科研之友
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摘要
China's Beijing-Tianjin-Hebei (BTH) region suffers from the country's worst air pollution. The problem has caused widespread concern both at home and abroad. Based on long-term and massive data mining of PM2.5 and PM10 concentration, we found that these pollutants showed similar variations in four seasons, but the most severe pollution was in winter. Through cluster analysis of the winter daily average concentration (DAC) of the two pollutants, we defined regions with similar variations in pollutant concentrations in winter. For the most polluted cities in BTH, the relationship between correlation coefficients for winter DAC and the distance between cities revealed that PM2.5 has regional, large-scale characteristics, with concentrated outbreaks, whereas PM10 has local, small-scale characteristics, with outbreaks at multiple locations. By selecting the key cities with the strongest linear relationship between the pollutant's DAC of each city and the daily individual air quality index values of the BTH region and through cluster analysis on the correlations between the pollutant DAC5 of the key cities, we defined regional divisions suitable for Joint Prevention and Control of Atmospheric Pollution (JPCAP) program to control PM2.5 and PM10. Comprehensively considering the degree of influence of regional atmospheric pollution control (RAPC) on air quality in BTH, as well as the elasticity and urgency of RAPC, we defined the control grades of the JPCAP regions. We found both the regions and corresponding control grades were consistent for PM2.5 and PM10. The thinking and methods of atmospheric pollution control we proposed will have broad significance for implementation of RAPC in other regions around the world.
- 出版日期2018-2
- 单位上海交通大学
