Assessment of Air Quality in Beijing-Tianjin-Hebei Using Multivariate Analysis
The multivariate statistical analysis was applied to the pollutant emissions, socio-economic dataset to evaluate the characteristics of air pollutant emissions within four cities selected in Beijing-Tianjin-Hebei.The Hierarchical Agglomerative Cluster Analysis grouped 28 samples into three clusters and the Factor Analysis showed that the sources of air pollution mainly resulted from industrial pollution, life pollution and industrial pollution for Group A, Group B and Group C, respectively.The Linear Regression analysis revealed that the industrial coal consumption (ICQ), industrial smoke emission make great contribution to GDP in Group A; life smoke emission exhibited the highest independent contribution to the GDP, followed by life sulfur oxides emission in Group B; for Group C, the contribution made by ICQ, industrial nitrogen oxides to GDP were 88.6%, 42.4%, respectively.The Multiple Linear Regression analysis demonstrated that the five industrial pollution factors made the main contribution to GDP, accounting for 99.66% in Group A, however, for Group B and Group C, is up to 66.34%, 85.63% respectively.Up to now, ICQ still has a strong, positive influence on GDP in the cities from Group A and Group C, reflecting the economic was still driven by coal consumption for the four cities.
Emission factors Air pollution Multivariate statistical Beijing-Tianjin-Hebei region
Zengqiang Liang Mintao Ma Gaifang Du
College of Environmental and Energy Engineering, Beijing University of Technology, Beijing, China
国际会议
北京
英文
347-348
2013-11-07（万方平台首次上网日期，不代表论文的发表时间）