环境保护科学2018，Vol.44Issue(3)：69-73,79,6.DOI:10.16803/j.cnki.issn.1004-6216.2018.03.011
基于灰色关联模型的中国城镇PM2.5浓度影响因素分析
Analysis of the lnfluencing Factors of PM2. 5 Concentration in the Urban Areas of China's Towns Based on Grey Correlation Model
摘要
Abstract
In this paper, the urban and rural areas in China in 2010 were taken as study targets, and grey correlation model was used to comprehensively study the influencing factors of PM2. 5 concentration of towns in the seven geographical subareas. The results showed that the annual average wind speed, NDVI and DEM were moderately correlated with PM2. 5 concentration, with the rest of the indicators strongly correlated. Terrain factor had the greatest influence on PM2. 5 concentration of the towns in North China. The influences of annual average temperature and annual average precipitation on PM2. 5 concentrations of the towns in South China were lower, but the annual average wind speed had stronger influence on PM2. 5 concentrations of the towns in the seven regions. Ecological factor had moderate or strong effect on PM2. 5 concentrations of the towns in all of the regions. Among the social and economic factors, urbanization factors had moderate impact on the PM2. 5 concentration in most regions, and economic factors had greater influence on the PM2. 5 concentration of the towns in the northeast, central, southwest and northwest China, providing a basis for decision－making of effective prevention and control of PM2. 5 pollution.关键词
PM2.5/7大地理分区/城镇城区/灰色关联模型/影响因素Key words
PM2. 5/Seven Geographical Subareas/Urban and Rural Areas/Grey Correlation Model/Influencing Factor分类
资源环境引用本文复制引用
韩婧,李元征,陈新闯,李锋..基于灰色关联模型的中国城镇PM2.5浓度影响因素分析[J].环境保护科学,2018,44(3):69-73,79,6.基金项目
国家重点研发计划(2016YFC0502800) （2016YFC0502800）
国家自然科学基金重点项目(71533004,71734006)资助 （71533004,71734006）
