Spatio-temporal changes of AOD in Xinjiang of China from 2000 to 2019: Which factor is more influential, natural factor or human factor?
Aerosol optical depth (AOD), which represents the optical attenuation, poses a major threat to the production activity, air quality, human health and regional sustainable development of arid and semi-arid areas. To some degree, AOD shows areal air pollution level and possesses obvious spatio-tempora...
Gespeichert in:
| Veröffentlicht in: | PloS one 2021-08, Vol.16 (8), p.e0253942-e0253942 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | e0253942 |
|---|---|
| container_issue | 8 |
| container_start_page | e0253942 |
| container_title | PloS one |
| container_volume | 16 |
| creator | Li, Jinglong He, Qing Ge, Xiangyu Abbas, Alim Jin, Lili |
| description | Aerosol optical depth (AOD), which represents the optical attenuation, poses a major threat to the production activity, air quality, human health and regional sustainable development of arid and semi-arid areas. To some degree, AOD shows areal air pollution level and possesses obvious spatio-temporal characteristics. However, long-time sequences and detailed AOD information can not be provided due to currently limited monitoring technology. In this paper, a daily AOD product, MODIS-based Multi-angle Implementation of Atmospheric Correction (MAIAC), is deployed to analyze the spatio-temporal characteristics in Xinjiang Uygur Autonomous Region from 2000 to 2019. In addition, the importance of influencing factors for AOD is calculated through Random Forest (RF) Model and the propagation trajectories of pollutants are simulated through Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) Model. Spatio distribution of AOD presents a tendency that AOD value in northern Xinjiang is low while the value in southern Xinjiang is high. Regions with high AOD values are mainly concentrated in Tarim Basin. AOD in southern Xinjiang is the highest, followed by that in eastern Xinjiang and AOD value in northern Xinjiang is the lowest. Seasonal variation of AOD is significant: Spring (0.309) > summer (0.200) > autumn (0.161) > winter (0.158). Average AOD value in Xinjiang is 0.196. AOD appears wavy from 2000 to 2014 with its low inflection point (0.157) appearing in 2005, and then increases, reaching its peak in 2014 (0.223). The obvious downward tendency after 2014 shows that the use of coal to natural gas (NG) conversion project improves the conditions of local environment. According to RF Model, NG contributes most to AOD. HYSPLIT Model reveals that aerosol in southern Xinjiang is related to the short-distant carriage of dust aerosol from the Taklimakan Desert. Aerosol there can affect Inner Mongolia through long-distant transport. Blocked by the Tianshan Mountains, fine dust particles can not cross the Tianshan Mountains to become a factor contributing to AOD in northern Xinjiang. |
| doi_str_mv | 10.1371/journal.pone.0253942 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_2562820469</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A672601046</galeid><doaj_id>oai_doaj_org_article_ab5b2663947a4bc58fd4967c71936123</doaj_id><sourcerecordid>A672601046</sourcerecordid><originalsourceid>FETCH-LOGICAL-c669t-67f2209f2ae3c23be57d98e311f37da4c0a60d9bd48a0d4ad782527a25fd3d763</originalsourceid><addsrcrecordid>eNqNk2uL1DAUhoso7jr6DwQDgig4Yy5t0u4HZRhvAwsLrrdv4TRNpxnaZGxS0X_gzzbdqbKV_WBbSHvynPc0b3KS5CHBK8IEebF3Q2-hXR2c1StMM1ak9FZySgpGl5xidvva-0lyz_s9xhnLOb-bnLA0JfFip8mvywME45ZBdwfXQ4tUA3anPXI1Wl-8Rsair8buTQyOoU1jLKC6dx2iGGMUXBxJcYa-NEY1qAYVXI-MR53rdUyu20HbYKB9jiyEYSwwMfFphg7s9P3qfnKnhtbrB9O4SD69ffNx8355fvFuu1mfLxXnRVhyUVOKi5qCZoqyUmeiKnLNCKmZqCBVGDiuirJKc8BVCpXIaUYF0KyuWCU4WySPjrqH1nk5meglzTjNKU55EYntkagc7OWhNx30P6UDI68Crt9J6INRrZZQZiXlPFovIC1VltdVWnChRHSeE8qi1sup2lB2ulLRjOjBTHQ-Y00jd-67zJngOMujwNNJoHffBu2D7IxXum3Bajdc_TdLKRk3eZE8_ge9eXUTtYO4gLhDLtZVo6hcc0E5JhGL1OoGKt6V7oyKJ642MT5LeDZLiEzQP8IOBu_l9vLD_7MXn-fsk2tso6ENjXftEM-s9XMwPYKqd973uv5rMsFybJg_bsixYeTUMOw3TTkEGQ</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2562820469</pqid></control><display><type>article</type><title>Spatio-temporal changes of AOD in Xinjiang of China from 2000 to 2019: Which factor is more influential, natural factor or human factor?