Detailed assessment of global transport-energy models’ structures and projections

• Published in: Transportation research. Part D, Transport and environment Vol. 55; no. C; pp. 294 - 309
• Main Authors: Yeh, Sonia, Mishra, Gouri Shankar, Fulton, Lew, Kyle, Page, McCollum, David L., Miller, Joshua, Cazzola, Pierpaolo, Teter, Jacob
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.08.2017; Elsevier
• Subjects: Climate mitigation; ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; Energy use; GCAM; GHG emissions; integrated assessment; Model comparison; model intercomparison; transportation; Transportation behaviors; Transportation demand; Transportation scenarios; Climate mitigation; Transportation behaviors; Transportation scenarios; Energy use; GHG emissions; Model comparison; Transportation demand
• DOI: 10.1016/j.trd.2016.11.001
• ISSN: 1361-9209

•We compare major global transportation models with considerable technology details to 2050.•There are significant differences in the base-year data and key parameters for future projections.•Main GHG mitigation differs for economics IA models vs transport-only expert models.•Significant EV gaps between policy targets and model trajectories to 2°C target.•We offer suggestions on access to data, model improvements, and future comparisons. This paper focuses on comparing the frameworks and projections from four global transportation models with considerable technology details. We analyze and compare the modeling frameworks, underlying data, assumptions, intermediate parameters, and projections to identify the sources of divergence or consistency, as well as key knowledge gaps. We find that there are significant differences in the base-year data and key parameters for future projections, especially for developing countries. These include passenger and freight activity, mode shares, vehicle ownership rates, and energy consumption by mode, particularly for shipping, aviation and trucking. This may be due in part to a lack of previous efforts to do such consistency-checking and “bench-marking.” We find that the four models differ in terms of the relative roles of various mitigation strategies to achieve a 2°C/450ppm target: the economics-based integrated assessment models favor the use of low carbon fuels as the primary mitigation option followed by efficiency improvements, whereas transport-only and expert-based models favor efficiency improvements of vehicles followed by mode shifts. We offer recommendations for future modeling improvements focusing on (1) reducing data gaps; (2) translating the findings from this study into relevant policy implications such as gaps of current policy goals, additional policy targets needed, regional vs. global reductions; (3) modeling strata of demographic groups to improve understanding of vehicle ownership levels, travel behavior, and urban vs. rural considerations; and (4) conducting coordinated efforts in aligning historical data, and comparing input assumptions and results of policy analysis and modeling insights.