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颗粒物激光雷达在大气复合污染立体监测中的应用
引用本文:伍德侠,宫正宇,潘本锋,王界,万学平.颗粒物激光雷达在大气复合污染立体监测中的应用[J].中国环境监测,2015,31(5):156-162.
作者姓名:伍德侠  宫正宇  潘本锋  王界  万学平
作者单位:无锡中科光电技术有限公司, 江苏 无锡 214135;中国科学院安徽光学精密机械研究所, 环境光学与技术重点实验室, 安徽 合肥 230031,中国环境监测总站, 国家环境保护环境监测质量控制重点实验室, 北京 100012,中国环境监测总站, 国家环境保护环境监测质量控制重点实验室, 北京 100012,无锡中科光电技术有限公司, 江苏 无锡 214135,无锡中科光电技术有限公司, 江苏 无锡 214135
基金项目:国家重大科学仪器研发与应用(2012YQ060147);江苏省创新资金(BC2012049)
摘    要:针对由于局地污染、沙尘输入、外源性输入与局地污染物相互叠加所导致的3种灰霾污染发生过程,分别选取3个典型案例,采用颗粒物激光雷达对污染物的时空分布特征进行解析。研究发现,在局地污染发生时,污染物从地面开始垂直向上扩散,扩散高度约1 km。重度污染过程中,气溶胶的日均垂直消光系数随高度的变化背离指数衰减特征,800 m高度处出现消光系数的极大值层,极大值超过2.5 km-1,800 m以下消光系数近乎常数,约为0.3 km-1。这说明,重污染过程中,有一层较厚重的颗粒物分布,使近地面污染物在垂直方向的扩散能力减弱,形成积累效应,造成大面积空气混浊。当有外源性沙尘输入时,激光雷达能够清晰地监测到污染团输入的全过程。沙团突然出现在高空2~3 km。污染团退偏振度较大,超过0.3。随着沙尘粒子的重力沉降,沙团的轮廓在垂直方向上不断地增大。沙团的输入,导致近地面粗颗粒质量浓度的增加幅度明显大于细颗粒。在第3个案例中,激光雷达清晰地监测到高空1.8~3 km突然出现含有大量球形细颗粒的污染团,同时还发现此污染团与近地面的污染物有不同的演化特征。近地面污染物随时间垂直向上扩散,12:00左右扩散高度超过1.8 km。而高空的污染团逐渐沉降进入边界层内,与近地面扩散的污染物相互混合,共同导致本地的灰霾天气。综上所述,激光雷达可以清晰地捕获污染物的垂直结构特征,对不同的致霾过程进行立体解析,实现对大气复合污染的监测和机理研判。

关 键 词:颗粒物激光雷达  消光廓线  沙尘输入  外源性输入  垂直分布  大气复合污染
收稿时间:2014/11/26 0:00:00
修稿时间:2014/12/29 0:00:00

The Applications Particulate LiDAR in the Stereo-Monitoring for the Complex Atmospheric Pollution
WU De-xi,GONG Zheng-yu,PAN Ben-feng,WANG Jie and WAN Xue-ping.The Applications Particulate LiDAR in the Stereo-Monitoring for the Complex Atmospheric Pollution[J].Environmental Monitoring in China,2015,31(5):156-162.
Authors:WU De-xi  GONG Zheng-yu  PAN Ben-feng  WANG Jie and WAN Xue-ping
Institution:Wuxi CAS Photonics Co. Ltd, Wuxi 214135, China;Key Laboratory of Environmental Optics & Technology, Anhui Institute of Optics & Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China,State Environmental Protection Key Laboratory of Quality Control in Environmental Monitoring, China National Environmental Monitoring Centre, Beijing 100012, China,State Environmental Protection Key Laboratory of Quality Control in Environmental Monitoring, China National Environmental Monitoring Centre, Beijing 100012, China,Wuxi CAS Photonics Co. Ltd, Wuxi 214135, China and Wuxi CAS Photonics Co. Ltd, Wuxi 214135, China
Abstract:To analyze the three different mechanisms for the haze formation respectively caused by local pollutants,dust sunk,and the superposition with local pollution diffusion and exogenous pollution input,we applied particulate LiDAR to detect the spatial and temporal characteristics of suspended particulate matter in three different examples. In the haze episodes resulting mainly from the local pollutions,the particulate matter always spread from the ground level to about 1 km. The daily-averaged aerosol profile violated the exponential function,especially in severe pollution days. The extinction coefficient was nearly a constant of 0.3 km-1 below 800 m. A layer with a maximum of extinction coefficient in the aerosol profile was shown at about 800 m,which was over 1 km-1. Such layer weakened the vertical dispersion of pollution contributing a primary factor for a wide visual range obstacle. For the haze pollution caused by dust mass input,LiDAR clearly outlined the dust profile varied in altitudes. The dust masses always suddenly occurred in 2-3 km with a depolarization coefficient over 0.3. It expanded in vertical direction due to the dust's gravitational settlement,which raising the concentration of coarse particulate matter (PM10) greatly larger than that of fine particle matter (PM2.5). In the third example,LiDAR mapped an input pollution mass floating in 1.8-3 km which containing mainly of fine particles. This input pollution felled into the atmospheric boundary layer (ABL) at noon mixing with the pollution diffused to 1.8 km from ground level,which eventually caused the local haze pollution. In conclusion,we found the LiDAR system could effectively describe the space-time distribution of particulate pollutants. It was advantage to explain three different mechanisms of haze-formation. As one kind of remote sensing techniques,LiDAR could be applied to study the atmospheric complex pollution.
Keywords:Particulate LiDAR  extinction coefficient profile  dust input  exogenous input  vertical distribution  atmospheric complex pollution
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