A decision support tool for modifications in crop cultivation method based on life cycle assessment: a case study on greenhouse gas emission reduction in Taiwanese sugarcane cultivation

Feeding a growing, increasingly affluent population while limiting environmental pressures of food production is a central challenge for society. Understanding the location and magnitude of food production is key to addressing this challenge because pressures vary substantially across food production types. Applying data and models from life cycle assessment with the methodologies for mapping cumulative environmental impacts of human activities (hereafter cumulative impact mapping) provides a powerful approach to spatially map the cumulative environmental pressure of food production in a way that is consistent and comprehensive across food types. However, these methodologies have yet to be combined. By synthesizing life cycle assessment and cumulative impact mapping methodologies, we provide guidance for comprehensively and cumulatively mapping the environmental pressures (e.g., greenhouse gas emissions, spatial occupancy, and freshwater use) associated with food production systems. This spatial approach enables quantification of current and potential future environmental pressures, which is needed for decision makers to create more sustainable food policies and practices.

Addressing the social life cycle inventory analysis data gap: Insights from a case study of cobalt mining in the Democratic Republic of the Congo

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third

The body of life cycle assessment (LCA) literature is vast and has grown over the last decade at a dauntingly rapid rate. Many LCAs have been published on the same or very similar technologies or products, in some cases leading to hundreds of publications. One result is the impression among decision makers that LCAs are inconclusive, owing to perceived and real variability in published estimates of life cycle impacts. Despite the extensive available literature and policy need formore conclusive assessments, only modest attempts have been made to synthesize previous research. A significant challenge to doing so are differences in characteristics of the considered technologies and inconsistencies in methodological choices (e.g., system boundaries, coproduct allocation, and impact assessment methods) among the studies that hamper easy comparisons and related decision support. An emerging trend is meta-analysis of a set of results from LCAs, which has the potential to clarify the impacts of a particular technology, process, product, or material and produce more robust and policy-relevant results. Meta-analysis in this context is defined here as an analysis of a set of published LCA results to estimate a single or multiple impacts for a single technology or a technology category, either in a statisticalmore » sense (e.g., following the practice in the biomedical sciences) or by quantitative adjustment of the underlying studies to make them more methodologically consistent. One example of the latter approach was published in Science by Farrell and colleagues (2006) clarifying the net energy and greenhouse gas (GHG) emissions of ethanol, in which adjustments included the addition of coproduct credit, the addition and subtraction of processes within the system boundary, and a reconciliation of differences in the definition of net energy metrics. Such adjustments therefore provide an even playing field on which all studies can be considered and at the same time specify the conditions of the playing field itself. Understanding the conditions under which a meta-analysis was conducted is important for proper interpretation of both the magnitude and variability in results. This special supplemental issue of the Journal of Industrial Ecology includes 12 high-quality metaanalyses and critical reviews of LCAs that advance understanding of the life cycle environmental impacts of different technologies, processes, products, and materials. Also published are three contributions on methodology and related discussions of the role of meta-analysis in LCA. The goal of this special supplemental issue is to contribute to the state of the science in LCA beyond the core practice of producing independent studies on specific products or technologies by highlighting the ability of meta-analysis of LCAs to advance understanding in areas of extensive existing literature. The inspiration for the issue came from a series of meta-analyses of life cycle GHG emissions from electricity generation technologies based on research from the LCA Harmonization Project of the National Renewable Energy Laboratory (NREL), a laboratory of the U.S. Department of Energy, which also provided financial support for this special supplemental issue. (See the editorial from this special supplemental issue [Lifset 2012], which introduces this supplemental issue and discusses the origins, funding, peer review, and other aspects.) The first article on reporting considerations for meta-analyses/critical reviews for LCA is from Heath and Mann (2012), who describe the methods used and experience gained in NREL's LCA Harmonization Project, which produced six of the studies in this special supplemental issue. Their harmonization approach adapts key features of systematic review to identify and screen published LCAs followed by a meta-analytical procedure to adjust published estimates to ones based on a consistent set of methods and assumptions to allow interstudy comparisons and conclusions to be made. In a second study on methods, Zumsteg and colleagues (2012) propose a checklist for a standardized technique to assist in conducting and reporting systematic reviews of LCAs, including meta-analysis, that is based on a framework used in evidence-based medicine. Widespread use of such a checklist would facilitate planning successful reviews, improve the ability to identify systematic reviews in literature searches, ease the ability to update content in future reviews, and allow more transparency of methods to ease peer review and more appropriately generalize findings. Finally, Zamagni and colleagues (2012) propose an approach, inspired by a meta-analysis, for categorizing main methodological topics, reconciling diverging methodological developments, and identifying future research directions in LCA. Their procedure involves the carrying out of a literature review on articles selected according to predefined criteria.« less

