Improving Estimation of Surface PM2.5 by Including Satellite Observations of Gasses, Aerosols, and Radiation in Tandem

The model performance for predicting PM2.5 concentration in Shanxi Province is enhanced by introducing CO, NO2, and UVAI, based on the optimal parameter combination. The mechanisms of their influences are also analyzed.

基于最优参数组合，引入一氧化碳（CO）、二氧化氮（NO2）与紫外线气溶胶指数（UVAI）后，山西省PM2.5浓度预测模型的性能得到提升，同时对各因素的影响机制进行了分析。