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Chemical Composition and Source of PM2.5 during Winter Heating Period in Guanzhong Basin
An intensive field campaign was carried out from December 2022 to March 2023 at six different sites across five major cities (Xi’an, Baoji, Xianyang, Weinan, and Hancheng) in the Guanzhong Basin, China, covering most of the heating period there, which is characterized by high PM2.5 pollution levels....
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Published in: | Atmosphere 2023-11, Vol.14 (11), p.1640 |
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description | An intensive field campaign was carried out from December 2022 to March 2023 at six different sites across five major cities (Xi’an, Baoji, Xianyang, Weinan, and Hancheng) in the Guanzhong Basin, China, covering most of the heating period there, which is characterized by high PM2.5 pollution levels. During the campaign, the mean PM2.5 concentrations at these sites exceeded the 24 h PM2.5 standard (75 μg m−3), except the site at Hancheng, with mean PM2.5 concentrations of 57.8 ± 32.3 μg m−3. The source apportionment of PM2.5 varied significantly across sites, with vehicle exhaust being the dominant source at urban sites located in Xi’an and Baoji, coal combustion at suburban sites in Hancheng, and comparable contribution from coal combustion and industrial emissions at suburban sites in Xianyang and Weinan. Compared with clean condition, the contribution of vehicle exhaust and secondary inorganic sources (SIs) were largely enhanced during heavy PM2.5 pollution periods, while the contribution from biomass burning (BB) and dust decreased significantly at all sites. Combined with an analysis of meteorological parameters, the study further found that higher contributions of SIs and heavy PM2.5 pollution were generally associated with higher relative humidity (RH). In addition, higher PM2.5 concentrations at suburban sites were related to lower wind speeds, which could be explained by the stagnant condition favoring the accumulation of local emissions as well as the formation of secondary pollutants. In contrast, at urban sites (e.g., Xianyang), higher PM2.5 concentrations were more associated with the strong influence of vehicle exhaust at slightly higher wind speeds. |
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During the campaign, the mean PM2.5 concentrations at these sites exceeded the 24 h PM2.5 standard (75 μg m−3), except the site at Hancheng, with mean PM2.5 concentrations of 57.8 ± 32.3 μg m−3. The source apportionment of PM2.5 varied significantly across sites, with vehicle exhaust being the dominant source at urban sites located in Xi’an and Baoji, coal combustion at suburban sites in Hancheng, and comparable contribution from coal combustion and industrial emissions at suburban sites in Xianyang and Weinan. Compared with clean condition, the contribution of vehicle exhaust and secondary inorganic sources (SIs) were largely enhanced during heavy PM2.5 pollution periods, while the contribution from biomass burning (BB) and dust decreased significantly at all sites. Combined with an analysis of meteorological parameters, the study further found that higher contributions of SIs and heavy PM2.5 pollution were generally associated with higher relative humidity (RH). In addition, higher PM2.5 concentrations at suburban sites were related to lower wind speeds, which could be explained by the stagnant condition favoring the accumulation of local emissions as well as the formation of secondary pollutants. In contrast, at urban sites (e.g., Xianyang), higher PM2.5 concentrations were more associated with the strong influence of vehicle exhaust at slightly higher wind speeds.</description><identifier>ISSN: 2073-4433</identifier><identifier>EISSN: 2073-4433</identifier><identifier>DOI: 10.3390/atmos14111640</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Aerosols ; Air pollution ; Atmospheric particulates ; Biomass burning ; Carbon ; Chemical composition ; Chemical industry ; Cities ; Coal ; Coal combustion ; Combustion ; Dust ; emission sources ; Emissions ; Guanzhong Basin ; Heating ; Industrial emissions ; Industrial plant emissions ; Meteorological parameters ; Outdoor air quality ; Particulate matter ; Particulate matter sources ; PM2.5 ; Pollutants ; Pollution levels ; Power plants ; Relative humidity ; River basins ; Seasons ; Urban areas ; Vehicle emissions ; Vehicles ; VOCs ; Volatile organic compounds ; Wind ; Wind speed ; Winter</subject><ispartof>Atmosphere, 2023-11, Vol.14 (11), p.1640</ispartof><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). 