</title><source>DOAJ Directory of Open Access Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Public Library of Science (PLoS)</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><creator>Li, Jinglong ; He, Qing ; Ge, Xiangyu ; Abbas, Alim ; Jin, Lili</creator><contributor>Lolli, Simone</contributor><creatorcontrib>Li, Jinglong ; He, Qing ; Ge, Xiangyu ; Abbas, Alim ; Jin, Lili ; Lolli, Simone</creatorcontrib><description>Aerosol optical depth (AOD), which represents the optical attenuation, poses a major threat to the production activity, air quality, human health and regional sustainable development of arid and semi-arid areas. To some degree, AOD shows areal air pollution level and possesses obvious spatio-temporal characteristics. However, long-time sequences and detailed AOD information can not be provided due to currently limited monitoring technology. In this paper, a daily AOD product, MODIS-based Multi-angle Implementation of Atmospheric Correction (MAIAC), is deployed to analyze the spatio-temporal characteristics in Xinjiang Uygur Autonomous Region from 2000 to 2019. In addition, the importance of influencing factors for AOD is calculated through Random Forest (RF) Model and the propagation trajectories of pollutants are simulated through Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) Model. Spatio distribution of AOD presents a tendency that AOD value in northern Xinjiang is low while the value in southern Xinjiang is high. Regions with high AOD values are mainly concentrated in Tarim Basin. AOD in southern Xinjiang is the highest, followed by that in eastern Xinjiang and AOD value in northern Xinjiang is the lowest. Seasonal variation of AOD is significant: Spring (0.309) > summer (0.200) > autumn (0.161) > winter (0.158). Average AOD value in Xinjiang is 0.196. AOD appears wavy from 2000 to 2014 with its low inflection point (0.157) appearing in 2005, and then increases, reaching its peak in 2014 (0.223). The obvious downward tendency after 2014 shows that the use of coal to natural gas (NG) conversion project improves the conditions of local environment. According to RF Model, NG contributes most to AOD. HYSPLIT Model reveals that aerosol in southern Xinjiang is related to the short-distant carriage of dust aerosol from the Taklimakan Desert. Aerosol there can affect Inner Mongolia through long-distant transport. Blocked by the Tianshan Mountains, fine dust particles can not cross the Tianshan Mountains to become a factor contributing to AOD in northern Xinjiang.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0253942</identifier><identifier>PMID: 34411113</identifier><language>eng</language><publisher>San Francisco: Public Library of Science</publisher><subject>Aerosol optical depth ; Aerosols ; Air pollution ; Air quality ; Arid regions ; Atmosphere ; Atmospheric aerosols ; Atmospheric correction ; Attenuation ; Autumn ; Biology and Life Sciences ; Climate change ; Dust ; Dust particles ; Earth Sciences ; Ecology and Environmental Sciences ; Engineering and Technology ; Environmental aspects ; Environmental health ; Health aspects ; Laboratories ; Mathematical analysis ; Meteorology ; Modelling ; MODIS ; Mountains ; Natural gas ; Optical analysis ; Optical thickness ; Particles ; Physical Sciences ; Pollutants ; Pollution levels ; Precipitation ; Radiation ; Regional development ; Regional planning ; Regions ; Seasonal variations ; Semi arid areas ; Sustainable development</subject><ispartof>PloS one, 2021-08, Vol.16 (8), p.e0253942-e0253942</ispartof><rights>COPYRIGHT 2021 Public Library of Science</rights><rights>2021 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 Li et al 2021 Li