Where does the Development of Road Transport Emission Macro Modelling Lead?

Mohammad Maghrour Zefreh, Adam Torok

Abstract

In recent years, road transport models have developed for better estimation of road traffic emissions with higher and higher temporal and spatial resolution, to be used as a tool in air quality management for the better living. Road transport related emission models are becoming more and more complex. In this paper, the key research question is how the improvement in modelling influences the results? The authors compared three different macro emission modelling system with the dataset of Hungary for 2010. One must notice that more precise model has larger data requirement. Firstly, the consumption-based model was run with 31 needed input data secondly, EURO standard based model was run with 261 needed data and finally, speed dependent model was run with 1060 needed input data. According to the results, it can be stated that a more complex model could cause significant differences in emission compared to simpler one. The differences can be caused by old Hungarian vehicle fleet or differences in estimation error.

References

  1. Ahrens, C.D., 2003. Meteorology today: an introduction to weather, climate, and the environment. Thomson/Brooks/Cole.
  2. André, M, Rapone, M, Adra, N, Poliák, J, Keller, M and McCrae, I (2006) Traffic characteristics for the estimation of the pollutant emissions from road transport - ARTEMIS WP1000 project. Report INRETS-LTE 0606.
  3. Andreoni, V., and Galmarini, S. (2012): European CO2 emission trends: A decomposition analysis for water and aviation transport sectors. Energy 45:595-602. doi: 10.1016/j.energy.2012.07.039.
  4. Astarita, V., Guido, G., Mongelli, D., & Giofrè, V. P. (2015). A co-operative methodology to estimate car fuel consumption by using smartphone sensors. Transport,30(3):307-311. doi: 10.3846/16484142.201 5.1081280.
  5. Axhausen, K.W., & Gärling, T. (1992). Activity-based approaches to travel analysis: Conceptual frameworks, models, and research problems. Transport Reviews, 12, 323-341.
  6. Azar, C., Lindgren, K., and Andersson, B.A. (2003): Global energy scenarios meeting stringent CO2 constraints-cost-effective fuel choices in the transportation sector. Energy Policy 31:961-976. doi: 10.1016/S0301-4215(02)00139-8.
  7. Barabás, I. (2015). Liquid densities and excess molar volumes of ethanol+ biodiesel binary system between the temperatures 273.15 K and 333.15 K. Journal of Molecular Liquids, 204:95-99. doi: 10.1016/j.molliq. 2015.01.048.
  8. Brand, C., Tran, M., & Anable, J. (2012). The UK transport carbon model: An integrated life cycle approach to explore low carbon futures. Energy Policy, 41, 107-124.
  9. Csikós, A., Tettamanti, T., Varga, I. (2015). Macroscopic modeling and control of emission in urban road traffic networks. Transport, 30(2), 152-161. doi: 10.3846/16 484142.2015.1046137.
  10. European Commission (1999). MEET: Methodology for calculating transport emissions and energy consumption. Office for Official Publications of the European Communities, L-2985 Luxembourg.
  11. European Environmental Agency (2015): Air quality in Europe - 2015 report, Luxembourg, ISBN 978-92- 9213-702-1.
  12. Fenger, J., 1999. Urban air quality. Atmospheric Environment 33(29), 4877-4900.
  13. Husnjak, S., Forenbacher, I., & Bucak, T. (2015). Evaluation of Eco-Driving Using Smart Mobile Devices. PROMET-Traffic&Transportation, 27(4), 335-344. doi: http://dx.doi.org/10.7307/ptt.v27i4.1712.
  14. Lakatos, I. (2015). Development of a New Method for Comparing the Cold Start-and the Idling Operation of Internal Combustion Engines. Periodica Polytechnica Transportation Engineering, 43(4), 225-231. doi: 10.3311/PPtr.8087.
