Multi-dimensional Sources Apportionment of PM2.5 in Zhongyuan Urban Agglomeration Based on the CAMx Mode
Abstract Based on the comprehensive air quality model with extensions (CAMx), the quantitative simulation was conducted on the transport impact of PM2.5 between Zhongyuan Urban Agglomeration and surrounding cities in 2017, and the contribution of 5 major emission sectors to urban PM2.5 concentration...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Springer
2022-04-01
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| Series: | Aerosol and Air Quality Research |
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| Online Access: | https://doi.org/10.4209/aaqr.210254 |
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| _version_ | 1825197541707218944 |
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| author | Jinyu He Wenbo Xue Li Yan Xurong Shi Yanchao Wang Yu Lei Yixuan Zheng Yu Zhang |
| author_facet | Jinyu He Wenbo Xue Li Yan Xurong Shi Yanchao Wang Yu Lei Yixuan Zheng Yu Zhang |
| author_sort | Jinyu He |
| collection | DOAJ |
| description | Abstract Based on the comprehensive air quality model with extensions (CAMx), the quantitative simulation was conducted on the transport impact of PM2.5 between Zhongyuan Urban Agglomeration and surrounding cities in 2017, and the contribution of 5 major emission sectors to urban PM2.5 concentrations, namely the sector of power, industry, household, transportation and agriculture. A two-dimensional cross matrix was established for 18 cities and major emission sectors in Zhongyuan Urban Agglomeration (hereafter referred as the Urban Agglomeration). The results showed that: On an annual average scale, among the transport contribution to the 18 cities of the Urban Agglomeration, 37.8%–57.8% was from local sources, 6.2%–26.3% from the transport within the Urban Agglomeration, and 5.9%–17.4% from other cities nearby; In terms of sectors contribution, industrial sources contributed the most to the annual average concentration of PM2.5 (12.7%–33.0%) in the Urban Agglomeration, followed by household, transportation and agriculture sources. Household source emissions contributed the most in winter. PM2.5 concentrations in Shangqiu, Puyang and Zhoukou affected by household sources emissions exceeding 30% in winter. |
| format | Article |
| id | doaj-art-d99be20c4cd44e0eb11c50a6b7fe7741 |
| institution | Kabale University |
| issn | 1680-8584 2071-1409 |
| language | English |
| publishDate | 2022-04-01 |
| publisher | Springer |
| record_format | Article |
| series | Aerosol and Air Quality Research |
| spelling | doaj-art-d99be20c4cd44e0eb11c50a6b7fe77412025-02-09T12:17:55ZengSpringerAerosol and Air Quality Research1680-85842071-14092022-04-0122511410.4209/aaqr.210254Multi-dimensional Sources Apportionment of PM2.5 in Zhongyuan Urban Agglomeration Based on the CAMx ModeJinyu He0Wenbo Xue1Li Yan2Xurong Shi3Yanchao Wang4Yu Lei5Yixuan Zheng6Yu Zhang7Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental PlanningCenter of Air Quality Simulation and System Analysis, Chinese Academy of Environmental PlanningCenter for Beijing-Tianjin-Hebei Regional Ecology and Environment, Chinese Academy of Environmental PlanningCenter of Air Quality Simulation and System Analysis, Chinese Academy of Environmental PlanningCenter of Air Quality Simulation and System Analysis, Chinese Academy of Environmental PlanningCenter of Air Quality Simulation and System Analysis, Chinese Academy of Environmental PlanningCenter of Air Quality Simulation and System Analysis, Chinese Academy of Environmental PlanningCollege of Chemistry, Zhengzhou UniversityAbstract Based on the comprehensive air quality model with extensions (CAMx), the quantitative simulation was conducted on the transport impact of PM2.5 between Zhongyuan Urban Agglomeration and surrounding cities in 2017, and the contribution of 5 major emission sectors to urban PM2.5 concentrations, namely the sector of power, industry, household, transportation and agriculture. A two-dimensional cross matrix was established for 18 cities and major emission sectors in Zhongyuan Urban Agglomeration (hereafter referred as the Urban Agglomeration). The results showed that: On an annual average scale, among the transport contribution to the 18 cities of the Urban Agglomeration, 37.8%–57.8% was from local sources, 6.2%–26.3% from the transport within the Urban Agglomeration, and 5.9%–17.4% from other cities nearby; In terms of sectors contribution, industrial sources contributed the most to the annual average concentration of PM2.5 (12.7%–33.0%) in the Urban Agglomeration, followed by household, transportation and agriculture sources. Household source emissions contributed the most in winter. PM2.5 concentrations in Shangqiu, Puyang and Zhoukou affected by household sources emissions exceeding 30% in winter.https://doi.org/10.4209/aaqr.210254PM2.5CAMxZhongyuan Urban AgglomerationRegion-industry cross matrix |
| spellingShingle | Jinyu He Wenbo Xue Li Yan Xurong Shi Yanchao Wang Yu Lei Yixuan Zheng Yu Zhang Multi-dimensional Sources Apportionment of PM2.5 in Zhongyuan Urban Agglomeration Based on the CAMx Mode Aerosol and Air Quality Research PM2.5 CAMx Zhongyuan Urban Agglomeration Region-industry cross matrix |
| title | Multi-dimensional Sources Apportionment of PM2.5 in Zhongyuan Urban Agglomeration Based on the CAMx Mode |
| title_full | Multi-dimensional Sources Apportionment of PM2.5 in Zhongyuan Urban Agglomeration Based on the CAMx Mode |
| title_fullStr | Multi-dimensional Sources Apportionment of PM2.5 in Zhongyuan Urban Agglomeration Based on the CAMx Mode |
| title_full_unstemmed | Multi-dimensional Sources Apportionment of PM2.5 in Zhongyuan Urban Agglomeration Based on the CAMx Mode |
| title_short | Multi-dimensional Sources Apportionment of PM2.5 in Zhongyuan Urban Agglomeration Based on the CAMx Mode |
| title_sort | multi dimensional sources apportionment of pm2 5 in zhongyuan urban agglomeration based on the camx mode |
| topic | PM2.5 CAMx Zhongyuan Urban Agglomeration Region-industry cross matrix |
| url | https://doi.org/10.4209/aaqr.210254 |
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