et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c669t-67f2209f2ae3c23be57d98e311f37da4c0a60d9bd48a0d4ad782527a25fd3d763</citedby><cites>FETCH-LOGICAL-c669t-67f2209f2ae3c23be57d98e311f37da4c0a60d9bd48a0d4ad782527a25fd3d763</cites><orcidid>0000-0003-0267-1820</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8376058/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8376058/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,724,777,781,861,882,2096,2915,23847,27905,27906,53772,53774,79349,79350</link.rule.ids></links><search><contributor>Lolli, Simone</contributor><creatorcontrib>Li, Jinglong</creatorcontrib><creatorcontrib>He, Qing</creatorcontrib><creatorcontrib>Ge, Xiangyu</creatorcontrib><creatorcontrib>Abbas, Alim</creatorcontrib><creatorcontrib>Jin, Lili</creatorcontrib><title>Spatio-temporal changes of AOD in Xinjiang of China from 2000 to 2019: Which factor is more influential, natural factor or human factor?</title><title>PloS one</title><description>Aerosol optical depth (AOD), which represents the optical attenuation, poses a major threat to the production activity, air quality, human health and regional sustainable development of arid and semi-arid areas. To some degree, AOD shows areal air pollution level and possesses obvious spatio-temporal characteristics. However, long-time sequences and detailed AOD information can not be provided due to currently limited monitoring technology. In this paper, a daily AOD product, MODIS-based Multi-angle Implementation of Atmospheric Correction (MAIAC), is deployed to analyze the spatio-temporal characteristics in Xinjiang Uygur Autonomous Region from 2000 to 2019. In addition, the importance of influencing factors for AOD is calculated through Random Forest (RF) Model and the propagation trajectories of pollutants are simulated through Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) Model. Spatio distribution of AOD presents a tendency that AOD value in northern Xinjiang is low while the value in southern Xinjiang is high. Regions with high AOD values are mainly concentrated in Tarim Basin. AOD in southern Xinjiang is the highest, followed by that in eastern Xinjiang and AOD value in northern Xinjiang is the lowest. Seasonal variation of AOD is significant: Spring (0.309) > summer (0.200) > autumn (0.161) > winter (0.158). Average AOD value in Xinjiang is 0.196. AOD appears wavy from 2000 to 2014 with its low inflection point (0.157) appearing in 2005, and then increases, reaching its peak in 2014 (0.223). The obvious downward tendency after 2014 shows that the use of coal to natural gas (NG) conversion project improves the conditions of local environment. According to RF Model, NG contributes most to AOD. HYSPLIT Model reveals that aerosol in southern Xinjiang is related to the short-distant carriage of dust aerosol from the Taklimakan Desert. Aerosol there can affect Inner Mongolia through long-distant transport. Blocked by the Tianshan Mountains, fine dust particles can not cross the Tianshan Mountains to become a factor contributing to AOD in northern Xinjiang.</description><subject>Aerosol optical depth</subject><subject>Aerosols</subject><subject>Air pollution</subject><subject>Air quality</subject><subject>Arid regions</subject><subject>Atmosphere</subject><subject>Atmospheric aerosols</subject><subject>Atmospheric correction</subject><subject>Attenuation</subject><subject>Autumn</subject><subject>Biology and Life Sciences</subject><subject>Climate change</subject><subject>Dust</subject><subject>Dust particles</subject><subject>Earth Sciences</subject><subject>Ecology and Environmental Sciences</subject><subject>Engineering and Technology</subject><subject>Environmental aspects</subject><subject>Environmental health</subject><subject>Health aspects</subject><subject>Laboratories</subject><subject>Mathematical analysis</subject><subject>Meteorology</subject><subject>Modelling</subject><subject>MODIS</subject><subject>Mountains</subject><subject>Natural gas</subject><subject>Optical analysis</subject><subject>Optical thickness</subject><subject>Particles</subject><subject>Physical