Spatio-temporal Variation and Driving Factors of PM2.5-O3 Compound Pollution in Anhui Province from 2015 to 2023 | ||
| Pollution | ||
| دوره 12، شماره 2، تابستان 2026، صفحه 626-639 اصل مقاله (919.8 K) | ||
| نوع مقاله: Original Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/poll.2026.410244.3273 | ||
| نویسندگان | ||
| Jun Yan* ؛ Shihan He؛ Shi Yan؛ Xuemei Yang؛ Xiaoyong Liu | ||
| School of Geographic Sciences, Xinyang Normal University, Xinyang 464000, China Henan Key Laboratory for Synergistic Prevention of Water and Soil Environmental Pollution, Xinyang Normal University, Xinyang 464000, China | ||
| چکیده | ||
| In order to explore the characteristics and driving factors of PM2.5 and O3 compound pollution in 16 prefecture-level cities in Anhui Province, multidimensional statistics, Pearson correlation coefficient and HYSPLIT model were used to analyze the cities in Anhui Province from 2015 to 2023. The results show that: From the spatial and temporal distribution, the cumulative occurrence of PM2.5-O3 compound pollution in cities of Anhui Province from 2015 to 2023 was 8-361 days, mainly concentrated in April-October, and the number of days of compound pollution in winter was the least. In Huaibei, Huainan, Suzhou, Bengbu, Chuzhou, Bozhou appear more frequently, Huangshan, Tongling, Xuancheng, Chizhou, Wuhu appear less frequently; The days of compound pollution were significantly positively correlated with PM2.5 and NO2, which are two key control parameters affecting the days of compound pollution; HYSPLIT model shows that the regional transmission in cities near Hefei also has an important impact on PM2.5-O3 compound pollution, mainly from the northeast. From 2015 to 2023 the fluctuation of PM2.5 concentration in Anhui province decreased and O3 concentration increased, and the synergistic relationship between the two became increasingly obvious, the meteorological data had a certain impact on the days of compound pollution. | ||
| کلیدواژهها | ||
| PM2.5؛ O3؛ compound pollution؛ Pearson correlation coefficient؛ HYSPLIT model | ||
| مراجع | ||
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