Transitioning to Environmentally Sustainable, Climate-Smart Radiation Oncology Care

Mitigating Curtailment and Carbon Emissions through Load Migration between Data Centers

Carbon footprint of renewable diesel from palm oil, jatropha oil and rapeseed oil

The aim of this study was to explore the association between travel mode choice and individual sociodemographic characteristics among urban city dwellers, as the selection of daily travel modes is influenced by several factors. The study collected 1,290 short daily trips data from 415 respondents living in Klang Valley using a random sampling technique. Logit regression models were utilized to identify the impact of sociodemographic traits on travel mode choices. Men, low education levels, students, and households without children and do not own private vehicles are more likely to choose active transportation. Besides, the study examines the potential for greenhouse gas (GHG) emission reduction. Based on Life Cycle Assessment (LCA), 142 kgCO2e or 108 kgCO2e/km of GHG were released by automobiles from the collected travel trip data. The result shows that active transport could potentially achieve 14.52% GHG emission reduction by stated preference and nearly 17% GHG emission reduction by criteria fulfillment. These findings could provide valuable information for developing practical planning policies aimed at reducing GHG emissions from the road transport sector.

Mitigation of greenhouse gas emissions from beef production in western Canada – Evaluation using farm-based life cycle assessment

Life-cycle assessment of greenhouse gas emissions from dairy production in Eastern Canada: A case study

Retrospective dynamic life cycle assessment of residential heating and cooling systems in four locations in the United States

Biofuels present a strong potential to support the rapid decarbonization of the mobility sector and substitution for fossil fuels. In the aviation sector, sustainable aviation fuels (SAF) are currently produced from various feedstocks and conversion pathways to achieve sustainability targets. A new SAF production pathway has been recently developed, which is based on enzymatic hydrolysis of softwood residues (saw dust), fermentation of wood sugars into isobutene, and subsequent conversion to SAF isoparaffins by oligomerization and hydrogenation. This pathway is currently under consideration for inclusion as an additional annex to ASTM standard D7566.In this study, several biorefinery set-up scenarios including various process energy provisions and co products valorization were considered in order to assess the environmental impact of SAF production. First, a life cycle assessment (LCA) was conducted to estimate the greenhouse gas (GHG) emissions of the conversion pathway. Second, the GHG reduction potential was evaluated according to the frameworks of EU RED 2018/2001/EC and CORSIA. Third, energetic and exergetic analyses were performed to evaluate the efficiency of the biorefinery. Inefficiencies of upstream processes, such as for electricity provision, were not considered.Depending on the plant layout, the GHG emissions vary between 18.7 and 56 gCO2eq/MJ. Thus, compared to the fossil reference, GHG emission reductions of up to 80.1% and 79% can be achieved for both frameworks, respectively. Plant set-up comparisons revealed that the highest reduction in GHG emissions can be achieved when using the by-product lignin for thermal energy provision and renewable energy sources (RES) to cover electricity demand.The energetic and exergetic efficiency analyses of SAF as a single product were 11.7%–14.9% and 11%–13.8%, respectively. A lignin-CHP plant set-up revealed the highest efficiencies and has the additional benefit of covering up to 82.3% of the total primary energy demand (PED) via RES. Taking all by-products into account, the energetic system efficiency ranged from 39.4% to 50.1% and the exergetic system efficiency from 40.4% to 56.9%, respectively. The highest efficiencies were achieved with the natural gas boiler set-up and electricity consumption from the public grid. The analysis revealed the importance of utilizing all biorefinery products (main and by-products) to increase the system efficiency of the biorefinery.

