Reply to L Aleksandrowicz et al.

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.

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

Well-to-wheel greenhouse gas emissions of electric versus combustion vehicles from 2018 to 2030 in the US

Nutrition guidelines now consider the environmental impact of food choices as well as maintaining health. In Australia there is insufficient data quantifying the environmental impact of diets, limiting our ability to make evidence-based recommendations. This paper used an environmentally extended input-output model of the economy to estimate greenhouse gas emissions (GHGe) for different food sectors. These data were augmented with food intake estimates from the 1995 Australian National Nutrition Survey. The GHGe of the average Australian diet was 14.5 kg carbon dioxide equivalents (CO2e) per person per day. The recommended dietary patterns in the Australian Dietary Guidelines are nutrient rich and have the lowest GHGe (~25% lower than the average diet). Food groups that made the greatest contribution to diet-related GHGe were red meat (8.0 kg CO2e per person per day) and energy-dense, nutrient poor “non-core” foods (3.9 kg CO2e). Non-core foods accounted for 27% of the diet-related emissions. A reduction in non-core foods and consuming the recommended serves of core foods are strategies which may achieve benefits for population health and the environment. These data will enable comparisons between changes in dietary intake and GHGe over time, and provide a reference point for diets which meet population nutrient requirements and have the lowest GHGe.

Interrogating greenhouse gas emissions of different dietary structures by using a new food equivalent incorporated in life cycle assessment method

The global food system accounts for roughly 25%–30% of total greenhouse gas (GHG) emissions. Without emission estimates, it is difficult to identify major sources of emissions as well as monitor the progress towards climate goals such as the Paris Agreement, net‐zero emissions and Carbon Credit. The rapidly evolving food system of India is contributing significantly to national GHG emissions; nevertheless, a comprehensive understanding of emissions across the food life cycle is still limited. Present study was undertaken to analyse state‐wise GHG emissions from on‐farm and off‐farm activities as well as various stages of agri‐food life cycle. For this, data pertaining to consumption of 12 major food groups (combination of 405 food items) across 30 states of India was extracted from NSSO report 2022–23, and different methodologies were used for getting GHG emissions at each stage of agri‐food life cycle. Findings indicated that production of livestock products, though less consumed than cereals, has disproportionately higher GHG intensities (89.81%) than crops (10.19%) due to enteric fermentation and feed production. Life cycle assessment (LCA) indicated that among all food crops, production of rice contributed to 2.26% followed by oilseeds (2.20%) and least by wheat (0.55%) towards GHG emission. Emission from other stages like transport of rice was highest (24%) followed by fruits (19%) and meat (10%), respectively. Regional disparities in dietary patterns and agricultural practices further influenced the emission profiles. Considering the production scenario, the top four GHG emitters (from production scenario) were Haryana (2079.44) > Telangana (1934.49) > Andhra Pradesh (1873.37) > Punjab (1844.72 kg CO 2 e/capita/year). In case of consumption the trend was Nagaland (1387.38 kg CO2e/capita/year) > Sikkim (1304.09 kg CO2/capita/year) > Ladakh (1085.11 kg CO2e/capita/year) > Arunachal Pradesh (1055.36 kg CO 2 e/capita/year) due to high per capita consumption of meat and rice. GHG emissions resulting from inter‐state transport to the union territories ranged between 0.886 and 1.734 kg CO 2 e/kg of product, highlighting their substantial dependence on external food sources. This study focused on the potential of dietary shifts, improved agricultural practices and reduced food waste as key mitigation strategies. These insights will provide critical direction for low‐carbon food system transitions in developing economies.

Progress in working towards a more sustainable agri-food industry

Carbon footprint and energy use of recycled fertilizers in arable farming

Background: Current scientific literature suggests healthy dietary patterns may have less environmental impact than current consumption patterns, but most of the studies rely on theoretical modeling. The aim of this study was to assess the impact on resources (land, water, and energy) use and greenhouse gas (GHG) emissions of healthy dietary patterns in a sample of Italian adults. Methods: Participants (n = 1806) were recruited through random sampling in the city of Catania, southern Italy. Dietary consumption was assessed through a validated food frequency questionnaire (FFQ); dietary patterns were calculated through dietary scores. The specific environmental footprints of food item production/processing were obtained from various available life-cycle assessments; a sustainability score was created based on the impact of the four environmental components calculated. Results: The contribution of major food groups to the environmental footprint showed that animal products (dairy, egg, meat, and fish) represented more than half of the impact on GHG emissions and energy requirements; meat products were the stronger contributors to GHG emissions and water use, while dairy products to energy use, and cereals to land use. All patterns investigated, with the exception of the Dietary Approach to Stop Hypertension (DASH), were linearly associated with the sustainability score. Among the components, higher adherence to the Mediterranean diet and Alternate Diet Quality Index (AHEI) was associated with lower GHG emissions, dietary quality index-international (DQI-I) with land use, while Nordic diet with land and water use. Conclusions: In conclusion, the adoption of healthy dietary patterns involves less use of natural resources and GHG emissions, representing eco-friendlier options in Italian adults.

