83 citations as recorded by crossref.

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15. Vehicular ammonia emissions: an underappreciated emission source in densely populated areas Y. Wen et al. 10.5194/acp-23-3819-2023
16. High resolution vehicular exhaust and non-exhaust emission analysis of urban-rural district of India G. Tomar et al. 10.1016/j.scitotenv.2021.150255
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19. Concentration and source changes of nitrous acid (HONO) during the COVID-19 lockdown in Beijing Y. Zhang et al. 10.5194/acp-24-8569-2024
20. A Newly Established Air Pollution Data Center in China M. Zheng et al. 10.1007/s00376-024-4055-4
21. Key driver analysis of greenhouse gas emissions in Thailand's public bus transport with comparative study on metropolitan Bangkok hotspots T. Champeecharoensuk et al. 10.1016/j.esd.2022.08.019
22. A Deep Transfer NOx Emission Inversion Model of Diesel Vehicles with Multisource External Influence Z. Xu et al. 10.1155/2021/4892855
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25. Efficient and expressive high-resolution image synthesis via variational autoencoder-enriched transformers with sparse attention mechanisms B. Tang & F. Feng 10.1117/1.JEI.33.3.033002
26. Vehicular Ammonia Emissions Significantly Contribute to Urban PM2.5 Pollution in Two Chinese Megacities Y. Wang et al. 10.1021/acs.est.2c06198
27. An updated model-ready emission inventory for Guangdong Province by incorporating big data and mapping onto multiple chemical mechanisms Z. Huang et al. 10.1016/j.scitotenv.2020.144535
28. Ammonium nitrate promotes sulfate formation through uptake kinetic regime Y. Liu et al. 10.5194/acp-21-13269-2021
29. Investigation of NOx and related secondary pollutants at Anand Vihar, one of the most polluted area of Delhi N. Kaushik & R. Das 10.1016/j.uclim.2023.101747
30. Variation of spatio-temporal distribution of on-road vehicle emissions based on real-time RFID data Y. Liu et al. 10.1016/j.jes.2021.07.018
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. 10.3390/su14095434
32. Simulating heat and CO2 fluxes in Beijing using SUEWS V2020b: sensitivity to vegetation phenology and maximum conductance Y. Zheng et al. 10.5194/gmd-16-4551-2023
33. Status and quality evaluation of precursor emission inventories for PM<sub>2.5</sub> and ozone in China Z. Huang et al. 10.1360/TB-2021-0783
34. A two-way coupled regional urban–street network air quality model system for Beijing, China T. Wang et al. 10.5194/gmd-16-5585-2023
35. Forecasting the Reduction in Urban Air Pollution by Expansion of Market Shares of Eco-Friendly Vehicles: A Focus on Seoul, Korea H. Jo et al. 10.3390/ijerph192215314
36. On-road emission measurements of reactive nitrogen compounds from heavy-duty diesel trucks in China L. He et al. 10.1016/j.envpol.2020.114280
37. High-resolution mapping of regional traffic emissions using land-use machine learning models X. Wu et al. 10.5194/acp-22-1939-2022
38. Sources and sinks driving sulfuric acid concentrations in contrasting environments: implications on proxy calculations L. Dada et al. 10.5194/acp-20-11747-2020
39. The future air quality impact of electric vehicle promotion and coordinated charging in the Beijing-Tianjin-Hebei region Y. Jiang et al. 10.1016/j.envpol.2023.121928
40. Spatially resolved hourly traffic emission over megacity Delhi using advanced traffic flow data A. Biswal et al. 10.5194/essd-15-661-2023
41. Characteristics of NOX and NH3 emissions from in-use heavy-duty diesel vehicles with various aftertreatment technologies in China L. He et al. 10.1016/j.jhazmat.2023.133073
42. A comprehensive spatial and temporal vehicular emissions for northeast China S. Ibarra-Espinosa et al. 10.1016/j.atmosenv.2020.117952
43. Evaluating the Real-World NOx Emission from a China VI Heavy-Duty Diesel Vehicle P. Li & L. Lü 10.3390/app11031335
44. Increased Impact of Aviation on Air Quality and Human Health in China J. Zhang et al. 10.1021/acs.est.3c05821
45. Evaluating on-board sensing-based nitrogen oxides (NOX) emissions from a heavy-duty diesel truck in China Y. Cheng et al. 10.1016/j.atmosenv.2019.116908
46. A big data approach to improving the vehicle emission inventory in China F. Deng et al. 10.1038/s41467-020-16579-w
47. Size-segregated particle number and mass concentrations from different emission sources in urban Beijing J. Cai et al. 10.5194/acp-20-12721-2020
48. Air quality and health benefits from fleet electrification in China X. Liang et al. 10.1038/s41893-019-0398-8
49. Review of Road Dust Resuspension Modelling Approaches and Comparisons Analysis for a UK Case Study F. Galatioto et al. 10.3390/atmos13091403
50. Mapping dynamic road emissions for a megacity by using open-access traffic congestion index data Y. Wen et al. 10.1016/j.apenergy.2019.114357
51. Four-Month Changes in Air Quality during and after the COVID-19 Lockdown in Six Megacities in China Y. Wang et al. 10.1021/acs.estlett.0c00605
