Preprints
https://doi.org/10.5194/acp-2022-818
https://doi.org/10.5194/acp-2022-818
09 Jan 2023
 | 09 Jan 2023
Status: a revised version of this preprint was accepted for the journal ACP and is expected to appear here in due course.

The role of temporal scales in extracting dominant meteorological drivers of major airborne pollutants

Miaoqing Xu, Jing Yang, Manchun Li, Xiao Chen, Qiancheng lv, Qi Yao, Bingbo Gao, and Ziyue Chen

Abstract. The influence of individual meteorological factors on different airborne pollutants has been massively conducted. However, few studies have considered the effect of temporal scales on the extracted pollutant-meteorology association. Based on Convergent Cross Mapping (CCM), we compared the influence of major meteorological factors on PM2.5, PM10 and O3 concentrations at the 3 h and 24 scale. In terms of the extracted dominant meteorological factor, the consistence between the analysis at 3 h and 24 h scale was relatively low, suggesting a large difference even from a qualitative perspective. In terms of the mean ρvalue, the effect of temporal scale on PM (PM2.5 and PM10)-Meteorology association was consistent, yet largely different from the temporal-scale effect on O3. Temperature was the most important meteorological factor for PM2.5, PM10 and O3 across China at both 3 h and 24 scale. For PM2.5 and PM10, the extracted PM-temperature association at the 24 h scale was stronger than that at the 3 h scale. Meanwhile, for summer O3, due to strong reactions between precursors, the extracted O3-temperature association at the 3 h scale was much stronger. Due to the discrete distribution, the extracted association between all pollutants and precipitation was much weaker at the 3 h scale. Similarly, the extracted PM-wind association was notably weaker at the 3 h scale. Due to precursor transport, summertime O3-wind association was stronger at the 3 h scale. For atmospheric pressure, the pollutant-pressure association was weaker at the 3 h scale except for summer, when interactions between atmospheric pressure and other meteorological factors were strong. From the spatial perspective, pollutant-meteorology association at 3 h and 24 h was more consistent in those heavily polluted regions. This research suggested that temporal scales should be carefully considered when extracting natural and anthropogenic drivers for airborne pollution.

Miaoqing Xu et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2022-818', Anonymous Referee #1, 27 Jan 2023
    • AC1: 'Reply on RC1', Ziyue Chen, 08 Mar 2023
  • RC2: 'Comment on acp-2022-818', Anonymous Referee #2, 15 Feb 2023
    • AC2: 'Reply on RC2', Ziyue Chen, 08 Mar 2023

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2022-818', Anonymous Referee #1, 27 Jan 2023
    • AC1: 'Reply on RC1', Ziyue Chen, 08 Mar 2023
  • RC2: 'Comment on acp-2022-818', Anonymous Referee #2, 15 Feb 2023
    • AC2: 'Reply on RC2', Ziyue Chen, 08 Mar 2023

Miaoqing Xu et al.

Miaoqing Xu et al.

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Short summary
Although the temporal-scale effects on Meteorology-PM2.5 associations have been discussed, no quantitative evidence proved this before. Based on a rare 3 h-meteorology data, we revealed that the dominant meteorological factor for PM2.5 concentrations across China extracted at the 3 h and 24 h scale presented large variations. This research suggested that data sources of different temporal scales should be comprehensively considered for better attribution and prevention airborne pollution.
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