Atmospheric pollutant poses a direct threat to human health. The prevalent aerosolic particles in the atmosphere can carry and spread various pathogens, endotoxins and allergens, potentially giving rise to allergies and respiratory disorders. Most of the traditional methods for monitoring aerosolic pollution require sampling and analysis at fixed stations, with limited monitoring ranges. Remote monitoring approach based on light detection and ranging (LiDAR) technology has offered an alternative way. The transmission attenuation characteristics of laser in the atmosphere is one of the main factors affecting the detection performance of LiDAR. Especially in a high-humidity environment, the effective detection range is notably reduced by the low atmospheric visibility. Here, we introduce a theoretical model for a marine atmospheric pollutant detection LiDAR utilizing both fluorescence and Mie scattering techniques. The MODTRAN software is used to calculate the atmospheric transmittance in a high-humidity environment. The detection performance of the LiDAR system is subsequently simulated and analyzed under various marine atmospheric conditions ranging from coastal to offshore environments by incorporating historical data from the National Meteorological Center of China. The results presented here offer valuable insights into optimizing LiDAR technology for enhanced monitoring of marine atmospheric pollutants.
Long-range detection LiDAR is a promising tool for online air quality monitoring in atmospheric research. Monitoring from a distance enables wide area coverage, allowing for the tracking of all changes and the increase of available response time compared with point detection methods. Here, we introduce a multi-channel laser-induced fluorescence LiDAR, achieving remote detection of environmental pollution and identification of organic pollutants based on scattering and fluorescence. A mathematical and physical model that encompasses the entire process of laser transmission in the atmosphere, interactions between aerosol particles and laser light, and the analysis of received echo signals is presented. Followed by a performance simulation and evaluation that takes into account the maximum detection distance. The results discussed herein can serve as a reference for future application of LiDAR in monitoring of environmental pollution.
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