Abstract

Based on the historical data of air ozone monitoring of Pearl River Delta from 2016 to 2020, the temporal and spatial variation characteristics of ozone in the Pearl River Delta were analyzed. The results showed that the mean change curves of Q3 in the seven cities in the Pearl River Delta region from 2016 to 2020 were M-shaped, and the change trend was basically the same, except Huizhou and Zhuhai. The over standard rate of daily mean value of Q3 in Jiangmen City from 2016 to 2020 was more than 10%, and the over standard situation of daily mean value of Q3 was serious. In the Pearl River Delta region, the change trend of the monthly mean value of Q3 in the same year was basically the same. On the whole, the mean value from August to November was higher, and the mean value in June was lower. The peak of Q3 concentration appeared between 12:00 and 16:00 in the daytime, and it was generally low at night.

Highlights

  • Based on the historical data of air Q3 monitoring in the Pearl River Delta from 2016 to 2020, this paper studies the temporal and spatial variation characteristics of Q3 in nine cities in the Pearl River Delta, in order to provide relevant basis for the prevention and treatment of ozone pollution in the Pearl River Delta

  • Concerning the data of the nine cities in the Pearl River Delta used in this study, the annual mean value of Q3 was based on the monthly mean value, and the annual over standard rate of Q3 was calculated by the daily mean value

  • It can be seen that the variation of Q3 concentration in the Pearl River Delta region shows a typical single-peaked type

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Summary

Data resource

The historical data of Q3-8h monitoring of the nine cities in the Pearl River Delta region from January 1, 2016 to December 31, 2020 were from the air quality historical data query network (www.aqistudy.cn/historydata). The daily and monthly mean values of Q3 in the nine cities were selected. The hourly monitoring data on June 30, 2019 and December 31, 2019 were from the website of Department of Ecology and Environment of Guangdong Province

Research methods and data processing
Annual variation characteristics of Q3
Monthly variation characteristics of Q3
Daily variation characteristics of Q3
Analysis of cities exceeding the standard of Q3 concentration
Conclusion
Full Text
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