Danting Zhao, Hong Chen , Xiaoke Sun, Zhuanzhuan Shi

School of Highway, Chang’an University, Xi’an 710064, China

Received: October 7, 2017
Revised: December 25, 2017
Accepted: January 1, 2018
Download Citation: ||https://doi.org/10.4209/aaqr.2017.09.0351  

  • Download: PDF

Cite this article:
Zhao, D., Chen, H., Sun, X. and Shi, Z. (2018). Spatio-temporal Variation of PM2.5 Pollution and its Relationship with Meteorology among Five Megacities in China. Aerosol Air Qual. Res. 18: 2318-2331. https://doi.org/10.4209/aaqr.2017.09.0351


  • Attainment rates in Guangzhou and Shanghai were obviously higher than other cities.
  • PM2.5 pollution in the daytime was lower than night in five cities except Shanghai.
  • PM2.5 concentrations in the weekends were higher than weekdays except Chengdu.
  • Time length of PM2.5 pollution in four seasons among five megacities was analyzed.
  • Pressure had positive impact on PM2.5 while temperature and rainfall were negative.


Fine particles are a crucial air pollutant in terms of their impact on the ambient environment, citizens’ health and traffic visibility. In this study, temporal and spatial variations in PM2.5 were analyzed in Beijing, Shanghai, Guangzhou, Chengdu and Shenyang in China from June 2013 till May 2017 using hourly data collected from the U.S. Embassy and Consulate monitoring system. The distributions of the annual, seasonal, monthly and diurnal concentration were illustrated by the attainment rate and the severity rate, as well as the length of time. After that, the coefficient of divergence (COD) was adopted to study the spatial heterogeneity among five typical megacities. Additionally, the relationship between PM2.5 and meteorology was calculated by Pearson’s correlation and stepwise multiple linear regression. The results show that annual PM2.5 concentrations were overall downward trends in all areas. Clear seasonal variations were identified, with the least pollution in summer and the most in winter. The hourly distribution was dramatically different, while the average concentration during the daytime was higher than at night except in Shanghai, and the weekends had higher pollution than the weekdays except in Chengdu. Also, the monthly attainment rate displayed an inverted-U distribution; oppositely, the severity rate revealed a U-shaped distribution. With the increasing pollution levels, the duration of the PM2.5 pollution was observed to be continuously declining in Guangzhou, Shanghai and Beijing but fluctuating in the other two cities. Furthermore, COD values indicated that there was an obvious spatial heterogeneity between Beijing–Chengdu–Shenyang and Shanghai–Guangzhou. As for meteorology, the pressure had a significantly positive impact on the PM2.5 concentration, while the temperature and rainfall had a negative influence. These results show the pollution levels of PM2.5 in different cities at distinct times and confirm the important role of meteorological conditions in air quality. The findings also provide forecast models of PM2.5 for the five cities.

Keywords: PM2.5; Spatio-temporal variations; Meteorological parameters; Attainment and severity rate; Time length.


Share this article with your colleagues 


Subscribe to our Newsletter 

Aerosol and Air Quality Research has published over 2,000 peer-reviewed articles. Enter your email address to receive latest updates and research articles to your inbox every second week.

77st percentile
Powered by
   SCImago Journal & Country Rank

2022 Impact Factor: 4.0
5-Year Impact Factor: 3.4

Aerosol and Air Quality Research partners with Publons

CLOCKSS system has permission to ingest, preserve, and serve this Archival Unit
CLOCKSS system has permission to ingest, preserve, and serve this Archival Unit

Aerosol and Air Quality Research (AAQR) is an independently-run non-profit journal that promotes submissions of high-quality research and strives to be one of the leading aerosol and air quality open-access journals in the world. We use cookies on this website to personalize content to improve your user experience and analyze our traffic. By using this site you agree to its use of cookies.