63 citations as recorded by crossref.

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7. Assessing the Future Vehicle Fleet Electrification: The Impacts on Regional and Urban Air Quality W. Ke et al. https://doi.org/10.1021/acs.est.6b04253
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20. Black carbon pollution for a major road in Beijing: Implications for policy interventions of the heavy-duty truck fleet S. Zhang et al. https://doi.org/10.1016/j.trd.2017.07.013
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22. Vehicle emission models and their applications in China: A comprehensive review T. Jia & J. Qi https://doi.org/10.1016/j.jtte.2025.03.004
23. Emission Inventories and Particulate Matter Air Quality Modeling over the Pearl River Delta Region D. Lopes et al. https://doi.org/10.3390/ijerph18084155
24. Establishment of high temporal-spatial resolution anthropogenic emission inventory of air pollutants in 2017 for Macao, China Y. Wu et al. https://doi.org/10.1016/j.atmosenv.2024.120735
25. Is a dedicated bus lane operationally and environmentally beneficial? A case study in Beijing Q. Jiang et al. https://doi.org/10.1080/19427867.2024.2439349
26. Exploring Food Waste at a Hospitality Staff Canteen With Meteorological Data S. Lei et al. https://doi.org/10.1177/10963480231188001
27. A real-time NO emission inventory from heavy-duty vehicles based on on-board diagnostics big data with acceptable quality in China Z. Lv et al. https://doi.org/10.1016/j.jclepro.2023.138592
28. Evaluation of the mid- and long-term effects of a private car driving–restriction policy under the carbon emission peak target Z. Chen et al. https://doi.org/10.1007/s11356-023-25391-0
29. RTVEMVS: Real-time modeling and visualization system for vehicle emissions on an urban road network H. Ding et al. https://doi.org/10.1016/j.jclepro.2021.127166
30. Super-learner model realizes the transient prediction of CO2 and NOx of diesel trucks: Model development, evaluation and interpretation N. Wei et al. https://doi.org/10.1016/j.envint.2021.106977
31. 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. https://doi.org/10.3390/su14095434
32. Hyperfine-resolution mapping of on-road vehicle emissions with comprehensive traffic monitoring and an intelligent transportation system L. Jiang et al. https://doi.org/10.5194/acp-21-16985-2021
33. High-resolution multi-scale air pollution system: Evaluation of modelling performance and emission control strategies D. Lopes et al. https://doi.org/10.1016/j.jes.2023.02.046
34. Spatiotemporal evolution pattern detection for heavy-duty diesel truck emissions using trajectory mining: A case study of Tianjin, China S. Cheng et al. https://doi.org/10.1016/j.jclepro.2019.118654
35. Emission characteristics and control scenario analysis of VOCs from heavy-duty diesel trucks S. Cheng et al. https://doi.org/10.1016/j.jenvman.2021.112915
36. Temporal-spatial dynamic characteristics of vehicle emissions on intercity roads in Guangdong Province based on vehicle identity detection data H. Ding et al. https://doi.org/10.1016/j.jes.2022.06.034
37. Modeling real-world fuel consumption and carbon dioxide emissions with high resolution for light-duty passenger vehicles in a traffic populated city S. Zhang et al. https://doi.org/10.1016/j.energy.2016.07.067
38. Benefits of transportation strategies to reduce on-road traffic pollution emissions: Evidence from Bogota, Colombia D. Jaime & S. Mangones https://doi.org/10.1016/j.cstp.2025.101527
39. Impact of urban block shape on traffic and air quality: A SUMO-based comparative study of rectangular, radial, and triangular forms I. Essamlali et al. https://doi.org/10.1016/j.trip.2025.101413
40. A high temporal-spatial vehicle emission inventory based on detailed hourly traffic data in a medium-sized city of China Y. Liu et al. https://doi.org/10.1016/j.envpol.2018.01.068
41. Spatial variation, temporal evolution, and source direction apportionment of PM1, PM2.5, and PM10: 3-year assessment in Turin (Po Valley) D. Mecca et al. https://doi.org/10.1007/s10661-024-13446-9
