Review of UAV-based Atmospheric Fine Particulate Matter and Ozone Pollution Detection and Source Localization

被引：1
作者：
Qu Y.-W. [1 ,2 ]
Wang T.-J. [3 ]
Yuan C. [2 ]
Wu H. [4 ]
机构：
[1] College of Intelligent Science and Control Engineering, Jinling Institute of Technology, Nanjing
[2] Key Laboratory of Meteorological Disaster(KLME), Ministry of Education, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing
[3] School of Atmospheric Sciences, Nanjing University, Nanjing
[4] Key Laboratory of Transportation Meteorology of China Meteorological Administration, Nanjing Joint Institute for Atmospheric Sciences, Nanjing
来源：
Huanjing Kexue/Environmental Science | 2023年 / 44卷 / 12期
关键词：
air pollution detection; air pollution source localization; ozone (03); PM2; 5; unmanned aerial vehicle (UAV);
D O I：
10.13227/j.hjkx.202211243
中图分类号：
学科分类号：
摘要：
In recent years, the management of atmospheric fine particulate matter (PM2 5) pollution in China has achieved staged success, but ozone (03) pollution has increased rapidly. Detection and source localization of atmospheric pollutants is the basis and key to controlling the combined pollution of PM2 5 and 03. With the rapid development of UAV technology and sensor technology, air pollution detection based on UAV platforms can effectively obtain the structural characteristics of PM2 5 and 03 near the surface and accurately trace the source of air pollution events by applying the computer algorithms, with the characteristics of high timeliness, flexibility, and spatial and temporal resolution. This will help researchers understand the distribution, changes, and sources of regional pollutants and provide a scientific basis for the synergistic control of combined air pollution. This study reviewed the traditional air pollution detection methods, summarized the types of UAV platforms and detection instruments commonly used in pollution detection, concluded the applications of UAV-based PM2 5 and 03 pollution detection and the algorithms of pollution source localization, and discussed the future trends of UAV-based air pollution detection. © 2023 Science Press. All rights reserved.
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页码：6598 / 6609
页数：11
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