Application of multiplatform remote sensing data over East Asia Ocean: aerosol characteristics and aerosol types
It is important to explore the characteristics and rules of atmospheric aerosol in the East Asian Sea for monitoring and evaluating atmospheric environmental quality. Based on Aerosol Robot Network (AERONET), Visible Infrared Imaging Radiometer (VIIRS), and Cloud-Aerosol Lidar and Infrared Pathfinde...
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description | It is important to explore the characteristics and rules of atmospheric aerosol in the East Asian Sea for monitoring and evaluating atmospheric environmental quality. Based on Aerosol Robot Network (AERONET), Visible Infrared Imaging Radiometer (VIIRS), and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data, the temporal and spatial variation characteristics and differences of aerosol parameters and types in the East Asian Sea were studied by using figure classification method (FIGCM), aerosol optical depth (AOD)
440
-Angstrom exponent (AE)
440–870
method (AA1M), and AOD
550
-AE
490-670
method (AA2M). The results show that the seasonal variation trend of aerosol characteristics and types is obvious in East Asia Sea. AOD, volume concentration (Cv), and aerosol effective radius (reff) in the Bohai-Yellow Sea and the Sea of Japan in autumn are lower than those in other seasons, and the occurrence frequency of ocean-type aerosols is high. Different from the Bohai-Yellow Sea and Sea of Japan, human activities in winter, summer, and autumn seriously affect the air quality in the East China Sea and South China Sea. Especially at the Taipei CWB site, from aerosol parameters and high biomass burning/urban industrial (BB/UI) aerosol, human activity is an important factor for high pollution at the Taipei CWB site. Aerosol types of AA1M, FIGCM, AA2M, and CALIPSO were compared at Anmyon and Yonsei University sites in the Bohai-Yellow Sea in March 2020. The results show that aerosol types based on threshold classification methods generally have higher mixed aerosol results, and the marine (MA) results of AA1M, FIGCM, and AA2M are close to the clean marine aerosol results of CALIPSO. Comparing the results of AA 2 M and CALIPSO on a spatial scale, it is found that the clean marine aerosol proportion identified by CALIPSO (0.38, 0.48, 0.82) is consistent with the MA proportion identified by AA 2 M (0.43, 0.46, 0.97) in the East China Sea, South China Sea, and Western Pacific Ocean. |
doi_str_mv | 10.1007/s11356-024-33458-9 |
format | Article |
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440
-Angstrom exponent (AE)
440–870
method (AA1M), and AOD
550
-AE
490-670
method (AA2M). The results show that the seasonal variation trend of aerosol characteristics and types is obvious in East Asia Sea. AOD, volume concentration (Cv), and aerosol effective radius (reff) in the Bohai-Yellow Sea and the Sea of Japan in autumn are lower than those in other seasons, and the occurrence frequency of ocean-type aerosols is high. Different from the Bohai-Yellow Sea and Sea of Japan, human activities in winter, summer, and autumn seriously affect the air quality in the East China Sea and South China Sea. Especially at the Taipei CWB site, from aerosol parameters and high biomass burning/urban industrial (BB/UI) aerosol, human activity is an important factor for high pollution at the Taipei CWB site. Aerosol types of AA1M, FIGCM, AA2M, and CALIPSO were compared at Anmyon and Yonsei University sites in the Bohai-Yellow Sea in March 2020. The results show that aerosol types based on threshold classification methods generally have higher mixed aerosol results, and the marine (MA) results of AA1M, FIGCM, and AA2M are close to the clean marine aerosol results of CALIPSO. Comparing the results of AA 2 M and CALIPSO on a spatial scale, it is found that the clean marine aerosol proportion identified by CALIPSO (0.38, 0.48, 0.82) is consistent with the MA proportion identified by AA 2 M (0.43, 0.46, 0.97) in the East China Sea, South China Sea, and Western Pacific Ocean.</description><identifier>ISSN: 1614-7499</identifier><identifier>ISSN: 0944-1344</identifier><identifier>EISSN: 1614-7499</identifier><identifier>DOI: 10.1007/s11356-024-33458-9</identifier><identifier>PMID: 38764086</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Aerosols ; Air quality ; Aquatic Pollution ; Atmospheric aerosols ; Atmospheric Protection/Air Quality Control/Air Pollution ; Autumn ; biomass ; Biomass burning ; CALIPSO (Pathfinder satellite) ; Classification ; Earth and Environmental Science ; East Asia ; East China Sea ; Ecotoxicology ; Environment ; Environmental Chemistry ; Environmental Health ; Environmental quality ; governmental programs and projects ; humans ; Imaging radiometers ; Infrared imaging ; Infrared radiometers ; Lidar ; Optical analysis ; Optical thickness ; Pacific Ocean ; Parameters ; pollution ; Radiometry ; Remote sensing ; Research Article ; Satellite observation ; satellites ; Sea of Japan ; seasonal variation ; Seasonal variations ; South China Sea ; Spatial variations ; summer ; Waste Water Technology ; Water Management ; Water Pollution Control ; winter</subject><ispartof>Environmental science and pollution research international, 2024-05, Vol.31 (25), p.37175-37195</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c2749-da95ec73be51ce82d7d8974280adc89abd2b46e355be038b8bc7daa90dedb5f23</cites><orcidid>0000-0002-8161-341X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11356-024-33458-9$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11356-024-33458-9$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,41467,42536,51298</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38764086$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Luan, Kuifeng</creatorcontrib><creatorcontrib>Cao, Zhaoxiang</creatorcontrib><creatorcontrib>Shen, Wei</creatorcontrib><creatorcontrib>Zhou, Peng</creatorcontrib><creatorcontrib>Qiu, Zhenge</creatorcontrib><creatorcontrib>Wan, Haixia</creatorcontrib><creatorcontrib>Wang, Zhenhua</creatorcontrib><creatorcontrib>Zhu, Weidong</creatorcontrib><title>Application of multiplatform remote sensing data over East Asia Ocean: aerosol characteristics and aerosol types</title><title>Environmental science and pollution research international</title><addtitle>Environ Sci Pollut Res</addtitle><addtitle>Environ Sci Pollut Res Int</addtitle><description>It is important to explore the characteristics and rules of atmospheric aerosol in the East Asian Sea for monitoring and evaluating atmospheric environmental quality. Based on Aerosol Robot Network (AERONET), Visible Infrared Imaging Radiometer (VIIRS), and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data, the temporal and spatial variation characteristics and differences of aerosol parameters and types in the East Asian Sea were studied by using figure classification method (FIGCM), aerosol optical depth (AOD)
440
-Angstrom exponent (AE)
440–870
method (AA1M), and AOD
550
-AE
490-670
method (AA2M). The results show that the seasonal variation trend of aerosol characteristics and types is obvious in East Asia Sea. AOD, volume concentration (Cv), and aerosol effective radius (reff) in the Bohai-Yellow Sea and the Sea of Japan in autumn are lower than those in other seasons, and the occurrence frequency of ocean-type aerosols is high. Different from the Bohai-Yellow Sea and Sea of Japan, human activities in winter, summer, and autumn seriously affect the air quality in the East China Sea and South China Sea. Especially at the Taipei CWB site, from aerosol parameters and high biomass burning/urban industrial (BB/UI) aerosol, human activity is an important factor for high pollution at the Taipei CWB site. Aerosol types of AA1M, FIGCM, AA2M, and CALIPSO were compared at Anmyon and Yonsei University sites in the Bohai-Yellow Sea in March 2020. The results show that aerosol types based on threshold classification methods generally have higher mixed aerosol results, and the marine (MA) results of AA1M, FIGCM, and AA2M are close to the clean marine aerosol results of CALIPSO. Comparing the results of AA 2 M and CALIPSO on a spatial scale, it is found that the clean marine aerosol proportion identified by CALIPSO (0.38, 0.48, 0.82) is consistent with the MA proportion identified by AA 2 M (0.43, 0.46, 0.97) in the East China Sea, South China Sea, and Western Pacific Ocean.</description><subject>Aerosols</subject><subject>Air quality</subject><subject>Aquatic Pollution</subject><subject>Atmospheric aerosols</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>Autumn</subject><subject>biomass</subject><subject>Biomass burning</subject><subject>CALIPSO (Pathfinder satellite)</subject><subject>Classification</subject><subject>Earth and Environmental Science</subject><subject>East Asia</subject><subject>East China Sea</subject><subject>Ecotoxicology</subject><subject>Environment</subject><subject>Environmental Chemistry</subject><subject>Environmental Health</subject><subject>Environmental quality</subject><subject>governmental programs and projects</subject><subject>humans</subject><subject>Imaging radiometers</subject><subject>Infrared imaging</subject><subject>Infrared radiometers</subject><subject>Lidar</subject><subject>Optical analysis</subject><subject>Optical thickness</subject><subject>Pacific Ocean</subject><subject>Parameters</subject><subject>pollution</subject><subject>Radiometry</subject><subject>Remote sensing</subject><subject>Research Article</subject><subject>Satellite observation</subject><subject>satellites</subject><subject>Sea of Japan</subject><subject>seasonal