A review of LCA greenhouse gas emissions results for advanced biofuels: The use of meta-regression analysis

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

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

The aim of this study was to estimate the total greenhouse gas (GHG) emissions generated from whole life cycle stages of a sewer pipeline system and suggest the strategies to mitigate GHG emissions from the system. The process-based life cycle assessment (LCA) with a city-scale inventory database of a sewer pipeline system was conducted. The GHG emissions (direct, indirect, and embodied) generated from a sewer pipeline system in Daejeon Metropolitan City (DMC), South Korea, were estimated for a case study. The potential improvement actions which can mitigate GHG emissions were evaluated through a scenario analysis based on a sensitivity analysis. The amount of GHG emissions varied with the size (150, 300, 450, 700, and 900 mm) and materials (polyvinyl chloride (PVC), polyethylene (PE), concrete, and cast iron) of the pipeline. Pipes with smaller diameter emitted less GHG, and the concrete pipe generated lower amount of GHG than pipes made from other materials. The case study demonstrated that the operation (OP) stage (3.67 × 104 t CO2eq year−1, 64.9%) is the most significant for total GHG emissions (5.65 × 104 t CO2eq year−1) because a huge amount of CH4 (3.51 × 104 t CO2eq year−1) can be generated at the stage due to biofilm reaction in the inner surface of pipeline. Mitigation of CH4 emissions by reducing hydraulic retention time (HRT), optimizing surface area-to-volume (A/V) ratio of pipes, and lowering biofilm reaction during the OP stage could be effective ways to reduce total GHG emissions from the sewer pipeline system. For the rehabilitation of sewer pipeline system in DMC, the use of small diameter pipe, combination of pipe materials, and periodic maintenance activities are suggested as suitable strategies that could mitigate GHG emissions. This study demonstrated the usability and appropriateness of the process-based LCA providing effective GHG mitigation strategies at a city-scale sewer pipeline system. The results obtained from this study could be applied to the development of comprehensive models which can precisely estimate all GHG emissions generated from sewer pipeline and other urban environmental systems.

Investigating the mitigation of greenhouse gas emissions from municipal solid waste management using ant colony algorithm, Monte Carlo simulation and LCA approach in terms of EU Green Deal

Abstract. Conferences, meetings and congresses are an important part of today's economic and scientific world. But the environmental impact, especially from greenhouse gas emissions associated with travel, can be extensive. Anthropogenic greenhouse gas (GHG) emissions account for the warming of the atmosphere and oceans. This study draws on the need to quantify and reduce greenhouse gas emissions associated with travel activities and aims to give suggestions for organizers and participants on possible ways to reduce greenhouse gas emissions, demonstrated on the example of the European Geography Association (EGEA) Annual Congress 2013 in Wasilkow, Poland. The lack of a comprehensive methodology for the estimation of greenhouse gas emissions from travel led to an outline of a methodology that uses geographic information systems (GIS) to calculate travel distances. The calculation of travel distances in GIS is adapted from actual transportation infrastructure, derived from the open-source platform OpenStreetMap. The methodology also aims to assess the possibilities to reduce GHG emissions by choosing different means of transportation and a more central conference location. The results of the participants of the EGEA congress, who shared their travel data for this study, show that the total travel distance adds up to 238 000 km, with average travel distance of 2429 km per participant. The travel activities of the participants in the study result in total GHG emissions of 39 300 kg CO2-eq including both outward and return trip. On average a participant caused GHG emissions of 401 kg CO2-eq. In addition, the analysis of the travel data showed differences in travel behaviour depending on the distance between conference site and point of origin. The findings on travel behaviour have then been used to give an estimation of total greenhouse gas emissions from travel for all participants of the conference, which result in a total amount of 79 711 kg CO2-eq. The potential for reducing greenhouse gas emissions by substituting short flights with train rides and car rides with bus and train rides is limited. Only 6 % of greenhouse gas emissions could be saved by applying these measures. Further considerable savings could only be made by substituting longer flights (32.6 %) or choosing a more central conference location (26.3 %).

