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Explora: Environment
            and Resource                                                        WTW emissions of road and rail transport



            3.  BITRE. Australian Infrastructure and Transport Statistics-  15.  Hastie T, Tibshirani R, Friedman J. The Elements of Statistical
               Yearbook; 2022. Canberra: Bureau of Infrastructure and   Learning. 2  ed. Berlin, Heidelberg, Germany: Springer; 2017.
                                                                          nd
               Transport Research Economics.
                                                               16.  TER. Net Zero Vehicle Emission Model (n0vem). Transport
            4.  DCCEEW. Australia’s Emissions Projections 2022; 2022.   Energy/Emission Research; 2023. Available from: https://
               Canberra: Australian Government Department of Climate   www.transport-e-research.com/software-novem  [Last
               Change, Energy, the Environment and Water.         accessed on 2023 Nov 20].
            5.   Smit R. An independent and detailed assessment of   17.  ABS.  Survey of Motor Vehicle Use, Australia, 12 Months
               greenhouse gas emissions, fuel use, electricity and energy   Ended 30  June 2018. Canberra: Australian Bureau of
               consumption from Australian road transport in 2019 and   Statistics; 2019.
               2050. Air Qual Clim Change. 2023;57(2):30-41.   18.  Andersson E, Lukaszewicz P.  Energy Consumption and
            6.   Dalkmann H, Brannigan C. Transport and Climate Change.   Related Air Pollution for Scandinavian Electric Passenger
               Module 5e: Sustainable Transport: A Sourcebook for Policy-  Trains. Report KTH/AVE 2006:46. Stockholm, Sweden: KTH
               makers in Developing Cities. Eschborn: Deutsche Gesellschaft   Swedish Royal Institute of Technology; 2006.
               fuer Technische Zusammenarbeit; 2007. Available from:   19.  Pérez-Martínez PJ, Sorba IA. Energy consumption
               https://city2030.org.ua/sites/default/files/documents/  of passenger land transport modes.  Energy Environ.
               giz_sutp_sb5e_transport-and-climate-change_eN.pdf [Last   2010;21(6):577-600.
               accessed on 2023 Nov 10].
                                                                  doi: 10.1260/0958-305X.21.6.577
            7.  CCA. Shifting Gear: The Path to Cleaner Transport. Climate
               Council of Australia; 2023. Available from: https://www.  20.  IUC. High Speed Rail and Sustainability. Paris: International
               climatecouncil.org.au/resources/shifting-gear-the-path-to-  Union of Railways; 2011.
               cleaner-transport [Last accessed on 2023 Nov 10].  21.  Bosquet R, Vandanjon PO, Coiret A, Lorino T. Model of
            8.   Smit R, Kennedy DW. Greenhouse gas emissions     high-speed train energy consumption. World Acad Sci Eng
               performance of electric and fossil-fueled passenger vehicles   Technol Int J Energy Power Eng. 2013;7(6):767-771.
               with uncertainty estimates using a probabilistic life-cycle      doi: 10.5281/zenodo.1079742
               assessment. Sustainability. 2022;14(6):3444.
                                                               22.  TRB. NCRRP Report 3: Comparison of Passenger Rail Energy
               doi: 10.3390/su14063444                            Consumption with Competing Modes. Washington, DC:
            9.   Smit R, Helmers E, Schwingshackl M, Opetnik M,   Transportation Research Board; 2015.
               Kennedy   D. Greenhouse gas emissions performance of   23.  Hasegawa D, Nicholson GL, Roberts C, Schmid   F,
               electric, hydrogen and fossil-fuelled freight trucks with   Nicholson  G.  Standardised  approach  to  energy
               uncertainty estimates using a probabilistic life-cycle   consumption calculations for high-speed rail. IET Electr Syst
               assessment (pLCA). Sustainability. 2024;16(2):762.  Transp. 2016;6(3):179-189.
               doi: 10.3390/su16020762                            doi: 10.1049/iet-est.2015.0002
            10.  ARTC. Inland Rail Programme Business Case. Australian Rail   24.  Dalkic G, Balaban O, Tuydes-Yaman H, Celikkol-Kocak T.
               Track Corporation; 2015. Available from: https://inlandrail.  An assessment of the CO  emissions reduction in high speed
                                                                                    2
               com.au/wp-content/uploads/2020/07/business-case-2015.  rail lines: Two case studies from Turkey.  J  Cleaner Prod.
               pdf [Last accessed on 2023 Nov 10].                2017;165:746-761.
            11.  McCleese DL, LaPuma PT. Using Monte Carlo simulation      doi: 10.1016/j.jclepro.2017.07.045
               in life cycle assessment for electric and internal combustion
               vehicles. Int J Life Cycle Assess. 2002;7:230-236.  25.  Fritz E, Klühspies J, Kircher R, Witt M, Blow L. Energy
                                                                  consumption of track-based high-speed trains: Maglev
               doi: 10.1007/BF02978878                            systems in comparison with wheel-rail systems. Transp Syst
            12.  Bastani P, Heywood JB, Hope C. Fuel use and CO  emissions   Technol. 2018;4(3 Suppl 1):134-155.
                                                  2
               under uncertainty from light-duty vehicles in the U.S. to      doi: 10.17816/transsyst201843s1134-155
               2050. J Energy Resour Technol. 2012;134:42202.
                                                               26.  Prussi M, Lonza L. Passenger aviation and high speed rail:
               doi: 10.1115/1.4007485                             A comparison of emissions profiles on selected European
                                                                  routes. J Adv Transp. 2018;2018:6205714.
            13.  Cullen AC, Frey HC.  Probabilistic Techniques in Exposure
               Assessment, Society of Risk Analysis. Berlin, Germany:      doi: 10.1155/2018/6205714
               Springer Science and Business Media; 1999.
                                                               27.  Chang Y, Lei S, Teng J, Zhang J, Zhang L, Xu X. The energy
            14.  Madachy RJ. Introduction to Statistics of Simulation, Software   use and environmental emissions of high-speed rail
               Process Dynamics. Piscataway, NJ, USA: The Institute of   transportation in China: A  bottom-up modeling.  Energy.
               Electrical and Electronics Engineers, Inc.; 2008.  2019;182(1):193-201.


            Volume 1 Issue 1 (2024)                         16                               doi: 10.36922/eer.3470
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