52. Mortality-based damages per ton due to the on-road mobile sector in the Northeastern and Mid-Atlantic U.S. by region, vehicle class and precursor C. Arter et al. 10.1088/1748-9326/abf60b
53. Quantifying vehicle restriction related PM2.5 reduction using field observations in an isolated urban basin Y. Guo et al. 10.1088/1748-9326/ad2238
54. Air quality and health impacts from using ethanol blended gasoline fuels in China X. Liang et al. 10.1016/j.atmosenv.2020.117396
55. A high-resolution emissions inventory and its spatiotemporal pattern variations for heavy-duty diesel trucks in Beijing, China S. Cheng et al. 10.1016/j.jclepro.2019.119445
56. Mitigation potential of black carbon emissions from on-road vehicles in China S. Zhang et al. 10.1016/j.envpol.2021.116746
57. Dynamic quantification of on-road emissions in Hong Kong: Impact from traffic congestion and fleet composition variation X. Li et al. 10.1016/j.atmosenv.2023.120059
58. 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. 10.1016/j.jclepro.2023.138592
59. Comparing Commercial Vehicle Fuel Consumption Models using Real-World Data under Calibration Constraints L. Yeow & L. Cheah 10.1177/03611981211007478
60. Assessing individual activity-related exposures to traffic congestion using GPS trajectory data Z. Kan et al. 10.1016/j.jtrangeo.2021.103240
61. Multiscale spatiotemporal variations of NOx emissions from heavy duty diesel trucks in the Beijing-Tianjin-Hebei region S. Cheng et al. 10.1016/j.scitotenv.2022.158753
62. Source–Receptor Relationship Revealed by the Halted Traffic and Aggravated Haze in Beijing during the COVID-19 Lockdown Z. Lv et al. 10.1021/acs.est.0c04941
63. Effect of alternative fuels on the emissions of a passenger car under real-world driving conditions: a comparison of biodiesel, gas-to-liquid, coal to liquid Y. Zhang et al. 10.1007/s11356-024-34778-6
64. The promotion effect of nitrous acid on aerosol formation in wintertime in Beijing: the possible contribution of traffic-related emissions Y. Liu et al. 10.5194/acp-20-13023-2020
65. Air quality improvement via modal shift: Assessment of rail-water-port integrated system planning in Shenzhen, China J. Zhang et al. 10.1016/j.scitotenv.2021.148158
66. Unprecedented Ambient Sulfur Trioxide (SO3) Detection: Possible Formation Mechanism and Atmospheric Implications L. Yao et al. 10.1021/acs.estlett.0c00615
67. Size-resolved particle number emissions in Beijing determined from measured particle size distributions J. Kontkanen et al. 10.5194/acp-20-11329-2020
68. Aggravated air pollution and health burden due to traffic congestion in urban China P. Wang et al. 10.5194/acp-23-2983-2023
69. Increased diurnal difference of NO2 concentrations and its impact on recent ozone pollution in eastern China in summer Y. Shen et al. 10.1016/j.scitotenv.2022.159767
70. 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. 10.1016/j.scitotenv.2024.175176
71. Real-world fuel consumption of light-duty passenger vehicles using on-board diagnostic (OBD) systems X. Zheng et al. 10.1007/s11783-019-1212-6
72. Impact of lockdown policies on urban traffic conditions and carbon dioxide emissions based on an emission model on the link level in hour granularity Z. Zhang et al. 10.1016/j.jclepro.2023.140426
73. PMIF v1.0: assessing the potential of satellite observations to constrain CO<sub>2</sub> emissions from large cities and point sources over the globe using synthetic data Y. Wang et al. 10.5194/gmd-13-5813-2020
74. Responses of photosynthesis and long-term water use efficiency to ambient air pollution in urban roadside trees M. Matsumoto et al. 10.1007/s11252-022-01212-z
75. Structural decomposition of heavy-duty diesel truck emission contribution based on trajectory mining S. Cheng et al. 10.1016/j.jclepro.2022.135172
76. Dynamic emission characteristics and control strategies of air pollutants from motor vehicles in downtown Beijing, China Y. Shen et al. 10.1016/j.jes.2023.01.019
77. High spatial and temporal resolution vehicular emissions in south-east Brazil with traffic data from real-time GPS and travel demand models S. Ibarra-Espinosa et al. 10.1016/j.atmosenv.2019.117136
78. Trends in ammonia emissions from light-duty gasoline vehicles in China, 1999–2017 S. Li et al. 10.1016/j.scitotenv.2019.134359
79. Estimating PM2.5 with high-resolution 1-km AOD data and an improved machine learning model over Shenzhen, China W. Chen et al. 10.1016/j.scitotenv.2020.141093
80. Emission characteristics and control scenario analysis of VOCs from heavy-duty diesel trucks S. Cheng et al. 10.1016/j.jenvman.2021.112915
81. On-board monitoring (OBM) for heavy-duty vehicle emissions in China: Regulations, early-stage evaluation and policy recommendations S. Zhang et al. 10.1016/j.scitotenv.2020.139045
82. The relationship between the altitude and the simulations of ozone and NO2 by WRF-Chem for the Tibetan Plateau X. Lu et al. 10.1016/j.atmosenv.2022.118981
83. A classic critique on concrete adsorbing pollutants emitted by automobiles and statistical envision using trend analysis P. Neelamegam & B. Muthusubramanian 10.1007/s11356-021-15962-4