基于CO2单拉曼管光源及多波长DIAL补偿技术的对流层臭氧廓线高精度探测及反演方法研究

对流层臭氧是光化学烟雾的代表性物质，臭氧的生成往往伴生有大量的PM2.5形成。因此，对对流层臭氧时空分布和区域输送的研究对认识我国大气复合污染的成因具有重要意义。差分吸收激光雷达是探测对流层臭氧时空演变的重要手段，但现有技术仍然存在灰霾时气溶胶修正误差大、近场多通道几何因子存在差异、对流层中高层信号信噪比较低等问题，测量精度无法满足灰霾天成因、区域输送等研究需要。.本项目拟通过探索提高CO2气体拉曼散射光源能量转换效率和光束质量的方法，提出CO2单拉曼管单发射光学系统方案，解决通道间几何因子差异问题；采用波长对间的自动补偿机制，研究能够消除气溶胶消光和散射影响的差分吸收算法，提高灰霾条件下的测量精度；建立信号信噪比与统计误差的定量关系，优化信号信噪比，测量对流层中高层臭氧廓线，实现不同天气类型的臭氧浓度反演算法自适应性，为大气复合污染科学研究提供高精度的臭氧时空分布立体探测方法和技术基础。

Tropospheric Ozone is a representative substance of photochemical smog, and the formation of ozone is often associated with the formation of a large number of PM2.5. Therefore, the studies of the temporal and spatial distribution of boundary layer ozone and regional transport are of great significance for understanding the origin of atmospheric compound pollution in China. The differential absorption lidar is an important mean to detect the spatial and temporal evolution of tropospheric ozone. However, because of the factors affected by large aerosols correction error in haze day, multi channel geometry factor differences in near field and low signal to noise ratio in middle to upper troposphere, measuring accuracy can not meet with the research of atmospheric haze formation in existing technology.. In our research, the method of improving the Raman shift light conversion efficiency and beam quality is explored. And then the scheme of the optical transmitting based on CO2 single Raman cell is proposed to solve the problem of geometric factor difference between channels. The differential absorption algorithm is studied to solve the problem of aerosol interference by use of automatic compensation mechanism between pairs of wavelengths to eliminate the influence of aerosol extinction and scattering. And the method will improve the measurement accuracy in haze conditions. The relationship between signal to noise ratio and statistical error is established and the signal to noise ratio is optimized, then the profile of ozone in middle to upper troposphere will be measured. Finally the real-time adaptive ozone concentration inversion algorithm in different weather condition can be realized. It will provide advanced detection method and technical foundation for temporal and spatial distribution of ozone in the field of atmospheric compound pollution research.