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Calibration Methods of Atmospheric Aerosol Lidar and a Case Study of Haze Process
Lidar is a reliable tool for active remote sensing detection of atmospheric aerosols. A multi-wavelength aerosol lidar (MWAL) with 355 nm, 532 and 1064 nm as detection light sources has been developed and deployed for operational observations at Haidian District Meteorological Service of Beijing. Th...
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Published in: | Frontiers in physics 2022-06, Vol.10 |
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container_title | Frontiers in physics |
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creator | Chen, Chao Song, Xiaoquan Wang, Zhangjun Chen, Yubao Wang, Xiaopeng Bu, Zhichao Zhang, Xi Zhuang, Quanfeng Pan, Xin Li, Hui Zhang, Feng Wang, Xiufen Li, Xianxin Zheng, Ronger |
description | Lidar is a reliable tool for active remote sensing detection of atmospheric aerosols. A multi-wavelength aerosol lidar (MWAL) with 355 nm, 532 and 1064 nm as detection light sources has been developed and deployed for operational observations at Haidian District Meteorological Service of Beijing. The structure design, specifications, observation campaign, and detection principle of the MWAL are introduced. To ensure the accuracy and reliability of the lidar observation data, the calibration contents, and methods of lidar are proposed, including the correction, and gluing of the original data, the collimation of the transmitting and receiving optical axes, the testing of signal saturation, the correction of molecular Rayleigh fitting and the determination of the depolarization ratio correction factor. Finally, a haze process from 29 September to 2 October 2019 was observed and analyzed using the data of lidar, digital radiosonde, air quality and relative humidity observed by the Haidian District Meteorological Service. The detection results show the reliability of lidar which can effectively obtain the temporal and spatial variation characteristics of the haze. The profiles of aerosol extinction coefficient, potential temperature and relative humidity can be effectively used to analyze the haze thickness and the influence of relative humidity on aerosol particles. The data of air quality monitor shows that PM
10
is the main pollutant and the ratio of PM
2.5
/PM
10
is negatively correlated with relative humidity. Finally, the HYSPLIT trajectory tracking model of the National Oceanic and Atmospheric Administration (NOAA) is used to further study the source of pollutants in this haze process. |
doi_str_mv | 10.3389/fphy.2022.942926 |
format | article |
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10
is the main pollutant and the ratio of PM
2.5
/PM
10
is negatively correlated with relative humidity. Finally, the HYSPLIT trajectory tracking model of the National Oceanic and Atmospheric Administration (NOAA) is used to further study the source of pollutants in this haze process.</description><identifier>ISSN: 2296-424X</identifier><identifier>EISSN: 2296-424X</identifier><identifier>DOI: 10.3389/fphy.2022.942926</identifier><language>eng</language><publisher>Frontiers Media S.A</publisher><subject>aerosol ; atmospheric lidar ; calibration ; depolarization ratio ; haze</subject><ispartof>Frontiers in physics, 2022-06, Vol.10</ispartof><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c351t-a5425dcfd744bced965742b42a605ae72188fb8c6914482254aebfc77d9e43f03</citedby><cites>FETCH-LOGICAL-c351t-a5425dcfd744bced965742b42a605ae72188fb8c6914482254aebfc77d9e43f03</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Chen, Chao</creatorcontrib><creatorcontrib>Song, Xiaoquan</creatorcontrib><creatorcontrib>Wang, Zhangjun</creatorcontrib><creatorcontrib>Chen, Yubao</creatorcontrib><creatorcontrib>Wang, Xiaopeng</creatorcontrib><creatorcontrib>Bu, Zhichao</creatorcontrib><creatorcontrib>Zhang, Xi</creatorcontrib><creatorcontrib>Zhuang, Quanfeng</creatorcontrib><creatorcontrib>Pan, Xin</creatorcontrib><creatorcontrib>Li, Hui</creatorcontrib><creatorcontrib>Zhang, Feng</creatorcontrib><creatorcontrib>Wang, Xiufen</creatorcontrib><creatorcontrib>Li, Xianxin</creatorcontrib><creatorcontrib>Zheng, Ronger</creatorcontrib><title>Calibration