Spatiotemporal variations of PM2.5 and PM10 concentrations between 31 Chinese cities and their relationships with SO2, NO2, CO and O3 |
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| Institution: | 1. Indian Institute of Tropical Meteorology (Branch), Prof Ram NathVij Marg, New Delhi 110060, India;2. TERI University, New Delhi 110070, India;1. Department of Urban and Regional Planning, University of Florida, P. O. Box 115706, Gainesville, FL 32601, USA;2. Department of Environmental Engineering Sciences, University of Florida, Gainesville, FL 32611-5706, USA;3. Shanghai Environmental Monitoring Center, No.55, Sanjiang Rd., Shanghai, 200235, China;4. Department of Urban and Regional Planning, University of Florida, P. O. Box 115706, Gainesville, FL 32611-5706, USA;5. School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, China;1. Nanjing University of Information Science and Technology, Nanjing 210044, China;2. State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China;3. Key Laboratory of Atmospheric Chemistry, China Meteorological Administration, Beijing 100081, China;4. Department of Atmospheric Science, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China;5. Weather Modification Office of Hebei Province, Shijiazhuang 050021, China;6. Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing 210044, China;7. Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China;8. University of Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | The variations of mass concentrations of PM2.5, PM10, SO2, NO2, CO, and O3 in 31 Chinese provincial capital cities were analyzed based on data from 286 monitoring sites obtained between March 22, 2013 and March 31, 2014. By comparing the pollutant concentrations over this length of time, the characteristics of the monthly variations of mass concentrations of air pollutants were determined. We used the Pearson correlation coefficient to establish the relationship between PM2.5, PM10, and the gas pollutants. The results revealed significant differences in the concentration levels of air pollutants and in the variations between the different cities. The Pearson correlation coefficients between PMs and NO2 and SO2 were either high or moderate (PM2.5 with NO2: r = 0.256–0.688, mean r = 0.498; PM10 with NO2: r = 0.169–0.713, mean r = 0.493; PM2.5 with SO2: r = 0.232–0.693, mean r = 0.449; PM10 with SO2: r = 0.131–0.669, mean r = 0.403). The correlation between PMs and CO was diverse (PM2.5: r = 0.156–0.721, mean r = 0.437; PM10: r = 0.06–0.67, mean r = 0.380). The correlation between PMs and O3 was either weak or uncorrelated (PM2.5: r = −0.35 to 0.089, mean r = −0.164; PM10: r = −0.279 to 0.078, mean r = −0.127), except in Haikou (PM2.5: r = 0.500; PM10: r = 0.509). |
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| Keywords: | Atmospheric air pollutant Indoor environment Outdoor environment |
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