Emergy and end-point impact assessment of agricultural and food production in the United States: A supply chain-linked Ecologically-based Life Cycle Assessment

Park, Yong Shin; Eğilmez, Gökhan; Küçükvar, Murat

doi:10.1016/j.ecolind.2015.11.045

Cited by 89 publications

(39 citation statements)

References 94 publications

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“…The importance of consideration of all indirect supply chain-related impacts (is also called economy-wide macro-level analysis) within the LCSA framework is emphasized in the Guinée et al [1] as "inter-related global sustainability issues require more comprehensive approaches in which the macro-level impacts (economy-wide, or global) covering entire supply chain is essential to reveal sustainability impacts of products, services, or systems". This is because process-based models involve a limited number of processes without tracing the entire supply chains of products, and the inclusion or exclusion of processes is decided on the basis of subjective choices, which create the so-called system boundary problem [67,86,87]. Past studies on the environmental footprint of sectors also showed that process-based models suffer from significant truncation errors, which can be of the order of 50% or higher [70,88,89].…”

Section: Broadening the Object Of Analysis: Revealing Macro-level Impmentioning

confidence: 99%

Systems Thinking for Life Cycle Sustainability Assessment: A Review of Recent Developments, Applications, and Future Perspectives

et al. 2017

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Abstract:Tracking the environmental impacts of production, use, and disposal of products (e.g., goods, and services) have been an important issue in the global economy. Although Life Cycle Assessment (LCA) is a widely applied method to track these environmental impacts and support policies, it has certain limitations and an isolated way of evaluating the environmental impacts with no consideration of social and economic impacts and mechanisms. To overcome the limits of current LCA, three mechanisms have been proposed in the literature: (1) broadening the indicators by including social and economic indicators in addition to the environmental impacts; (2) broadening the scope of analysis from product-level assessment to national and global levels; (3) deepening the assessment by inclusion of more mechanisms to account for interrelations among the system elements, uncertainty analysis, stakeholder involvement, etc. With these developments, LCA has been evolving into a new framework called Life Cycle Sustainability Assessment (LCSA). Practical application of LCSA requires integration of various methods, tools, and disciplines. In this study, a comprehensive literature review is conducted to investigate recent developments, current challenges, and future perspectives in the LCSA literature. According to the review, a high number (40%) of LCSA studies are from the environmental science discipline, while contributions from other disciplines such as economics (3%) and social sciences (9%) are very low. On broadening the scope of analysis, 58% of the studies are product-level works, while 37% quantified the impacts at national level and achieved an economy-wide analysis, and only 5% of the studies were able to quantify the global impacts of products using LCSA framework. Furthermore, current applications of LCSA have not considered the rebound effects, feedback mechanisms, and interrelations of the system of interest sufficiently. To address these challenges, we present a complete discussion about the overarching role of systems thinking to bring tools, methods and disciplines together, and provide practical examples from the earlier studies that have employed various system-based methods. We discuss the importance of integrated system-based methods for advancement of LCSA framework in the following directions: (1) regional and global level LCSA models using multi-region input-output analysis that is capable of quantitatively capturing macro-level social, environmental, and economic impacts; (2) dealing with uncertainties in LCSA during multi-criteria decision-making process and expert judgments in weighting of LCSA indicators; and (3) integration of system dynamics modeling to reveal complex interconnections, dependencies, and causal relationships between sustainability indicators.

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Section: Broadening the Object Of Analysis: Revealing Macro-level Impmentioning

confidence: 99%

Systems Thinking for Life Cycle Sustainability Assessment: A Review of Recent Developments, Applications, and Future Perspectives

et al. 2017

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“…Not all indicators are available for every food category. Many studies have indicated that meat and other animal products are less water efficient than plant-based products in providing nutrition on both a gravimetric (mass) and caloric (energy) basis [5,[28][29][30][31]. Nevertheless, generalizations regarding the LCA-derived impacts of meats should be cautiously interpreted because end products can vary from raw cuts to highly processed foodstuffs, which have very different water-related impacts depending on how and to what extent the meat is processed.…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, different software versions (e.g., 2008 and 2016 releases of ReCiPe) and similar, but nonetheless distinct, algorithms utilized by various programs can be an issue. Interpretive challenges associated with comparing results from different LCA methodologies have been identified in the literature, reportedly complicating their use as a universal metric for quantifying product impacts [31,36].…”