Methods of Atmospheric Aerosol Lidar and a Case Study of Haze Process</title><title>Frontiers in physics</title><description>Lidar is a reliable tool for active remote sensing detection of atmospheric aerosols. A multi-wavelength aerosol lidar (MWAL) with 355 nm, 532 and 1064 nm as detection light sources has been developed and deployed for operational observations at Haidian District Meteorological Service of Beijing. The structure design, specifications, observation campaign, and detection principle of the MWAL are introduced. To ensure the accuracy and reliability of the lidar observation data, the calibration contents, and methods of lidar are proposed, including the correction, and gluing of the original data, the collimation of the transmitting and receiving optical axes, the testing of signal saturation, the correction of molecular Rayleigh fitting and the determination of the depolarization ratio correction factor. Finally, a haze process from 29 September to 2 October 2019 was observed and analyzed using the data of lidar, digital radiosonde, air quality and relative humidity observed by the Haidian District Meteorological Service. The detection results show the reliability of lidar which can effectively obtain the temporal and spatial variation characteristics of the haze. The profiles of aerosol extinction coefficient, potential temperature and relative humidity can be effectively used to analyze the haze thickness and the influence of relative humidity on aerosol particles. The data of air quality monitor shows that PM
10
is the main pollutant and the ratio of PM
2.5
/PM
10
is negatively correlated with relative humidity. Finally, the HYSPLIT trajectory tracking model of the National Oceanic and Atmospheric Administration (NOAA) is used to further study the source of pollutants in this haze process.</description><subject>aerosol</subject><subject>atmospheric lidar</subject><subject>calibration</subject><subject>depolarization ratio</subject><subject>haze</subject><issn>2296-424X</issn><issn>2296-424X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNpN0M9LwzAUwPEiCo65u8f8A53Ja9Imx1HUDSYqKngLr_nhOrplJPUw_3pbJ-Ipj_D4wPtm2TWj86KQ6sYfNsc5UIC54qCgPMsmAKrMOfD383_zZTZLaUspZSCUBD7Jnmvs2iZi34Y9eXD9JthEgieLfhfSYeNia8jCxZBCR9atxUhwbwmSGpMjL_2nPY7bS_xy5CkG41K6yi48dsnNft9p9nZ3-1ov8_Xj_aperHNTCNbnKDgIa7ytOG-Ms6oUFYeGA5ZUoKuASekbaUrFOJcAgqNrvKkqqxwvPC2m2erk2oBbfYjtDuNRB2z1z0eIHxpj35rOaSNReC-oG_QB440H1hQURSErJio3WPRkmeHSFJ3_8xjVY2E9FtZjYX0qXHwDM0tumQ</recordid><startdate>20220624</startdate><enddate>20220624</enddate><creator>Chen, Chao</creator><creator>Song, Xiaoquan</creator><creator>Wang, Zhangjun</creator><creator>Chen, Yubao</creator><creator>Wang, Xiaopeng</creator><creator>Bu, Zhichao</creator><creator>Zhang, Xi</creator><creator>Zhuang, Quanfeng</creator><creator>Pan, Xin</creator><creator>Li, Hui</creator><creator>Zhang, Feng</creator><creator>Wang, Xiufen</creator><creator>Li, Xianxin</creator><creator>Zheng, Ronger</creator><general>Frontiers Media S.A</general><scope>AAYXX</scope><scope>CITATION</scope><scope>DOA</scope></search><sort><creationdate>20220624</creationdate><title>Calibration Methods of Atmospheric Aerosol Lidar and a Case Study of Haze Process</title><author>Chen, Chao ; Song, Xiaoquan ; Wang, Zhangjun ; Chen, Yubao ; Wang, Xiaopeng ; Bu, Zhichao ; Zhang, Xi ; Zhuang, Quanfeng ; Pan, Xin ; Li, Hui ; Zhang, Feng ; Wang, Xiufen ; Li, Xianxin ; Zheng, Ronger</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c351t-a5425dcfd744bced965742b42a605ae72188fb8c6914482254aebfc77d9e43f03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>aerosol</topic><topic>atmospheric lidar</topic><topic>calibration</topic><topic>depolarization ratio</topic><topic>haze</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Chao</creatorcontrib><creatorcontrib>Song, Xiaoquan</creatorcontrib><creatorcontrib>Wang, Zhangjun</creatorcontrib><creatorcontrib>Chen, Yubao</creatorcontrib><creatorcontrib>Wang, Xiaopeng</creatorcontrib><creatorcontrib>Bu, Zhichao</creatorcontrib><creatorcontrib>Zhang, Xi</creatorcontrib><creatorcontrib>Zhuang, Quanfeng</creatorcontrib><creatorcontrib>Pan, Xin</creatorcontrib><creatorcontrib>Li, Hui</creatorcontrib><creatorcontrib>Zhang, Feng</creatorcontrib><creatorcontrib>Wang, Xiufen</creatorcontrib><creatorcontrib>Li, Xianxin</creatorcontrib><creatorcontrib>Zheng, Ronger</creatorcontrib><collection>CrossRef</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Frontiers in physics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Chao</au><au>Song, Xiaoquan</au><au>Wang, Zhangjun</au><au>Chen, Yubao</au><au>Wang, Xiaopeng</au><au>Bu, Zhichao</au><au>Zhang, Xi</au><au>Zhuang, Quanfeng</au><au>Pan, Xin</au><au>Li, Hui</au><au>Zhang, Feng</au><au>Wang, Xiufen</au><au>Li, Xianxin</au><au>Zheng, Ronger</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Calibration Methods of Atmospheric Aerosol Lidar and a Case Study of Haze Process</atitle><jtitle>Frontiers in physics</jtitle><date>2022-06-24</date><risdate>2022</risdate><volume>10</volume><issn>2296-424X</issn><eissn>2296-424X</eissn><abstract>Lidar is a reliable tool for active remote sensing detection of atmospheric aerosols. A multi-wavelength aerosol lidar (MWAL) with 355 nm, 532 and 1064 nm as detection light sources has been developed and deployed for operational observations at Haidian District Meteorological Service of Beijing. The structure design, specifications, observation campaign, and detection principle of the MWAL are introduced. To ensure the accuracy and reliability of the lidar observation data, the calibration contents, and methods of lidar are proposed, including the correction, and gluing of the original data, the collimation of the transmitting and receiving optical axes, the testing of signal saturation, the correction of molecular Rayleigh fitting and the determination of the depolarization ratio correction factor. Finally, a haze process from 29 September to 2 October 2019 was observed and analyzed using the data of lidar, digital radiosonde, air quality and relative humidity observed by the Haidian District Meteorological Service. The detection results show the reliability of lidar which can effectively obtain the temporal and spatial variation characteristics of the haze. The profiles of aerosol extinction coefficient, potential temperature and relative humidity can be effectively used to analyze the haze thickness and the influence of relative humidity on aerosol particles. The data of air quality monitor shows that PM
10
is the main pollutant and the ratio of PM
2.5
/PM
10
is negatively correlated with relative humidity. Finally, the HYSPLIT trajectory tracking model of the National Oceanic and Atmospheric Administration (NOAA) is used to further study the source of pollutants in this haze process.</abstract><pub>Frontiers Media S.A</pub><doi>10.3389/fphy.2022.942926</doi><oa>free_for_read</oa></addata></record> |
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subjects | aerosol atmospheric lidar calibration depolarization ratio haze |
title | Calibration Methods of Atmospheric Aerosol Lidar and a Case Study of Haze Process |
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