Capturing uncertainty in emission estimates related to vehicle electrification and implications for metropolitan greenhouse gas emission inventories

An Wang, Ran Tu, Yijun Gai, Lucas G. Pereira, J. Vaughan, I. Daniel Posen, Eric J. Miller and Marianne Hatzopoulou

Applied Energy, 2020, vol. 265, issue C, No S030626192030310X

Abstract: Various sources of uncertainty exist in current on-road emission and energy consumption modelling approaches, which could affect the evaluation of energy and power distribution systems and related policies. These uncertainties are ever more pertinent today as urban transportation systems undergo drastic changes. This study presents a greenhouse gas emission and energy consumption accounting approach for on-road transportation, developed to estimate well-to-wheel emission distributions for household gasoline and electric vehicles, while capturing specific sources of uncertainty in the modelling process. Using data for Greater Toronto and Hamilton, the combined effects of vehicle electrification and well-to-wheel emission uncertainty were investigated. Under the base case, and for the study years 2011 and 2017, mean values for daily regional greenhouse gas emissions from household transportation, were estimated at 31,000 and 29,000 metric tons of CO2eq. The results of the policy scenarios present insight into the effectiveness of electric vehicles at reducing emissions and point out possible risks of using deterministic and single point estimates in policy appraisal. A sensitivity analysis demonstrates that well-to-tank emissions have the largest uncertainty, while tank-to-wheel emissions contribute the most to total uncertainty as they make up 75% of total emissions.

Keywords: Well-to-wheel emissions; Road transport; Uncertainty; Greenhouse gases; Emission distribution; Energy consumption; Electric vehicle; Monte-Carlo simulation; Stochasticity; Decision-making; Robustness (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (4)

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DOI: 10.1016/j.apenergy.2020.114798

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