激光雷达以其高垂直空间分辨率和高时间分辨率的优势在大气气溶胶监测中具有重要作用。在利用Fernald法反演气溶胶消光系数和光学厚度的过程中，雷达比是反演结果的主要误差源。在目前的应用中雷达比普遍都是取固定值，这就必然给雷达反演带来误差。通过对污染物以及气象数据与雷达比的逐步回归分析，建立了雷达比估算模型，从而实现雷达比的动态估算。研究表明：雷达比的变化与空气中PM2.5质量浓度、相对湿度、SO2和NO2质量浓度等具有明显相关性。相比于固定值，利用动态雷达比反演的气溶胶消光系数和光学厚度精度明显提高。

Lidar plays an important role in monitoring atmospheric aerosol for its high vertical spatial and temporal resolution. During the process of inversing aerosol extinction coefficient and optical depth by Fernald method, Lidar ratio is the main error source. However, in the present application, Lidar ratio is commonly taken as a fixed value, which may inevitably bring a certain amount of errors to the retrieval from Lidar measurement. An estimating model to calculate varied Lidar ratio through the stepwise regression analysis of pollutant data, meteorological data and Lidar data is established. The study shows that Lidar ratio has significant correlation with PM2.5 mass concentration, relative humidity and the mass concentration of SO2 and NO2. Compared to the fixed value, the usage of varied Lidar ratio can significantly improve the inversion accuracy of aerosol extinction coefficient and optical depth.