  15. Li, Q., Guo, R. Y., & Yang, W. J. (2015): An EmissionsBased User Equilibrium Model and Algorithm for Left-turn Prohibition Planning. PROMETTraffic&Transportation,27(5):379-386. doi: http://dx. doi.org/10.7307/ptt.v27i4.1712.
  16. Liu, R. (2007). DRACULA 2.4 user manual. Leeds: Institute for Transport Studies.
  17. Mcnally, M. G., & Rindt, C. R. (2008). The activity-based approach. In D. A. Hensher & K. J. Button (Eds.), Handbook of transport modelling (2nd ed., pp. 55-72). Oxford: Elsevier.
  18. PTV Group. (2015). Emissions modelling. Retrieved January 16, 2015, from http://vision-traffic.ptvgr oup.com/en-us/products/ptv-vissim/use-cases/emission s-modelling/
  19. Samaras, Z., Ntziachristos, L., Burzio, G., Toffolo, S., Tatschl, R., Mertz, J., & Monzon, A. (2012). Development of a methodology and tool to evaluate the impact of ICT measures on road transport emissions. In P. Papaioannou (Ed.), Transport Research Arena 2012 (pp. 3418-3427). Amsterdam: Elsevier Science.
  20. Stamos, I., Salanova Grau, J. M., Mitsakis, E., & Mamarikas, S. (2015). Macroscopic Fundamental Diagrams: Simulation Findings For Thessaloniki's Road Network. International Journal for Traffic & Transport Engineering, 5(3):225-237 doi: 10.7708/ijtte.2015.5(3).01.
  21. Stern, N. (2007). The economics of climate change: The stern review. Cambridge: Cambridge University Press.
  22. Szendro G, Török A (2014): Theoretical Investigation of Environmental Development Pathways in the Road Transport Sector in the European Region, Transport 29(1):12-17, doi:10.3846/16484142.2014.893538.
  23. Tosa, C., Antov, D., Köllo, G., Rõuk, H., & Rannala, M. (2015). A methodology for modelling traffic related emissions in suburban areas. Transport, 30(1), 80-87. doi: 10.3846/16484142.2013.819034.
  24. Török Ádám (2015): Development path of road transport CO2 modelling, In: Stanislaw Szwaja, Technologia uprawy mikroglonów w bioreaktorach zamknietych z recyklingiem CO2 i innych odpadów z biogazowni. Konferencia helye, ideje: Kroczyce, Lengyelország, 2015.11.17-2015.11.20. Czestochowa: Instytut Maszyn Cieplnych Politechnika Czestochowska, pp. 343-348. (ISBN:978-83-942332-1-1).
  25. Tutak, W., Lukács, K., Szwaja, S., & Bereczky, Á. (2015). Alcohol-diesel fuel combustion in the compression ignition engine. Fuel, 154:196-206, doi: 10.1016/j.fuel.2015.03.071.
  26. Verkehr, P. T. (2011). VISSIM 5.30-05 user manual. Karlsruhe: Germany.
  27. Wismans, L., Van Berkum, E., & Bliemer, M. (2011). Modelling externalities using dynamic traffic assignment models: A review. Transport Reviews, 31, 521-545.
  28. Zachariadis, Th. and Samaras, Z (1997) Comparative assessment of European tools to estimate traffic emissions. International Journal of Vehicle Design, 18 (3/4), 312-325.
  29. Zöldy, M., & Török, Á. (2015). Road Transport Liquid Fuel Today and Tomorrow: Literature Overview. Periodica Polytechnica Transportation Engineering, 43(4):172-176. doi: 10.3311/PPtr.8095.
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Paper Citation


in Harvard Style

Zefreh M. and Torok A. (2016). Where does the Development of Road Transport Emission Macro Modelling Lead? . In Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS, ISBN 978-989-758-184-7, pages 100-104. DOI: 10.5220/0005901801000104


in Bibtex Style

@conference{smartgreens16,
author={Mohammad Maghrour Zefreh and Adam Torok},
title={Where does the Development of Road Transport Emission Macro Modelling Lead?},
booktitle={Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,},
year={2016},
pages={100-104},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005901801000104},
isbn={978-989-758-184-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,
TI - Where does the Development of Road Transport Emission Macro Modelling Lead?
SN - 978-989-758-184-7
AU - Zefreh M.
AU - Torok A.
PY - 2016
SP - 100
EP - 104
DO - 10.5220/0005901801000104