Articles | Volume 15, issue 2 
            
                
                    
            
            
            https://doi.org/10.5194/essd-15-661-2023
                    © Author(s) 2023. This work is distributed under 
the Creative Commons Attribution 4.0 License.
                the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-661-2023
                    © Author(s) 2023. This work is distributed under 
the Creative Commons Attribution 4.0 License.
                the Creative Commons Attribution 4.0 License.
Spatially resolved hourly traffic emission over megacity Delhi using advanced traffic flow data
Akash Biswal
                                            National Atmospheric Research Laboratory, Gadanki, AP, 517112, India
                                        
                                    
                                            Department of Environment Studies, Panjab University, Chandigarh,
160014, India
                                        
                                    
                                            National Atmospheric Research Laboratory, Gadanki, AP, 517112, India
                                        
                                    Leeza Malik
                                            Department of Civil Engineering, Indian Institute of Technology
(Indian School of Mines), Dhanbad, Jharkhand 826004, India
                                        
                                    Geetam Tiwari
                                            Transportation Research and Injury Prevention Programme, Indian
Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India
                                        
                                    Khaiwal Ravindra
                                            Department of Community Medicine and School of Public Health, Post
Graduate Institute of Medical Education and Research (PGIMER), Chandigarh
160012, India
                                        
                                    Suman Mor
                                            Department of Environment Studies, Panjab University, Chandigarh,
160014, India
                                        
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                            Cited
18 citations as recorded by crossref.
- Black carbon pollution over India simulated with recent emission inventories and WRF-CHEM model R. Sheoran et al. 10.1016/j.atmosres.2025.107931
 - Real-Time IoT-Based Connected Vehicle Infrastructure for Intelligent Transportation Safety N. Sharma & R. Garg 10.1109/TITS.2023.3263271
 - The analysis of the operating conditions of a heavy-duty engine of a vehicle designated for timber transport in terms of compliance with the RDE procedures M. Bednarek et al. 10.19206/CE-193859
 - Changing tropospheric NO2 dynamics across Indian air pollution hotspots A. Biswal et al. 10.1016/j.envpol.2025.126160
 - Health Risks of Major Air Pollutants, their Drivers and Mitigation Strategies: A Review S. Maji et al. 10.1177/11786221231154659
 - Nighttime NO emissions strongly suppress chlorine and nitrate radical formation during the winter in Delhi S. Haslett et al. 10.5194/acp-23-9023-2023
 - A method for identifying exceedances of permissible NOX air pollutants by car traffic in a polish city J. Kwiecień & P. Olenkowicz-Trempała 10.1007/s13762-024-05937-6
 - Weak coupling of observed surface PM2.5 in Delhi-NCR with rice crop residue burning in Punjab and Haryana P. Mangaraj et al. 10.1038/s41612-025-00901-8
 - Decoding temporal patterns and trends of PM10 pollution over Delhi: a multi-year analysis (2015–2022) . Chetna et al. 10.1007/s10661-024-12638-7
 - Introducing Governing Dynamics for IS3C in Intelligent Transportation Systems W. Zhang et al. 10.1109/TITS.2025.3573574
 - Quantifying vehicle restriction related PM2.5 reduction using field observations in an isolated urban basin Y. Guo et al. 10.1088/1748-9326/ad2238
 - Scaling traffic variables from sensors sample to the entire city at high spatiotemporal resolution with machine learning: applications to the Paris megacity X. Bonnemaizon et al. 10.1088/2634-4505/ad6bbf
 - Harmonized Annual Averaged Traffic Data at Street Segment Level for European Cities X. Bonnemaizon et al. 10.1038/s41597-025-05698-y
 - Analysis of Low-Carbon, Energy-Saving, and Emission Reduction Models Based on Rail Transit J. Sun & V. Le 10.4018/IJISMD.355708
 - Recent Advances in Carbon Nanomaterials: Pioneering Sustainable Environmental Contamination Remediation and Advancing Circular Economy Practices P. Thamarai et al. 10.1007/s44169-025-00094-4
 - Study of Airborne Particulate Pollution from Road Traffic Emissions in the Coastal Urban Center of Sousse City, Tunisia A. Komti et al. 10.1007/s41742-025-00918-0
 - Employing an Eigenfunction Eigendecomposition algorithm to cartographically and statistically delineate traffic-related carbon monoxide pollution in Hillsborough County, Florida L. Jing et al. 10.5897/JPHE2023.1461
 - Impact of allocation factors on spatial disaggregation of road traffic emissions in Megacity Delhi A. Swarnkar et al. 10.1007/s11869-025-01706-7
 
