Abstract
Severe air pollution, especially particulate pollution, is a distressful problem for many regions. This study focused on a respective inland area-Hunan province China, which was surrounded by mountains in three sides. This unique characteristic of terrain contributed largely to the heavy pollution level. We used Multiple Linear Regression (MLR) model, Artificial Neutral Network (ANN) model and the Hybrid Single Paricle Lagrangian Integrated Trajectory Model to study pollution characteristics of PM2.5. The results showed that the meteorological parameters were correlated with PM2.5 concentration and ANN model performed better than MLR model in predicting PM2.5 concentrations in Hunan. According to the trajectory, several peaks were observed in January. The first one occurred at the beginning of January. We supposed that the firework used to celebrate the New Year accounted for the climb of PM2.5 concentration. Moreover, peaks were found in the same day in 14 cities during heavy polluted period. Based on the trajectory, we found that there were successive air masses coming from the northern or northwest China entered into Hunan in January. The pocket-like terrain of Hunan led to the stagnation of air masses causing the air pollution. Besides, the trajectories also implied that the air masses would bypass Changsha, Zhuzhou and Xiangtan, which were regarded as pollution sources, before reaching other cities. Therefore, the pollutants emission should be strictly regulated during the polluted period. Moreover, ozone pollution is becoming more obvious during summer time, which might be a major pollutant after particulate pollution is under control.
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