Green House Gases(GHG) emissions from the ornamental plant nursery industry: a Life Cycle Assessment(LCA) approach in a nursery district in central Italy

The estimation of greenhouse gas (GHG) emissions from a change in land‐use and management resulting from growing biofuel feedstocks has undergone extensive – and often contentious – scientific and policy debate. Emergent renewable fuel policies require life cycle GHG emission accounting that includes biofuel‐induced global land‐use change (LUC) GHG emissions. However, the science of LUC generally, and biofuels‐induced LUC specifically, is nascent and underpinned with great uncertainty. We critically review modeling approaches employed to estimate biofuel‐induced LUC and identify major challenges, important research gaps, and limitations of LUC studies for transportation fuels. We found LUC modeling philosophies and model structures and features (e.g. dynamic vs. static model) significantly differ among studies. Variations in estimated GHG emissions from biofuel‐induced LUC are also driven by differences in scenarios assessed, varying assumptions, inconsistent definitions (e.g. LUC), subjective selection of reference scenarios against which (marginal) LUC is quantified, and disparities in data availability and quality. The lack of thorough sensitivity and uncertainty analysis hinders the evaluation of plausible ranges of estimates of GHG emissions from LUC. The relatively limited fuel coverage in the literature precludes a complete set of direct comparisons across alternative and conventional fuels sought by regulatory bodies and researchers.Improved modeling approaches, consistent definitions and classifications, availability of high‐resolution data on LUC over time, development of standardized reference and future scenarios, incorporation of non‐economic drivers of LUC, and more rigorous treatment of uncertainty can help improve LUC estimates in effectively achieving policy goals. © 2013 Society of Chemical Industry and John Wiley & Sons, Ltd

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.

Understanding spatial and temporal variations of greenhouse gas (GHG) emissions at local level is important for both companies in the agri-food sector working to improve sustainability in their supply chains and local governments following a low-carbon development pathway. For this reason, it is necessary to count with methodologies that do not only estimate GHG emissions, but provide analytics about their location and temporal variations. Factors such as spatial distribution of farms, variations on the requirement of inputs depending on the age of the farms, as well as transportation distances for the main and complementary products, should be assessed at farm level. To accomplish this, spatial and temporal analytics can be incorporated into life cycle assessment (LCA) by joining it with geographic information systems (GIS). This paper explores how spatial statistics tools can be applied to identify spatial and temporal trends in GHG emission results obtained from an LCA conducted on cocoa farming in the region of San Martin in Peru. Results indicate that it is possible to identify temporal and spatial trends of statistically significant clusters of farms with high GHG emissions (hot spot analysis).

An excess of material input in fruit orchards has brought serious environmental problems, particularly in China. However, studies on the estimation of greenhouse gas (GHG) emissions in peach orchards are limited. In this study, based on questionnaire surveys in major peach-producing regions, including the North China Plain (n = 214), as well as northwest (n = 22) and southwest (n = 33) China, the carbon footprints (CFs) of these orchards were calculated by the life cycle assessment. The potential emission reduction in each region was estimated by combining the GHG emissions and CFs with plantation areas and fruit yields. The results showed that the average GHG emissions in the North China Plain, northwest, and southwest regions were 15,668 kg CO2-eq ha−1, 10,386 kg CO2-eq ha−1, and 5580 kg CO2-eq ha−1, with corresponding CFs of 0.48 kg CO2-eq ha−1, 0.27 kg CO2-eq ha−1, and 0.20 kg CO2-eq kg−1, respectively. The main contribution source of GHG emissions in these three regions was fertilizer (77–95%), followed by electricity, pesticides, and diesel. By adopting advanced farming practices with high yield and a high partial factor productivity of fertilizer, the GHG emissions could be reduced by ~13–35%, with the highest potential reduction in the North China Plain. In conclusion, the GHG emissions and their CFs were impressively high in China’s major peach-producing regions, but these GHG emissions could be substantially decreased by optimizing nutrients and irrigation management, including the rational selection of fertilizer rates and types with water-saving irrigation systems or practices (e.g., mulching) for increasing fertilizer and water use efficiency, and maintaining a sustainable peach production in China or similar countries.

