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We present a dynamic perspective to quantify the air quality-related health impacts of the electrification of light-duty vehicles in the United States between 2022 and 2050. Using a fleet turnover model and future electricity generation mix scenarios, we compare ambitious vehicle electrification to fleet renewal relying on newer internal combustion engine vehicles, without electric vehicles. The model includes vehicle-level pollutant emission factors and a reduced complexity air quality and valuation model and covers direct (tailpipe, brake wear, and tire wear) and indirect (production of electricity and liquid fuels) emissions of NO x , SO 2 , PM 2.5 , NH 3 , and VOCs, with a breakdown at the county level to identify geographical disparities in the distribution of health impacts. Short-term health benefits are mostly generated by reductions in NO x emissions from newer gasoline vehicles, while fleet electrification generates further benefits in the long term. The electricity mix plays a crucial role in the success of electrification policies. With continued grid decarbonization, electrification would reduce harmful air quality-related health impacts cumulatively by 84 to 188 billion USD over the study period, compared with fleet renewal without electric vehicles. In contrast, artificially freezing the 2022 grid would make electrification responsible for 32 to 71 billion USD additional health disbenefits compared with fleet renewal. Finally, we show that while fleet electrification achieves most of its benefits over fleet renewal in the long term, delaying the implementation of such policies would sacrifice meaningful cumulative benefits., Competing Interests: Competing interests statement:A. Abdul-Manan is employed by Saudi Aramco. The research was funded in part by Saudi Aramco Technologies Company. The authors retained scientific independence in pursuing this work and no editorial control was exercised by the sponsor.

A sustainable low-carbon transition via electric vehicles will require a comprehensive understanding of lithium-ion batteries' global supply chain environmental impacts. Here, we analyze the cradle-to-gate energy use and greenhouse gas emissions of current and future nickel-manganese-cobalt and lithium-iron-phosphate battery technologies. We consider existing battery supply chains and future electricity grid decarbonization prospects for countries involved in material mining and battery production. Currently, around two-thirds of the total global emissions associated with battery production are highly concentrated in three countries as follows: China (45%), Indonesia (13%), and Australia (9%). On a unit basis, projected electricity grid decarbonization could reduce emissions of future battery production by up to 38% by 2050. An aggressive electric vehicle uptake scenario could result in cumulative emissions of 8.1 GtCO 2 eq by 2050 due to the manufacturing of nickel-based chemistries. However, a switch to lithium iron phosphate-based chemistry could enable emission savings of about 1.5 GtCO 2 eq. Secondary materials, via recycling, can help reduce primary supply requirements and alleviate the environmental burdens associated with the extraction and processing of materials from primary sources, where direct recycling offers the lowest impacts, followed by hydrometallurgical and pyrometallurgical, reducing greenhouse gas emissions by 61, 51, and 17%, respectively. This study can inform global and regional clean energy strategies to boost technology innovations, decarbonize the electricity grid, and optimize the global supply chain toward a net-zero future., (© The Author(s) 2023. Published by Oxford University Press on behalf of National Academy of Sciences.)

Lifestyle choices and consumption play a large role in contributing to per capita greenhouse gas emissions. Certain activities, like fossil fuel ground transportation, long-haul flights, diets with animal products and residential heating and cooling contribute significantly to per capita emissions. There is uncertainty around whether literacy about these actions encourages individuals to act pro-environmentally to reduce personal carbon footprints or to prioritize the most effective actions. This study investigated the relationship between carbon literacy and pro-environmental actions performed to reduce greenhouse gas emissions among undergraduate engineering students at the University of Toronto. The pro-environmental actions by the participants produced an average carbon footprint of 4.8 tCO 2 (within the subset of actions included in the survey) which was lower than the average for residents each of Toronto, Ontario, and Canada overall but still higher than the global target of ∼2.8 tCO 2 e. The carbon literacy by participants was best for high impact actions like ground transportation and dietary choices but less so for air travel and there was mixed awareness for the moderate and low impact actions. For high impact actions and many moderate and low impact actions, participants who thought the action was high impact (even if incorrect) had lower carbon footprints related to the associated activity than those who thought the action was moderate or low impact. The overall relationship between pro-environmental action and carbon literacy was weak. It showed that for high impact actions, there is a slight negative correlation between carbon literacy and personal carbon footprint whereas for moderate and low impact actions, there is a positive correlation., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Sherry-Ann Ram reports financial support was provided by 10.13039/501100004489Mitacs Research Training Award. Sherry-Ann Ram, I. Daniel Posen, Heather MacLean, Deborah Tihanyi reports a relationship with 10.13039/501100003579University of Toronto Faculty of Applied Science & Engineering that includes: employment and funding grants. As a follow-up to the response provided in Question 2, authors I. Daniel Posen, Heather MacLean, Deborah Tihanyi are professors and Sherry-Ann Ram is a PhD student at the University of Toronto within the Faculty of Applied Science and Engineering. This is the Faculty in which the survey for the study was administered., (© 2023 The Authors.)

