• Energy Research

Purpose: The objective of this study is to discuss the implications of product loss rates in terms of the environmental performance of bottled wine. Wine loss refers to loss occurring when the consumer does not consume the wine contained in the bottle and disposes of it because of taste alteration, which is caused by inadequate product protection rendering the wine unpalatable to a knowledgeable consumer. The decision of whether or not to drink the wine in such cases is guided by subjective consumer taste perception and wine quality expectation (drinking the bottle or disposing of the wine down the drain and replacing it with a new bottle). This study aims to illustrate the importance of accurately defining system boundaries related to wine packaging systems. Methods: The environmental impacts resulting from wine loss rates as related to two types of wine bottle closures—natural cork stoppers and screw caps—have been estimated based on literature review data and compared to the impact of the respective closure system. The system studied relates to the functional unit “a 750 mL bottle of drinkable wine” and includes bottled wine, bottle and closure production, wine production, wine loss and wine poured down the drain. Results: The range of wine alteration rates due to corked wine is estimated to be 2–5% based on interviews with wine experts. Consumer behavior was assessed through a sensitivity study on replacement rates. When the increase in loss rate with the cork stopper is higher than 1.2% (corresponding to 3.5% corked wine multiplied by a consumer replacement rate of 35%), the influence of losses on the impact results is higher than that of the closure material itself. The different closures and associated wine losses represent less than 5% of the total life cycle impact of bottled wine.

Author(s): Hauschild, M.Z.; Huijbregts, M.; Jolliet, O.; MacLeod, M.; Margni, M.; Meent, D. van de; Rosenbaum, R.K.; McKone, T.E. | Abstract: Achieving consensus among scientists is often a challenge?particularly in model development. In this article we describe a recent scientific consensus-building process for Life Cycle Impact Assessment (LCIA) models applied to chemical emissions?including the strategy, execution, and results of a process that used model comparison to achieve parsimony. This process has succeeded in establishing a transparent LCIA consensus model. We present the lessons that may be adapted by similar consensus processes in other fields. LCIA characterizes potential impacts on human health and the environment attributable to chemical emissions over the life cycle of a product. LCIA relies on substance-specific characterization factors (CFs) that combine exposure potential and toxicity to represent the relative contribution of the substance to health and environmental impacts (1). LCIA focuses on comparative assessment, using approaches adapted from risk assessment. In 2003, in response to large variations in available methods, an international model comparison/consensus process was initiated. This process was under the umbrella of the Life Cycle Initiative, a joint effort of the United Nations Environment Program (UNEP) and the Society of Environmental Toxicology and Chemistry (SETAC) (2). The process encompassed an international group of model developers responsible for the most commonly-used worldwide LCIA characterization models and focused on characterization of human and ecosystem health impacts. It also involved disciplinary experts in fate and transport, exposure assessment, health risk assessment, and ecotoxicology. The comparison/consensus process fostered a common understanding among the participants of which model elements contribute most to the relative magnitude of LCIA characterization factors. It became clear that with a careful focus on the most influential model elements a consensus model could be established. Experience dictated that a more transparent model would be more likely to gain and retain acceptance and wide-spread use. The need for consistent documentation and transparency led the participants to create an entirely new model, building on contributions from the existing models. This required consensus on essential model elements, provided robust results consistent with existing models, and made parsimony a guiding principle. The tangible outcome is "USEtox", named in recognition of the UNEP-SETAC Life Cycle Initiative under which it was developed. The model is supported by all participating model teams as a basis for future global recommendations of LCIA characterization factors.

In 2005, a comprehensive comparison of life cycle impact assessment toxicity characterisation models was initiated by the United Nations Environment Program (UNEP)–Society for Environmental Toxicology and Chemistry (SETAC) Life Cycle Initiative, directly involving the model developers of CalTOX, IMPACT 2002, USES-LCA, BETR, EDIP, WATSON and EcoSense. In this paper, we describe this model comparison process and its results—in particular the scientific consensus model developed by the model developers. The main objectives of this effort were (1) to identify specific sources of differences between the models’ results and structure, (2) to detect the indispensable model components and (3) to build a scientific consensus model from them, representing recommended practice. A chemical test set of 45 organics covering a wide range of property combinations was selected for this purpose. All models used this set. In three workshops, the model comparison participants identified key fate, exposure and effect issues via comparison of the final characterisation factors and selected intermediate outputs for fate, human exposure and toxic effects for the test set applied to all models. Through this process, we were able to reduce inter-model variation from an initial range of up to 13 orders of magnitude down to no more than two orders of magnitude for any substance. This led to the development of USEtox, a scientific consensus model that contains only the most influential model elements. These were, for example, process formulations accounting for intermittent rain, defining a closed or open system environment or nesting an urban box in a continental box. The precision of the new characterisation factors (CFs) is within a factor of 100–1,000 for human health and 10–100 for freshwater ecotoxicity of all other models compared to 12 orders of magnitude variation between the CFs of each model, respectively. The achieved reduction of inter-model variability by up to 11 orders of magnitude is a significant improvement. USEtox provides a parsimonious and transparent tool for human health and ecosystem CF estimates. Based on a referenced database, it has now been used to calculate CFs for several thousand substances and forms the basis of the recommendations from UNEP-SETAC’s Life Cycle Initiative regarding characterisation of toxic impacts in life cycle assessment. We provide both recommended and interim (not recommended and to be used with caution) characterisation factors for human health and freshwater ecotoxicity impacts. After a process of consensus building among stakeholders on a broad scale as well as several improvements regarding a wider and easier applicability of the model, USEtox will become available to practitioners for the calculation of further CFs.