Food processing is a major thriving industry globally and provides livelihood to millions of workers. Food processing is an energy intensive process and often has an impact on the environment which remains undiagnosed and hence not quantified. Food processing industry comprises the organized as well as unorganized sector with varying levels of energy requirement and therefore the carbon foot prints also significantly vary. Higher energy use is often related to higher greenhouse gas (GHG) emission which is responsible for global warming and climate change. Carbon footprint (CFP) of food industry is an estimate of the energy use and GHG emissions caused due to the processing and delivery of food items to the consumer and also disposal of packaging. Recently there is a growing interest in estimating the carbon footprint of food industries to know how improved technologies can be used to make food processing less energy and carbon intensive. In this book chapter we would like to provide an overview of energy use and carbon footprint of different types of food industries. Quantification of CFP is generally done using Life Cycle Assessment (LCA) in which GHG emissions are measured from the very beginning of the production process to its final use and disposal. GHG emission from a food industry will include both direct emissions as well as indirect emissions. The CFP of different sectors like fruit and beverage industry, sugar production, dairy sector, fisheries, meat and poultry supply chains are presented. Apart from this, research gaps and possible steps to minimize the carbon footprint will be mentioned. Assessing the CFP of food industries can help in identifying the GHG sources and can be useful in developing alternative technologies which are more energy efficient and reduces GHG emission. Further, change in dietary pattern also contributes immensely to reduce the environmental impact of food consumption.

New energy and renewable widely available in Indonesia. One of them is the biomass that can be used with gasification technology. Biomass is an organic matter to which derived from biological materials. This research was used integration gasification system with a gas engine, which works more properly with CO, and H2. The advantage of this biomass power plant compared the environmental impact on other types of plants such as coal-fired power plants, diesel power plants, etc. Therefore the potential of environmental impacts was generated, it is necessary to calculate quantitatively through the life cycle assessment methods. This research aimed to calculate impact assessment on electricity production from a Biomass Power Plant system through a life cycle assessment with boundary cradle to grave in Indonesia. The study revealed that greenhouse gas (GHG) emission of electricity production from an empty fruit bunch palm oil mill was 0.15 kg CO2-eq kWh–1. The gas engine was the highest GHG emission contributor during its life cycle. Empty fruit bunch as a source of biomass for electricity production was considered as climate-friendly power plant system due to its potential in reducing GHG emission from palm oil production and released lower GHG emission.

SummaryThis research reports on a multivariate analysis that examined the relationship between direct greenhouse gas (GHG) emissions and socioeconomic and well‐being variables for 1,920 respondents living in Halifax Regional Municipality, Nova Scotia, Canada, using results from the Halifax Space‐Time Activity Research Project. The unique data set allows us to estimate direct GHG emissions with an unprecedented level of specificity based on household energy use survey data and geographic positioning system–verified personal travel data. Of the variables analyzed, household size, income, community zone, age, and marital status are all statistically significant predictors of direct GHG emissions. Birthplace, ethnicity, educational attainment, perceptions of health, life satisfaction, job satisfaction, happiness, volunteering, or community belonging did not seem to matter. In addition, we examined whether those reporting energy‐efficient behaviors had lower GHG emissions. No significant differences were discovered among the groups analyzed, supporting a growing body of research indicating a disconnect between environmental attitudes and behaviors and environmental impact. Among the predictor variables, those reporting to be married, young, low income, and living in households with more people have correspondingly lower direct GHG emissions than other categories in respective groupings. Our finding that respondents with lifestyles that generate higher GHG emissions did not report to be healthier, happier, or more connected to their communities suggest that individuals can experience similar degrees of well‐being regardless of the amount of GHG emissions associated with his or her respective lifestyle.

Mitigating greenhouse gas (GHG) emissions from the production of concrete, a critical infrastructure material around the world, has been highlighted as necessary to meet climate change goals. Concrete is made of water, aggregates (e.g., crushed rocks), and Portland cement (PC), a hydraulic binder. PC is the primary source of GHG emissions from concrete, a function of the emissions derived from the production of its clinker, a kilned, quenched material composed of calcium silicates that, by mass, makes up the majority of PC. While considerable attention has been given to reducing the GHG emissions from PC manufacture, better utilization of other resources used in concrete can lower the demand for the level of clinker necessary in any given mixture. In this work, we examine how changing the size of aggregates, the use of a superplasticizer (SP), and the use of supplementary cementitious materials (SCMs) can lower GHG emissions from concrete. We derive a system of equations based fundamentally on standard mixture proportioning guidelines to determine the most efficient use of PC in a concrete mixture for specified strength and workability and quantify GHG emissions using life cycle assessment methods. Findings show that the use of reactive SCMs can contribute to reduced GHG emissions, as can the use of a higher maximum aggregate diameter and higher SP dosage. Our models also suggest that a concrete producer could follow standard mixture proportioning guidelines and yield a mixture that has over 2 times the PC content needed. The efficient use of PC within concrete mixtures by appropriately selecting other constituents can lower GHG emissions, contributing to GHG emissions reduction goals.

Greenhouse gas emissions and land use from confinement dairy farms in the Guanzhong plain of China – using a life cycle assessment approach

Diets have been changing drastically in China in the recent decades and this change has contributed considerably to greenhouse gas (GHG) emissions. In determining effective mitigation strategies for future emissions, it is necessary to know how emissions related to diet vary over time in overall magnitude and due to compositional changes driven by socioeconomic dynamics. This study evaluates the change in dietary GHG emissions in China during the 1997–2011 period by linking environmentally extended input–output tables with individual daily food intake data. It further decomposes the contribution to GHG emission changes of various socioeconomic driving factors. The results show that GHG emissions related to national diet have been decreasing from 1,180 Mt CO 2 e to 640 Mt CO 2 e (a 54% decline), largely due to technical innovation that has reduced the emissions per calorie of food (135% of the total reduction). The change in dietary patterns has had mixed effects, with a decline in calorie intake reducing emissions by 21% while increases in animal‐sourced food consumption have raised emissions by 25%. Our findings stress the importance of technical progress in the historical change in dietary GHG emissions and suggest a focus on behavior changes for future research and policymaking, which has the potential to promote dietary changes toward less animal product consumption. Our findings highlight the importance of both technological and demand‐side behavioral options in reducing the impact of diets on GHG emissions.