Particulate Matters Pollution Characteristic and the Correlation between PM (PM2.5, PM10) and Meteorological Factors during the Summer in Shijiazhuang

Abstract

In recent years, the haze occurs frequently and air pollution is getting worse in Beijing-Tianjin-Hebei Region, China. The particulate matter pollution characteristic researches are playing a sig-nificant role especially in the districts where have higher concentration PM and air pollution. In this study, we collected daily particulate matter (PM10, PM2.5) mass concentration data from 7 air pollution monitoring stations in Shijiazhuang City, Hebei, China over a 3-month period from June to August to investigate particulate matter pollution characteristic and the relationship with me-teorological conditions. Statistical results show that PM10 is the major pollutant in Shijiazhuang City; the average daily concentrations of PM2.5 and PM10 are 94.45 μg/m3 and 219.15 μg/m3, respectively. The daily average of PM10 and PM2.5 level over the period exceeded the first grade of the daily average limit of the ambient air quality standards (GB3095-2012). And there is a significantly positive correlation between atmospheric pressure and particulate matter pollution, but there is a significantly negative correlation between atmospheric temperature and PM concentrations. Precipitation has a clear role mainly in the coarse particles; however, there has little effect on fine particulate matter. Relative humidity and wind speed have a poor correlation with atmospheric pollutant concentrations (not remarkably high).

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Li, H. , Guo, B. , Han, M. , Tian, M. and Zhang, J. (2015) Particulate Matters Pollution Characteristic and the Correlation between PM (PM2.5, PM10) and Meteorological Factors during the Summer in Shijiazhuang. Journal of Environmental Protection, 6, 457-463. doi: 10.4236/jep.2015.65044.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Liu, X.S. and Liu, N.H. (2014) The Current Situation of China’s Urban Air Pollution, the Consequences and Counter Measures. Beijing, Tianjin and Hebei Province Steel Cleaner Production, Environmental Protection Exchanges, 91-94.
[2] Wang, Y., Pei, J.G. and Wang, B. (2013) Where Is the Way to Improve the Air Quality of the Environment in Hebei. Environmental Economy, 117, 59-61.
[3] Deng, L.Q., Qian, J. and Liao, R.X. (2012) Pollution Characteristics of Atmospheric Particulates in Chengdu from August to September in 2009 and Their Relationship with Meteorological Conditions. China Environmental Science, 32, 1433-1438.
[4] Sun, Y.M. (2007) Using SPSS Software to Analyze the Correlation between Variables. Journal of Xinjiang Education Institute, 23, 120-123.
[5] Tai, A.P.K., Mickley, L.J. and Jacob, D.J. (2010) Correlations between Fine Particulate Matter (PM2.5) and Meteorological Variables in the United States: Implications for the Sensitivity of PM2.5 to Climate Change. Atmospheric Environment, 44, 3976-3984.
http://dx.doi.org/10.1016/j.atmosenv.2010.06.060
[6] Pateraki, S., Asimakopoulos, D.N., Flocas, H.A., et al. (2012) The Role of Meteorology on Different Sized Aerosol Fractions (PM10, PM2.5, PM2.5-10). Science of the Total Environment, 419, 124-135.
http://dx.doi.org/10.1016/j.scitotenv.2011.12.064
[7] Wu, H.M., Wang, W.Z., Ma, B.H., et al. (2012) Temporal and Spatial Distributions of Air Pollutions in Lishui and Their Correlation with Meteorological Elements. Environmental Pollution and Control, 34, 51-55.
[8] Zhao, C.X., Wang, Y.Q., Wang, Y.J., et al. (2014) Temporal and Spatial Distribution of PM2.5 and PM10 Pollution Status and the Correlation of Particulate Matters and Meteorological Factors during Winter and Spring in Beijing. Environmental Science, 35, 418-427.
[9] Ben, J.D. (2012) The Correlation Analysis between the Air Pollution Status and Meteorological Conditions in Changchun. Ph.D. Thesis, Jilin University, Changchun.

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