安徽省冬季PM2.5污染来源及其成因分析

随着中国城市化和工业化的加速发展，大气污染的问题日益突出，严重危害公众身体健康。基于安徽省逐小时PM2.5浓度监测数据，采用后向轨迹模式、潜在源因子分析法（PSCF）和权重浓度分析法（CWT），构建PM2.5来源分析模型，分析了安徽省PM2.5的来源，并结合地理探测器辨析了影响PM2.5本底贡献浓度的驱动因子。结果表明：（1）本底贡献、本底外溢和外地输送这3个动态过程对安徽省PM2.5浓度的时空变化有重要的影响；（2）PM2.5月累计逐小时测量浓度、总浓度、外地输送浓度、本底贡献浓度、本底外溢浓度和月均PM2.5本底排放贡献率，均在整体呈现出西南高、东北低的分布趋势，但前3项在安徽西北部的阜阳、亳州和淮北等地出现高值区；（3）安徽省约97.5%的面积外地输送贡献率>50%，下辖市PM2.5本底排放贡献率在30%~50%，说明1月污染以外地输送为主；（4）工厂密度、车辆保有量密度和人口密度对PM2.5月累计本底贡献浓度的解释力q值分别为0.33、0.47和0.61，通过与PM2.5月累计测量浓度地理探测分析结果的比较，表明人为要素与PM2.5月累计本底贡献浓度的关系更加密切。研究结果可为区域大气污染治理提供科学的参考依据。

Sources and Causes of PM2.5 Pollution in Winter in Anhui Province

With the accelerated development of urbanization and industrialization in China, air pollution is becoming more and more serious, which seriously endangers public health. Based on the hourly PM2.5 concentration monitoring data of Anhui, the backward trajectory model, the Potential Source Contribution Function (PSCF) and the Concentration Weighted Trajectory (CWT) were used to construct the PM2.5 source analysis model, and the source of PM2.5 in Anhui was analyzed. Combined with geographical detector, the driving factors affecting the concentration of PM2.5 local emission were analyzed. The results show that: (1) The three dynamic processes of local contribution, local spillover and external transmission of pollution have important influence on the temporal and spatial variation of PM2.5 concentration in Anhui; (2) Monthly cumulative measured concentration, total concentration, external transport concentration, local contribution concentration, local spillover concentration and monthly average local contribution rate of PM2.5 all showed a high trend of southwest and the opposite in the northeast, but the first three appeared high value in northwest of Anhui, such as Fuyang, Bozhou and Huaibei; (3) Approximate 97.5% of external transport contribution rate is more than 50% in Anhui, and the contribution rate of PM2.5 local emission in the cities is 30% ~ 50%, indicating that the pollution in January is mainly from external transmission. (4) The explanatory power q values of factory density, vehicle ownership density and population density for monthly cumulative local contribution concentration of PM2.5 are 0.33, 0.47 and 0.61, respectively. By comparing with the results of geographical detector of monthly cumulative measured concentration of PM2.5, it is indicated that the relationship between artificial factors and monthly cumulative local contribution concentration of PM2.5 is closer. The results can provide a scientific reference for the control of regional air pollution.