Analysis Of Adaptive Capacity For Profiling Particu-Late Matter Mass Concentration Based On Multi-Wavele-Ngth Lidar

With the rapid industrialization and urbanization in China, the environmental pollution mainly caused by particulate matter (PM2.5) is one of the most prominent problems affecting air quality and human health. Recently, detection methods of particulate matter mass concentration are still mainly limited to ground-based point/net measurements and indirect equivalent measurements. New detection techniques are needed for large scale measurement with high spatial and temporal resolutions.In this paper, the application scope of the new algorithm for particle mass concentration measurements is estimated. The new algorithm is based on multi-wavelength lidar data, where we combined the observed extinction coefficients at working wavelengths with quantity of mass extinction efficiency (MEE), which based on the extinction efficiency data of certain wavelength reported by the Mie theory and the particle size distribution data derived from a multi-wavelength lidar. We first calculated the particulate matter mass concentration to examine the influences of parameters (complex refractive index, particle radius, etc) on the inversion results under different weather conditions in Xi'an area. Inversion results show that the change trend of particle mass concentration is basically similar with the extinction coefficient for the cloudless, outside the cloud, fog and haze conditions. The effects caused by the complex refractive index are relative small, and the change trend of particle mass concentration is also reasonable with different radii. Based on the retrieved results, we also found that the maximum difference of particle mass concentration obtained by different wavelengths is quite small in the cloudless condition and outside the clouds, while large within the height of the boundary layer in fog and haze condition, which thus is not suitable for lower atmosphere measurements in fog and haze weather. Meanwhile,the complex refractive index has a great influence on the change trend of the mass concentration within the clouds, and the obtained mass concentrations from three wavelengths are not consistent with the corresponding particle sizes. The algorithm is thus not suitable for cloud particle retrieval as well.The retrieved results with different weather conditions including 65-day measurements were statistically analyzed to further estimate the application scopes, where we mainly focused on the change trend between the mass concentration and the extinction coefficient, the maximum differences in particle mass concentrations between wavelengths, and the variations of mass concentrations for the different particle sizes within the same wavelength. The application scopes with different atmospheric conditions, particle size distributions and observed atmospheric heights were finally assessed. Statistical analysis results show that the algorithm can accurately reflect the trend of particle concentrations above the boundary layer(about 1.5km) in cloudless, outside the clouds, fog and haze conditions, where the particle diameter is limited to 2.5?m or 10?m.