High-resolution mapping of vehicle emissions of atmospheric pollutants based on large-scale, real-world traffic datasets
<p>On-road vehicle emissions are a major contributor to elevated air pollution levels in populous metropolitan areas. We developed a link-level emissions inventory of vehicular pollutants, called EMBEV-Link (Link-level Emission factor Model for the BEijing Vehicle fleet), based on multiple dat...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2019-07-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://www.atmos-chem-phys.net/19/8831/2019/acp-19-8831-2019.pdf |
| _version_ | 1818582263131013120 |
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| author | D. Yang D. Yang S. Zhang S. Zhang S. Zhang T. Niu T. Niu Y. Wang H. Xu K. M. Zhang Y. Wu Y. Wu |
| author_facet | D. Yang D. Yang S. Zhang S. Zhang S. Zhang T. Niu T. Niu Y. Wang H. Xu K. M. Zhang Y. Wu Y. Wu |
| author_sort | D. Yang |
| collection | DOAJ |
| description | <p>On-road vehicle emissions are a major contributor to
elevated air pollution levels in populous metropolitan areas. We developed a
link-level emissions inventory of vehicular pollutants, called EMBEV-Link (Link-level Emission factor Model for the BEijing Vehicle fleet),
based on multiple datasets extracted from the extensive road traffic
monitoring network that covers the entire municipality of Beijing, China
(16 400 km<span class="inline-formula"><sup>2</sup></span>). We employed the EMBEV-Link model under various traffic
scenarios to capture the significant variability in vehicle emissions,
temporally and spatially, due to the real-world traffic dynamics and the
traffic restrictions implemented by the local government. The results
revealed high carbon monoxide (CO) and total hydrocarbon (THC) emissions in
the urban area (i.e., within the Fifth Ring Road) and during rush hours,
both associated with the passenger vehicle traffic. By contrast,
considerable fractions of nitrogen oxides (<span class="inline-formula">NO<sub><i>x</i></sub></span>), fine particulate
matter (PM<span class="inline-formula"><sub>2.5</sub></span>) and black carbon (BC) emissions were present beyond the
urban area, as heavy-duty trucks (HDTs) were not allowed to drive through
the urban area during daytime. The EMBEV-Link model indicates that nonlocal
HDTs could account for 29 % and 38 % of estimated total on-road emissions of
<span class="inline-formula">NO<sub><i>x</i></sub></span> and PM<span class="inline-formula"><sub>2.5</sub></span>, which were ignored in previous conventional
emission inventories. We further combined the EMBEV-Link emission inventory
and a computationally efficient dispersion model, RapidAir<sup>®</sup>,
to simulate vehicular <span class="inline-formula">NO<sub><i>x</i></sub></span> concentrations at fine resolutions (10 m <span class="inline-formula">×</span> 10 m in the entire municipality and 1 m <span class="inline-formula">×</span> 1 m in the
hotspots). The simulated results indicated a close agreement with ground
observations and captured sharp concentration gradients from line sources to
ambient areas. During the nighttime when the HDT traffic restrictions are
lifted, HDTs could be responsible for approximately 10 <span class="inline-formula">µ</span>g m<span class="inline-formula"><sup>−3</sup></span> of
<span class="inline-formula">NO<sub><i>x</i></sub></span> in the urban area. The uncertainties of conventional top-down
allocation methods, which were widely used to enhance the spatial resolution
of vehicle emissions, are also discussed by comparison with the EMBEV-Link
emission inventory.</p> |
| first_indexed | 2024-12-16T07:46:36Z |
| format | Article |
| id | doaj.art-b2066c4ae4364107bae3fba1fbe7387d |
| institution | Directory Open Access Journal |
| issn | 1680-7316 1680-7324 |
| language | English |
| last_indexed | 2024-12-16T07:46:36Z |
| publishDate | 2019-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Chemistry and Physics |
