Vertical distribution of aerosol mass concentration over Pearl River Delta observed by Lidar during autumn and winter

Abstract

This study aims to analyze the vertical distribution of aerosol particles during autumn and winter by deriving the number density of aerosol particles from Mie Lidar return signals. Haze has always existed in regions with low humidity and stable weather. In such regions,particle vertical distribution characters are needed for transport mechanisms. As a widely used instrument, Mie Lidar surfer from the uncertainties caused by the Lidar ratio and boundary value assumption. However, Mie Lidar is the most powerful tool to observe the atmospheric vertical distribution because it performs well in day and night under all weather conditions in comparison with passive sensors.Moreover, Mie Lidar is easier to carry compared with Raman Lidar.Lidar radiation principles were studied to understand the Lidar equation and its solution. Several parameters were carefully chosen for the numerical solutions. Instead of using boundary value for approximation, the Lidar parameter k was directly calculated on the basis of Lidar-validated parameters to avoid uncertainties. Thus, aerosol particles backscatter and extinction coefficient were retrieved by solving the Lidar equation and integrated for Aerosol Optical Depth(AOD) results. A Cimel CE318 sun photometer and an ASD Field Spec3 were used to measure AOD as validation data. Lastly, the number density of aerosol particles was derived on the basis of Mie theory with the estimation of aerosol particle distribution, size, and refractive index of particles.According to the number density vertical profile, nearly no difference was observed between the number density vertical profile of aerosol particles during daytime and nighttime in one day at a low altitude. This result indicated that the sunlight effect is ignorable for aerosol particle distribution near ground. The retrieved AODs with the CE318 and ASD observations showed a root mean square error of approximately 0.0541 and 0.0100, demonstrating that the retrieved result is reliable. The comparison with traditional method showed that the proposed algorithm in this study improved the accuracy of the traditional Lidar equation solution. The near-real distribution results showed aerosol particle distribution characteristics near the ground. The number density of aerosol particles in Guangzhou was mainly distributed in low-altitude regions, and its relationship with height was approximately a negative exponential distribution. The retrieved results of the aerosol particle number density were similar to those from the previous years, indicating that the air pollution in Guangzhou has not worsened. However, potential environmental threats and air pollution problems still need to be governed.Several uncertainties, such as changes in air temperature and pressure, validation of Lidar instrument k, and overlap factor, that could cause deviation were identified. The overlap factor and molecular backscatter coefficient were carefully calculated using the theoretical method. Frequent updates on Lidar parameters will be requested from the Lidar company in the future. The theoretical and experimental methods were combined for the calculation of the overlap factor and molecular backscatter coefficient. Raman Lidar was used to measure the actual Lidar ratios and characteristics of molecular scatter.The aerosol particle number density-retrieved algorithm was based on Lidar radiation principles and revealed the particles’ spatial distribution characters. The vertical distribution characters remained unchanged for several days under stable weather in the autumn and winter seasons, and its relationship with height was approximately a negative exponential distribution;hence, air conditions can have huge effect on human health. Air pollution problem still needs to be governed.