Preprints
https://doi.org/10.5194/egusphere-2023-2640
https://doi.org/10.5194/egusphere-2023-2640
18 Dec 2023
 | 18 Dec 2023

Diagnosing Ozone-NOx-VOCs-Aerosols Sensitivity to Uncover Urban-nonurban Discrepancies in Shandong, China using Transformer-based High-resolution Air Pollution Estimations

Chenliang Tao, Yanbo Peng, Qingzhu Zhang, Yuqiang Zhang, Bing Gong, Qiao Wang, and Wenxing Wang

Abstract. Narrowing surface ozone disparities between urban and nonurban areas escalate health risks in densely populated urban zones. A comprehensive understanding of the impact of ozone photochemistry processes on this transition remains constrained by our knowledge of aerosol effects and the spatial availability of surface monitoring. Here we developed a novel deep learning framework, which could perceive spatiotemporal dynamics from adjacent grids by multidimensional self-attention operation, integrating multi-sources data to estimate daily 500 m surface ozone, nitrogen dioxide (NO2) and fine particulate matter (PM2.5) concentrations. Subsequently, three distinct ozone formation regimes linked with its precursors, aerosols, and meteorology were delineated through an interpretable machine learning method. The evaluations of the framework exhibited average out-of-sample cross-validation coefficient of determination of 0.96, 0.92 and 0.95 for ozone, NO2 and PM2.5, respectively. In 2020, urban ozone levels in Shandong surpassed those in nonurban due to a more pronounced decrease in ozone in the latter where PM2.5 is the dominant anthropogenic driver. The ozone sensitivity to volatile organic compounds (VOCs), the dominant regime in urban areas, was observed to shift towards a NOx-limited when extended to rural areas. A third ‘aerosol-inhibited’ regime was identified in the Jiaodong Peninsula, where the uptake of hydroperoxyl radicals onto aerosols suppressed ozone production under low NOx levels during summertime. The reduction of PM2.5 would increase the sensitivity of ozone to VOCs, necessitating more stringent VOC emission abatement for urban ozone mitigation. Our case study demonstrates the critical need for advanced modeling approaches providing finer spatially resolved estimations.

Chenliang Tao, Yanbo Peng, Qingzhu Zhang, Yuqiang Zhang, Bing Gong, Qiao Wang, and Wenxing Wang

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-2640', Anonymous Referee #1, 26 Dec 2023
  • RC2: 'Comment on egusphere-2023-2640', Anonymous Referee #1, 05 Jan 2024
  • RC3: 'Comment on egusphere-2023-2640', Anonymous Referee #2, 13 Jan 2024

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-2640', Anonymous Referee #1, 26 Dec 2023
  • RC2: 'Comment on egusphere-2023-2640', Anonymous Referee #1, 05 Jan 2024
  • RC3: 'Comment on egusphere-2023-2640', Anonymous Referee #2, 13 Jan 2024
Chenliang Tao, Yanbo Peng, Qingzhu Zhang, Yuqiang Zhang, Bing Gong, Qiao Wang, and Wenxing Wang

Data sets

Surface Ozone, NO2, and PM2.5 Concentrations Estimated by the Deep Learning model (Air Transformer) based on Satellite data. Chenliang Tao https://doi.org/10.5281/zenodo.10071408

Model code and software

Air-Transformer Chenliang Tao https://github.com/myles-tcl/Air-Transformer

Chenliang Tao, Yanbo Peng, Qingzhu Zhang, Yuqiang Zhang, Bing Gong, Qiao Wang, and Wenxing Wang

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Short summary
We developed a novel Transformer framework to bridge the sparse surface monitoring for inferring ozone-NOx-VOCs-aerosols sensitivity and their urban-nonurban discrepancies at a finer-scale with implications for improving our understanding in ozone variations. The change of urban-rural disparities in ozone was dominated by PM2.5 from 2019 to 2020. The aerosol-inhibited regime on top of the two traditional NOx- and VOCs-limited regimes was identified in Jiaodong Peninsula, Shandong, China.