Cold weather operability is sometimes a limiting factor in the use of biodiesel blends for transportation. Regional temperature variability can therefore influence biodiesel adoption, with potential economic and environmental implications. This study assesses present and future biodiesel cold weather operability limits in North America according to temperature data from weather stations, atmospheric reanalysis, and global climate models with highest resolution over Ontario, Canada. Future temperature projections using the RCP8.5 climate change scenario show increases in the potential duration for certain seasonal fuel blends. For example, biodiesel blends whose cloud point temperature is -9 °C may expand their duration by 3-7% in North America for nonwinter seasons according to projections for 2040. Cloud point specifications among supply orbits in Ontario increase up to +6 °C during nonwinter seasons, with most increases observed in Fall and Spring. In winter, however, the modeling suggests no change in Ontario cloud point specifications because the coldest temperatures by mid-century are not significantly warmer than the past climate normal according to our climate simulations. This study provides a quantitative analysis on biodiesel usage scenarios under a changing climate, including Ontario region geographic temperature clusters that could prove useful for biodiesel blend-related decision-making.

Urban passenger land transport is an important source of greenhouse gas (GHG) emissions globally, but it is challenging to mitigate these emissions as this sector interacts with many other economic sectors. We develop the Climate change constrained Urban passenger Transport Integrated Life cycle assessment (CURTAIL) model to outline mitigation pathways of urban passenger land transport that are consistent with ambitious climate targets. CURTAIL uses the transport activity of exogenously defined modal shares to simulate the associated annual vehicle stocks, sales, and life cycle GHG emissions. It estimates GHG emission budgets that are consistent with global warming below 2 and 1.5 °C above preindustrial levels and seeks mitigation strategies to remain within the budgets. We apply it to a case study of Singapore, a city-state. Meeting a 1.5 °C target requires strong commitments in the transport and electricity sectors, such as reducing the motorized passenger activity, accelerating the deployment of public transit and of electrification, and decarbonizing the power generation system. Focusing on one mitigation technology or one mode of transport alone will not be sufficient to meet the target. Our novel model could be applied to any city to provide insights relevant to the design of urban climate change mitigation targets and policies.

Green policies currently incentivize concrete producers to replace portland cement with industrial byproducts to reduce their greenhouse gas (GHG) emissions. However, policies are based on attributional life cycle assessments (LCAs) that do not account for market constraints and consider byproducts either available burden-free to the user (cutoff approach) or partially responsible for the emissions generated in the upstream processes (allocation). The goal of this study was to investigate whether these approaches (and incentives) could lead to a mismanagement of byproducts and to suboptimal solutions in terms of regional GHG emissions. The use of ground granulated blast-furnace slag (GGBS) in Ontario was studied, and an optimization model to find the least GHG-intense way of using GGBS was developed. Results showed that producers should replace 30 to 40% of portland cement in high-strength concrete to minimize the regional GHG emissions associated with concrete. However, traditional LCA approaches do not suggest this solution and are estimated to lead to up to a 10% increase in concrete GHG emissions in Ontario. The substitution method, which assigns emissions or credits to byproducts based on emissions associated with the products they may displace, can yield decisions consistent with the regional emission optimization model. A revision of current policies is recommended to include market constraints.

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

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 km 2 , 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 (NO 2 ) and black carbon (BC), depending on the municipality, but is systematically lower than 3% for fine particulate matter (PM 2.5 ) and ozone (O 3 ). 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 NO 2 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., (Copyright © 2020 Elsevier Inc. All rights reserved.)

A key motivation behind the development and adoption of industrial biotechnology is the reduction of negative environmental impacts. However, accurately assessing these impacts remains a formidable task. Environmental impacts of industrial biotechnology may be significant across a number of categories that include, but may not be limited to, nonrenewable resource depletion, water withdrawals and consumption, climate change, and natural land transformation/occupation. In this chapter, we highlight some key environmental issues across two broad areas: (a) processes that use biobased feedstocks and (b) industrial activity that is supported by biological processes. We also address further issues in accounting for related environmental impacts such as geographic and temporal scope, co-product management, and uncertainty and variability in impacts. Case studies relating to (a) lignocellulosic ethanol, (b) biobased plastics, and (c) enzyme use in the detergent industry are then presented, which illustrate more specific applications. Finally, emerging trends in the area of environmental impacts of biotechnology are discussed.

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.

