Analysis of Typical Weather Circulation Patterns of Heavy PM2. 5 Pollution and the Transport Pattern in the Yangtze River Middle Basin

被引：2

作者：

Wang Y. ^{[1
,2
]}

Zhi X.-F. ^{[1
,2
]}

Bai Y.-Q. ^{[3
]}

Dong F. ^{[1
,2
]}

Zhang L. ^{[1
,2
]}

机构：

[1] Key Laboratory of Meteorological Disasters, Ministry of Education, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing

[2] Weather Online Institute of Meteorological Applications, Wuxi

[3] Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research, Institute of Heavy Rain, China Meteorological Administration, Wuhan

来源：

Huanjing Kexue/Environmental Science | 2022年 / 43卷 / 08期

关键词：

circulation classification; obliquely rotated T-mode principal component analysis (PCT); PM[!sub]2. 5[!/sub; regional transport; the Yangtze River middle basin;

D O I：

10.13227/j.hjkx.202110137

中图分类号：

学科分类号：

摘要：

The dominant transportation and accumulation patterns of heavy PM2. 5 pollution events over the Yangtze River middle basin were identified based on the obliquely rotated T-mode principal component analysis (PCT) method and the daily mean surface pressure. The heavy PM2. 5 pollution events over the Yangtze River middle basin during 2015-2019 were divided into four patterns, namely, PCT1: high-pressure bottom transport pattern (number of days: 41 d, accounting for 55. 4% of the total heavy PM2. 5 pollution days), PCT2: low-pressure convergence accumulation pattern (12 d, 16. 2%), PCT3: high-pressure static stability accumulation pattern (11 d, 14. 9%), and PCT4: high-pressure rear transport pattern (10 d, 13. 5%). Regional transport patterns (PCT1 and PCT4) accounted for 69% of the total heavy PM2. 5 pollution days and were the major pattern of heavy PM2. 5 pollution in the Yangtze River middle basin. PCT1 occurred most frequently among the four patterns, accompanied with strong northerly winds, which could drive the rapid transportation of pollutants from the upstream areas and cause the explosive increase in PM2. 5 over the Yangtze River middle basin. The PM2. 5 pollution events in the transport corridor, including Xiangyang, Jingmen, and Jingzhou, exhibited a 12-hour lag feature. Most parts of northern China were the source of PM2. 5, especially in central and northern Henan and western Shandong. The PCT4 transport pattern was featured by the low-level easterly winds, and the pollution level rose quickly. The PCT2 and PCT3 were characterized by the low ground wind speed, associated with the low-level horizontal convergence and subsidence. Such synoptic conditions were favorable for the accumulation of local PM2. 5 pollution, and the pollution rise rate was slower, and the duration was longer than those of other patterns. © 2022 Science Press. All rights reserved.

引用

页码：3913 / 3922

页数：9

共 46 条

[1] Chan C K, Yao X H., Air pollution in mega cities in China, Atmospheric Environment, 42, 1, pp. 1-42, (2008)
[2] Yan S Q, Zhu B, Kang H Q., Long-term fog variation and its impact factors over polluted regions of East China[J], Journal of Geophysical Research: Atmospheres, 124, 3, pp. 1741-1754, (2019)
[3] Yang X H, Song C J, Fan L X, 藻贼葬造, High-resolution estimation of spatio-temporal variation in PM<sub>2. 5</sub> concentrations in the Beijing-Tianjin-Hebei region, Environmental Science, 42, 9, pp. 4083-4094, (2021)
[4] Lian H Y, Yang X, Zhang P, 藻贼葬造, Analysis of characteristics and causes of a typical haze pollution in Beijing in the winter of 2019, Environmental Science, 42, 5, pp. 2121-2132, (2021)
[5] Zhang X Y, Wang Y Q, Niu T, 藻贼葬造, Atmospheric aerosol compositions in China: spatial/ temporal variability, chemical signature, regional haze distribution and comparisons with global aerosols[ J], Atmospheric Chemistry and Physics, 12, 2, pp. 779-799, (2012)
[6] Zhang X Y., Characteristics of the chemical components of aerosol particles in the various regions over China, Acta Meteorologica Sinica, 72, 6, pp. 1108-1117, (2014)
[7] Bai Y Q, Qi H X, Liu L, 藻贼葬造, Study on the nonlinear relationship among the visibility, PM<sub>2. 5</sub> concentration and relative humidity in Wuhan and the visibility prediction, Acta Meteorologica Sinica, 74, 2, pp. 189-199, (2016)
[8] Ma D L, Li L, Ju Y Q., Climate characteristics of haze days and analysis of summer haze weather event in Hubei Province, Environmental Science & Technology, 38, 11, pp. 148-153, (2015)
[9] Shen L J, Wang H L, Zhao T L, 葬造藻贼, Characterizing regional aerosol pollution in central China based on 19 years of MODIS data: spatiotemporal variation and aerosol type discrimination [ J], Environmental Pollution, 263, (2020)
[10] Zhu Y, Zhao T L, Bai Y Q, 藻贼葬造, Characteristics of atmospheric particulate matter pollution and the unique wind and underlying surface impact in the Twain-Hu basin in winter, Environmental Science, 42, 10, pp. 4669-4677, (2021)

← 1 2 3 4 5 →