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.%文章以2010年中国城镇城区为研究单元,采用灰色关联模型对中国7大地理分区城镇PM2. 5浓度影响因素进行综合研究.结果表明:年平均风速、NDVI和DEM与PM2. 5浓度的关联度为中度,其余为强度关联.地形因素对华北地区的城镇PM2. 5浓度影响最大,年平均气温和年平均降水量对华南地区城镇PM2. 5浓度影响程度较小,年平均风速对各分区城镇PM2. 5浓度均有较强的影响.生态因素对各区域城镇PM2. 5浓度均有中度或强度影响.社会经济因素中城市化因素对各区域城镇PM2. 5浓度多为中度影响,经济因素对东北、华中、西南、西北地区影响程度较大.研究结果可为有效防控PM2. 5污染提供决策依据.
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