemistry contribution to PRD and NCP are not significant and weaker than other two regions due to lighter pollution and less water vapor, respectively. In addition, the average contribution of cloud chemistry during the pollution period was significantly greater than that for all December. This study provides a way to analyze the over-estimate phenomenon of SO2 in many chemical transport models.

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Jian-yan Lu, Sunling Gong, Chun-hong Zhou, Jian Zhang, Jian-min Chen, and Lei Zhang

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2022-716', Anonymous Referee #1, 07 Dec 2022
  • RC2: 'Comment on acp-2022-716', Anonymous Referee #2, 16 Dec 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2022-716', Anonymous Referee #1, 07 Dec 2022
  • RC2: 'Comment on acp-2022-716', Anonymous Referee #2, 16 Dec 2022
Jian-yan Lu, Sunling Gong, Chun-hong Zhou, Jian Zhang, Jian-min Chen, and Lei Zhang
Jian-yan Lu, Sunling Gong, Chun-hong Zhou, Jian Zhang, Jian-min Chen, and Lei Zhang

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Short summary
A regional online chemical weather model WRF/ CUACE was used to assess the contributions of cloud chemistry to the SO2 and sulfate levels in typical regions in China. The cloud chemistry scheme in CUACE was evaluated, and well reproduces the cloud chemistry processes. During cloud availability in a heavy pollution episode, the sulfate production increases 40–80 % and SO2 reduces over 80 %. This study provides a way to analyze the over-estimate phenomenon of SO2 in many chemical transport models.
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