Substituting conventional materials with lightweight materials is an effective way to reduce the life cycle greenhouse gas (GHG) emissions from light-duty vehicles. However, estimated GHG emission reductions of lightweighting depend on multiple factors including the vehicle powertrain technology and efficiency, lightweight material employed, and end-of-life material recovery. We developed a fleet-based life cycle model to estimate the GHG emission changes due to lightweighting the U.S. light-duty fleet from 2016 to 2050, using either high strength steel or aluminum as the lightweight material. Our model estimates that implementation of an aggressive lightweighting scenario using aluminum reduces 2016 through 2050 cumulative life cycle GHG emissions from the fleet by 2.9 Gt CO 2 eq (5.6%), and annual emissions in 2050 by 11%. Lightweighting has the greatest GHG emission reduction potential when implemented in the near-term, with two times more reduction per kilometer traveled if implemented in 2016 rather than in 2030. Delaying implementation by 15 years sacrifices 72% (2.1 Gt CO 2 eq) of the cumulative GHG emission mitigation potential through 2050. Lightweighting is an effective solution that could provide important near-term GHG emission reductions especially during the next 10-20 years when the fleet is dominated by conventional powertrain vehicles.

Fuel economy standards, driver behavior, and biofuel mandates are driving a decline in the Gasoline-to-Diesel ratio (G:D) in U.S. refineries. This paper investigates the GHG implications associated with two methods available to shift refinery output: 1) refinery operational changes and 2) input crude slate variation. This analysis uses an open-source refinery GHG emissions model, PRELIM. Newly developed modeling capabilities and publicly available data are used to present Petroleum Administration for Defense District (PADD) level results (energy consumption and GHG emissions) for U.S. refineries. The results are indicative of negligible changes in the U.S. refining GHG emissions on a country level (∼3%), while variations up to 8% are observed within individual regions. Meeting the 2040 national G:D projections may require drastic changes to the current U.S. crude mix (e.g., more than 30% shift from the current U.S. crude mix), which could increase the U.S. refining GHG emissions by 25%. The analysis provides insights about future changes in refining GHG emissions due to a shift in product demand and a framework for additional analyses such as evaluation of crude market changes or biofuel blending on refining GHG emissions that can inform development of environmental regulations such as low carbon fuel standards.

Interest in biobased products has been motivated, in part, by the claim that these products have lower life cycle greenhouse gas (GHG) emissions than their fossil counterparts. This study investigates GHG emissions from U.S. production of three important biobased polymer families: polylactic acid (PLA), polyhydroxybutyrate (PHB) and bioethylene-based plastics. The model incorporates uncertainty into the life cycle emission estimates using Monte Carlo simulation. Results present a range of scenarios for feedstock choice (corn or switchgrass), treatment of coproducts, data sources, end of life assumptions, and displaced fossil polymer. Switchgrass pathways generally have lower emissions than corn pathways, and can even generate negative cradle-to-gate emissions if unfermented residues are used to coproduce energy. PHB (from either feedstock) is unlikely to have lower emissions than fossil polymers once end of life emissions are included. PLA generally has the lowest emissions when compared to high emission fossil polymers, such as polystyrene (mean GHG savings up to 1.4 kg CO2e/kg corn PLA and 2.9 kg CO2e/kg switchgrass PLA). In contrast, bioethylene is likely to achieve the greater emission reduction for ethylene intensive polymers, like polyethylene (mean GHG savings up to 0.60 kg CO2e/kg corn polyethylene and 3.4 kg CO2e/kg switchgrass polyethylene).

The narrow scope of the U.S. renewable fuel standard (RFS2) is a missed opportunity to spur a wider range of biomass use. This is especially relevant as RFS2 targets are being missed due to demand-side limitations for ethanol consumption. This paper examines the greenhouse gas (GHG) implications of a more flexible policy based on RFS2, which includes credits for chemical use of bioethanol (to produce bioethylene). A Monte Carlo simulation is employed to estimate the life-cycle GHG emissions of conventional low-density polyethylene (LDPE), made from natural gas derived ethane (mean: 1.8 kg CO2e/kg LDPE). The life-cycle GHG emissions from bioethanol and bio-LDPE are examined for three biomass feedstocks: U.S. corn (mean: 97g CO2e/MJ and 2.6 kg CO2e/kg LDPE), U.S. switchgrass (mean: -18g CO2e/MJ and -2.9 kg CO2e/kg LDPE), and Brazilian sugar cane (mean: 33g CO2e/MJ and -1.3 kg CO2e/kg LDPE); bioproduct and fossil-product emissions are compared. Results suggest that neither corn product (bioethanol or bio-LDPE) can meet regulatory GHG targets, while switchgrass and sugar cane ethanol and bio-LDPE likely do. For U.S. production, bioethanol achieves slightly greater GHG reductions than bio-LDPE. For imported Brazilian products, bio-LDPE achieves greater GHG reductions than bioethanol. An expanded policy that includes bio-LDPE provides added flexibility without compromising GHG targets.