| spelling | doaj.art-b2066c4ae4364107bae3fba1fbe7387d2022-12-21T22:38:57ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242019-07-01198831884310.5194/acp-19-8831-2019High-resolution mapping of vehicle emissions of atmospheric pollutants based on large-scale, real-world traffic datasetsD. Yang0D. Yang1S. Zhang2S. Zhang3S. Zhang4T. Niu5T. Niu6Y. Wang7H. Xu8K. M. Zhang9Y. Wu10Y. Wu11School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, PR ChinaThese authors contributed equally to this work.School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, PR ChinaSibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY 14853, USAThese authors contributed equally to this work.School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, PR ChinaRicardo Energy & Environment, Beijing 100028, PR ChinaSchool of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, PR ChinaTransport Planning and Research Institute, Ministry of Transport, Beijing 100028, PR ChinaSibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY 14853, USASchool of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, PR ChinaState Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, PR China<p>On-road vehicle emissions are a major contributor to elevated air pollution levels in populous metropolitan areas. We developed a link-level emissions inventory of vehicular pollutants, called EMBEV-Link (Link-level Emission factor Model for the BEijing Vehicle fleet), based on multiple datasets extracted from the extensive road traffic monitoring network that covers the entire municipality of Beijing, China (16 400 km<span class="inline-formula"><sup>2</sup></span>). We employed the EMBEV-Link model under various traffic scenarios to capture the significant variability in vehicle emissions, temporally and spatially, due to the real-world traffic dynamics and the traffic restrictions implemented by the local government. The results revealed high carbon monoxide (CO) and total hydrocarbon (THC) emissions in the urban area (i.e., within the Fifth Ring Road) and during rush hours, both associated with the passenger vehicle traffic. By contrast, considerable fractions of nitrogen oxides (<span class="inline-formula">NO<sub><i>x</i></sub></span>), fine particulate matter (PM<span class="inline-formula"><sub>2.5</sub></span>) and black carbon (BC) emissions were present beyond the urban area, as heavy-duty trucks (HDTs) were not allowed to drive through the urban area during daytime. The EMBEV-Link model indicates that nonlocal HDTs could account for 29 % and 38 % of estimated total on-road emissions of <span class="inline-formula">NO<sub><i>x</i></sub></span> and PM<span class="inline-formula"><sub>2.5</sub></span>, which were ignored in previous conventional emission inventories. We further combined the EMBEV-Link emission inventory and a computationally efficient dispersion model, RapidAir<sup>®</sup>, to simulate vehicular <span class="inline-formula">NO<sub><i>x</i></sub></span> concentrations at fine resolutions (10 m <span class="inline-formula">×</span> 10 m in the entire municipality and 1 m <span class="inline-formula">×</span> 1 m in the hotspots). The simulated results indicated a close agreement with ground observations and captured sharp concentration gradients from line sources to ambient areas. During the nighttime when the HDT traffic restrictions are lifted, HDTs could be responsible for approximately 10 <span class="inline-formula">µ</span>g m<span class="inline-formula"><sup>−3</sup></span> of <span class="inline-formula">NO<sub><i>x</i></sub></span> in the urban area. The uncertainties of conventional top-down allocation methods, which were widely used to enhance the spatial resolution of vehicle emissions, are also discussed by comparison with the EMBEV-Link emission inventory.</p>https://www.atmos-chem-phys.net/19/8831/2019/acp-19-8831-2019.pdf |
| spellingShingle | D. Yang D. Yang S. Zhang S. Zhang S. Zhang T. Niu T. Niu Y. Wang H. Xu K. M. Zhang Y. Wu Y. Wu High-resolution mapping of vehicle emissions of atmospheric pollutants based on large-scale, real-world traffic datasets Atmospheric Chemistry and Physics |
| title | High-resolution mapping of vehicle emissions of atmospheric pollutants based on large-scale, real-world traffic datasets |
| title_full | High-resolution mapping of vehicle emissions of atmospheric pollutants based on large-scale, real-world traffic datasets |
| title_fullStr | High-resolution mapping of vehicle emissions of atmospheric pollutants based on large-scale, real-world traffic datasets |
| title_full_unstemmed | High-resolution mapping of vehicle emissions of atmospheric pollutants based on large-scale, real-world traffic datasets |
| title_short | High-resolution mapping of vehicle emissions of atmospheric pollutants based on large-scale, real-world traffic datasets |
| title_sort | high resolution mapping of vehicle emissions of atmospheric pollutants based on large scale real world traffic datasets |
| url | https://www.atmos-chem-phys.net/19/8831/2019/acp-19-8831-2019.pdf |
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