This paper studies the problem of pollution of PM2.5. The air quality monitoring data of Bengbu city of nearly a year were selected,with the air quality index monitoring indicators as a departure point. Using correlation analysis and multiple regression method,it was first found that PM2.5 has a significant positive correlation with PM10、CO、O3、NO2 but has low correlation with SO2、O3、CO. Besides,with the intelligent use of the softwares like SUEFER,EXCLE and so on,the contour map of PM concentration distribution on 9:00,21:00 and 12:00 was drawn and a high concentration of PM2.5 was disclosed in the downtown areas including where the department store is located probably due to the serious automobile exhaust pollution. Finally,through establishing the classical Gauss diffusion model,using the software of MATLAB diffusion map and excluding the effect of humidity,we found that the stronger the wind,the faster PM2.5 diffusion and attenuation will be. In the meanwhile,by improving the model,introducing the effect of humidity factors,it was revealed that in the case of high humidity, the diffusion of PM2.5 is only slightly faster,and that humidity has little effect on PM2.5diffusion.%针对PM2.5污染，选取蚌埠市近1年的空气质量监测数据，以空气质量指数监测指标为切入点，运用相关性分析法与多元回归法，得到PM2.5与PM10、CO、O3、NO2呈显著正相关，与SO2、O3、CO之间的相关性很低。其次，巧妙运用SUEFER、EXCLE等软件，得出9：00、12：00和21：00的PM2.5浓度分布等值图，发现在百货大楼这些市中心地区，PM2.5浓度很高,说明可能该地区汽车尾气污染较严重。最后建立经典的高斯扩散模型，运用MATLAB软件出扩散图，排除湿度影响，发现随着风力增大，PM2.5扩散与衰减也在加快。同时，改进模型，引入湿度影响因素，得到在湿度较大的情况下， PM2.5扩散只是稍微加快，说明湿度对其扩散影响较小。
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