Smart City Gnosys
Smart city article details
| Title | The Correlation Of The Smart City Concept With The Costs Of Toxic Exhaust Gas Emissions Based On The Analysis Of A Selected Population Of Motor Vehicles In Urban Traffic |
|---|---|
| ID_Doc | 55214 |
| Authors | Lewicki W.; Bera M.; Śpiewak-Szyjka M. |
| Year | 2024 |
| Published | Energies, 17, 21 |
| DOI | http://dx.doi.org/10.3390/en17215375 |
| Abstract | The intensive development of road transport has resulted in a significant increase in air pollution. This phenomenon is particularly noticeable in urban areas. This creates the need for analyses and forecasts of the scale and extent of future emissions of harmful substances into the environment. The aim of this study was to estimate the costs of the emission of toxic components of exhaust gases generated by all users of conventionally propelled vehicles travelling on a section of urban road in the next 25 years. The traffic study was carried out on an urban traffic route, playing a key role for road transport in the dimension of a given urban agglomeration. The traffic forecast for the analysed road section was based on the results of our own measurements carried out in April 2023 and external data from the General Directorate for Roads and Motorways. The results of the observations concerned six categories of vehicles for the morning and afternoon rush hours. Based on the data obtained, the generic structure of the vehicle population on the analysed section and the average daily traffic were determined. Using the methodology contained in the Blue Book of Road Infrastructure, parameters were calculated in the form of annual indicators of traffic growth on the analysed section, travel speed, and annual air pollution costs for selected vehicle categories, remembering at the same time that the Blue Book-based methodology does not distinguish between unit costs in relation to the type of emissions. The results of the study confirmed that there was an increase in the cost of toxic emissions for each vehicle category over the projected 25-year period. The largest increases were seen for trucks with trailers and passenger cars. In total, for all vehicle categories, emission costs nearly doubled from 2024 to 2046, from EUR 3,745,229 to EUR 7,443,384, due to the doubling of the number of vehicles resulting from the traffic forecast. The analyses presented here provide an answer to the question of what pollution costs may be faced by cities in which road transport will continue to be based on conventional types of propulsion. In addition, the research presented can be used to develop urban mobility transformation plans for the coming years, within the scope of the widely promoted smart city concept and the idea of electromobility, by pointing out to local authorities the direct economic benefits of these changes. © 2024 by the authors. |
| Author Keywords | combustion vehicles; electromobility; exhaust emission costs; exhaust modelling; smart city; transport; urban traffic |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
843  | 0.893 | Tripp-Barba C.; Barbecho P.; Urquiza L.; Aguilar-Calderón J.A. | A Comparison Of Vehicle Emissions Control Strategies For Smart Cities | PeerJ Computer Science, 9 (2023) |
| 58525 | 0.885 | Ilarri S.; Trillo-Lado R.; Marrodán L. | Traffic And Pollution Modelling For Air Quality Awareness: An Experience In The City Of Zaragoza | SN Computer Science, 3, 4 (2022) |
| 5612 | 0.878 | Dutta P.; Sur S.; Choudhury S.; Khatua S. | A Traffic Management System By Identifying Pollution Hotspots Among Sensitive Points In A Smart City | IEEE Access, 13 (2025) |
| 27256 | 0.875 | Po L.; Rollo F.; Bachechi C.; Corni A. | From Sensors Data To Urban Traffic Flow Analysis | 5th IEEE International Smart Cities Conference, ISC2 2019 (2019) |
| 8567 | 0.873 | Zaky M.O.; Soubra H. | An Intelligent Transportation System For Air And Noise Pollution Management In Cities | International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS - Proceedings, 2021-April (2021) |
| 42700 | 0.871 | Sathiamoorthy V.; Ahmed E.K.; Veeravalli B.; Zengxiang L. | Predicting Emission Costs For Urban Transportation In Smart Cities Using Machine Learning Models | ACM International Conference Proceeding Series (2020) |
| 41491 | 0.868 | Rodriguez Garzon S.; Küpper A. | Pay-Per-Pollution: Towards An Air Pollution-Aware Toll System For Smart Cities | Proceedings - 2019 IEEE International Conference on Smart Internet of Things, SmartIoT 2019 (2019) |
| 35078 | 0.861 | Alabi O.O.; Ajagbe S.A.; Kuti O.; Afe O.F.; Ajiboye G.O.; Adigun M.O. | Leveraging Environmental Data For Intelligent Traffic Forecasting In Smart Cities | Communications in Computer and Information Science, 2159 CCIS (2024) |
| 49327 | 0.859 | Kharchenko H.; Kharchenko V. | Smart Cities And Ecological Transport: Challenges, Prospects And Impact On Sustainable Development | Lecture Notes in Networks and Systems, 1335 LNNS (2025) |
| 32092 | 0.859 | Pascale A.; Mascolo A.; Rossi D.; Coelho M.C.; Guarnaccia C. | Integrating Vehicle Noise Emission Models Into Eco-Routing For Smart Transportation: Implications In A Case Study | AIP Conference Proceedings, 3308, 1 (2025) |