Disability adjusted life years (DALYs) is a health burden metric that combines years of life lost due to disease disability and premature mortality. The Global Burden of Disease (GBD) has been using DALYs to determine the health burden associated with numerous health risks, including risks associated with dietary intakes, at the global and national level. To translate such information at the food level in the U.S., variables in What We Eat in America (WWEIA) need to be aligned with those in the GBD. In this paper, we develop the necessary new variables needed to account for differences in definitions and units between WWEIA and the GBD. We use the Food Patterns Equivalents Database, Food Patterns Equivalents Ingredient Database, Food and Nutrient Database for Dietary Studies, and Standard Reference databases that provide data for WWEIA to develop food group and nutrient variables that align with definitions and units used in the GBD. Considerable effort was needed to disaggregate mixed dishes to GBD components. We also developed a new “non-starchy” vegetable variable, since the GBD vegetables do not include potatoes and corn, and we report fruits and vegetables in grams instead of household measures. New fiber variables were created to avoid double counting of fiber from legumes, whole grains, fruits, and vegetables. Regression analyses were used to predict trans-fat content for foods in WWEIA with missing or incomplete information. The majority of foods in various U.S. Department of Agriculture (USDA) categories contain multiple GBD food groups (e.g., vegetables, whole grains, and processed meat). For most nutrients considered in the GBD, composition is more evenly distributed across the main food categories; however, seafood omega-3 fats were predominantly from either protein foods or mixed dishes and sugar sweetened beverages were from a single category. Dietary intakes in the U.S. fall short of recommendations for all food groups/nutrients with established theoretical minimum-risk targets in GBD. To our knowledge, this is the first approach that aligns WWEIA intake variables with those used in the health burden-based GBD reports. These methods will facilitate researchers to begin comparing data from the U.S. with that from other countries, as well as assess food sustainability performances by concomitantly evaluating DALYs for environmental and nutritional impacts.

Purpose: Understanding the main factors affecting the environmental impacts of milk production and consumption along the value chain is key towards reducing these impacts. This paper aims to present detailed spatialized distributions of impacts associated with milk production and consumption across the United States (U.S.), accounting for locations of both feed and on-farm activities, as well as variations in impact intensity. Using a Life Cycle Analysis (LCA) approach, focus is given to impacts related to (a) water consumption, (b) eutrophication of marine and freshwater, (c) land use, (d) human toxicity and ecotoxicity, and (e) greenhouse gases. Methods: Drawing on data representing regional agricultural practices, feed production is modelled for 50 states and 18 main watersheds and linked to regions of milk production in a spatialized matrix-based approach to yield milk produced at farm gate. Milk processing, distribution, retail, and consumption are then modelled at a national level, accounting for retail and consumer losses. Custom characterization factors are developed for freshwater and marine eutrophication in the U.S. context. Results and discussion: In the overall life cycle, up to 30% of the impact per kg milk consumed is due to milk losses that occur during the retail and consumption phases (i.e., after production), emphasizing the importance of differentiating between farm gate and consumer estimates. Water scarcity is the impact category with the highest spatial variability. Watersheds in the western part of the U.S. are the dominant contributors to the total water consumed, with 80% of water scarcity impacts driven by only 40% of the total milk production. Freshwater eutrophication also has strong spatial variation, with high persistence of emitted phosphorus in Midwest and Great Lakes area, but high freshwater eutrophication impacts associated with extant phosphorus concentration above 100 µg/L in the California, Missouri, and Upper Mississippi water basins. Overall, normalized impacts of fluid milk consumption represent 0.25% to 0.8% of the annual average impact of a person living in the U.S. As milk at farm gate is used for fluid milk and other dairy products, the production of milk at farm gate represents 0.5% to 3% of this annual impact. Dominant contributions to human health impacts are from fine particulate matter and from climate change, whereas ecosystem impacts of milk are mostly due to land use and water consumption. Conclusion: This study provides a systematic, national perspective on the environmental impacts of milk production and consumption in the United States, showing high spatial variation in inputs, farm practices, and impacts.

The first Swiss national dietary survey (MenuCH) was used to screen disease burdens and greenhouse gas emissions (GHG) of Swiss diets (vegan, vegetarian, gluten-free, slimming), with a focus on gender and education level. The Health Nutritional Index (HENI), a novel disease burden-based nutritional index built on the Global Burden of Disease studies, was used to indicate healthiness using comparable, relative disease burden scores. Low whole grain consumption and high processed meat consumption are priority risk factors. Non-processed red meat and dairy make a nearly negligible contribution to disease burden scores, yet are key drivers of diet-related GHGs. Swiss diets, including vegetarian, ranged between 1.1–2.6 tons of CO2e/person/year, above the Swiss federal recommendation 0.6 ton CO2e/person/year for all consumption categories. This suggests that only changing food consumption practices will not suffice towards achieving carbon reduction targets: Systemic changes to food provisioning processes are also necessary. Finally, men with higher education had the highest dietary GHG emissions per gram of food, and the highest disease burden scores. Win–win policies to improve health and sustainability of Swiss diets would increase whole grain consumption for all, and decrease alcohol and processed meat consumption especially for men of higher education levels.