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Int. J. Environ. Res. Public Health 2015, 12(6), 6608-6625; doi:10.3390/ijerph120606608

Spatial and Temporal Distribution of PM2.5 Pollution in Xi’an City, China

State Key Laboratory of Explosion Science and Technology, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
These authors contributed equally to this work.
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Author to whom correspondence should be addressed.
Academic Editors: P. Grady Dixon and Scott C. Sheridan
Received: 31 March 2015 / Accepted: 5 June 2015 / Published: 10 June 2015
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Abstract

The monitoring data of the 13 stations in Xi’an city for the whole years of 2013 and 2014 was counted and analyzed. Obtaining the spatial and temporal distribution characteristics of PM2.5 was the goal. Cluster analysis and the wavelet transform were utilized to discuss the regional distribution characteristics of PM2.5 concentration (ρ(PM2.5)) and the main features of its yearly changes and sudden changes. Additionally, some relevant factors were taken into account to interpret the changes. The results show that ρ(PM2.5) in Xi’an during 2013 was generally higher than in 2014, it is high in winter and low in summer, and the high PM2.5 concentration centers are around the People’s Stadium and Caotan monitoring sites; For the regional PM2.5 distribution, the 13 sites can be divided into three categories, in which Textile city is Cluster 1, and High-tech Western is Cluster 2, and Cluster 3 includes the remaining 11 monitoring sites; the coefficient of goodness of the cluster analysis is 0.6761, which indicates that the result is acceptable. As for the yearly change, apart from June and July, the average ρ(PM2.5) concentration has been above the normal concentration criteria of Chinese National Standard (50 g/m3); cloudy weather and low winds are the major meteorological factors leading to the sudden changes of ρ(PM2.5). View Full-Text
Keywords: PM2.5; spatial and temporal distribution; cluster analysis; wavelet transform PM2.5; spatial and temporal distribution; cluster analysis; wavelet transform
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Huang, P.; Zhang, J.; Tang, Y.; Liu, L. Spatial and Temporal Distribution of PM2.5 Pollution in Xi’an City, China. Int. J. Environ. Res. Public Health 2015, 12, 6608-6625.

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