Spatiotemporal Variations in Summertime Ground-Level Ozone around Gasoline Stations in Shenzhen between 2014 and 2020

Yingying Mei, Xueqi Xiang and Deping Xiang
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Yingying Mei: School of Sociology, Wuhan University, Wuhan 430072, China
Xueqi Xiang: School of Philosophy, Zhongnan University of Economics and Law, Wuhan 430073, China
Deping Xiang: School of Sociology, Huazhong University of Science and Technology, Wuhan 430074, China

Sustainability, 2022, vol. 14, issue 12, 1-15

Abstract: Ground-level ozone has become the primary air pollutant in many urban areas of China. Oil vapor pollution from gasoline stations accelerates the generation of ground-level ozone, especially in densely populated urban areas with high demands for transportation. An accurate spatiotemporal distribution of ground-level ozone concentrations (GOCs) around gasoline stations is urgently needed. However, urban GOCs vary sharply over short distances, increasing the need for GOCs at a high-spatial resolution. Thus, a high-spatial resolution (i.e., 1 km) concentration retrieval model based on the GLM and BME method was developed to obtain the daily spatiotemporal characteristics of GOCs. The hourly ozone records provided by the national air quality monitoring stations and multiple geospatial datasets were used as input data. The model exhibited satisfactory performance (R 2 = 0.75, RMSE = 10.86 µg/m 3 ). The derived GOCs show that the ozone levels at gasoline stations and their adjacent areas (1~3 km away from the gasoline stations) were significantly higher than the citywide average level, and this phenomenon gradually eased with the increasing distance from the gasoline stations. The findings indicate that special attention should be given to the prevention and control of ground-level ozone exposure risks in human settlements and activity areas near gasoline stations.

Keywords: ground-level ozone; gasoline stations; urban area; spatiotemporal distribution; retrieval model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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