High concentration of PM_2.5 has seriously affected people’s daily lives in recent years. It is necessary to analyze PM_2.5 and the correlations with other pollutants in winter. Data presented in this paper were obtained from monitoring stations from 2016 to 2018. Attention was fixed on PM_2.5 and its monthly and daily variations in winter. Furthermore, the correlations between PM_2.5 and CO, SO₂, NO₂, O₃ and PM₁₀ were studied. The results showed concentrating PM_2.5 was roughly consistent with the monthly and daily trends. It was January>December>February>November>March. The mass concentration ranges of PM_2.5 before and after the adjustment of heating energy structures were 64.5-184.1 μg/m³, and 86.4-140.1 μg/m³, respectively. The average concentrations of PM_2.5 were 135.5 μg/m³, and 109.1 μg/m³, decreased by 26.4 μg/m³. PM_2.5/PM₁₀ was changed from 64.6% to 62.6%, reduced by 2%. The linear correlation analysis revealed a strong correlation between PM_2.5 and CO, SO₂, NO₂, and PM₁₀, but a negative correlation between PM_2.5 and O₃. Two multiple linear regression models on the pollutants were established, respectively. This study helps understand the concentrating distribution of PM_2.5 and other pollutants in winter. It will provide some useful references to control air pollution for some cities, which have a similar type of heating energy structure.