| 基于无人机的大气细颗粒物与臭氧污染探测与溯源研究进展 |
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| 引用本文： | 曲雅微,王体健,袁成,吴昊.基于无人机的大气细颗粒物与臭氧污染探测与溯源研究进展[J].环境科学,2023,44(12):6598-6609. |
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| 作者姓名： | 曲雅微 王体健 袁成 吴昊 |
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| 作者单位： | 金陵科技学院智能科学与控制工程学院, 南京 211169;南京信息工程大学气象灾害教育部重点实验室, 气象灾害预报预警与评估协同创新中心, 南京 210044;南京大学大气科学学院, 南京 210023;南京气象科技创新研究院中国气象局交通气象重点开放实验室, 南京 210041 |
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| 基金项目： | 江苏省高等学校自然科学研究项目（22KJB170012）；国家自然科学基金项目（42005085）；金陵科技学院高层次人才科研启动基金项目（JIT-B-202108）；南京信息工程大学气象灾害教育部重点实验室&气象灾害预报预警与评估协同创新中心联合开放课题项目（KLME202109）；中央级公益性科研院所基本科研业务费专项（2022Y023） |
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| 摘 要： | 近年来，中国大气细颗粒物(PM2.5)污染的治理已取得阶段性成效，但臭氧(O3)污染快速上升，实现PM2.5和O3协同控制的基础与关键是针对大气污染物的精细化探测和污染溯源.随着无人机技术和传感器技术的迅速发展，基于无人机平台的大气污染探测可以有效获得近地层的PM2.5和O3结构特征，并结合计算机算法对大气污染事件进行精准溯源，具有高时效性、高灵活性和高时空分辨率的特征，有助于研究人员了解区域污染物的分布、变化以及来源，为大气复合污染的协同控制提供科学依据.通过回顾传统的大气污染探测方法，总结了污染探测领域常用的无人机飞行平台类型和探测仪器，归纳了基于无人机的PM2.5和O3污染探测应用与相关溯源算法，并展望了无人机大气探测的未来研究方向.
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| 关 键 词： | 无人机(UAV) PM2.5 臭氧(O3) 大气污染探测 大气污染溯源 |
| 收稿时间： | 2022/11/22 0:00:00 |
| 修稿时间： | 2023/2/17 0:00:00 |
Review of UAV-based Atmospheric Fine Particulate Matter and Ozone Pollution Detection and Source Localization |
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| QU Ya-wei,WANG Ti-jian,YUAN Cheng,WU Hao.Review of UAV-based Atmospheric Fine Particulate Matter and Ozone Pollution Detection and Source Localization[J].Chinese Journal of Environmental Science,2023,44(12):6598-6609. |
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| Authors: | QU Ya-wei WANG Ti-jian YUAN Cheng WU Hao |
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| Institution: | College of Intelligent Science and Control Engineering, Jinling Institute of Technology, Nanjing 211169, China;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 210044, China;School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China; Key Laboratory of Transportation Meteorology of China Meteorological Administration, Nanjing Joint Institute for Atmospheric Sciences, Nanjing 210041, China |
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| Abstract: | In recent years, the management of atmospheric fine particulate matter(PM2.5) pollution in China has achieved staged success, but ozone(O3) 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 O3. 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 O3 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 O3 pollution detection and the algorithms of pollution source localization, and discussed the future trends of UAV-based air pollution detection. |
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| Keywords: | unmanned aerial vehicle(UAV) PM2 5 ozone(O3) air pollution detection air pollution source localization |
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