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The U.S. agri-food system is a driver of climate change and other impacts. In order to achieve environmental targets that limit global mean temperature rise ≤2 °C, a shift in American dietary patterns is critical. The purpose of this study was twofold: (1) to determine the environmental impact (i.e., land use, water use, and GHG emissions) related to consumption of five U.S. dietary patterns (i.e., Current U.S., the Healthy U.S., Mediterranean, Healthy Vegetarian, and Vegan), and (2) to determine the specific impact of each food group in each dietary pattern on the three environmental indicators. This study utilized existing datasets to synthesize information related to the study's environmental indicators and food production and connected these data to the current U.S. diet and the USDA-defined diets. Results indicate that the three omnivore diets contributed the greatest to GHG emissions, land use and water use. The Vegan diet scored the lowest across all indicators, although the water required for plant-based protein nearly offset other water gains. For the omnivore diets, red meat and dairy milk contributed the most to each environmental indicator. By considering sustainability as well as health outcomes in their recommendations in the Dietary Guidelines, the USDA can have a critical role in shifting diets necessary to alter climate change trends.

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PURPOSE: Prior versions of the Tool for Reduction and Assessment of Chemical and other environmental Impacts (TRACI) have recognized the need for spatial variability when characterizing eutrophication. However, the method's underlying environmental models had not been updated to reflect the latest science. This new research provides the ability to differentiate locations with a high level of detail within the USA and provides global values at the country level. METHODS: In previous research (Morelli et al. 2018), the authors reviewed a broad range of domain-specific models and life cycle assessment methods for characterization of eutrophication and ranked these by levels of importance to the field and readiness for further development. The current research is rooted in the decision outcome of Morelli et al. (2018) to separate freshwater and marine eutrophication to allow for the most tailored characterization of each category individually. The current research also assumes that freshwater systems are limited by phosphorus and marine systems are limited by nitrogen. Using a combination of spatial modeling methods for soil, air, and water, we calculate midpoint characterization factors for freshwater and marine eutrophication categories and evaluate the results through a US-based case application. RESULTS AND DISCUSSION: Maps of the nutrient inventories, characterization factors, and overall impacts of the case application illustrate the spatial variation and patterns in the results. The importance of variation in geographic location is demonstrated using nutrient-based activity likelihood categories of agricultural (rural fertilizer), non-agricultural (urban fertilizer), and general (human waste processing). Proximity to large bodies of water, as well as individual hydraulic residence times, was shown to affect the comparative values of characterization factors across the USA. CONCLUSIONS: In this paper, we have calculated and applied finely resolved freshwater and marine eutrophication characterization factors for the USA and country-level factors for the rest of the globe. Additional research is needed to provide similarly resolved characterization factors for the entire globe, which would require expansion of publicly available data and further development of applicable fate and transport models. Further scientific advances may also be considered as computing capabilities become more sophisticated and widely accessible.

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Existing methods that apply the planetary boundary for the nitrogen cycle in life cycle assessment are spatially generic and use an indicator with limited environmental relevance. Here, we develop a spatially resolved method that can quantify the impact of nitrogen emissions to air, soil, freshwater or coastal water on "safe operating space" (SOS) for natural soil, freshwater and coastal water. The method can be used to identify potential "planetary boundary hotspots" in the life cycle of products and to inform appropriate interventions. The method is based on a coupling of existing environmental models and the identification of threshold and reference values in natural soil, freshwater and coastal water. The method is demonstrated for a case study on nitrogen emissions from open-field tomato production in 27 farming areas based on data for 199 farms in the year 2014. Nitrogen emissions were modelled from farm-level data on fertilizer application, fuel consumption and climate- and soil conditions. Two sharing principles, "status quo" and "gross value added", were tested for the assignment of SOS to 1 t of tomatoes. The coupling of models and identification of threshold and reference values resulted in spatially resolved characterization factors applicable to any nitrogen emission and estimations of SOS for each environmental compartment. In the case study, tomato production was found to range from not transgressing to transgressing its assigned SOS in each of the 27 farming areas, depending on the receiving compartment and sharing principle. A high nitrogen use efficiency scenario had the potential to reverse transgressions of assigned SOS for up to three farming locations. Despite of several sources of uncertainty, the developed method may be used in decision-support by stakeholders, ranging from individual producers to global governance institutions. To avoid sub-optimization, it should be applied with methods covering the other planetary boundaries.

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This paper evaluates the current state of life cycle impact assessment (LCIA) methods used to estimate potential eutrophication impacts in freshwater and marine ecosystems and presents a critical review of the underlying surface water quality, watershed, marine, and air fate and transport (F&T) models. Using a criteria rubric, we assess the potential of each method and model to contribute to further refinements of life cycle assessment (LCA) eutrophication mechanisms and nutrient transformation processes as well as model structure, availability, geographic scope, and spatial and temporal resolution. We describe recent advances in LCIA modeling and provide guidance on the best available sources of fate and exposure factors, with a focus on midpoint indicators. The critical review identifies gaps in LCIA characterization modeling regarding the availability and spatial resolution of fate factors in the soil compartment and identifies strategies to characterize emissions from soil. Additional opportunities are identified to leverage detailed F&T models that strengthen existing approaches to LCIA or that have the potential to link LCIA modeling more closely with the spatial and temporal realities of the effects of eutrophication.