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During the campaign, the mean PM2.5 concentrations at these sites exceeded the 24 h PM2.5 standard (75 μg m−3), except the site at Hancheng, with mean PM2.5 concentrations of 57.8 ± 32.3 μg m−3. The source apportionment of PM2.5 varied significantly across sites, with vehicle exhaust being the dominant source at urban sites located in Xi’an and Baoji, coal combustion at suburban sites in Hancheng, and comparable contribution from coal combustion and industrial emissions at suburban sites in Xianyang and Weinan. Compared with clean condition, the contribution of vehicle exhaust and secondary inorganic sources (SIs) were largely enhanced during heavy PM2.5 pollution periods, while the contribution from biomass burning (BB) and dust decreased significantly at all sites. Combined with an analysis of meteorological parameters, the study further found that higher contributions of SIs and heavy PM2.5 pollution were generally associated with higher relative humidity (RH). In addition, higher PM2.5 concentrations at suburban sites were related to lower wind speeds, which could be explained by the stagnant condition favoring the accumulation of local emissions as well as the formation of secondary pollutants. In contrast, at urban sites (e.g., Xianyang), higher PM2.5 concentrations were more associated with the strong influence of vehicle exhaust at slightly higher wind speeds.</description><subject>Aerosols</subject><subject>Air pollution</subject><subject>Atmospheric particulates</subject><subject>Biomass burning</subject><subject>Carbon</subject><subject>Chemical composition</subject><subject>Chemical industry</subject><subject>Cities</subject><subject>Coal</subject><subject>Coal combustion</subject><subject>Combustion</subject><subject>Dust</subject><subject>emission sources</subject><subject>Emissions</subject><subject>Guanzhong Basin</subject><subject>Heating</subject><subject>Industrial emissions</subject><subject>Industrial plant emissions</subject><subject>Meteorological parameters</subject><subject>Outdoor air quality</subject><subject>Particulate matter</subject><subject>Particulate matter sources</subject><subject>PM2.5</subject><subject>Pollutants</subject><subject>Pollution levels</subject><subject>Power plants</subject><subject>Relative humidity</subject><subject>River basins</subject><subject>Seasons</subject><subject>Urban areas</subject><subject>Vehicle emissions</subject><subject>Vehicles</subject><subject>VOCs</subject><subject>Volatile organic compounds</subject><subject>Wind</subject><subject>Wind speed</subject><subject>Winter</subject><issn>2073-4433</issn><issn>2073-4433</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpVUU1PwzAMrRBITGNH7pE4d6T5aJsjVLBNGmISILhFTppsmdZmJO0Bfj0dQwh8sf389Gz5JcllhqeUCnwNXeNjxrIsyxk-SUYEFzRljNLTP_V5Molxi4dgghLKRslbtTGN07BDlW_2PrrO-RZBW6Mn3wdtkLdo9UCmHNV9cO0avbq2MwHNDXSHdmWC8zVyLZr10H5u_IDdQnTtRXJmYRfN5CePk5f7u-dqni4fZ4vqZplqWuAu5coIU1qmlOLMAM-txdyCZQXXOqNU5UrbGg9zLQoKdUGsVoZrrBhmWDA6ThZH3drDVu6DayB8SA9OfgM-rCWEzumdkTTnpc1JqfOCMCAl1HnGaFETEDYXVg1aV0etffDvvYmd3A5PaIfzJSkFEbwkrBxY6ZGlg48xGPu7NcPy4IX85wX9AlHBfE8</recordid><startdate>20231101</startdate><enddate>20231101</enddate><creator>Cao, Lei</creator><creator>Tao, Yanan</creator><creator>Zheng, Hao</creator><creator>Wang, Mei</creator><creator>Li, Shiying</creator><creator>Xu, Yongjiang</creator><creator>Li, Mei</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7ST</scope><scope>7TG</scope><scope>7TN</scope><scope>7UA</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>L.G</scope><scope>PCBAR</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>SOI</scope><scope>DOA</scope></search><sort><creationdate>20231101</creationdate><title>Chemical Composition and Source of PM2.5 during Winter Heating Period in Guanzhong Basin</title><author>Cao, Lei ; Tao, Yanan ; Zheng, Hao ; Wang, Mei ; Li, Shiying ; Xu, Yongjiang ; Li, Mei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c370t-5be9e8f4bbb54ea56ff05faf475cc133b6bcfd04bbc973ad72fcbe5c0b4040943</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Aerosols</topic><topic>Air pollution</topic><topic>Atmospheric particulates</topic><topic>Biomass burning</topic><topic>Carbon</topic><topic>Chemical composition</topic><topic>Chemical industry</topic><topic>Cities</topic><topic>Coal</topic><topic>Coal