基于三维大气探测激光雷达的大气颗粒物污染探测

赵文豪; 闫利; 王成义; 马昕; 李松; 马跃

doi:10.13203/j.whugis20190105

基于三维大气探测激光雷达的大气颗粒物污染探测

赵文豪^{1, 2,},
闫利¹,
王成义¹,
马昕^3, ,,
李松³,
马跃³

1.
武汉大学测绘学院, 湖北武汉, 430079
2.
国家基础地理信息中心, 北京, 100830
3.
武汉大学电子信息学院, 湖北武汉, 430072

基金项目:

国家自然科学基金 41801261

国家自然科学基金 41827801

国家自然科学基金 41601351

中国博士后科学基金 2016M600612

中国博士后科学基金 2016M602362

详细信息

作者简介:
赵文豪, 博士, 主要从事遥感信息提取和挖掘分析。zhaowh@ngcc.cn

通讯作者:
马昕, 博士, 讲师。maxinwhu@gmail.com

中图分类号: P208
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- 文章访问数: 1573
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出版历程
- 收稿日期: 2019-01-19
- 发布日期: 2019-10-04

Detection of Atmospheric Particulate Matter Pollution Based on Three-Dimensional Atmospheric Detection LiDAR

ZHAO Wenhao^{1, 2,},
YAN Li¹,
WANG Chengyi¹,
MA Xin^3, ,,
LI Song³,
MA Yue³

1.
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
2.
National Basic Geographic Information Center, Beijing 100830, China
3.
Electronic Information School, Wuhan University, Wuhan 430072, China

Funds:

The National Natural Science Foundation of China 41801261

The National Natural Science Foundation of China 41827801

The National Natural Science Foundation of China 41601351

Postdoctoral Science Foundation of China 2016M600612

Postdoctoral Science Foundation of China 2016M602362

More Information

Author Bio:
ZHAO Wenhao, PhD, specializes in remote sensing information extraction and analysis. E-mail: zhaowh@ngcc.cn

Corresponding author:
MA Xin, PhD, lecturer. E-mail:maxinwhu@gmail.com

摘要

摘要: 激光雷达是一种监测大气颗粒物分布和传输的有效遥感手段，能够克服常规地面监测站零星分布、无法实现区域覆盖监测的问题。通过布设一台垂直探测激光雷达和一台水平扫描激光雷达，实现大气颗粒物的垂直结构探测以及半径6 km内水平分布情况监测，并结合斜率法和Fernald算法实现更加精确的水平方向消光系数反演，进而实现以三维数据分析颗粒物的传输、分布和浓度变化情况；并利用地面国控站点数据同水平消光系数进行相关性对比。结果表明，利用三维大气探测激光雷达能够有效地揭示城市地区较大区域内的颗粒物分布和传输情况，具有覆盖范围大、探测效率高的优点。
- 颗粒物污染 /
- 激光雷达 /
- 三维数据 /
- 水平扫描
Abstract: LiDAR is an effective remote sensing method for monitoring the distribution of atmospheric particulate matter (PM), which can overcome the shortcoming of scattered distribution and failure to achieve regional monitor of the conventional ground monitoring stations. In order to determine the horizontal distribution and transportation of PMs in urban areas, a vertical observation LiDAR and a horizontal scanning LiDAR are applied to achieve the goal. A more accurate retrieval method is developed by combining the slope algorithm and Fernald algorithm. The transport, distribution and concentration are analyzed using three-dimensional LiDAR data. The results of the horizontal aerosol extinction coefficient of the LiDAR are compared with the PM concentration from the ground state-controlled station to analyze their correlation. The results show that the three-dimensional atmospheric LiDAR can effectively reveal the distribution of PMs in large urban areas, and has the advantages of wide coverage and high detection efficiency.
- particulate pollution /
- LiDAR /
- three-dimensional data /
- horizontal scanning

HTML全文

图 1 垂直激光雷达探测结果

Figure 1. Observation Results of Vertical LiDAR

下载: 全尺寸图片幻灯片

图 2 水平扫描激光雷达探测结果

Figure 2. Observation Results of Horizontal Scanning LiDAR

下载: 全尺寸图片幻灯片

图 3 气溶胶消光系数和PM10的相关性对比分析图

Figure 3. Comparison and Analysis of Correlation Between Aerosol Extinction Coefficient and PM10

