Articles | Volume 22, issue 3
https://doi.org/10.5194/acp-22-1939-2022
https://doi.org/10.5194/acp-22-1939-2022
Research article
 | 
10 Feb 2022
Research article |  | 10 Feb 2022

High-resolution mapping of regional traffic emissions using land-use machine learning models

Xiaomeng Wu, Daoyuan Yang, Ruoxi Wu, Jiajun Gu, Yifan Wen, Shaojun Zhang, Rui Wu, Renjie Wang, Honglei Xu, K. Max Zhang, Ye Wu, and Jiming Hao

Related authors

Integrating Point Sources to Map Anthropogenic Atmospheric Mercury Emissions in China, 1978–2021
Yuying Cui, Qingru Wu, Shuxiao Wang, Kaiyun Liu, Shengyue Li, Zhezhe Shi, Daiwei Ouyang, Zhongyan Li, Qinqin Chen, Changwei Lü, Fei Xie, Yi Tang, Yan Wang, and Jiming Hao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-252,https://doi.org/10.5194/essd-2024-252, 2024
Preprint under review for ESSD
Short summary
Automated compound speciation, cluster analysis, and quantification of organic vapours and aerosols using comprehensive two-dimensional gas chromatography and mass spectrometry
Xiao He, Xuan Zheng, Shuwen Guo, Lewei Zeng, Ting Chen, Bohan Yang, Shupei Xiao, Qiongqiong Wang, Zhiyuan Li, Yan You, Shaojun Zhang, and Ye Wu
EGUsphere, https://doi.org/10.5194/egusphere-2024-1671,https://doi.org/10.5194/egusphere-2024-1671, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Emission trends of air pollutants and CO2 in China from 2005 to 2021
Shengyue Li, Shuxiao Wang, Qingru Wu, Yanning Zhang, Daiwei Ouyang, Haotian Zheng, Licong Han, Xionghui Qiu, Yifan Wen, Min Liu, Yueqi Jiang, Dejia Yin, Kaiyun Liu, Bin Zhao, Shaojun Zhang, Ye Wu, and Jiming Hao
Earth Syst. Sci. Data, 15, 2279–2294, https://doi.org/10.5194/essd-15-2279-2023,https://doi.org/10.5194/essd-15-2279-2023, 2023
Short summary
Measurement report: Rapid changes of chemical characteristics and health risks for highly time resolved trace elements in PM2.5 in a typical industrial city in response to stringent clean air actions
Rui Li, Yining Gao, Yubao Chen, Meng Peng, Weidong Zhao, Gehui Wang, and Jiming Hao
Atmos. Chem. Phys., 23, 4709–4726, https://doi.org/10.5194/acp-23-4709-2023,https://doi.org/10.5194/acp-23-4709-2023, 2023
Short summary
Vehicular ammonia emissions: an underappreciated emission source in densely populated areas
Yifan Wen, Shaojun Zhang, Ye Wu, and Jiming Hao
Atmos. Chem. Phys., 23, 3819–3828, https://doi.org/10.5194/acp-23-3819-2023,https://doi.org/10.5194/acp-23-3819-2023, 2023
Short summary

Related subject area

Subject: Gases | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Potential of 14C-based vs. ΔCO-based ΔffCO2 observations to estimate urban fossil fuel CO2 (ffCO2) emissions
Fabian Maier, Christian Rödenbeck, Ingeborg Levin, Christoph Gerbig, Maksym Gachkivskyi, and Samuel Hammer
Atmos. Chem. Phys., 24, 8183–8203, https://doi.org/10.5194/acp-24-8183-2024,https://doi.org/10.5194/acp-24-8183-2024, 2024
Short summary
On the uncertainty of anthropogenic aromatic volatile organic compound emissions: model evaluation and sensitivity analysis
Kevin Oliveira, Marc Guevara, Oriol Jorba, Hervé Petetin, Dene Bowdalo, Carles Tena, Gilbert Montané Pinto, Franco López, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 24, 7137–7177, https://doi.org/10.5194/acp-24-7137-2024,https://doi.org/10.5194/acp-24-7137-2024, 2024
Short summary
A mechanism of stratospheric O3 intrusion into the atmospheric environment: a case study of the North China Plain
Yuehan Luo, Tianliang Zhao, Kai Meng, Jun Hu, Qingjian Yang, Yongqing Bai, Kai Yang, Weikang Fu, Chenghao Tan, Yifan Zhang, Yanzhe Zhang, and Zhikuan Li
Atmos. Chem. Phys., 24, 7013–7026, https://doi.org/10.5194/acp-24-7013-2024,https://doi.org/10.5194/acp-24-7013-2024, 2024
Short summary
Influence of atmospheric circulation on the interannual variability of transport from global and regional emissions into the Arctic
Cheng Zheng, Yutian Wu, Mingfang Ting, and Clara Orbe
Atmos. Chem. Phys., 24, 6965–6985, https://doi.org/10.5194/acp-24-6965-2024,https://doi.org/10.5194/acp-24-6965-2024, 2024
Short summary
Surface networks in the Arctic may miss a future methane bomb
Sophie Wittig, Antoine Berchet, Isabelle Pison, Marielle Saunois, and Jean-Daniel Paris
Atmos. Chem. Phys., 24, 6359–6373, https://doi.org/10.5194/acp-24-6359-2024,https://doi.org/10.5194/acp-24-6359-2024, 2024
Short summary

Cited articles

Alam, I., Farid, D. M., and Rossetti, R. J.: The prediction of traffic flow with regression analysis, in: Emerging Technologies in Data Mining and Information Security, 661–671, Springer, Singapore, 2019. 
Boukerche, A. and Wang, J.: Machine Learning-based traffic prediction models for Intelligent Transportation Systems, Comput. Netw., 181, 107530, https://doi.org/10.1016/j.comnet.2020.107530, 2020. 
Brokamp, C., Jandarov, R., Hossain, M., and Ryan, P.: Predicting Daily Urban Fine Particulate Matter Concentrations Using a Random Forest Model, Environ. Sci. Technol., 52, 4173–4179, https://doi.org/10.1021/acs.est.7b05381, 2018. 
Chapman, L.: Transport and climate change: a review, J. Transp. Geogr., 15, 354–367, https://doi.org/10.1016/j.jtrangeo.2006.11.008, 2007. 
Gately, C. K., Hutyra, L. R., and Sue Wing, I.: Cities, traffic, and CO2: A multidecadal assessment of trends, drivers, and scaling relationships, P. Natl. Acad. Sci. USA, 112, 4999–5004, https://doi.org/10.1073/pnas.1421723112, 2015. 
Download
Short summary
Our work pioneered land-use machine learning methods for developing link-level emission inventories, utilizing hourly traffic profiles, including volume, speed, and fleet mix, obtained from the governmental intercity highway monitoring network in the "capital circles" of China. This research provides a platform to realize the near-real-time process of establishing high-resolution vehicle emission inventories for policy makers to engage in sophisticated traffic management.
Altmetrics
Final-revised paper
Preprint