Laser remote sensing of air pollution clouds

Yong Chen; Ze-hou Yang; Fan Dong; Chun-li Chen; Ren Peng; Xiao-feng Li; Zhen-zhong Feng; Pi-e Zhao; Guo-juan Zhang; Yu Chen

doi:10.1117/12.2542541

18 December 2019 Laser remote sensing of air pollution clouds

Yong Chen, Ze-hou Yang, Fan Dong, Chun-li Chen, Ren Peng, Xiao-feng Li, Zhen-zhong Feng, Pi-e Zhao, Guo-juan Zhang, Yu Chen

Author Affiliations +

Proceedings Volume 11337, AOPC 2019: Optical Spectroscopy and Imaging; 113370H (2019) https://doi.org/10.1117/12.2542541
Event: Applied Optics and Photonics China (AOPC2019), 2019, Beijing, China

Abstract

In the past few decades, environmental pollution problems have become more and more serious because of development of modern industry and science technology. The real-time detection and identification of atmospheric pollutants, has aroused widespread concern. Differential Absorption Lidar (DIAL) technology has become a common method for atmospheric remote sensing pollution measurement. 9~11-m-band lasers have small scattering cross sections for the air pollution cloud particles, so the laser output energy is required to reach the Joule level. The system engineering is difficult to realize detection of air pollution clouds with technology. The developed remote sensing pollution detection system is used to detect the types, concentration, orientation and distance information of common industrial chemical pollution. It is mainly divided into two parts: DIAL channel and Front Range Detecting Lidar (FRDL) channel. This paper mainly discusses remote sensing of air pollution clouds using FRDL. The working principle of FRDL is to use the Doppler effect of aerosol on the laser backward Mie scattering to realize the measurement of the aerosol cloud. In July 2017, the verification test was completed at a certain place in the north of China. The simulated pollutant spraying device and sampler were set at 400m in front of the 5km target. The measured results are in agreement with the actual situation.

Citation Download Citation

Yong Chen, Ze-hou Yang, Fan Dong, Chun-li Chen, Ren Peng, Xiao-feng Li, Zhen-zhong Feng, Pi-e Zhao, Guo-juan Zhang, and Yu Chen "Laser remote sensing of air pollution clouds", Proc. SPIE 11337, AOPC 2019: Optical Spectroscopy and Imaging, 113370H (18 December 2019); https://doi.org/10.1117/12.2542541

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KEYWORDS

Clouds

Pollution

Air contamination

Remote sensing

Atmospheric sensing

Laser scattering

Signal detection

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