下载: 全尺寸图片幻灯片

表 1 激光雷达技术参数

Table 1 Parameters of the Two LiDARs

参数	垂直LiDAR	水平LiDAR
波长/nm	1 064	1 064
能量/μJ	＞100	＞20
脉冲频率/kHz	1	1
望远镜口径/ mm	100	100
距离分辨率/m	30	15
滤光片带宽/nm	0.5	0.5

下载: 导出CSV

参考文献(21)

[1]	田晓敏, 刘东, 徐继伟, 等.大气探测激光雷达技术综述[J].大气与环境光学学报, 2018, 13(5):321-341 http://d.old.wanfangdata.com.cn/Periodical/dqyhjgxxb201805001 Tian Xiaomin, Liu Dong, Xu Jiwei, et al. Review of LiDAR Technology for Atmosphere Monitoring[J]. Journal of Atmospheric and Environmental Optics, 2018, 13(5):321-341 http://d.old.wanfangdata.com.cn/Periodical/dqyhjgxxb201805001
[2]	Fan W Z, Qin K, Xu J, et al. Aerosol Vertical Distribution and Sources Estimation at a Site of the Yangtze River Delta Region of China[J]. Atmospheric Research, 2019, 217:128-136 doi: 10.1016/j.atmosres.2018.11.002
[3]	陶燕, 刘雅梦, 米生权, 等.大气细颗粒物的污染特征及对人体健康的影响[J].环境科学学报, 2014, 34(3):592-597 http://d.old.wanfangdata.com.cn/Periodical/kxsd201514087 Tao Yan, Liu Yameng, Mi Shengquan, et al. Atmospheric Pollution Characteristics of Fine Particles and Their Effects on Human Health[J]. Acta Scientiae Circumstantiate, 2014, 34(3):592-597 http://d.old.wanfangdata.com.cn/Periodical/kxsd201514087
[4]	杜其成, 纪玉峰, 徐赤东.MPL探测气溶胶水平分布数据处理方法研究[J].大气与环境光学学报, 2008, 3(1):23-27 doi: 10.3969/j.issn.1673-6141.2008.01.004 Du Qicheng, Ji Yufeng, Xu Chidong. Data Processing Method of Aerosol Horizontal Distribution Detected by MPL[J]. Journal of Atmospheric and Environmental Optics, 2008, 3(1):23-27 doi: 10.3969/j.issn.1673-6141.2008.01.004
[5]	董云升, 刘文清, 刘建国, 等.激光雷达在城市交通污染中应用研究[J].光学学报, 2010, 30(2):315-320 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=gxxb201002001 Dong Yunsheng, Liu Wenqing, Liu Jianguo, et al. Application Study of LiDAR in Urban Traffic Pollution[J]. Acta Optica Sinica, 2010, 30(2):315-320 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=gxxb201002001
[6]	鲁先洋, 李学彬, 秦武斌, 等, 微脉冲激光雷达反演气溶胶的水平分布[J].光学精密工程, 2017, 25(7):1697-1704 http://d.old.wanfangdata.com.cn/Periodical/gxjmgc201707002 Lu Xianyang, Li Xuebin, Qin Wubin, et al. Retrieval of Horizontal Distribution of Aerosol Mass Concentration by Micro Pulse LiDAR[J]. Optics and Precision Engineering, 2017, 25(7):1697-1704 http://d.old.wanfangdata.com.cn/Periodical/gxjmgc201707002
[7]	Bo Guangyu, Xu Chidong, Li Aiyue, et al. Optical and Hygroscopic Properties of Asian Dust Particles Based on a Horizontal Mie LiDAR:Case Study at Hefei, China[J]. Chinese Optics Letter, 2017, 15:020102 doi: 10.3788/COL201715.020102
[8]	田礼乔, 陈晓玲, 邱凤, 等.星载激光雷达气溶胶数据辅助的近岸浑浊水体大气校正研究[J].武汉大学学报·信息科学版, 2011, 36(8):960-963 http://ch.whu.edu.cn/CN/abstract/abstract626.shtml Tian Liqiao, Chen Xiaoling, Qiu Feng, et al. Atmospheric Correction over Coastal Turbid Waters Based on Space-borne LiDAR Aerosol Data[J]. Geomatics and Information Science of Wuhan University, 2011, 36(8):960-963 http://ch.whu.edu.cn/CN/abstract/abstract626.shtml
[9]	刘君, 华灯鑫, 李言, 等.小型米散射激光雷达系统设计[J].西安理工大学学报, 2007, 23(1):1-5 doi: 10.3969/j.issn.1006-4710.2007.01.001 Liu Jun, Hua Dengxin, Li Yan, et al. Design of a Compact Mie LiDAR System[J]. Journal of Xian University of Technology, 2007, 23(1):1-5 doi: 10.3969/j.issn.1006-4710.2007.01.001
