Comparative assessment of road transport technologies

The aim of the paper is to assess energy technologies in road transport sector in terms of atmospheric emissions and costs and to indicate the most competitive and environmentally friendly transport technologies. The main tasks of the paper are: to develop the multi-criteria framework for comparative assessment of energy technologies in road transport and to apply MCDM methods for the transport technologies assessment. One of the MCDM methods, viz. the interval TOPSIS method, is employed in order to tackle the uncertain criteria. The assessment framework allows comparing road transport technologies in terms of their environmental and economic impacts and facilitates decision making process in transport sector. The main indicators selected for technologies assessment are: private costs and life cycle emissions of the main pollutants (GHG; particulates, NOx, CO, HCs). The ranking of road transport technologies based on private costs and atmospheric emissions allowed prioritizing these technologies in terms of environmental friendliness the lowest costs. However the extent, capacity, and quality of road infrastructure affects the overall level of transportation activity, which in turn affects how much energy is consumed by vehicles and the amount of greenhouse gases (GHG) emitted. The paper presents the impact of transportation infrastructure on GHG emissions from road vehicles and policy implications of performed assessment.

[1]  Aymeric Rousseau,et al.  Impact of Real World Drive Cycles on PHEV Fuel Efficiency and Cost for Different Powertrain and Battery Characteristics , 2009 .

[2]  Mohammad Izadikhah,et al.  An algorithmic method to extend TOPSIS for decision-making problems with interval data , 2006, Appl. Math. Comput..

[3]  Mark A. Delucchi,et al.  A Retail and Lifecycle Cost Analysis of Hybrid Electric Vehicles , 2006 .

[4]  E. Zavadskas,et al.  Performance evaluating of rural ICT centers (telecenters), applying fuzzy AHP, SAW-G and TOPSIS Grey, a case study in Iran , 2012 .

[5]  Philippe Delarue,et al.  Possibilities of reduction of the on-board energy for an innovative subway , 2009 .

[6]  Robert Gross,et al.  What policies are effective at reducing carbon emissions from surface passenger transport? - a review of interventions to encourage behavioural andtechnological change , 2009 .

[7]  Mariano Gallo,et al.  A fuel surcharge policy for reducing road traffic greenhouse gas emissions , 2011 .

[8]  Lee Schipper,et al.  Automobile use, fuel economy and CO2 emissions in industrialized countries: Encouraging trends through 2008? , 2011 .

[9]  Andrew D. Jones,et al.  Supporting Online Material for: Ethanol Can Contribute To Energy and Environmental Goals , 2006 .

[10]  Ridvan Arslan,et al.  An evaluation of the alternative transport fuel policies for Turkey , 2010 .

[11]  Constantine Samaras,et al.  Life cycle assessment of greenhouse gas emissions from plug-in hybrid vehicles: implications for policy. , 2008, Environmental science & technology.

[12]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[13]  T. Sterner.  Fuel taxes : An important instrument for climate policy , 2007 .

[14]  Dragisa Stanujkic,et al.  Extension of Ratio System Part of MOORA Method for Solving Decision-Making Problems with Interval Data , 2012, Informatica.

[15]  E. Løken.  Use of multicriteria decision analysis methods for energy planning problems , 2007 .

[16]  Todd Litman,et al.  Generated Traffic and Induced Travel , 2013 .

[17]  Jurate Sliogeriene,et al.  Comparative assessment of future motor vehicles under various climate change mitigation scenarios , 2011 .