| 王东生,彭仲仁,李白,李小兵,修光利.基于多旋翼无人机平台的大气PM2.5垂直结构观测技术[J].装备环境工程,2019,16(6):35-40. WANG Dong-sheng,PENG Zhong-ren,LI Bai,LI Xiao-bing,XIU Guang-li.Vertical Atmospheric Structure Observation Technology Based on Multi-rotor Unmanned Aerial Vehicle (UAV) Platform[J].Equipment Environmental Engineering,2019,16(6):35-40. |
| 基于多旋翼无人机平台的大气PM2.5垂直结构观测技术 |
| Vertical Atmospheric Structure Observation Technology Based on Multi-rotor Unmanned Aerial Vehicle (UAV) Platform |
| 投稿时间：2018-12-28 修订日期：2019-06-25 |
| DOI：10.7643/ issn.1672-9242.2019.06.007 |
| 中文关键词: 大气污染 无人机 垂直廓线 大气边界层 PM2.5 细颗粒物 垂直观测 环境监测 |
| 英文关键词:air pollution unmanned aerial vehicle vertical profiles atmospheric boundary layer PM2.5 fine particular matter vertical observation environmental monitoring |
| 基金项目:国家重点研发计划 (2016YFC0200500) |
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| Author | Institution |
| WANG Dong-sheng | 1. Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China |
| PENG Zhong-ren | 1. Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; 2. International Center for Adaptation Planning and Design, College of Design, University of Florida, Gainesville 32611, USA |
| LI Bai | 1. Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China |
| LI Xiao-bing | 1. Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China |
| XIU Guang-li | 3. State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Processes, East China University of Science and Technology, Shanghai 200237, China |
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| 中文摘要: |
| 目的 设计可用于大气边界层范围的大气污染观测平台。方法 使用多旋翼无人机作为载体，集成多种大气污染物和气象要素的便携式检测设备，组建无人机观测平台。通过地面比对实验，保障所搭载的设备数据可靠，通过与大载荷系留气艇平台的垂直比对实验验证平台集成后的数据可靠性。结果 对于重点观测指标PM2.5而言，无人机和系留气艇所获取的垂直廓线表现出良好的一致性，各个航次的R2最低值为0.762，多数航次的组内相关系数为0.94以上。在2017年12月18日的案例中，无人机的观测数据表明，早上的大气垂直结构呈现了明显分层，0~200 m高度较为稳定的大气层结阻碍了污染物向上扩散，导致了近地面PM2.5 80 μg/m3的较高浓度，而下午的观测数据有助于解释污染消散。结论 文中搭建的多旋翼无人机平台可以用于0~1000 m范围内的边界层观测，尽管个别航次数据和系留气艇平台仍存在差异，但现有观测结果已表明，该平台有助于研究人员了解污染事件的发生和消散，可以进一步推广应用。 |
| 英文摘要: |
| Objective To design an atmospheric pollution observation platform that can be used around the atmospheric boundary layer. Methods A multi-rotor UAV was used as a carrier to integrate a variety of portable devices for measuring at-mospheric pollutants and meteorological parameters to build a UAV observation platform. Through ground comparison experiment, the data measured by the portable devices were considered as reliable. The data reliability of the integrated platform was verified by a vertical comparison experiment with the large-loaded tethered balloon platform. Results For the main observation indicator PM2.5, the vertical profiles obtained by the UAV and the tethered balloon showed good consistency. Even the lowest R-square value of each flight reached 0.761, and the intraclass correlation coefficient (ICC) of most flights reached more than 0.94. In the case of December 18, 2017, the observation data showed that there was a significant stratification of the atmospheric vertical structure in the morning, and the relatively stable atmospheric layer at 0-200 m hindered the upward dispersion of air pollutants, resulting in a concentration of PM2.5 at 80 μg/m3 near ground. The observations in the afternoon also helped explain the dissipation process of air pollution. Conclusion The multi-rotor UAV platform built in this paper can be used for boundary layer observations in the range of 0-1000 meters. Although there is still some differences between the data measured by UAV and tethered balloon in some cases, the existing observation results show that the platform is helpful for understanding the occurrence and dissipation of air pollution. This platform can be further promoted and applied in other places. |
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