Statistical Characteristics of Urban Changzhou PM2.5 Based on k-means Analysis

Abstract

Statistical analysis methods was utilized to investigate the variations of monthly average concentrations of the six basic pollutants (SO2, NO2, CO, O3, PM2.5 and PM10) of six national standard monitoring sites from 2013 to 2014 in urban Changzhou. The results showed that, except for O3, SO2, NO2, CO, PM2.5 and PM10 concentrations were all high in winter and low in summer. The relationship between particulate matter and wind speed showed, with increasing wind speed, the concentration of PM2.5 reduced. However, the concentration variations of PM10 were complicated and when wind speed increased, its concentration started to go down and then elevated. Fast-cluster analysis (k-means) and the index of SWV & DIV were used to classify the six basic pollutants into four clusters, and then the relationship between gaseous pollutants and PM2.5in each cluster was emphatically discussed by statistical analysis method. Four clusters were assigned to fossil fuel combustion emissions (cluster1), O3 and secondary aerosols (cluster2), incomplete combustion emissions and regional haze (cluster3), urban city "background" (cluster4). Incomplete combustion cluster accounted for the smallest percentage of urban Changzhou and city "background" was cluster of urban Changzhou with the largest contribution. k-means analysis results also showed that PM2.5 had complex sources in urban Changzhou.