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1.
Environ Pollut ; 265(Pt A): 114983, 2020 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-32590240

RESUMEN

This study presents the results of an integrated model developed to evaluate the environmental and health impacts of Electric Vehicle (EV) deployment in a large metropolitan area. The model combines a high-resolution chemical transport model with an emission inventory established with detailed transportation and power plant information, as well as a framework to characterize and monetize the health impacts. Our study is set in the Greater Toronto and Hamilton Area (GTHA) in Canada with bounding scenarios for 25% and 100% EV penetration rates. Our results indicate that even with the worst-case assumptions for EV electricity supply (100% natural gas), vehicle electrification can deliver substantial health benefits in the GTHA, equivalent to reductions of about 50 and 260 premature deaths per year for 25% and 100% EV penetration, compared to the base case scenario. If EVs are charged with renewable energy sources only, then electrifying all passenger vehicles can prevent 330 premature deaths per year, which is equivalent to $3.8 Billion (2016$CAD) in social benefits. When the benefit of EV deployment is normalized per vehicle, it is higher than most incentives provided by the government, indicating that EV incentives can generate high social benefits.


Asunto(s)
Electricidad , Emisiones de Vehículos/análisis , Canadá , Clima , Transportes
2.
Environ Res ; 183: 109193, 2020 04.
Artículo en Inglés | MEDLINE | ID: mdl-32036271

RESUMEN

Commercial vehicle movements have a large effect on traffic-related air pollution in metropolitan areas. In the Greater Toronto and Hamilton Area (GTHA), commercial vehicles include large and medium diesel trucks as well as light-duty gasoline-fuelled trucks. In this study, the emissions of various air pollutants associated with diesel commercial vehicles were estimated and their impacts on urban air quality, population exposure, and public health were quantified. Using data on diesel trucks in the GTHA and a chemical transport model at a spatial resolution of 1 km2, the contribution of commercial diesel movements to air quality was estimated. This contribution amounts to about 6-22% of the mean population exposure to nitrogen dioxide (NO2) and black carbon (BC), depending on the municipality, but is systematically lower than 3% for fine particulate matter (PM2.5) and ozone (O3). Using a comparative risk assessment approach, we estimated that the emissions of all diesel commercial vehicles within the GTHA are responsible for an annual total of at least 9810 Years of Life Lost (YLL), corresponding to $3.2 billion of annual social costs. We also assessed the impact of decreasing freeway-sourced diesel emissions along Highway 401, one of the busiest highways in North America. This is comparable with a removal of 250 to 1000 diesel trucks per day along that corridor, which could be replaced by alternative technologies. The mean NO2 and BC exposures of the population living within 500 m of the highway would decrease by 9% and 11%, respectively, with reductions as high as 22%. Such a measure would save 1310 YLL annually, equivalent to $428 million in social benefits.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Emisiones de Vehículos , Contaminación del Aire/prevención & control , Comercio , Monitoreo del Ambiente , Vehículos a Motor , América del Norte , Material Particulado , Transportes
3.
Environ Sci Technol ; 53(13): 7903-7912, 2019 Jul 02.
Artículo en Inglés | MEDLINE | ID: mdl-31244061

RESUMEN

To estimate greenhouse gas (GHG) emission reductions of electric vehicles (EVs) deployment, it is important to account for emissions from electricity generation. Since such emissions change according to temporal patterns of electricity generation and EV charging, this study operationalizes the concept of marginal emission factors (MEFs) and uses person-level travel activity data to simulate charging scenarios. Our study is set in the Greater Toronto and Hamilton Area in Ontario, Canada. After generating hourly MEFs using a multiple linear regression model, we estimated GHG emissions for EV charging at two EV penetration rates, 5% and 30%, and five charging scenarios: home, work and shopping, night, downtown vs suburb, and an optimal low emission charging scenario, matching charging time with the lowest available MEF. We observed that vehicle electrification substantially reduces GHG emissions, even when using MEFs that are up to seven times higher than average electricity emission factors. With Ontario's 2017 electricity generation mix, EVs achieve over 80% lower fuel cycle emissions compared with equivalent sets of gasoline vehicles. At 5% penetration, night charging nearly matches low emission charging, but night charging emissions increase with 30% EV penetration, suggesting a need for policy that can smooth out charging demand after midnight.


Asunto(s)
Gases de Efecto Invernadero , Electricidad , Efecto Invernadero , Ontario , Emisiones de Vehículos
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