基于无人机平台的细颗粒物三维分布监测
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上海交通大学,上海交通大学,上海交通大学,上海交通大学,上海交通大学

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X831

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国家重点研发计划;上海市环保科研项目


Three-dimensional distribution of fine particulate matter measured by an UAV sampling platform
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National Key Research and Development Program;Foundation of Shanghai Municipal Environmental Protection Bureau

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    摘要:

    为获取高空间分辨率的污染物浓度数据,搭建了基于无人机技术的大气污染物立体监测平台,并成功获取临安市2014年11月一次重污染事件1 km以下高度的细颗粒物(PM2.5)浓度及同步气象场的三维分布数据。结果表明:大气湍流对PM2.5浓度时空变化具有重要影响。清晨及上午大气垂直湍流活动较弱,大气稳定度较高,逆温等温层多重大气结构不利于PM2.5垂直扩散。中午大气湍流活跃度最高,PM2.5混合充分,垂直浓度梯度较小。下午PM2.5在边界层内水平输送显著,并逐步向下沉降,说明此次重污染事件主要受外地污染源输送影响。

    Abstract:

    To obtain fine particulate matter concentration with high spatial resolution, three-dimensional atmospheric pollutant sampling platform based on unmanned aerial vehicle (UAV) technology was built. Research was conducted during a heavy haze pollution event in Lin’an city on November 2014. 3D distribution of PM2.5 concentration and synchronous meterology were successfully obtained. Research showed turbulence activity has great influence on the spatiotemporal distribution of PM2.5 concentration. Weak atmospheric vertical turbulence activity could cause stable atmospheric stratification during the morning and noon. The vertical dispersion of pollutants was obstructed by the inversion and isothermal layers in the atmosphere. The atmospheric turbulence enhanced at noon and the pollutant was well mixed, so that the vertical gradient of PM2.5 concentration was smaller than other times. At around 16:00, fine particulate matters transported horizontally and settled down, which means that the heavy pollution could mainly affected by the foreign sources of pollution.

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王东生,李小兵,王占永,等. 基于无人机平台的细颗粒物三维分布监测[J]. 科学技术与工程, 2017, 17(8): .
. Three-dimensional distribution of fine particulate matter measured by an UAV sampling platform[J]. Science Technology and Engineering,2017,17(8).

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  • 收稿日期:2016-09-29
  • 最后修改日期:2016-09-29
  • 录用日期:2016-11-25
  • 在线发布日期: 2017-03-17
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