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1. A household-scale life cycle assessment model for understanding the food-energy-water nexus

   https://doi.org/10.3389/fenvs.2023.1059301  

   Daignault, Jessica; Wallace, Charles; Watkins, David; Handler, Robert; Yang, Yi; Heaney, Danielle; Ahamed, Sonya (February 2023, Frontiers in Environmental Science)

   Vörösmarty, C. (Ed.)

   The household is an important locus of decision-making regarding food, energy, and water (FEW) consumption. Changes in household FEW consumption behaviors can lead to significant reductions in environmental impacts, but it can be difficult for consumers to compare the relative impacts of their consumption quantitatively, or to recognize the indirect impacts of their household consumption patterns. We describe two novel tools designed to address this problem: A hybrid life cycle assessment (LCA) framework to translate household consumption of food, energy, and water into key environmental impacts including greenhouse gas emissions, energy use, and water use; and a novel software application calledHomeTrackerthat implements the framework by collecting household FEW data and providing environmental impact feedback to households. We explore the question:How can a life cycle assessment-based software application facilitate collection and translation of household consumption data to meaningful environmental impact metrics?A case study in Lake County, Illinois is presented to illustrate use of theHomeTrackerapplication. Output data describing environmental impacts attributable to household FEW consumption in the study area are shown in order to illustrate key features and trends observed in the case study population. The framework and its associated output data can be used to support experimental research at the household scale, allowing for examination of what users purchase and consume over an extended period of time as well as increased understanding of household behavior trends and environmental impacts, and as future work. 

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2. Estimating energy left in discarded alkaline batteries: Evaluating consumption and recovery opportunities

   https://doi.org/10.1016/j.wasman.2024.08.016  

   Sabbaghi, Mostafa; Behdad, Sara (December 2024, Waste Management)

   Each year, a significant number of single-use alkaline batteries with untapped energy are discarded. This study aims to analyze the usage patterns of alkaline batteries based on a dataset of 1021 used batteries, ranging from Size AA to 9V, collected from households in the State of New York. We measure the energy loss resulting from underutilized batteries and examine the corresponding environmental and economic impacts on a national scale. Discarded AA alkaline batteries maintain about 13 % of their initial energy, that results in an estimated annual energy loss of 660 MWh for all AA alkaline batteries in the U.S., and about 40 MWh in New York State. Annually in the U.S., consumers discard AA alkaline batteries with approximately $80 million worth of unused energy, including $4.8 million in New York State alone. We also show that the lifecycle impact of batteries should be multiplied by 1.25 to account for their underutilization. To address these issues, we propose actionable recommendations for improving battery consumption practices and facilitating End-of-Life/Use (EoL/U) recovery processes. The findings show the need for policy interventions to better manage battery usage and disposal toward reducing energy waste and mitigating environmental impacts. 

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3. Household activity pattern problem with automated vehicle-enabled intermodal trips

   https://doi.org/10.1016/j.trc.2024.104930  

   Bahk, Younghun; Hyland, Michael (January 2025, Transportation Research Part C: Emerging Technologies)

   Driverless or fully automated vehicles (AVs) are expected to fundamentally change how individuals and households travel and how vehicles use roadway infrastructure. The first goal of this study is to develop a modeling framework of activity-constrained household travel in a future multi-modal network with private AVs, shared-use AVs, transit, and intermodal AV-transit travel options. The second goal is to analyze the potential impacts of AVs—including intermodal AV-transit travel—on (a) household-level travel behavior, (b) household travel costs, (c) demand for transport modes, including transit, and (d) vehicle kilometers traveled or VKT. To meet the first goal, we propose and formulate the Household Activity Pattern Problem with AV-enabled Intermodal Trips (HAPP-AV-IT) that incorporates AV deadheading and intermodal AV-transit trips. The modeling framework extends prior HAPP-based formulations that model household-level travel decisions as vehicle (and person) routing and scheduling problems, similar to the pickup and delivery problem with time-windows. To meet the second goal, we apply the HAPP-AV-IT to two case studies and conduct many computational experiments. We use synthetic activity location data for synthetic households and a fictitious medium-size network with a road network, transit network, residential locations, activity locations, and parking locations. The computational results illustrate (a) the critical role that household AV ownership plays in terms of household travel decisions, modal demand, and VKT, (b) that with AVs, deadheading accounts for 30–40 % of vehicle operating distances, (c) that around 10 % of households in the study region benefit from AV-based intermodal trips, and (d) that those 10 % of households see 5 % reductions in household travel costs and 25 % reductions in VKT on average in the most transit friendly scenario. This last finding suggests that intermodal AV-transit trips may exist in a driverless vehicle future, and therefore, transit agencies and transportation planners should consider how to serve this market. We also propose and test a simple heuristic algorithm that quickly solves HAPP-AV-IT problem instances. 

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4. An integrated bioeconomic local economy-wide assessment of the environmental impacts of poverty programs

   https://doi.org/10.1073/pnas.1816093116  

   Gilliland, Ted E.; Sanchirico, James N.; Taylor, J. Edward (April 2019, Proceedings of the National Academy of Sciences)

   A new generation of poverty programs around the globe provides cash payments to poor and vulnerable households. Studies show that these social cash transfer programs create income and welfare benefits for poor households and the local economies where they live. However, this may come at the cost of damaging local environments if cash payments stimulate food production that conflicts with natural resource conservation. Evaluations of the economic impacts of poverty programs do not account for the welfare consequences of environmental impacts, which are potentially large for poor communities closely tied to natural resources. We use an ex-ante policy simulation tool, a bioeconomic local computable general equilibrium model parameterized with microsurvey data, to analyze the expected welfare consequences of environmental degradation caused by a cash transfer program. For a Philippine fishing community that is a net importer of fish, we show that a government cash transfer program initially increases real incomes for all households. However, increased demand for fish leads to a decline in the local fish stock that reduces program benefits. Household groups experience declines in real income benefits of 2–63%, with fishing households suffering the largest declines. Impacts on local fish stocks depend on the extent to which markets link fishing communities to outside regions through trade. Greater market integration can mitigate the fish stock decline, but this reduces the local income benefits of cash transfers. 

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5. Exploring equality and sustainability trade-offs of energy transition outcomes in the United States in 2050

   https://doi.org/10.1016/j.apenergy.2024.123376  

   Goforth, Teagan; Nock, Destenie; Brown, Maxwell; Ghosh, Tapajyoti; Lamers, Patrick (August 2024, Applied Energy)

   With increasing focus on equitable and just energy transition, it is critical to understand the trade-offs of different decarbonization outcomes across economic, environmental, and social sustainability criteria. In this analysis, we use a multi-criteria decision analysis to quantify sustainability outcomes across 32 decarbonization outcomes in 2050 in the U.S. The economic sustainability criteria we use are system cost, national average retail rate, and electricity system employment. The environmental sustainability criteria we use are life cycle greenhouse gas emissions, life cycle water depletion, life cycle land transformation, and air pollution fatalities. The social sustainability (distributional impacts) criteria we use are retail rate equality across states, electricity employment equality across low-income households, and air pollution disparities across census tracts. We evaluate performance across these criteria under eleven different stakeholder preference scenarios. We find that decarbonization policies with indefinitely extended tax credits have the highest sustainability score under equal criteria weighting, with greater investments in renewable energy technologies, and result in better environmental, system cost, job, and air pollution disparities compared to mid-case scenarios, that only include current policies and CO2 reduction targets. We also see that our multi-criteria decision analysis identifies decarbonization outcomes that would not have been identified as optimal under a single objective, which highlights the importance of trade-off analyses to understand decarbonization outcomes more holistically. 

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