Qingyu Zhang1, Renchang Yan1, Juwang Fan1, Shaocai Yu 1, Weidong Yang1, Pengfei Li1, Si Wang1, Bixin Chen1, Weiping Liu1, Xiaoyu Zhang2

  • 1 Research Center for Air Pollution and Health, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
  • 2 Department of Earth Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China

Received: April 23, 2015
Revised: July 15, 2015
Accepted: August 12, 2015
Download Citation: ||https://doi.org/10.4209/aaqr.2015.03.0179  

  • Download: PDF


Cite this article:
Zhang, Q., Yan, R., Fan, J., Yu, S., Yang, W., Li, P., Wang, S., Chen, B., Liu, W. and Zhang, X. (2015). A Heavy Haze Episode in Shanghai in December of 2013: Characteristics, Origins and Implications. Aerosol Air Qual. Res. 15: 1881-1893. https://doi.org/10.4209/aaqr.2015.03.0179


HIGHLIGHTS

  • PM2.5 contributed more than 80% of PM10 for the haze period with PM2.5 > 75 µg m–3.
  • The clean air masses were coming from the far away regions with the high wind speed.
  • The very heavy haze was mainly from nearby industrialized and urbanized provinces.
  • PM2.5 formation in Shanghai is affected by the sources similar to those of CO.

 

ABSTRACT


As the largest Chinese city by population and the largest city proper by population in the world, Shanghai has frequently suffered the heavy haze in recent years. In this study, the observational data (PM2.5, PM10, O3, NO2, CO and SO2) at the ten urban monitoring stations in Shanghai from November 25 to December 9, 2013, were used to analyze the haze pollution. The source contributions of PM2.5 in Shanghai were identified by trajectory clustering and hybrid receptor models (potential source contribution function (PSCF) and concentration weighted trajectory (CWT)). The results showed that for the whole study period, the ranges of pollutant concentrations are 2.0–635.0 µg m–3 (PM2.5), 2.0–726.0 µg m–3 (PM10), 1.0–139.0 µg m–3 (O3), 11.0–197.0 µg m–3 (SO2), 7.0–221.0 µg m–3 (NO2), and 0.3–8.5 mg m–3 (CO). It was found that PM2.5 contributed more than 80% of PM10 for the whole period except the relatively clean period in which only 45% of PM10 is PM2.5. The model analyses show that clean air masses reaching at Shanghai were from the far away regions like Mongolia and Inner Mongolia with the high mean wind speed (fast air masses). On the other hand, the heavy haze air masses were mainly from the nearby industrialized and urbanized provinces with industrial cities. It was found that the formation of the extremely heavy haze from December 5 to 7 in Shanghai was mainly because of the air pollution transported from the nearby provinces (i.e., Anhui, Jiangsu, Zhejiang) and central part provinces (such as Shandong, Hebei) of eastern China. The correlation analyses among PM2.5 and other pollutants show that the PM2.5 formation in Shanghai is affected by the sources similar to those of CO such as combustion, industry, mobile and oxidation of hydrocarbons. Finally, the controlling strategies are discussed on the basis of this result.


Keywords: Air quality; Back trajectories; Cluster analysis; PSCF; CWT


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.

7.3
2022CiteScore
 
 
77st percentile
Powered by
Scopus
 
   SCImago Journal & Country Rank

2021 Impact Factor: 4.53
5-Year Impact Factor: 3.668

The Future Environment and Role of Multiple Air Pollutants

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.