Using unmanned aerial vehicle to investigate the vertical distribution of fine particulate matter

编号 030023005

推送时间 20200316

研究领域 森林经理 

年份 2020 

类型 期刊 

语种 英语

标题 Using unmanned aerial vehicle to investigate the vertical distribution of fine particulate matter

来源期刊 INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY

期 第230期

发表时间 20190706

关键词 PM2.5;  Vertical distribution;  Cluster analysis;  Unmanned aerial vehicle; 

摘要 The vertical distribution of fine particulate matter (PM2.5) is a vital link in understanding the transport and evolution of haze. However, existing ground stations cannot provide sufficient vertical observations of PM2.5, especially at fine scales regarding space and time. This study deployed a six-rotor unmanned aerial vehicle (UAV) equipped with portable monitors to observe the vertical distributions of PM2.5 and meteorological parameters within 1000 m lower troposphere. By comparing with ground-based monitoring station and tethered balloon platform for PM2.5 measurements, the UAV was improved and then used to perform a field observation experiment in the Qingpu district of Shanghai, China. The UAV-based observations showed a decreasing vertical profile of PM2.5 in the experimental day, with a decrease of more than 50% at 0-1000 m height. PM2.5 had a vertical pattern that declined rapidly after 700 m in the afternoon, but the morning PM2.5 had a rapid decline from 200 to 500 m compared with other height intervals in this period. A temperature inversion at a lower height in the morning blocked newly formed PM2.5 at ground to disperse upward, and PM2.5 above the temperature inversion was composed of residuals in last night. The temperature inversion gradually climbed up in the afternoon, which was beneficial to the dispersion of near-ground PM2.5. The difference of relative humidity above and below 700 m height implies different geographical origins that were well identified and explained by a cluster analysis. This study generally highlights the significance of using a lightweight UAV to understand air pollution and governance environments in the urban area.

服务人员 付贺龙

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