Abstract
This paper aims to investigate the impact of the built environment (BE) and emerging transit and car technologies on household transport-related greenhouse gas emissions (GHGs) across three urban regions. Trip-level GHG emissions are first estimated by combining different data sources such as origin–destination (OD) surveys, vehicle fleet fuel consumption rates, and transit ridership data. BE indicators for the different urban regions are generated for each household and the impact of neighborhood typologies is derived based on these indicators. A traditional ordinary least square (OLS) regression approach is then used to investigate the direct association between the BE indicators, socio-demographics, and household GHGs. The effect of neighborhood typologies on GHGs is explored using both OLS and a simultaneous equation modeling approach. Once the best models are determined for each urban region, the potential impact of BE is determined through elasticities and compared with the impact of technological improvements. For this, various fuel efficiency scenarios are formulated and the reductions on household GHGs are determined. Once the potential impact of green transit and car technologies is determined, the results are compared to those related to BE initiatives. Among other results, it is found that BE attributes have a statistically significant effect on GHGs. However, the elasticities are very small, as reported in several previous studies. For instance, a 10 % increase in population density will result in 3.5, 1.5 and 1.4 % reduction in Montreal, Quebec and Sherbrooke, respectively. It is also important to highlight the significant variation of household GHGs among neighborhoods in the same city, variation which is much greater than among cities. In the short term, improvements on the private passenger vehicle fleet are expected to be much more significant than BE and green transit technologies. However, the combined effect of BE strategies and private-motor vehicle technological improvement would result in more significant GHGs reductions in the long term.
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Notes
The city of Sherbrooke is the fourth largest metropolitan area in the province of Quebec (after greater Montreal, Quebec city and Gatineau, located in the south of the province.
National Inventory Report 1990–2009 (2011 submission), Environment Canada. (http://www.ec.gc.ca/ges-ghg/default.asp?lang=En&n=AC2B7641-1).
The Quebec government initially adopted its own standards for MY2009 to MY2016. These standards were similar to those adopted in California. However, the Quebec government recently announced that it will align its regulation to the Federal norms.
Specifically, we assume that the age structure of the fleet in 2021 will be the same as in 2008 and that the standards will be met at the level of the province. We also assume that the mix of sales across vehicle footprint for both cars and light trucks will be those observed for MY-2006 to MY-2008.
For comparison, the US DOE (US Department of Energy 2012) estimates that light trucks will account for 39 % of new LDV in 2025.
This is about the penalty used by NHTSA (compare Table I.B.2-1 and 2 of the Federal Register,)Federal Register 2010
The null hypothesis that the BE and car ownership variables are exogenous.
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Acknowledgments
We would like to acknowledge the financial aid provided by Ministère des Transports du Québec (MTQ) and FQRNT. We would also like to thank the AMT and MTQ for providing us with the data necessary for this research, including O-D surveys.
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Zahabi, S.A.H., Miranda-Moreno, L., Patterson, Z. et al. Impacts of built environment and emerging green technologies on daily transportation greenhouse gas emissions in Quebec cities: a disaggregate modeling approach. Transportation 44, 159–180 (2017). https://doi.org/10.1007/s11116-015-9631-0
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DOI: https://doi.org/10.1007/s11116-015-9631-0