Fogs and hazes broke out many times in winter and spring of 2015～2016 in Baotou, China. It is not only very seriously influential on visibility, but also seriously harmful for human health. Based on this, data of 8 monitoring stations recording characteristics of particulate matters (PM) were analyzed to determine the characteristics of temporal and spatial pollution variation of PM2.5 and PM10 in the central urban districts of Baotou. According to the different functions of monitoring region, 5 districts were divided and the data of each district were screened and sorted. Winter and spring regional PM mass concentration order from high to low were obtained as follows: industrial area>commercial area>cultural area>transportation hub area>park sight spot. The monthly changing characteristics of particles about each district were obtained, and then the cause of formation was analyzed and summarized. Monthly variation curve of PM2.5 and PM10 mass concentration showed single valley in double peak pattern: the maximum was in December and the minimum was in February; daily variation indicated a good correlation between PM2.5 and PM10, both of which were significantly influenced by meteorological conditions; diurnal variation curve showed adouble peak-valley type. Meteorological factors such as daily average temperature, atmospheric pressure, relative humidity, precipitation were chosen and their individual relationships with concentrations of PM2.5 and PM10 were investigated using Spearman rank correlation analyses. It was demonstrated that the concentrations of PM2.5 and PM10 were positively correlated with temperature and atmospheric pressure, respectively, and strongly negatively correlated with wind speed and relative humidity. Wind speed, atmospheric pressure (with raining and snowing) and relative humidity were three key factors affecting the distributions of PM2.5 and PM10 concentration.