Sciences</subject><subject>Pollutants</subject><subject>Pollution levels</subject><subject>Precipitation</subject><subject>Radiation</subject><subject>Regional development</subject><subject>Regional planning</subject><subject>Regions</subject><subject>Seasonal variations</subject><subject>Semi arid areas</subject><subject>Sustainable development</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNk2uL1DAUhoso7jr6DwQDgig4Yy5t0u4HZRhvAwsLrrdv4TRNpxnaZGxS0X_gzzbdqbKV_WBbSHvynPc0b3KS5CHBK8IEebF3Q2-hXR2c1StMM1ak9FZySgpGl5xidvva-0lyz_s9xhnLOb-bnLA0JfFip8mvywME45ZBdwfXQ4tUA3anPXI1Wl-8Rsair8buTQyOoU1jLKC6dx2iGGMUXBxJcYa-NEY1qAYVXI-MR53rdUyu20HbYKB9jiyEYSwwMfFphg7s9P3qfnKnhtbrB9O4SD69ffNx8355fvFuu1mfLxXnRVhyUVOKi5qCZoqyUmeiKnLNCKmZqCBVGDiuirJKc8BVCpXIaUYF0KyuWCU4WySPjrqH1nk5meglzTjNKU55EYntkagc7OWhNx30P6UDI68Crt9J6INRrZZQZiXlPFovIC1VltdVWnChRHSeE8qi1sup2lB2ulLRjOjBTHQ-Y00jd-67zJngOMujwNNJoHffBu2D7IxXum3Bajdc_TdLKRk3eZE8_ge9eXUTtYO4gLhDLtZVo6hcc0E5JhGL1OoGKt6V7oyKJ642MT5LeDZLiEzQP8IOBu_l9vLD_7MXn-fsk2tso6ENjXftEM-s9XMwPYKqd973uv5rMsFybJg_bsixYeTUMOw3TTkEGQ</recordid><startdate>20210819</startdate><enddate>20210819</enddate><creator>Li, Jinglong</creator><creator>He, Qing</creator><creator>Ge, Xiangyu</creator><creator>Abbas, Alim</creator><creator>Jin, Lili</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-0267-1820</orcidid></search><sort><creationdate>20210819</creationdate><title>Spatio-temporal changes of AOD in Xinjiang of China from 2000 to 2019: Which factor is more influential, natural factor or human factor?</title><author>Li, Jinglong ; He, Qing ; Ge, Xiangyu ; Abbas, Alim ; Jin, Lili</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c669t-67f2209f2ae3c23be57d98e311f37da4c0a60d9bd48a0d4ad782527a25fd3d763</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Aerosol optical depth</topic><topic>Aerosols</topic><topic>Air pollution</topic><topic>Air quality</topic><topic>Arid regions</topic><topic>Atmosphere</topic><topic>Atmospheric aerosols</topic><topic>Atmospheric correction</topic><topic>Attenuation</topic><topic>Autumn</topic><topic>Biology and Life Sciences</topic><topic>Climate change</topic><topic>Dust</topic><topic>Dust particles</topic><topic>Earth Sciences</topic><topic>Ecology and Environmental Sciences</topic><topic>Engineering and Technology</topic><topic>Environmental aspects</topic><topic>Environmental health</topic><topic>Health aspects</topic><topic>Laboratories</topic><topic>Mathematical analysis</topic><topic>Meteorology</topic><topic>Modelling</topic><topic>MODIS</topic><topic>Mountains</topic><topic>Natural gas</topic><topic>Optical analysis</topic><topic>Optical thickness</topic><topic>Particles</topic><topic>Physical Sciences</topic><topic>Pollutants</topic><topic>Pollution levels</topic><topic>Precipitation</topic><topic>Radiation</topic><topic>Regional development</topic><topic>Regional planning</topic><topic>Regions</topic><topic>Seasonal variations</topic><topic>Semi arid areas</topic><topic>Sustainable development</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Jinglong</creatorcontrib><creatorcontrib>He, Qing</creatorcontrib><creatorcontrib>Ge, Xiangyu</creatorcontrib><creatorcontrib>Abbas, Alim</creatorcontrib><creatorcontrib>Jin, Lili</creatorcontrib><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>ProQuest Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Jinglong</au><au>He, Qing</au><au>Ge, Xiangyu</au><au>Abbas, Alim</au><au>Jin, Lili</au><au>Lolli, Simone</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatio-temporal changes of AOD in Xinjiang of China from 2000 to 2019: Which factor is more influential, natural factor or human factor?