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PURPOSE: Life cycle impact assessment (LCIA) results are used to assess potential environmental impacts of different products and services. As part of the UNEP-SETAC life cycle initiative flagship project that aims to harmonize indicators of potential environmental impacts, we provide a consensus viewpoint and recommendations for future developments in LCIA related to the ecosystem quality area of protection (AoP). Through our recommendations, we aim to encourage LCIA developments that improve the usefulness and global acceptability of LCIA results. METHODS: We analyze current ecosystem quality metrics and provide recommendations to the LCIA research community for achieving further developments towards comparable and more ecologically relevant metrics addressing ecosystem quality. RESULTS AND DISCUSSION: We recommend that LCIA development for ecosystem quality should tend towards species-richnessrelated metrics, with efforts made towards improved inclusion of ecosystem complexity. Impact indicators-which result from a range of modeling approaches that differ, for example, according to spatial and temporal scale, taxonomic coverage, and whether the indicator produces a relative or absolute measure of loss-should be framed to facilitate their final expression in a single, aggregated metric. This would also improve comparability with other LCIA damage-level indicators. Furthermore, to allow for a broader inclusion of ecosystem quality perspectives, the development of an additional indicator related to ecosystem function is recommended. Having two complementary metrics would give a broader coverage of ecosystem attributes while remaining simple enough to enable an intuitive interpretation of the results. CONCLUSIONS: We call for the LCIA research community to make progress towards enabling harmonization of damage-level indicators within the ecosystem quality AoP and, further, to improve the ecological relevance of impact indicators.

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This paper addresses water use impacts of agriculture, developing a spatially explicit approach tracing the location of water use and water scarcity related to feed production, transport, and livestock, tracking uncertainties and illustrating the approach with a case study on dairy production in the United States. This approach was developed as a step to bring spatially variable production and impacts into a process-based life cycle assessment (LCA) context. As water resources and demands are spatially variable, it is critical to take into account the location of activities to properly understand the impacts of water use, accounting for each of the main feeds for milk production. At the crop production level, the example of corn grain shows that 59% of water stress associated with corn grain production in the United States is located in Nebraska, a state with moderate water stress and moderate corn production (11%). At the level of milk production, four watersheds account for 78% of the national water stress impact, as these areas have high milk production and relatively high water stress; it is the production of local silage and hay crops that drives water consumption in these areas. By considering uncertainty in both inventory data and impact characterization factors, we demonstrate that spatial variability may be larger than uncertainty, and that not systematically accounting for the two can lead to artificially high uncertainty. Using a nonspatial approach in a spatially variable setting can result in a significant underestimation or overestimation of water impacts. The approach demonstrated here could be applied to other spatially variable processes.

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We present a novel multi-pathway, mass balance based, fate and exposure model compatible with life cycle and high-throughput screening assessments of chemicals in cosmetic products. The exposures through product use as well as post-use emissions and environmental media were quantified based on the chemical mass originally applied via a product, multiplied by the product intake fractions (PiF, the fraction of a chemical in a product that is taken in by exposed persons) to yield intake rates. The average PiFs for the evaluated chemicals in shampoo ranged from 3×10(-4) up to 0.3 for rapidly absorbed ingredients. Average intake rates ranged between nano- and micrograms per kilogram bodyweight per day; the order of chemical prioritization was strongly affected by the ingredient concentration in shampoo. Dermal intake and inhalation (for 20% of the evaluated chemicals) during use dominated exposure, while the skin permeation coefficient dominated the estimated uncertainties. The fraction of chemical taken in by a shampoo user often exceeded, by orders of magnitude, the aggregated fraction taken in by the population through post-use environmental emissions. Chemicals with relatively high octanol-water partitioning and/or volatility, and low molecular weight tended to have higher use stage exposure. Chemicals with low intakes during use (<1%) and subsequent high post-use emissions, however, may yield comparable intake for a member of the general population. The presented PiF based framework offers a novel and critical advancement for life cycle assessments and high-throughput exposure screening of chemicals in cosmetic products demonstrating the importance of consistent consideration of near- and far-field multi-pathway exposures.

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In Life Cycle Impact Assessment (LCIA) both spatial variability and model choices may be influential. In the case of the effect model, the effect factors differ with respect to their assumption of linear/nonlinear responses to increases in environmental stressor levels, and whether or not they account for the current stressor levels in the environment. Here, we derived spatially explicit characterization factors of phosphorus emissions causing eutrophication based on three different effect models (depicted by marginal, linear, and average effect factors) and two freshwater types (lakes and streams) and we performed an analysis of variance (ANOVA) to investigate how the selection of the effect models and the freshwater types influence the impacts of phosphorus emissions to freshwater on heterotrophic species. We found that 56% of the variability of ecological impacts per unit of phosphorus emission was explained, primarily, by the difference between freshwater types and, to a lesser extent, by the difference between effect models. The remaining variability was attributed to the spatial variation between river basins, mainly due to the variability in fate factors. Our study demonstrates the particular importance of accounting for spatial variability and model choices in LCIA.

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Iron sulfide (FeS) has been extensively assessed as a reactive medium to remove both metals and halogenated organics from groundwater. However, to address its suitability as a material for permeable reactive barriers (PRBs), its propensity for solids and gas production, which result in reduced permeability, must be evaluated. The reduction in permeability for sands coated with FeS (as mackinawite), under the anoxic conditions often encountered at contaminated groundwater sites, was examined through column experiments and geochemical modeling under conditions of high calcium and nitrate, which have been previously shown to cause significant permeability reduction in zero-valent iron (ZVI) systems. The column experiments showed negligible production of both solids and gases. The geochemical modeling predicted a maximum reduction in permeability of 1% due to solids and about 30% due to gas formation under conditions for which a complete loss of permeability was predicted for ZVI systems. This difference in permeability reduction is driven by the differences in thermodynamic stability of ZVI and FeS in aqueous solutions. The results suggest that geochemical conditions that result in high permeability losses for ZVI systems will likely not be problematic for FeS-based reactive materials.

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