Effect of Evaluation of Various Emission Control Policies on PM_2.5 Reduction

In previous work, a methodology was developed to discuss the influence of meteorological factors, policies, and surrounding cities on PM_2.5 concentrations in a city. Two models were constructed using Zibo City, Shandong Province, as the target city. Initially, we improved the established PM_2.5-Meteorological-Policy (PMP) model and applied it to six other target cities in Shandong Province. Concurrently, a novel model named the PM_2.5-Interregional (PI) model was further developed in each city to directly express the influence of surrounding cities on the target cities. The model construction period was from January 2014 to August 2022, with the extended prediction period until November 2022. The results confirmed that disparities in the spatial distribution in seasons became smaller after the implementation of environmental policies. Moreover, two models in each city revealed good interpretation with high adjusted R² values (>0.7) and lower MAPE and RMSE values (the lowest was 5.53% and 2.57), suggesting reasonable short-term prediction. Additionally, meteorological factors and the combined implementation of different policy types played crucial roles in reducing PM_2.5 concentrations in all cities. Specifically, the temperature and wind speed were negatively correlated with PM_2.5 concentrations in all models, with temperature having a stronger influence. The Law of the People's Republic of China on the Prevention and Control of Atmospheric Pollution (LAPAP), implemented in 2016, had a clear influence on reducing PM_2.5 concentrations, with the highest absolute fitted coefficient in most cities (-0.166 to -0.344). On the contrary, the influence of temperature seemed to be more significant compared to policies, due to the larger standardized coefficient in each city (-0.606 to -0.864).