combustion</topic><topic>Combustion</topic><topic>Dust</topic><topic>emission sources</topic><topic>Emissions</topic><topic>Guanzhong Basin</topic><topic>Heating</topic><topic>Industrial emissions</topic><topic>Industrial plant emissions</topic><topic>Meteorological parameters</topic><topic>Outdoor air quality</topic><topic>Particulate matter</topic><topic>Particulate matter sources</topic><topic>PM2.5</topic><topic>Pollutants</topic><topic>Pollution levels</topic><topic>Power plants</topic><topic>Relative humidity</topic><topic>River basins</topic><topic>Seasons</topic><topic>Urban areas</topic><topic>Vehicle emissions</topic><topic>Vehicles</topic><topic>VOCs</topic><topic>Volatile organic compounds</topic><topic>Wind</topic><topic>Wind speed</topic><topic>Winter</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cao, Lei</creatorcontrib><creatorcontrib>Tao, Yanan</creatorcontrib><creatorcontrib>Zheng, Hao</creatorcontrib><creatorcontrib>Wang, Mei</creatorcontrib><creatorcontrib>Li, Shiying</creatorcontrib><creatorcontrib>Xu, Yongjiang</creatorcontrib><creatorcontrib>Li, Mei</creatorcontrib><collection>CrossRef</collection><collection>Aqualine</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Earth, Atmospheric & Aquatic Science Database</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>Environment Abstracts</collection><collection>Open Access: DOAJ - Directory of Open Access Journals</collection><jtitle>Atmosphere</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cao, Lei</au><au>Tao, Yanan</au><au>Zheng, Hao</au><au>Wang, Mei</au><au>Li, Shiying</au><au>Xu, Yongjiang</au><au>Li, Mei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Chemical Composition and Source of PM2.5 during Winter Heating Period in Guanzhong Basin</atitle><jtitle>Atmosphere</jtitle><date>2023-11-01</date><risdate>2023</risdate><volume>14</volume><issue>11</issue><spage>1640</spage><pages>1640-</pages><issn>2073-4433</issn><eissn>2073-4433</eissn><abstract>An intensive field campaign was carried out from December 2022 to March 2023 at six different sites across five major cities (Xi’an, Baoji, Xianyang, Weinan, and Hancheng) in the Guanzhong Basin, China, covering most of the heating period there, which is characterized by high PM2.5 pollution levels. During the campaign, the mean PM2.5 concentrations at these sites exceeded the 24 h PM2.5 standard (75 μg m−3), except the site at Hancheng, with mean PM2.5 concentrations of 57.8 ± 32.3 μg m−3. The source apportionment of PM2.5 varied significantly across sites, with vehicle exhaust being the dominant source at urban sites located in Xi’an and Baoji, coal combustion at suburban sites in Hancheng, and comparable contribution from coal combustion and industrial emissions at suburban sites in Xianyang and Weinan. Compared with clean condition, the contribution of vehicle exhaust and secondary inorganic sources (SIs) were largely enhanced during heavy PM2.5 pollution periods, while the contribution from biomass burning (BB) and dust decreased significantly at all sites. Combined with an analysis of meteorological parameters, the study further found that higher contributions of SIs and heavy PM2.5 pollution were generally associated with higher relative humidity (RH). In addition, higher PM2.5 concentrations at suburban sites were related to lower wind speeds, which could be explained by the stagnant condition favoring the accumulation of local emissions as well as the formation of secondary pollutants. In contrast, at urban sites (e.g., Xianyang), higher PM2.5 concentrations were more associated with the strong influence of vehicle exhaust at slightly higher wind speeds.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/atmos14111640</doi><oa>free_for_read</oa></addata></record> |
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subjects | Aerosols Air pollution Atmospheric particulates Biomass burning Carbon Chemical composition Chemical industry Cities Coal Coal combustion Combustion Dust emission sources Emissions Guanzhong Basin Heating Industrial emissions Industrial plant emissions Meteorological parameters Outdoor air quality Particulate matter Particulate matter sources PM2.5 Pollutants Pollution levels Power plants Relative humidity River basins Seasons Urban areas Vehicle emissions Vehicles VOCs Volatile organic compounds Wind Wind speed Winter |
title | Chemical Composition and Source of PM2.5 during Winter Heating Period in Guanzhong Basin |
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