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Evaluation of the Changes of the Concentration, Composition and Possible Sources of Size-Resolved Particulate Matter between 2010 and 2011 in a Western Chinese Mega City

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Volume: 14 | Issue: 5 | Pages: 1500-1514
DOI: 10.4209/aaqr.2013.04.0108
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Yu-Fen Zhang1, Hong Xu1, Gui-Rong Liu1, Ying-Ze Tian1, Guo-Liang Shi 1, Jian-Hui Wu1, Pu Zhang2, Lai-Dong Zhou2, Yin-Chang Feng1

  • 1 State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
  • 2 Chengdu Research Academy of Environmental Sciences, Chengdu 610041, China

Abstract

In this work, PM2.5 and PM10 samples were collected from four functional regions in Chengdu city from Jan. to Feb. in 2010 and 2011. The chemical concentrations of nineteen elements, two water-soluble ions and TC were measured. The results showed that the levels of particulates and their chemical components were relatively higher in 2010 than those in 2011: for PM10, PM (39%), Si (27%), TC (76%), NO3 (16%), SO42– (19%); for PM2.5, PM (33%), Si (11%), TC (67%), NO3 (32%), SO42– (17%). Ternary diagram analysis, enrichment and other statistical methods were employed to study the spatial and temporal variations of the concentrations of PM and their compositions. Moreover, relative changes (%) of concentrations combined with the relative reported data from statistical yearbook and environmental quality reports are discussed to evaluate the effects of pollution control strategies for different functional regions. Finally, back-trajectory and factor-cluster analysis are proposed as an aid for the discussion of the meteorological influences and the possible source categories. The reduction of crustal dust may be attributed from the influence of long-range air transport. All the methods used above resulted in an overall agreement that showed the pollution control strategies were effective in reducing particulate air pollution: the total carbon (TC) reduction, accounting for 40–49% (PM10) and 35–48% (PM2.5), was mostly attributed to the strategy of banning high-emission yellow-tag vehicles, especially in commercial regions; the reduction of SO2 and NOx emissions had an impact on the sulphate (17.03% for PM10 and 15.37% for PM2.5) and nitrate (12.48% for PM10 and 21.58% for PM2.5) decrease. The findings of this study can provide useful information for developing effective control strategies.

Keywords

PM10 PM2.5 Control strategies Enrichment Factor-cluster analysis


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