Section: Discussionmentioning

confidence: 99%

Water Footprint of Meat Analogs: Selected Indicators According to Life Cycle Assessment

Fresán

Marrin²,

Mejía

et al. 2019

Water

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Animal-based products reportedly have substantial water footprints. One alternative to meat products is meat analogs, which are processed plant-based foods mimicking real meat products. As data for the water footprints of meat analogs are limited, the present study assesses their water consumption and their potential for contributing to eutrophication and ecotoxicity in fresh and marine receiving waters. Life cycle assessments, which encompassed the generation of ingredients to the packaging of products, were performed for 39 meat analogs. Estimates for consumptive water use, ecotoxicity, and eutrophication are reported per ton of product and per kilogram of protein. On average, 3800 m3 of water were consumed per ton of product, whereas 0.56 kg P equivalents. and 12 kg 1,4-DCB (1,4-dichlorobenzene)) equivalents. were potentially released to terrestrial freshwaters and 2.2 kg N equivalents. and 7 kg 1,4-DCB equivalents. to marine waters. The predominant driver for water consumption and marine ecotoxicity was processing the meat analogs, whereas producing the raw ingredients was the main driver for freshwater toxicity and eutrophication. For reducing the use of and potential impacts on water, meat analogs may represent a viable alternative to processed meat products.

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“…Sustainable food production and agriculture are integral elements of sustainable development efforts due to steeply rising worldwide socio-economic and environmental problems as a result of profit-onlyminded economic growth and unsustainable food consumption (Park et al, 2016). Like any manufacturing process, food manufacturing also utilizes natural resources such as water, energy and has various environmental impacts such as atmospheric pollution, hazardous waste generation and toxic releases (Egilmez et al, 2013;Kucukvar and Samadi, 2015).…”

Section: Introductionmentioning

confidence: 99%

A fuzzy data envelopment analysis framework for dealing with uncertainty impacts of input–output life cycle assessment models on eco-efficiency assessment

Eğilmez

Gümüş

Küçükvar

et al. 2016

Journal of Cleaner Production

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102

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The uncertainty in the results of input-output-based life cycle assessment models makes the sustainability performance assessment and ranking a challenging task. Therefore, introducing a new approach, fuzzy data envelopment analysis, is critical; since such a method could make it possible to integrate the uncertainty in the results of the life cycle assessment models into the decision-making for sustainability benchmarking and ranking. In this paper, a fuzzy data envelopment analysis model was coupled with an input-output-based life cycle assessment approach to perform the sustainability performance assessment of the 33 food manufacturing sectors in the United States. Seven environmental impact categories were considered the inputs and the total production amounts were identified as the output category, where each food manufacturing sector was considered a decision-making unit. To apply the proposed approach, the life cycle assessment results were formulated as fuzzy crisp valued-intervals and integrated with fuzzy data envelopment analysis model, thus, sustainability performance indices were quantified. Results indicated that majority (31 out of 33) of the food manufacturing sectors were not found to be efficient, where the overall sustainability performance scores ranged between 0.21 and 1.00 (efficient), and the average sustainability performance was found to be 0.66. To validate the current study's findings, a comparative analysis with the results of a previous work was also performed. The major contribution of the proposed framework is that the effects of uncertainty associated with input-output-based life cycle assessment approaches can be successfully tackled with the proposed Fuzzy DEA framework which can have a great area of application in research and business organizations that use with eco-efficiency as a sustainability performance metric.

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Emergy and end-point impact assessment of agricultural and food production in the United States: A supply chain-linked Ecologically-based Life Cycle Assessment

Cited by 89 publications

References 94 publications

Systems Thinking for Life Cycle Sustainability Assessment: A Review of Recent Developments, Applications, and Future Perspectives

Systems Thinking for Life Cycle Sustainability Assessment: A Review of Recent Developments, Applications, and Future Perspectives

Water Footprint of Meat Analogs: Selected Indicators According to Life Cycle Assessment

A fuzzy data envelopment analysis framework for dealing with uncertainty impacts of input–output life cycle assessment models on eco-efficiency assessment

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