Estimating Urban Road Transport Vehicles Emissions in the Rijeka City Streets
Abstract
The growing demand for private and public transport services in urban areas requires sophisticated approaches to achieve satisfactory mobility standards in urban areas. Some of the main problems in urban areas today are road congestions and consequently vehicle emissions. The aim of this paper is to propose a methodological approach for the estimation of vehicle emissions. The proposed methodology is based on two interrelated models. The first model is a microscopic simulation SUMO model which can be used to identify the most congested urban areas and roads with critical values of traffic parameters. The second model is the COPERT Street Level for estimating vehicle emissions. The proposed models were tested on the urban area of Rijeka. The results of the microscopic SUMO simulation model indicate six urban roads with the critical traffic flow parameters. On the basis of the six identified urban roads, an estimation of vehicle emissions was carried out for specific time periods: 2017, 2020, 2025, and 2030. According to the results of the second model, the urban road R20-21 was identified as the most polluted road in the urban district of Rijeka. The results indicate that over the period 2017–2030, CO emissions will be reduced on average by 57% on all observed urban roads, CO2 emissions by 20%, and PM emissions by 58%, while the largest reduction of 65% will be in NOx emissions.
References
Liu J, Han K, Chen X, Ong G-P. Spatial-temporal inference of urban traffic emissions based on taxi trajectories and multi-source urban data. Transportation Research Part C: Emerging Technologies. 2019;106: 145-165. DOI: 10.1016/j.trc.2019.07.005
The Intergovernmental Panel on Climate Change (IPCC). AR5 Climate Change 2014: Mitigation of Climate Change. Chapter 8 – Transport; 2014. Available from: http://www.ipcc.ch/ [Accessed 1st Nov. 2019].
Wang H, Zeng W. Revealing Urban Carbon Dioxide (CO2) Emission Characteristics and Influencing Mechanisms from the Perspective of Commuting. Sustainability. 2019;11(2): 385. DOI: 10.3390/su11020385
Bakker S, Haq G, Peet K, Gota S, Medimorec N, Yiu, A, Jennings G, Rogers J. Low-Carbon Quick Wins: Integrating Short-Term Sustainable Transport Options in Climate Policy in Low-Income Countries. Sustainability. 2019;11(16): 4369. DOI: 10.3390/su11164369
Zhang W, Lu J, Zhang Y. Moving towards Sustainability: Road Grades and On-Road Emissions of Heavy-Duty Vehicles-A Case Study. Sustainability. 2015;7: 12644-12671. DOI: 10.3390/su70912644
Ntziachristos L, Gkatzoflias D, Kouridis C, Samaras Z. COPERT: A European Road Transport Emission Inventory Model. Environmental Science and Engineering. 2009: 491-504. DOI: 10.1007/978-3-540-88351-7_37
Gualtieri G, Camilli F, Cavaliere A, et al. An integrated low-cost road traffic and air pollution monitoring platform to assess vehicles air quality impact in urban areas. Transportation Research Procedia. 2017;27: 609-616. DOI: 10.1016/j.trpro.2017.12.043
Park J, Noland R, Polak J. Microscopic Model of Air Pollutant Concentrations: Comparison of Simulated Results with Measured and Macroscopic Estimates. Journal of the Transportation Research Board. 2001;1750(1): 64-73. DOI: 10.3141/1750-08
Smit R, Ntziachristos L, Boulter P. Validation of road vehicle and traffic emission models – A review and meta-analysis. Atmospheric Environment. 2010;44(25): 2943-2953. DOI: 10.1016/j.atmosenv.2010.05.022
Beckx C, Panis L-I, Vankerkom J, Janssens D, Wets G, Arentze T. An Integrated Activity-Based Modelling Framework to Assess Vehicle Emissions: Approach and Application. Environment and Planning B: Planning and Design. 2009;36(6): 1086-1102. DOI: 10.1068/b35044
Federal Register. Official Release of EMFAC 2017 Motor Vehicle Emission Factor Model for Use in the State of California, 2017. Available from: https://www.federalregister.gov/documents/2019/08/15/2019-17476/official-release-of-emfac2017-motor-vehicle-emission-factor-model-for-use-in-the-state-of-california [Accessed 9th Nov. 2019].
Abou SH, Radwan S, Westerlund K, Cooper D. Using a traffic simulation model (VISSIM) with an emissions model (MOVES) to predict emissions from vehicles on a limited-access highway. Journal of the Air and Waste Management Association. 2013;63(7): 819-831. DOI: 10.1080/10962247.2013.795918
Hirschmann K, Zallinger M, Fellendorf M, Hausberger S. A new method to calculate emissions with simulated traffic conditions. 13th International IEEE Annual Conference on Intelligent Transportation Systems, Portugal; 2010. p. 33-38. DOI: 10.1109/ITSC.2010.5625030
Song G, Yu L, Zhang Y. Applicability of Traffic Microsimulation Models in Vehicle Emissions Estimates: Case Study of VISSIM. Journal of the Transportation Research Board. 2012;2270(1): 132-141. DOI: 10.3141/2270-16
Stathopoulos FG, Noland RB. Induced Travel and Emissions from Traffic Flow Improvement Projects. Journal of the Transportation Research Board. 2003;1842(1): 57-63. DOI: 10.3141/1842-07
Simulation of Urban Mobility. Passenger Car and Heavy Duty Emission Model. Available from: https://sumo.dlr.de/docs/Models/Emissions/PHEMlight.html [Accessed 19th Nov. 2019]
The Handbook of Emission Factors for Road Transport. Available from: https://www.hbefa.net/e/index.html [Accessed 19th Nov. 2019].
Papson A, Hartley S, Kuo KL. Analysis of Emissions at Congested and Uncongested Intersections with Motor Vehicle Emission Simulation 2010. Journal of the Transportation Research Board. 2012;2270: 124-131. DOI: 10.3141/2270-15
European Environment Agency. COPERT III: Computer programme to calculate emissions from road transport. Available online: https://www.eng.auth.gr/mech0/lat/copert/C3v2_1MR.pdf [Accessed 13th Nov. 2019].
Forehead H, Huynh N. Review of modelling air pollution from traffic at street-level – The state of the science. Environmental Pollution. 2018;241: 775-786. DOI: 10.1016/j.envpol.2018.06.019
Primorsko-goranska County. Population. Available from: https://www.pgz.hr/Nas_kraj/Stanovnistvo [Accessed 1st Dec. 2019].
Croatian Bureau of Statistics. Statistical Yearbook of the Republic of Croatia. Available from: https://www.dzs.hr/ [Accessed 3rd Dec. 2019].
Department of City Administration for development, urbanism, ecology and land management. Spatial Plan of City of Rijeka. Available from: https://www.rijeka.hr/teme-za-gradane/stanovanje-i-gradnja/urbanisticko-planiranje-2/prostorni-planovi/prostorni-plan-uredenja-grada-rijeke/ [Accessed 4th Dec. 2019].
Traffic Control Center Rijeka promet d.d. Road Categorization. Available from: http://www.rijekapromet.hr/hr/kategorizacija_cesta/433/69 [Accessed 1st Dec. 2019].
Centar za vozila Hrvatske (Department of Motor Vehicles). Available from: https://www.cvh.hr/naslovnica/ [Accessed 5th Dec. 2019].
Primorsko-goranska County Police Administration. Available from: https://primorsko-goranska-policija.gov.hr/ [Accessed 5th Dec. 2019].
Copyright (c) 2021 Livia Maglić, Tomislav Krljan, Neven Grubišić, Lovro Maglić
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).