Articles | Volume 21, issue 22
https://doi.org/10.5194/acp-21-16985-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-16985-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Nov 2021
Research article |
| 23 Nov 2021
| 23 Nov 2021
Hyperfine-resolution mapping of on-road vehicle emissions with comprehensive traffic monitoring and an intelligent transportation system
Linhui Jiang
Research Center for Air Pollution and Health, Key Laboratory of Environmental Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, PR China
Yan Xia
Research Center for Air Pollution and Health, Key Laboratory of Environmental Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, PR China
Lu Wang
Research Center for Air Pollution and Health, Key Laboratory of Environmental Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, PR China
Xue Chen
Research Center for Air Pollution and Health, Key Laboratory of Environmental Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, PR China
Jianjie Ye
ByteDance Inc., Hangzhou, Zhejiang 310058, PR China
Tangyan Hou
Research Center for Air Pollution and Health, Key Laboratory of Environmental Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, PR China
Liqiang Wang
Research Center for Air Pollution and Health, Key Laboratory of Environmental Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, PR China
Yibo Zhang
Research Center for Air Pollution and Health, Key Laboratory of Environmental Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, PR China
Mengying Li
Research Center for Air Pollution and Health, Key Laboratory of Environmental Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, PR China
Zhen Li
Research Center for Air Pollution and Health, Key Laboratory of Environmental Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, PR China
Zhe Song
Research Center for Air Pollution and Health, Key Laboratory of Environmental Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, PR China
Yaping Jiang
Research Center for Air Pollution and Health, Key Laboratory of Environmental Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, PR China
Weiping Liu
Research Center for Air Pollution and Health, Key Laboratory of Environmental Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, PR China
Pengfei Li
CORRESPONDING AUTHOR
College of Science and Technology, Hebei Agricultural University, Baoding, Hebei 071000, PR China
Daniel Rosenfeld
Institute of Earth Sciences, Hebrew University of Jerusalem, Jerusalem, Israel
John H. Seinfeld
Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
Research Center for Air Pollution and Health, Key Laboratory of Environmental Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, PR China
Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
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Cited
10 citations as recorded by crossref.
- Quantifying on-road vehicle emissions during traffic congestion using updated emission factors of light-duty gasoline vehicles and real-world traffic monitoring big data X. Chen et al. 10.1016/j.scitotenv.2022.157581
- Spatially resolved hourly traffic emission over megacity Delhi using advanced traffic flow data A. Biswal et al. 10.5194/essd-15-661-2023
- Comparison of PM spatiotemporal variations and exposure at adjacent signalized intersection and roundabout W. Li et al. 10.1016/j.uclim.2023.101590
- Operational Data-Driven Intelligent Modelling and Visualization System for Real-World, On-Road Vehicle Emissions—A Case Study in Hangzhou City, China L. Wang et al. 10.3390/su14095434
- Development of Artificial Intelligent-Based Methodology to Prepare Input for Estimating Vehicle Emissions E. Yavuz et al. 10.3390/app142311175
- Predicting high-resolution air quality using machine learning: Integration of large eddy simulation and urban morphology data S. Wang et al. 10.1016/j.envpol.2024.123371
- Characterization of ammonia emissions from light-duty gasoline vehicles based on real-world driving and dynamometer measurements L. Wu et al. 10.1016/j.scitotenv.2024.172644
- Uncovering the CO2 emissions of vehicles: A well-to-wheel approach Z. Zhang et al. 10.1016/j.fmre.2023.06.009
- Transportation emissions monitoring and policy research: Integrating machine learning and satellite imaging H. Fu et al. 10.1016/j.trd.2024.104421
- Data fusion for enhancing urban air quality modeling using large-scale citizen science data A. O'Regan et al. 10.1016/j.scs.2024.105896
10 citations as recorded by crossref.
- Quantifying on-road vehicle emissions during traffic congestion using updated emission factors of light-duty gasoline vehicles and real-world traffic monitoring big data X. Chen et al. 10.1016/j.scitotenv.2022.157581
- Spatially resolved hourly traffic emission over megacity Delhi using advanced traffic flow data A. Biswal et al. 10.5194/essd-15-661-2023
- Comparison of PM spatiotemporal variations and exposure at adjacent signalized intersection and roundabout W. Li et al. 10.1016/j.uclim.2023.101590
- Operational Data-Driven Intelligent Modelling and Visualization System for Real-World, On-Road Vehicle Emissions—A Case Study in Hangzhou City, China L. Wang et al. 10.3390/su14095434
- Development of Artificial Intelligent-Based Methodology to Prepare Input for Estimating Vehicle Emissions E. Yavuz et al. 10.3390/app142311175
- Predicting high-resolution air quality using machine learning: Integration of large eddy simulation and urban morphology data S. Wang et al. 10.1016/j.envpol.2024.123371
- Characterization of ammonia emissions from light-duty gasoline vehicles based on real-world driving and dynamometer measurements L. Wu et al. 10.1016/j.scitotenv.2024.172644
- Uncovering the CO2 emissions of vehicles: A well-to-wheel approach Z. Zhang et al. 10.1016/j.fmre.2023.06.009
- Transportation emissions monitoring and policy research: Integrating machine learning and satellite imaging H. Fu et al. 10.1016/j.trd.2024.104421
- Data fusion for enhancing urban air quality modeling using large-scale citizen science data A. O'Regan et al. 10.1016/j.scs.2024.105896
Latest update: 13 Dec 2024
Short summary
This paper establishes 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 inventories. The results show that the hourly average on-road vehicle emissions of CO, NOx, HC, and PM2.5 are 74 kg, 40 kg, 8 kg, and 2 kg, respectively. Integrating our traffic-monitoring-based approach with urban measurements, we could address major data gaps between urban air pollutant emissions and concentrations.
This paper establishes a bottom-up approach to reveal a unique pattern of urban on-road vehicle...
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