variation</subject><subject>Seasonal variations</subject><subject>South China Sea</subject><subject>Spatial variations</subject><subject>summer</subject><subject>Waste Water Technology</subject><subject>Water Management</subject><subject>Water Pollution Control</subject><subject>winter</subject><issn>1614-7499</issn><issn>0944-1344</issn><issn>1614-7499</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNqFkU1rFzEQhxdRbK1-AQ8S8OJlNa-bxNufUl-g0Iuew2wyW1N2N2uSFfrtjf5rFQ96msA885sMT9c9Z_Q1o1S_KYwJNfSUy14IqUxvH3SnbGCy19Lah3-8T7onpdxQyqnl-nF3IoweJDXDabcdtm2OHmpMK0kTWfa5xm2GOqW8kIxLqkgKriWu1yRABZK-YSYXUCo5lAjkyiOsbwlgTiXNxH-BDL5ijqVGXwis4b5XbzcsT7tHE8wFn93Vs-7zu4tP5x_6y6v3H88Pl73n7cd9AKvQazGiYh4NDzoYqyU3FII3FsbARzmgUGpEKsxoRq8DgKUBw6gmLs66V8fcLaevO5bqllg8zjOsmPbiBFNCGysk-z9KlaZaCioa-vIv9CbteW2HNGow1nIzmEbxI-Xb4SXj5LYcF8i3jlH3Q507qnNNnfupztk29OIueh8XDPcjv1w1QByB0lrrNebfu_8R-x25YaWb</recordid><startdate>20240501</startdate><enddate>20240501</enddate><creator>Luan, Kuifeng</creator><creator>Cao, Zhaoxiang</creator><creator>Shen, Wei</creator><creator>Zhou, Peng</creator><creator>Qiu, Zhenge</creator><creator>Wan, Haixia</creator><creator>Wang, Zhenhua</creator><creator>Zhu, Weidong</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QL</scope><scope>7SN</scope><scope>7T7</scope><scope>7TV</scope><scope>7U7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>K9.</scope><scope>M7N</scope><scope>P64</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope><orcidid>https://orcid.org/0000-0002-8161-341X</orcidid></search><sort><creationdate>20240501</creationdate><title>Application of multiplatform remote sensing data over East Asia Ocean: aerosol characteristics and aerosol types</title><author>Luan, Kuifeng ; 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Based on Aerosol Robot Network (AERONET), Visible Infrared Imaging Radiometer (VIIRS), and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data, the temporal and spatial variation characteristics and differences of aerosol parameters and types in the East Asian Sea were studied by using figure classification method (FIGCM), aerosol optical depth (AOD)
440
-Angstrom exponent (AE)
440–870
method (AA1M), and AOD
550
-AE
490-670
method (AA2M). The results show that the seasonal variation trend of aerosol characteristics and types is obvious in East Asia Sea. AOD, volume concentration (Cv), and aerosol effective radius (reff) in the Bohai-Yellow Sea and the Sea of Japan in autumn are lower than those in other seasons, and the occurrence frequency of ocean-type aerosols is high. Different from the Bohai-Yellow Sea and Sea of Japan, human activities in winter, summer, and autumn seriously affect the air quality in the East China Sea and South China Sea. Especially at the Taipei CWB site, from aerosol parameters and high biomass burning/urban industrial (BB/UI) aerosol, human activity is an important factor for high pollution at the Taipei CWB site. Aerosol types of AA1M, FIGCM, AA2M, and CALIPSO were compared at Anmyon and Yonsei University sites in the Bohai-Yellow Sea in March 2020. The results show that aerosol types based on threshold classification methods generally have higher mixed aerosol results, and the marine (MA) results of AA1M, FIGCM, and AA2M are close to the clean marine aerosol results of CALIPSO. Comparing the results of AA 2 M and CALIPSO on a spatial scale, it is found that the clean marine aerosol proportion identified by CALIPSO (0.38, 0.48, 0.82) is consistent with the MA proportion identified by AA 2 M (0.43, 0.46, 0.97) in the East China Sea, South China Sea, and Western Pacific Ocean.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>38764086</pmid><doi>10.1007/s11356-024-33458-9</doi><tpages>21</tpages><orcidid>https://orcid.org/0000-0002-8161-341X</orcidid></addata></record> |
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subjects | Aerosols Air quality Aquatic Pollution Atmospheric aerosols Atmospheric Protection/Air Quality Control/Air Pollution Autumn biomass Biomass burning CALIPSO (Pathfinder satellite) Classification Earth and Environmental Science East Asia East China Sea Ecotoxicology Environment Environmental Chemistry Environmental Health Environmental quality governmental programs and projects humans Imaging radiometers Infrared imaging Infrared radiometers Lidar Optical analysis Optical thickness Pacific Ocean Parameters pollution Radiometry Remote sensing Research Article Satellite observation satellites Sea of Japan seasonal variation Seasonal variations South China Sea Spatial variations summer Waste Water Technology Water Management Water Pollution Control winter |
title | Application of multiplatform remote sensing data over East Asia Ocean: aerosol characteristics and aerosol types |
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