[10]	Ancellet, Penner E, Pelon J, et al. Aerosol Monitoring in Siberia Using an 808 nm Automatic Compact LiDAR[J]. Atmospheric Measurement Techniques, 2019, 12:147-168 doi: 10.5194/amt-12-147-2019
[11]	Sugimoto N, Uno I, Nishikawa M, et al. Record Heavy Asian Dust in Beijing in 2002:Observations and Model Analysis of Recent Events[J]. Geophysical Research Letters, 2003, 30(12):1640
[12]	Yumimoto K, Uno I, Sugimoto N, et al. Numerical Modeling of Asian Dust Emission and Transport with Adjoint Inversion Using LiDAR Network Observations[J]. Atmospheric Chemistry and Physics, 2007, 7:15955-15987
[13]	Pappalardo G, Amodeo A, Pandolfi M, et al. Aerosol LiDAR Intercomparison in the Framework of the EARLINET Project. 3. Raman LiDAR Algorithm for Aerosol Extinction, Backscatter and LiDAR Ratio[J]. Applied Optics, 2004, 43(28):5370-5385 doi: 10.1364/AO.43.005370
[14]	John B, Parikh S, Trevor K. Atmospheric Aerosol Profiling with a Bistatic Imaging LiDAR System[J]. Applied Optics, 2007, 46:2922-2929 doi: 10.1364/AO.46.002922
[15]	Zhao G Y, Malmqvist E, T r k S, et al. Particle Profiling and Classification by a Dual-band Continuous-Wave LiDAR System[J]. Applied Optics, 2018, 57:10164-10171 doi: 10.1364/AO.57.010164
[16]	方欣, 王敏, 胡顺星.合肥梅雨季节大气污染物分布特征的激光雷达探测[J].中国激光, 2019, 46(1):302-309 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgjg201901037 Fang Xin, Wang Min, Hu Shunxing. Distribution Characteristics of Atmospheric Pollutions in Meiyu Season Observed by LiDAR over Hefei[J]. Chinese Journal of Lasers, 2019, 46(1):302-309 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgjg201901037
[17]	狄慧鸽, 侯晓龙, 赵虎, 等.多波长激光雷达探测多种天气气溶胶光学特性与分析[J].物理学报, 2014, 63(24):248-255 http://d.old.wanfangdata.com.cn/Periodical/wlxb201424029 Di Huige, Hou Xiaolong, Zhao Hu, et al. Detections and Analyses of Aerosol Optical Properties Under Different Weather Conditions Using Multi-Wavelength Mie LiDAR[J]. Acta Physica Sinica, 2014, 63(24):248-255 http://d.old.wanfangdata.com.cn/Periodical/wlxb201424029
[18]	Fernald F G. Analysis of Atmospheric LiDAR Observation-Some Comments[J]. Applied Optics, 1984, 23(5):652-653 doi: 10.1364/AO.23.000652
[19]	Gerard J K, Gerritde L. Inversion of LiDAR Signals with the Slope Method[J]. Applied Optics, 1993, 32(18):3249-3251 doi: 10.1364/AO.32.003249
[20]	Zeng X J, Guo W P, Yang K C. Noise Reduction and Retrieval by Modified LiDAR Inversion Method Combines Joint Retrieval Method and Machine Learning[J]. Applied Physics B:Laser and Optics, 2018, 124(12):238 doi: 10.1007/s00340-018-7095-6
[21]	吕立慧, 刘文清, 张天舒, 等.微脉冲激光雷达水平探测气溶胶两种反演算法对比与误差分析[J].光谱学与光谱分析, 2015(7):1774-1778 doi: 10.3964/j.issn.1000-0593(2015)07-1774-05 Lü Lihui, Liu Wenqing, Zhang Tianshu, et al. Two Data Inversion Algorithms of Aerosol Horizontal Distribution Detected by MPL and Error Analysis[J]. Spectroscopy and Spectral Analysis, 2015(7):1774-1778 doi: 10.3964/j.issn.1000-0593(2015)07-1774-05

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