多波长激光雷达颗粒物质量浓度探测方法适用范围分析

发布时间：2018-05-15 02:28

本文选题：颗粒物质量浓度 + 复折射率　；参考：《西安理工大学》2017年硕士论文

【摘要】：随着我国工业化和城市化进程的迅速发展,以PM2.5为代表的大气颗粒物环境污染成为影响我国空气质量和民众健康的突出问题。目前,对颗粒物质量浓度的探测仍主要局限于地面点测量、布网测量和间接等效测量等方法,亟待需要可以实现大范围、大尺度、高空间分辨率的颗粒物质量浓度新算法。本文主要对激光雷达探测颗粒物质量浓度新型算法的适用范围进行估计。新型颗粒物质量浓度算法以多波长激光雷达回波信号数据为基础反演大气气溶胶光学参数,利用气溶胶体积谱结合米散射理论得到的消光效率来计算颗粒物质量消光效率,再通过实测消光系数获得颗粒物质量浓度。本文基于激光雷达回波信号数据反演得到颗粒物质量浓度,分析西安地区不同天气下算法参数(复折射率、粒子半径等)对反演结果的影响。反演结果表明,对无云天气、云层外、以及雾霾天气边界层上的大气进行探测时,颗粒物质量浓度与消光系数的变化趋势基本一致,复折射率对其变化趋势影响较小,不同的粒子半径下反演结果与实际相符。无云及多云天气云层外的不同波长探测的质量浓度最大差值较小,而边界层内雾霾主要发生区域的最大差值较大,不同波长的反演结果重合度低,该算法不适用于雾霾天气边界层内的颗粒物质量浓度反演。云内的复折射率对反演质量浓度的变化趋势影响较大,反演得到的不同粒径颗粒物质量浓度差异较大,说明该算法同样不适用于云粒子的参量反演。分别对不同天气条件下的颗粒物质量浓度反演结果(65组)进行统计分析,以进一步确定该算法的适用范围。重点考察了颗粒物质量浓度与消光系数之间的变化趋势是否一致,不同波长探测的颗粒物质量浓度的最大差值,以及同一波长探测下,不同粒径的颗粒物质量浓度的变化规律,评估不同大气状况、粒径分布和大气高度的适用范围。统计分析表明,算法能够较为准确的反映边界层高度(约1.5km)之上,粒子直径小于2.5μm和10μm的无云、雾霾和多云天气云层外的颗粒物质量浓度的变化趋势。
[Abstract]:With the rapid development of industrialization and urbanization in China, the environmental pollution of atmospheric particulates, represented by PM2.5, has become a prominent problem affecting the air quality and the health of the people in China. At present, the detection of mass concentration of particulate matter is still mainly limited to ground point measurement, netting measurement and indirect equivalent measurement. It is urgent to realize a new algorithm of mass concentration of particulate matter in large range, large scale and high spatial resolution. In this paper, the application range of a new algorithm for detecting particle mass concentration by lidar is estimated. Based on the echo signal data of multi-wavelength lidar, the new particle mass concentration algorithm is used to invert the optical parameters of atmospheric aerosol. The extinction efficiency of aerosol mass is calculated by using aerosol volume spectrum combined with the extinction efficiency obtained by rice scattering theory. The mass concentration of particulate matter was obtained by measuring extinction coefficient. Based on the data of laser radar echo signal, the particle mass concentration is obtained, and the influence of algorithm parameters (complex refractive index, particle radius, etc.) on the inversion results in different weather conditions in Xi'an region is analyzed. The inversion results show that the variation trend of particle mass concentration and extinction coefficient is basically consistent with that of cloud free weather, outside clouds and the atmosphere on the haze weather boundary layer, while the complex refractive index has little effect on the change trend. The inversion results under different particle radius are in agreement with the actual results. In cloudless and cloudy weather, the maximum difference of mass concentration of different wavelengths is small, while the maximum difference of the main region of haze in the boundary layer is larger, and the coincidence of the inversion results of different wavelengths is low. This algorithm is not suitable for the inversion of particle mass concentration in the haze weather boundary layer. The complex refractive index in the cloud has a great influence on the change trend of the inversion mass concentration, and the difference of the mass concentration of different particle size obtained from the inversion is quite large, which indicates that the algorithm is not suitable for the parameter inversion of cloud particles. The inversion results of particle mass concentration under different weather conditions were analyzed statistically in order to further determine the applicable range of the algorithm. The variation trend between particle mass concentration and extinction coefficient, the maximum difference between particle mass concentration detected at different wavelengths and the variation law of particle mass concentration with different particle size under the same wavelength detection were investigated. To evaluate the applicable range of different atmospheric conditions, particle size distribution and atmospheric height. Statistical analysis shows that the algorithm can accurately reflect the change trend of particle mass concentration above boundary layer height (about 1.5km), particle diameter less than 2.5 渭 m and 10 渭 m, haze and cloud layer outside cloud layer.
【学位授予单位】：西安理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN958.98

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