Capturing uncertainty in emission estimates related to vehicle electrification and implications for metropolitan greenhouse gas emission inventories
| Autor: | James Vaughan, Lucas Pereira, Ran Tu, Marianne Hatzopoulou, Eric J. Miller, I. Daniel Posen, Yijun Gai, An Wang |
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| Rok vydání: | 2020 |
| Předmět: |
business.product_category
020209 energy Mechanical Engineering 02 engineering and technology Building and Construction Energy consumption Management Monitoring Policy and Law Environmental economics 7. Clean energy Metropolitan area General Energy Electrification 020401 chemical engineering 13. Climate action Greenhouse gas 11. Sustainability Electric vehicle 0202 electrical engineering electronic engineering information engineering Environmental science 0204 chemical engineering Gasoline business Tonne Robustness (economics) |
| Zdroj: | Applied Energy. 265:114798 |
| ISSN: | 0306-2619 |
| DOI: | 10.1016/j.apenergy.2020.114798 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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