Harmonizing the quantification of CCS GHG emission reductions through oil and natural gas industry project guidelines

Author(s): Winans, K; Marvinney, E; Gillman, A; Spang, E | Abstract: The majority of the environmental impacts associated with the agri-food supply chain occur at the production phase. Interests in using life-cycle assessment (LCA) for accounting for agri-food supply chains as well as food losses and waste (FLW) has increased in recent years. Here, for the first time, we estimate production-phase embedded resources and greenhouse gas (GHG) emissions in California specialty crops considering on-farm food losses. We use primary, survey-derived qualitative and quantitative data to consider on-farm food loss prevention and avoided GHG emissions through two different scenarios applied in an illustrative example for processing peach at the production stage. Further, we contribute a mathematical approach for accounting for discrete, unique flows within the net flow of loss in a supply chain, in LCA. Through the detailed LCAs, we identify the hotspots for the four crops as on-farm diesel use, fertilizer application, direct water use, and electricity for irrigation pumping. Impacts from cultivation practices and the additional impacts from on-farm food losses vary significantly by crop. Including the losses in the LCAs resulted in increases in overall resource use and GHG emissions by 4–38% (percent varies depending on the crop type). We used the LCA models and a set of straightforward calculations to evaluate the environmental impacts of a prevention action (a 50% reduction in on-farm food losses) and the secondary use of end-of-life (EOL) biomass from processing peach. The results of this evaluation showed an 11% reduction in GHG emissions compared to the baseline (full harvest). In conclusion, by explicitly including the impacts of on-farm food losses in LCA, we highlight challenges and opportunities to target interventions that simultaneously reduce these losses and the associated environmental impacts in agricultural systems.

Increasing concerns about greenhouse gas (GHG) emissions in the United States have spurred interest in alternate low carbon fuel sources, such as natural gas. Life cycle assessment (LCA) methods can be used to estimate potential emissions reductions through the use of such fuels. Some recent policies have used the results of LCAs to encourage the use of low carbon fuels to meet future energy demands in the U.S., without, however, acknowledging and addressing the uncertainty and variability prevalent in LCA. Natural gas is a particularly interesting fuel since it can be used to meet various energy demands, for example, as a transportation fuel or in power generation. Estimating the magnitudes and likelihoods of achieving emissions reductions from competing end-uses of natural gas using LCA offers one way to examine optimal strategies of natural gas resource allocation, given that its availability is likely to be limited in the future. In this study, the uncertainty in life cycle GHG emissions of natural gas (domestic and imported) consumed in the U.S. was estimated using probabilistic modeling methods. Monte Carlo simulations are performed to obtain sample distributions representing life cycle GHG emissions from the use of 1 MJ of domestic natural gas and imported LNG. Life cycle GHG emissions per energy unit of average natural gas consumed in the U.S were found to range between -8 and 9% of the mean value of 66 g CO(2)e/MJ. The probabilities of achieving emissions reductions by using natural gas for transportation and power generation, as a substitute for incumbent fuels such as gasoline, diesel, and coal were estimated. The use of natural gas for power generation instead of coal was found to have the highest and most likely emissions reductions (almost a 100% probability of achieving reductions of 60 g CO(2)e/MJ of natural gas used), while there is a 10-35% probability of the emissions from natural gas being higher than the incumbent if it were used as a transportation fuel. This likelihood of an increase in GHG emissions is indicative of the potential failure of a climate policy targeting reductions in GHG emissions.