</atitle><jtitle>PloS one</jtitle><date>2021-08-19</date><risdate>2021</risdate><volume>16</volume><issue>8</issue><spage>e0253942</spage><epage>e0253942</epage><pages>e0253942-e0253942</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Aerosol optical depth (AOD), which represents the optical attenuation, poses a major threat to the production activity, air quality, human health and regional sustainable development of arid and semi-arid areas. To some degree, AOD shows areal air pollution level and possesses obvious spatio-temporal characteristics. However, long-time sequences and detailed AOD information can not be provided due to currently limited monitoring technology. In this paper, a daily AOD product, MODIS-based Multi-angle Implementation of Atmospheric Correction (MAIAC), is deployed to analyze the spatio-temporal characteristics in Xinjiang Uygur Autonomous Region from 2000 to 2019. In addition, the importance of influencing factors for AOD is calculated through Random Forest (RF) Model and the propagation trajectories of pollutants are simulated through Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) Model. Spatio distribution of AOD presents a tendency that AOD value in northern Xinjiang is low while the value in southern Xinjiang is high. Regions with high AOD values are mainly concentrated in Tarim Basin. AOD in southern Xinjiang is the highest, followed by that in eastern Xinjiang and AOD value in northern Xinjiang is the lowest. Seasonal variation of AOD is significant: Spring (0.309) > summer (0.200) > autumn (0.161) > winter (0.158). Average AOD value in Xinjiang is 0.196. AOD appears wavy from 2000 to 2014 with its low inflection point (0.157) appearing in 2005, and then increases, reaching its peak in 2014 (0.223). The obvious downward tendency after 2014 shows that the use of coal to natural gas (NG) conversion project improves the conditions of local environment. According to RF Model, NG contributes most to AOD. HYSPLIT Model reveals that aerosol in southern Xinjiang is related to the short-distant carriage of dust aerosol from the Taklimakan Desert. Aerosol there can affect Inner Mongolia through long-distant transport. Blocked by the Tianshan Mountains, fine dust particles can not cross the Tianshan Mountains to become a factor contributing to AOD in northern Xinjiang.</abstract><cop>San Francisco</cop><pub>Public Library of Science</pub><pmid>34411113</pmid><doi>10.1371/journal.pone.0253942</doi><tpages>e0253942</tpages><orcidid>https://orcid.org/0000-0003-0267-1820</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2021-08, Vol.16 (8), p.e0253942-e0253942 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_2562820469 |
| source | DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Public Library of Science (PLoS); PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Aerosol optical depth Aerosols Air pollution Air quality Arid regions Atmosphere Atmospheric aerosols Atmospheric correction Attenuation Autumn Biology and Life Sciences Climate change Dust Dust particles Earth Sciences Ecology and Environmental Sciences Engineering and Technology Environmental aspects Environmental health Health aspects Laboratories Mathematical analysis Meteorology Modelling MODIS Mountains Natural gas Optical analysis Optical thickness Particles Physical Sciences Pollutants Pollution levels Precipitation Radiation Regional development Regional planning Regions Seasonal variations Semi arid areas Sustainable development |
| title | Spatio-temporal changes of AOD in Xinjiang of China from 2000 to 2019: Which factor is more influential, natural factor or human factor? |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-21T02%3A28%3A13IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Spatio-temporal%20changes%20of%20AOD%20in%20Xinjiang%20of%20China%20from%202000%20to%202019:%20Which%20factor%20is%20more%20influential,%20natural%20factor%20or%20human%20factor?&rft.jtitle=PloS%20one&rft.au=Li,%20Jinglong&rft.date=2021-08-19&rft.volume=16&rft.issue=8&rft.spage=e0253942&rft.epage=e0253942&rft.pages=e0253942-e0253942&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0253942&rft_dat=%3Cgale_plos_%3EA672601046%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2562820469&rft_id=info:pmid/34411113&rft_galeid=A672601046&rft_doaj_id=oai_doaj_org_article_ab5b2663947a4bc58fd4967c71936123&rfr_iscdi=true |