Hyperfine-resolution mapping of on-road vehicle emissions with comprehensive traffic monitoring and an intelligent transportation system
<p>Urban on-road vehicle emissions affect air quality and human health locally and globally. Given uneven sources, they typically exhibit distinct spatial heterogeneity, varying sharply over short distances (10 m–1 km). However, all-around observational constraints on the emission sources are...
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Copernicus Publications
2021
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oai:doaj.org-article:d2217d005057409b8c3cd97140e7970c2021-11-23T14:37:21ZHyperfine-resolution mapping of on-road vehicle emissions with comprehensive traffic monitoring and an intelligent transportation system10.5194/acp-21-16985-20211680-73161680-7324https://doaj.org/article/d2217d005057409b8c3cd97140e7970c2021-11-01T00:00:00Zhttps://acp.copernicus.org/articles/21/16985/2021/acp-21-16985-2021.pdfhttps://doaj.org/toc/1680-7316https://doaj.org/toc/1680-7324<p>Urban on-road vehicle emissions affect air quality and human health locally and globally. Given uneven sources, they typically exhibit distinct spatial heterogeneity, varying sharply over short distances (10 m–1 km). However, all-around observational constraints on the emission sources are limited in much of the world. Consequently, traditional emission inventories lack the spatial resolution that can characterize the on-road vehicle emission hotspots. Here we establish a bottom-up approach to reveal a unique pattern of urban on-road vehicle emissions at a spatial resolution 1–3 orders of magnitude higher than current emission inventories. We interconnect all-around traffic monitoring (including traffic fluxes, vehicle-specific categories, and speeds) via an intelligent transportation system (ITS) over Xiaoshan District in the Yangtze River Delta (YRD) region. This enables us to calculate single-vehicle-specific emissions over each fine-scale (10 m–1 km) road segment. Thus, the most hyperfine emission dataset of its type is achieved, and on-road emission hotspots appear. The resulting map shows that the hourly average on-road vehicle emissions of CO, <span class="inline-formula">NO<sub><i>x</i></sub></span>, HC, and PM<span class="inline-formula"><sub>2.5</sub></span> are 74.01, 40.35, 8.13, and 1.68 kg, respectively. More importantly, widespread and persistent emission hotspots emerged. They are of significantly sharp small-scale variability, up to 8–15 times within individual hotspots, attributable to distinct traffic fluxes, road conditions, and vehicle categories. On this basis, we investigate the effectiveness of routine traffic control strategies on on-road vehicle emission mitigation. Our results have important implications for how the strategies should be designed and optimized. Integrating our traffic-monitoring-based approach with urban air quality measurements, we could address major data gaps between urban air pollutant emissions and concentrations.</p>L. JiangY. XiaL. WangX. ChenJ. YeT. HouL. WangY. ZhangM. LiZ. LiZ. SongY. JiangW. LiuP. LiD. RosenfeldJ. H. SeinfeldS. YuS. YuCopernicus PublicationsarticlePhysicsQC1-999ChemistryQD1-999ENAtmospheric Chemistry and Physics, Vol 21, Pp 16985-17002 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
Physics QC1-999 Chemistry QD1-999 |
| spellingShingle |
Physics QC1-999 Chemistry QD1-999 L. Jiang Y. Xia L. Wang X. Chen J. Ye T. Hou L. Wang Y. Zhang M. Li Z. Li Z. Song Y. Jiang W. Liu P. Li D. Rosenfeld J. H. Seinfeld S. Yu S. Yu Hyperfine-resolution mapping of on-road vehicle emissions with comprehensive traffic monitoring and an intelligent transportation system |
| description |
<p>Urban on-road vehicle emissions affect air quality and human health locally
and globally. Given uneven sources, they typically exhibit distinct spatial
heterogeneity, varying sharply over short distances (10 m–1 km). However, all-around observational constraints on the emission sources
are limited in much of the world. Consequently, traditional emission
inventories lack the spatial resolution that can characterize the on-road
vehicle emission hotspots. Here we establish a bottom-up approach to reveal
a unique pattern of urban on-road vehicle emissions at a spatial resolution 1–3 orders of magnitude higher than current emission
inventories. We interconnect all-around traffic monitoring (including
traffic fluxes, vehicle-specific categories, and speeds) via an intelligent
transportation system (ITS) over Xiaoshan District in the Yangtze River
Delta (YRD) region. This enables us to calculate single-vehicle-specific
emissions over each fine-scale (10 m–1 km) road segment. Thus,
the most hyperfine emission dataset of its type is achieved, and on-road
emission hotspots appear. The resulting map shows that the hourly average
on-road vehicle emissions of CO, <span class="inline-formula">NO<sub><i>x</i></sub></span>, HC, and PM<span class="inline-formula"><sub>2.5</sub></span> are 74.01,
40.35, 8.13, and 1.68 kg, respectively. More importantly, widespread and
persistent emission hotspots emerged. They are of significantly sharp
small-scale variability, up to 8–15 times within individual
hotspots, attributable to distinct traffic fluxes, road conditions, and
vehicle categories. On this basis, we investigate the effectiveness of
routine traffic control strategies on on-road vehicle emission mitigation.
Our results have important implications for how the strategies should be
designed and optimized. Integrating our traffic-monitoring-based approach
with urban air quality measurements, we could address major data gaps
between urban air pollutant emissions and concentrations.</p> |
| format |
article |
| author |
L. Jiang Y. Xia L. Wang X. Chen J. Ye T. Hou L. Wang Y. Zhang M. Li Z. Li Z. Song Y. Jiang W. Liu P. Li D. Rosenfeld J. H. Seinfeld S. Yu S. Yu |
| author_facet |
L. Jiang Y. Xia L. Wang X. Chen J. Ye T. Hou L. Wang Y. Zhang M. Li Z. Li Z. Song Y. Jiang W. Liu P. Li D. Rosenfeld J. H. Seinfeld S. Yu S. Yu |
| author_sort |
L. Jiang |
| title |
Hyperfine-resolution mapping of on-road vehicle emissions with comprehensive traffic monitoring and an intelligent transportation system |
| title_short |
Hyperfine-resolution mapping of on-road vehicle emissions with comprehensive traffic monitoring and an intelligent transportation system |
| title_full |
Hyperfine-resolution mapping of on-road vehicle emissions with comprehensive traffic monitoring and an intelligent transportation system |
| title_fullStr |
Hyperfine-resolution mapping of on-road vehicle emissions with comprehensive traffic monitoring and an intelligent transportation system |
| title_full_unstemmed |
Hyperfine-resolution mapping of on-road vehicle emissions with comprehensive traffic monitoring and an intelligent transportation system |
| title_sort |
hyperfine-resolution mapping of on-road vehicle emissions with comprehensive traffic monitoring and an intelligent transportation system |
| publisher |
Copernicus Publications |
| publishDate |
2021 |
| url |
https://doaj.org/article/d2217d005057409b8c3cd97140e7970c |
| work_keys_str_mv |
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| _version_ |
1718416730840104960 |