Based on the mechanism of PM_2.5 concentration change in Beijing in 2015, the generalized additive model (GMA) of PM_2.5 and atmospheric pollutants (PM₁₀, SO₂,NO₂,CO,O₃), as well as the meteorological factors (daily mean temperature, wind scale, wind direction) are established to explore the impact of different factors on PM_2.5 concentration changes. The results showe that: (1) Beijing PM_2.5 concentration has the characteristics of low distribution of summer and autumn, however higher in spring and winter; (2) The PM_2.5 concentration in Beijing is linearly positively correlated with PM₁₀, SO₂, NO₂, CO. The positive correlation is from strong to weak: CO> PM₁₀> SO₂> NO₂, and the relationship with O₃, temperature and wind factor is more complicated. (3) The goodness R² of the GAM model is 0.725, and the goodness of the linear regression model is 0.519. Compared with the GAM model, the explanatory degree of the PM_2.5 concentration increased by 20.6%. The results show that the GAM model is more flexible and reliable than the linear regression model in establishing the complex relationship between PM_2.5 concentration and influencing factors.