Diversity in reservoir surface morphology and climate limits ability to compare and upscale estimates of greenhouse gas emissions

BackgroundHealth authorities are increasingly integrating environmental sustainability considerations into food-based dietary guidelines. However, concerns persist about the accuracy of the data used to assess environmental impacts, as well as the extent to which these guidelines are followed in practice. AimTo compare dietary greenhouse gas (GHG) emissions estimates using different top-down and bottom-up life cycle assessment (LCA) databases; and to estimate GHG emissions of food consumption within the ranges set for meat and dairy in recently proposed environmentally sustainable diets. MethodsDietary GHG emissions were estimated for participants in the 2019–2021 Icelandic National Dietary Survey (n = 822) using three publicly available LCA databases from Denmark, the US, and France. GHG emissions among participants whose consumption was aligned with the EAT-Lancet diet, the 2021 Danish food-based dietary guidelines and the 2023 Nordic Nutrition Recommendations were also quantified. ResultsThe mean dietary GHG emissions among participants were 6.3, 6.1, and 6.1 kg CO2-eq/day based on the Danish (top-down), US (bottom-up), and French (bottom-up) databases, respectively. The relative ranking of foods was also consistent across all three databases. For example, the relative contribution of total CO2-eq (% range for the three databases) was highest for red meat (39–51%), followed by dairy (10–17%) and beverages (9–13%). The contribution from plant-based foods (6–10%), seafood (4–11%), and poultry/eggs (<5%) was modest. The dietary habits of most participants (86%) were outside the ranges for meat and dairy consumption as set by the three sustainable diets. However, participants reporting consumption within the ranges for meat and dairy had mean GHG emissions ranging between 4.2 and 4.7 kg CO2-eq/day, depending on the diet. In comparison, the mean for participants not adhering to the sustainable diets was 7.7 kg CO2-eq/day. These results are higher than those reported in other Nordic and European studies, likely due to high consumption of lamb, beef, and dairy, and low consumption of plant-based food. ConclusionAll three LCA databases provided similar estimates for total dietary GHG emissions and relative ranking of different food groups. Based on current dietary habits in Iceland, adherence to environmentally sustainable diets would lead to a substantial reduction in dietary GHG emissions.

Rank-order concordance among conflicting emissions estimates for informing flight choice

Porvair makes environmental improvements across its global operations

Biofuels are being promoted as a low-carbon alternative to fossil fuels as they could help to reduce greenhouse gas (GHG) emissions and the related climate change impact from transport. However, there are also concerns that their wider deployment could lead to unintended environmental consequences. Numerous life cycle assessment (LCA) studies have considered the climate change and other environmental impacts of biofuels. However, their findings are often conflicting, with a wide variation in the estimates. Thus, the aim of this paper is to review and analyse the latest available evidence to provide a greater clarity and understanding of the environmental impacts of different liquid biofuels. It is evident from the review that the outcomes of LCA studies are highly situational and dependent on many factors, including the type of feedstock, production routes, data variations and methodological choices. Despite this, the existing evidence suggests that, if no land-use change (LUC) is involved, first-generation biofuels can—on average—have lower GHG emissions than fossil fuels, but the reductions for most feedstocks are insufficient to meet the GHG savings required by the EU Renewable Energy Directive (RED). However, second-generation biofuels have, in general, a greater potential to reduce the emissions, provided there is no LUC. Third-generation biofuels do not represent a feasible option at present state of development as their GHG emissions are higher than those from fossil fuels. As also discussed in the paper, several studies show that reductions in GHG emissions from biofuels are achieved at the expense of other impacts, such as acidification, eutrophication, water footprint and biodiversity loss. The paper also investigates the key methodological aspects and sources of uncertainty in the LCA of biofuels and provides recommendations to address these issues.