2017 Volume 11 Issue 9
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DENG Xuwei, HUANG Yu, LI Zhongqiang, LI Haibo, SU Ming, ZHU Zhichao, ZHAO Sujuan. Temporal and spatial variations characteristics of atmospheric particulate matter in Hubei province, China[J]. Chinese Journal of Environmental Engineering, 2017, 11(9): 5152-5158. doi: 10.12030/j.cjee.201610095
Citation: DENG Xuwei, HUANG Yu, LI Zhongqiang, LI Haibo, SU Ming, ZHU Zhichao, ZHAO Sujuan. Temporal and spatial variations characteristics of atmospheric particulate matter in Hubei province, China[J]. Chinese Journal of Environmental Engineering, 2017, 11(9): 5152-5158. doi: 10.12030/j.cjee.201610095
shu

Temporal and spatial variations characteristics of atmospheric particulate matter in Hubei province, China

  • 1.

    Hubei Province Key Laboratory of Regional Development and Environmental Response, Faculty of Resources and Environment, Hubei University, Wuhan 430062, China

  • 2.

    Wuhan Research Academy of Environmental Protection Sciences, Wuhan 430015, China

  • 3.

    Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China

  • 4.

    School of Public Health, Anhui Medical University, Hefei 230032, China

  • Received Date: 15/03/2017
    Accepted Date: 17/10/2016
    Available Online: 26/08/2017
    Fund Project:
  • The analysis of spatial and temporal variations of atmospheric particulate matter is significant for atmosphere pollution control, early warning and forecast. In this study, the spatial and temporal variations of PM10 and PM2.5 in Hubei province were studied through PM10 and PM2.5 per hour concentration data which collected from 53 monitoring sites distributed in 13 main cities during January 2015 to December 2015.The results showed that there were obvious spatial heterogeneous in the distribution of PM10 and PM2.5 concentrations in east-west and north-south, with lowest in the west region, highest in the central region, and middle in east region. Also, the PM10 and PM2.5 concentrations in all cities changed dramatically with time, and there was a pattern of PM10 and PM2.5 concentrations in summer 10 and PM2.5 concentrations in autumn 10 and PM2.5 concentrations in spring 10 and PM2.5 concentrations in winter. The lowest PM10 and PM2.5 concentrations occured in the summer and the highest occured in January. Correlation analysis indicated that there were a significant negative correlation between PM10 and PM2.5 concentrations and precipitation and temperature, and sin significant postive correlation existed between PM10 and PM2.5 concentrations and human factors, such as construction area, motor vehicle ownership, freight and passenger traffic, the per capita GDP and per capita output.
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Temporal and spatial variations characteristics of atmospheric particulate matter in Hubei province, China

  • Received Date: 15/03/2017
  • Accepted Date: 17/10/2016
  • Available Online: 26/08/2017
Fund Project:

Abstract: The analysis of spatial and temporal variations of atmospheric particulate matter is significant for atmosphere pollution control, early warning and forecast. In this study, the spatial and temporal variations of PM10 and PM2.5 in Hubei province were studied through PM10 and PM2.5 per hour concentration data which collected from 53 monitoring sites distributed in 13 main cities during January 2015 to December 2015.The results showed that there were obvious spatial heterogeneous in the distribution of PM10 and PM2.5 concentrations in east-west and north-south, with lowest in the west region, highest in the central region, and middle in east region. Also, the PM10 and PM2.5 concentrations in all cities changed dramatically with time, and there was a pattern of PM10 and PM2.5 concentrations in summer 10 and PM2.5 concentrations in autumn 10 and PM2.5 concentrations in spring 10 and PM2.5 concentrations in winter. The lowest PM10 and PM2.5 concentrations occured in the summer and the highest occured in January. Correlation analysis indicated that there were a significant negative correlation between PM10 and PM2.5 concentrations and precipitation and temperature, and sin significant postive correlation existed between PM10 and PM2.5 concentrations and human factors, such as construction area, motor vehicle ownership, freight and passenger traffic, the per capita GDP and per capita output.

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