42. A review of on-road vehicle emission inventory D. Yang et al. https://doi.org/10.1051/e3sconf/202236001027
43. A license plate recognition data to estimate and visualise the restriction policy for diesel vehicles on urban air quality: A case study of Shenzhen W. Huang et al. https://doi.org/10.1016/j.jclepro.2022.130401
44. Recent development of a refined multiple air pollutant emission inventory of vehicles in the Central Plains of China X. Gu et al. https://doi.org/10.1016/j.jes.2019.04.010
45. Reducing the road freight emissions through integrated strategy in the port cities P. Zhao et al. https://doi.org/10.1038/s41467-025-57861-z
46. Long-term historical trends in air pollutant emissions in Asia: Regional Emission inventory in ASia (REAS) version 3 J. Kurokawa & T. Ohara https://doi.org/10.5194/acp-20-12761-2020
47. Evaluating traffic emission control policies based on large-scale and real-time data: A case study in central China C. Zou et al. https://doi.org/10.1016/j.scitotenv.2022.160435
48. Regional vehicle energy consumption evaluation framework to quantify the benefits of vehicle electrification in plateau city: A case study of Xining, China Z. Jia et al. https://doi.org/10.1016/j.apenergy.2024.124626
49. Revealing uncertainties of on-road emissions in a mountainous city using multi-source data Z. Zhang et al. https://doi.org/10.1016/j.trd.2026.105270
50. Improving the accuracy of emission inventories with a machine-learning approach and investigating transferability across cities R. Tu et al. https://doi.org/10.1080/10962247.2019.1668872
51. High-resolution mapping of vehicle emissions of atmospheric pollutants based on large-scale, real-world traffic datasets D. Yang et al. https://doi.org/10.5194/acp-19-8831-2019
52. The spatial and temporal disaggregation models of high-accuracy vehicle emission inventory H. Feng et al. https://doi.org/10.1016/j.envint.2023.108287
53. Simulation modelling as a tool for urban air pollution forecasting M. Logachev et al. https://doi.org/10.1051/e3sconf/202346008011
54. Assessing on-road emissions from urban buses in different traffic congestion scenarios by integrating real-world driving, traffic, and emissions data F. Rosero et al. https://doi.org/10.1016/j.scitotenv.2022.161002
55. Pioneers of electric mobility: Lessons about transport decarbonisation from two bay areas K. Tsoi et al. https://doi.org/10.1016/j.jclepro.2021.129866
56. Development of a highly spatiotemporally resolved vehicular volatile organic compounds emission inventory based on on-line measurement of speed-dependent emission factor M. Wang et al. https://doi.org/10.1016/j.scitotenv.2024.175176
57. A diurnal story of Δ17O($$\rm{NO}_{3}^{-}$$) in urban Nanjing and its implication for nitrate aerosol formation Y. Zhang et al. https://doi.org/10.1038/s41612-022-00273-3
58. Air Quality and Health Gains from Truck Electrification: Accounting for Feasible Spatial Patterns and Integrated Emission Control R. Wu et al. https://doi.org/10.1021/acsestair.5c00343
59. High-resolution mapping of on-road vehicle emissions with real-time traffic datasets based on big data Y. Wang et al. https://doi.org/10.5194/acp-25-5537-2025
60. Unveiling PM2.5 Transport Pathways: A Trajectory-Channel Model Framework for Spatiotemporally Quantitative Source Apportionment Y. Pan et al. https://doi.org/10.3390/atmos16070883
61. High resolution vehicular exhaust and non-exhaust emission analysis of urban-rural district of India G. Tomar et al. https://doi.org/10.1016/j.scitotenv.2021.150255
62. Multiscale spatiotemporal variations of NOx emissions from heavy duty diesel trucks in the Beijing-Tianjin-Hebei region S. Cheng et al. https://doi.org/10.1016/j.scitotenv.2022.158753
63. Dynamic quantification of on-road emissions in Hong Kong: Impact from traffic congestion and fleet composition variation X. Li et al. https://doi.org/10.1016/j.atmosenv.2023.120059