Impact of Meteorology on PM_2.5 and O₃ Pollution in Three Provincial Cities in Northeastern Provinces of China

In recent years, China has faced severe air pollution of fine particulate matter (with an aerodynamic diameter of smaller than 2.5 µm, PM_2.5) and ozone (O₃). It is importance to investigate the driving factors to air pollution. Numerous studies have emerged on the impact of meteorology on PM_2.5 and O₃, but most of them have concentrated on the highly developed and heavily populated areas of eastern China. There is insufficient research on PM_2.5 and O₃ pollution in the three northeastern provinces of China. To further understand the effect of meteorology on PM_2.5 and O₃ in the three northeastern of China, back-propagation neural network (BPNN) and random forest (RF) was used in this study. Firstly, meteorological factors (temperature, relative humidity, precipitation, wind speed, pressure and planetary boundary layer (PBL) height, cloud cover) were put into BPNN and RF models to investigate the influence of weather conditions on PM_2.5 and O₃ during 2015–2021. Results showed that RF performed better than BPNN. Among meteorological factors, precipitation and PBL significantly affect PM_2.5; temperature and pressure (PRS) significantly affect O₃. Then, when pollutants factors, such as PM_2.5, O₃, carbon monoxide (CO), sulfur dioxide (SO₂), nitrogen dioxide (NO₂) and formaldehyde (HCHO) were also inputted into BPNN and RF, it was illustrated that prediction accuracy of them had been improved. This study also revealed that the contribution of meteorology to PM_2.5 and O₃ were 16.73%–30.08%, 15.31%–25.35%, respectively, and the contribution of pollutants to PM_2.5 and O₃ were 69.92%–83.27%, 74.65%–84.69%, respectively. This research may reveal the driving factors affecting PM_2.5 and O₃ and deliver scientific guidance for policy-making in the three northeastern provinces of China.