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With the expected rapid growth of renewable electricity generation, charging plug-in hybrid electric vehicles (PHEVs) from the grid promise ever higher reductions in CO2 emissions. Previous analyses have found that the share that PHEVs are driven in electric mode can differ substantially depending on region, battery size, and trip purpose. Here, we provide a first fleet-wide emissions mitigation potential of US-based PHEV drivers adopting high or low shares of electric driving. Specifically, we illustrate scenarios of different combinations of PHEV uptake, renewable electricity generation shares, and PHEV fueling behavior. Across 21 analyzed scenarios, annual greenhouse gas (GHG) emissions of the light-duty vehicle (LDV) fleet could differ by an average of 21% (5–43% range) in 2050 depending alone on the fueling behavior of PHEV drivers. This behavior could further determine the discharge of about 1.3 (0.7–1.9) Gt CO2 (or roughly one year of current emissions) over the next three decades, significantly influencing the feasibility of reaching an 80% emission reduction target for the LDV sector. Governments can nudge PHEV drivers toward environmentally favorable fueling behavior. We discuss several options for nudging, including charging infrastructure availability, battery design, and consumer education. ; publishedVersion

[Image: see text] With the expected rapid growth of renewable electricity generation, charging plug-in hybrid electric vehicles (PHEVs) from the grid promise ever higher reductions in CO(2) emissions. Previous analyses have found that the share that PHEVs are driven in electric mode can differ substantially depending on region, battery size, and trip purpose. Here, we provide a first fleet-wide emissions mitigation potential of US-based PHEV drivers adopting high or low shares of electric driving. Specifically, we illustrate scenarios of different combinations of PHEV uptake, renewable electricity generation shares, and PHEV fueling behavior. Across 21 analyzed scenarios, annual greenhouse gas (GHG) emissions of the light-duty vehicle (LDV) fleet could differ by an average of 21% (5–43% range) in 2050 depending alone on the fueling behavior of PHEV drivers. This behavior could further determine the discharge of about 1.3 (0.7–1.9) Gt CO(2) (or roughly one year of current emissions) over the next three decades, significantly influencing the feasibility of reaching an 80% emission reduction target for the LDV sector. Governments can nudge PHEV drivers toward environmentally favorable fueling behavior. We discuss several options for nudging, including charging infrastructure availability, battery design, and consumer education.

While quality of life (QOL) is the result of satisfying human needs, our current provision strategies result in global environmental degradation. To ensure sustainable QOL, we need to understand the environmental impact of human needs satisfaction. In this paper we deconstruct QOL, and apply the fundamental human needs framework developed by Max-Neef et al to calculate the carbon and energy footprints of subsistence, protection, creation, freedom, leisure, identity, understanding and participation. We find that half of global carbon emissions are driven by subsistence and protection. A similar amount are due to freedom, identity, creation and leisure together, whereas understanding and participation jointly account for less than 4% of global emissions. We use 35 objective and subjective indicators to evaluate human needs satisfaction and their associated carbon footprints across nations. We find that the relationship between QOL and environmental impact is more complex than previously identified through aggregated or single indicators. Satisfying needs such as protection, identity and leisure is generally not correlated with their corresponding footprints. In contrast, the likelihood of satisfying needs for understanding, creation, participation and freedom, increases steeply when moving from low to moderate emissions, and then stagnates. Most objective indicators show a threshold trend with respect to footprints, but most subjective indicators show no relationship, except for freedom and creation. Our study signals the importance of considering both subjective and objective satisfaction to assess QOL-impact relationships at the needs level. In this way, resources could be strategically invested where they strongly relate to social outcomes, and spared where non-consumption satisfiers could be more effective. Through this approach, decoupling human needs satisfaction from environmental damage becomes more attainable.

Multimedia fate and exposure models are widely used to regulate the release of toxic chemicals, to set cleanup standards for contaminated sites, and to evaluate emissions in life‐cycle assessment. CalTOX, one of these models, is used to calculate the potential dose, an outcome that is combined with the toxicity of the chemical to determine the Human Toxicity Potential (HTP), used to aggregate and compare emissions. The comprehensive assessment of the uncertainty in the potential dose calculation in this article serves to provide the information necessary to evaluate the reliability of decisions based on the HTP. A framework for uncertainty analysis in multimedia risk assessment is proposed and evaluated with four types of uncertainty. Parameter uncertainty is assessed through Monte Carlo analysis. The variability in landscape parameters is assessed through a comparison of potential dose calculations for different regions in the United States. Decision rule uncertainty is explored through a comparison of the HTP values under open and closed system boundaries. Model uncertainty is evaluated through two case studies, one using alternative formulations for calculating the plant concentration and the other testing the steady state assumption for wet deposition. This investigation shows that steady state conditions for the removal of chemicals from the atmosphere are not appropriate and result in an underestimate of the potential dose for 25% of the 336 chemicals evaluated.

The human toxicity potential, a weighting scheme used to evaluate toxicemissions for life cycle assessment and toxics release inventories, is based on potential dose calculations and toxicity factors. This paper evaluatesthe variance in potential dose calculations that can be attributed to the uncertainty in chemical‐specific input parameters as well as the variabilit in exposure factors and landscape parameters. A knowledge of the uncertainty allows us to assess the robustness of a decision based on the toxicity potential; a knowledge of the sources of uncertainty allows us to focus our resources if we want to reduce the uncertainty. The potential dose of 236 chemicals was assessed. The chemicals were grouped by dominant exposure route, and a Monte Carlo analysis was conducted for one representative chemical in each group. The variance is typically one to two orders of magnitude. For comparison, the point estimates in potential dose for 236 chemicals span ten orders of magnitude. Most of the variance in the potential dose is due to chemical‐specific input parameters, especially half‐lives, although exposure factors such as fish intake and the source of drinking water can be important for chemicals whose dominant exposure is through indirect routes. Landscape characteristics are generally of minor importance.