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首页> 外文期刊>Atmospheric environment >A study of vertical distribution patterns of PM2.5 concentrations based on ambient monitoring with unmanned aerial vehicles: A case in Hangzhou, China
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A study of vertical distribution patterns of PM2.5 concentrations based on ambient monitoring with unmanned aerial vehicles: A case in Hangzhou, China

机译：基于无人飞行器环境监测的PM2.5浓度垂直分布模式研究：以杭州为例

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摘要

Measurements of the vertical distribution of air pollutant concentrations can provide essential information for accurate estimates of the dispersion mechanism of local pollutants between boundary layer and troposphere. This paper reports unique measurements using an unmanned aerial vehicle (UAV) with mobile sensors to collect three-dimensional fine particulate matter (PM2.5) mass concentration data on sixteen flights within 1000 m altitude from August, 2014 to December, 2014 in Hangzhou, China. The study demonstrates the feasibility of UAV with mobile monitoring devices as an effective and flexible means to collect three-dimensional air pollutant concentration data, particularly for monitoring the vertical profile of air pollutants. The experimental results show that in general, the PM2.5 concentrations decrease as height increases, with an exception when the air temperature inversion layer appears, and the decrease rate of PM2.5 concentrations is larger in the morning than in the afternoon flights. This is a result of the accumulated pollutant emission of human activities during the day and the varied meteorological conditions. At the same horizontal layer, there are fluctuations in PM2.5 concentrations during different time periods of the day. The vertical fluctuations of PM2.5 concentrations become nearly uniform in two afternoon flights, which is directly related with the extent of atmospheric mixture. Seen from the multiple regression models, the distribution of relative PM2.5 concentrations between vertical and ground observations is well characterized and the regression coefficients of four measured factors (i.e., air temperature, relative humidity, air pressure and height) effectively explain their impacts on the vertical distribution patterns. Air temperature and relative humidity are the most influential factors that affect the vertical distribution of PM2.5 concentrations. (C) 2015 Elsevier Ltd. All rights reserved.
机译：测量空气污染物浓度的垂直分布可以为准确估算边界层与对流层之间局部污染物的扩散机理提供重要信息。本文报告了使用无人飞行器（UAV）和移动传感器进行的独特测量，该数据收集了2014年8月至2014年12月在杭州，海拔1000 m内的16次飞行中的三维细颗粒物（PM2.5）质量浓度数据。中国。这项研究证明了无人飞行器结合移动监测设备作为收集三维空气污染物浓度数据的有效而灵活的手段的可行性，特别是用于监测空气污染物的垂直剖面。实验结果表明，总体而言，PM2.5浓度随高度的增加而降低，但当出现空气温度倒置层时例外，并且早晨PM2.5浓度的降低幅度大于下午飞行时的PM2.5浓度降低幅度。这是白天人类活动累积的污染物排放以及气象条件变化的结果。在同一水平层，一天中不同时间段的PM2.5浓度会有波动。在两次下午的飞行中，PM2.5浓度的垂直波动变得几乎均匀，这与大气混合物的程度直接相关。从多元回归模型可以看出，垂直和地面观测值之间的相对PM2.5浓度分布得到了很好的表征，四个测量因子（即气温，相对湿度，气压和高度）的回归系数有效地解释了它们对环境的影响。垂直分布模式。空气温度和相对湿度是影响PM2.5浓度垂直分布的最主要因素。 （C）2015 Elsevier Ltd.保留所有权利。

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  • 来源
    《Atmospheric environment》 |2015年第decaptab期|357-369|共13页
  • 作者

    Peng Zhong-Ren; Wang Dongsheng; Wang Zhanyong; Gao Ya; Lu Sijia;

  • 作者单位

    Shanghai Jiao Tong Univ, Sch Naval Architecture Ocean & Civil Engn, State Key Lab Ocean Engn, Ctr ITS & UAV Applicat Res, Shanghai 200240, Peoples R China|Univ Florida, Dept Urban & Reg Planning, Gainesville, FL 32611 USA;

    Shanghai Jiao Tong Univ, Sch Naval Architecture Ocean & Civil Engn, State Key Lab Ocean Engn, Ctr ITS & UAV Applicat Res, Shanghai 200240, Peoples R China;

    Shanghai Jiao Tong Univ, Sch Naval Architecture Ocean & Civil Engn, State Key Lab Ocean Engn, Ctr ITS & UAV Applicat Res, Shanghai 200240, Peoples R China;

    Shanghai Jiao Tong Univ, Sch Naval Architecture Ocean & Civil Engn, State Key Lab Ocean Engn, Ctr ITS & UAV Applicat Res, Shanghai 200240, Peoples R China;

    Shanghai Jiao Tong Univ, Sch Naval Architecture Ocean & Civil Engn, State Key Lab Ocean Engn, Ctr ITS & UAV Applicat Res, Shanghai 200240, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    Fine particulate matter; Vertical distribution; Meteorological parameters; Unmanned aerial vehicle;

    机译：细颗粒物垂直分布气象参数无人机;

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