18 citations as recorded by crossref.
- Black carbon pollution over India simulated with recent emission inventories and WRF-CHEM model R. Sheoran et al. 10.1016/j.atmosres.2025.107931
 - Real-Time IoT-Based Connected Vehicle Infrastructure for Intelligent Transportation Safety N. Sharma & R. Garg 10.1109/TITS.2023.3263271
 - The analysis of the operating conditions of a heavy-duty engine of a vehicle designated for timber transport in terms of compliance with the RDE procedures M. Bednarek et al. 10.19206/CE-193859
 - Changing tropospheric NO2 dynamics across Indian air pollution hotspots A. Biswal et al. 10.1016/j.envpol.2025.126160
 - Health Risks of Major Air Pollutants, their Drivers and Mitigation Strategies: A Review S. Maji et al. 10.1177/11786221231154659
 - Nighttime NO emissions strongly suppress chlorine and nitrate radical formation during the winter in Delhi S. Haslett et al. 10.5194/acp-23-9023-2023
 - A method for identifying exceedances of permissible NOX air pollutants by car traffic in a polish city J. Kwiecień & P. Olenkowicz-Trempała 10.1007/s13762-024-05937-6
 - Weak coupling of observed surface PM2.5 in Delhi-NCR with rice crop residue burning in Punjab and Haryana P. Mangaraj et al. 10.1038/s41612-025-00901-8
 - Decoding temporal patterns and trends of PM10 pollution over Delhi: a multi-year analysis (2015–2022) . Chetna et al. 10.1007/s10661-024-12638-7
 - Introducing Governing Dynamics for IS3C in Intelligent Transportation Systems W. Zhang et al. 10.1109/TITS.2025.3573574
 - Quantifying vehicle restriction related PM2.5 reduction using field observations in an isolated urban basin Y. Guo et al. 10.1088/1748-9326/ad2238
 - Scaling traffic variables from sensors sample to the entire city at high spatiotemporal resolution with machine learning: applications to the Paris megacity X. Bonnemaizon et al. 10.1088/2634-4505/ad6bbf
 - Harmonized Annual Averaged Traffic Data at Street Segment Level for European Cities X. Bonnemaizon et al. 10.1038/s41597-025-05698-y
 - Analysis of Low-Carbon, Energy-Saving, and Emission Reduction Models Based on Rail Transit J. Sun & V. Le 10.4018/IJISMD.355708
 - Recent Advances in Carbon Nanomaterials: Pioneering Sustainable Environmental Contamination Remediation and Advancing Circular Economy Practices P. Thamarai et al. 10.1007/s44169-025-00094-4
 - Study of Airborne Particulate Pollution from Road Traffic Emissions in the Coastal Urban Center of Sousse City, Tunisia A. Komti et al. 10.1007/s41742-025-00918-0
 - Employing an Eigenfunction Eigendecomposition algorithm to cartographically and statistically delineate traffic-related carbon monoxide pollution in Hillsborough County, Florida L. Jing et al. 10.5897/JPHE2023.1461
 - Impact of allocation factors on spatial disaggregation of road traffic emissions in Megacity Delhi A. Swarnkar et al. 10.1007/s11869-025-01706-7
 
Latest update: 03 Nov 2025
Short summary
                    This paper presents detailed emission estimates of on-road traffic exhaust emissions of nine major pollutants for Delhi. We use advanced traffic data and emission factors as a function of speed to estimate emissions for each hour and 100 m × 100 m spatial resolution. We examine the source contribution according to the vehicle, fuel, road and Euro types to identify the most polluting vehicles. These data are useful for high-resolution air quality modelling for developing suitable strategies.
                    This paper presents detailed emission estimates of on-road traffic exhaust emissions of nine...
                    
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