The food system plays a crucial role in mitigating climate change. Even if fossil fuel emissions are halted immediately, current trends in global food systems may prevent the achieving of the Paris Agreement's climate targets. The high degree of variability and uncertainty involved in calculating diet-related greenhouse gas emissions limits the ability to evaluate reduction potentials to remain below a global warming of 1.5 or 2 degrees. This study assessed Western European dietary patterns while accounting for uncertainty and variability. An extensive literature review provided value ranges for climate impacts of animal-based foods to conduct an uncertainty analysis via Monte Carlo simulation. The resulting carbon footprints were assessed against food system-specific greenhouse gas emission thresholds. The range and absolute value of a diet carbon footprint become larger the higher the amount of products with highly varying emission values in the diet. All dietary pattern carbon footprints overshoot the 1.5 degrees threshold. The vegan, vegetarian, and diet with low animal-based food intake were predominantly below the 2 degrees threshold. Omnivorous diets with more animal-based product content trespassed them. Reducing animal-based foods is a powerful strategy to decrease emissions. However, further mitigation strategies are required to achieve climate goals.
Causal strands for social bonds : a case study on the credibility of claims from impact reporting
(2022)
The study investigates if causal claims based on a theory-of-change approach for impact reporting are credible. The authors use their most recent impact report for a Social Bond to show how theory-based logic models can be used to map the sustainability claims of issuers to quantifiable indicators. A single project family (homeownership loans) is then used as a case study to test the underlying hypotheses of the sustainability claims. By applying Bayes Theorem, evidence for and against the claims is weighted to calculate the degree to which the belief in the claims is warranted. The authors found that only one out of three claims describe a probable cause–effect chain for social benefits from the loans. The other two claims either require more primary data to be corroborated or should be re-defined to link the intervention more closely and robustly with the overarching societal goals. However, all previous reported indicators are below the thresholds of the most conservative estimates for fractions of beneficiaries in the paper at hand. We conclude that the combination of a Theory-of-Change with a Bayesian Analysis is an effective way to test the plausibility of sustainability claims and to mitigate biases. Nevertheless, the method is - in the presented form - also too elaborate and time-consuming for impact reporting in the sustainable finance market.
Nowadays, the main impetus to apply additive manufacturing (AM) of metals is the high geometric flexibility of the processes and its ability to produce pilot or small batch series. In contrast, resource and energy intensities are often not considered as constraints, even though the turnout of additive manufacturing is high, at least compared to chip removing processes.
The study at hand analyses the material characteristics and environmental impacts of a hose nozzle as an example of a commercial product of simple geometry. The production routes turning (conventional manufacturing) and laser beam melting (additive manufacturing) are compared to each other in terms of natural resource use, climate change potential and primary energy demand. It is found, that the product shows a lower demand for natural resources when produced via AM, but higher carbon emissions and energy demand when using a steel, that is mainly (80%) produced from high-alloyed steel scrap. However, different case studies during the sensitivity analyses showed that a number of factors highly influence the results: the steel source as well as the source of electricity play a major role in determining the environmental performance of the production routes. The authors also found that other production processes (here cold forging of tubes) might be an eco-friendly alternative to both routes, if feasible from an economic point of view.
In regard to the material characteristics, experimental testing revealed that the material advantages of AM produced hose nozzles (in particular higher yield strength) are reduced after a solution heat treatment is applied to the as-produced material, in order to increase corrosion resistance. However, products that do not require this production step might benefit from the higher yield strength, as a lower wall thickness could be realised.
The implementation of energy efficiency improvement actions not only yields energy and greenhouse gas emission savings, but also leads to other multiple impacts such as air pollution reductions and subsequent health and eco-system effects, resource impacts, economic effects on labour markets, aggregate demand and energy prices or on energy security. While many of these impacts have been studied in previous research, this work quantifies them in one consistent framework based on a common underlying bottom-up funded energy efficiency scenario across the EU. These scenario data are used to quantify multiple impacts by energy efficiency improvement action and for all EU28 member states using existing approaches and partially further developing methodologies. Where possible, impacts are integrated into cost-benefit analyses. We find that with a conservative estimate, multiple impacts sum up to a size of at least 50% of energy cost savings, with substantial impacts coming from e.g., air pollution, energy poverty reduction and economic impacts.
Footprint calculators are efficient tools to monitor the environmental impact of private consumption. We present the results of an analysis of data entered into an online Material Footprint calculator undertaken to identify the socioeconomic drivers of the Material Footprint in different areas of consumption, from housing to holidaymaking. We developed regression models to reveal (1) the impact of socioeconomic characteristics on Material Footprints of private households and (2) correlations between the components of Material Footprints for different arrays of consumption. Our results show that an increasing Material Footprint in one array of consumption comes with an increasing Material Footprint in all other arrays, with the exception of housing and holidaymaking. The socioeconomic characteristics of users have a significant impact on their Material Footprints. However, this impact varies by the array of consumption. Households only exhibit generally bigger Material Footprints as a result of higher incomes and larger dwellings. We conclude that indicators which strive to monitor resource efficiency should survey disaggregated data in order to classify the resource use to different population groups and arrays of consumption.
Green Information Systems in general, and footprint calculators in particular, are promising feedback tools to assist people in adopting sustainable behaviour. Therefore, a Material Footprint model for use in an online footprint calculator was developed by identifying the most important predictors of the Material Footprint of the calculator's users. By means of statistical learning, the analysis revealed that 22 of the 95 predictors identified accounted for 74% of the variance in Material Footprints. Ten predictors out of the 95, mainly from the mobility domain, were capable of showing a prediction accuracy of 61%. The authors conclude that 22 predictors from the areas of mobility, housing and nutrition, as well as sociodemographic information, accurately predict a person's Material Footprint. The short and concise Material Footprint model may help developers and researchers to enhance their information systems with additional items while ensuring the data quality of such applications.
Measure or management? : Resource use indicators for policymakers based on microdata by households
(2018)
Sustainable Development Goal 12 (SDG 12) requires sustainable production and consumption. One indicator named in the SDG for resource use is the (national) material footprint. A method and disaggregated data basis that differentiates the material footprint for production and consumption according to, e.g., sectors, fields of consumption as well as socioeconomic criteria does not yet exist. We present two methods and its results for analyzing resource the consumption of private households based on microdata: (1) an indicator based on representative expenditure data in Germany and (2) an indicator based on survey data from a web tool. By these means, we aim to contribute to monitoring the Sustainable Development Goals, especially the sustainable management and efficient use of natural resources. Indicators based on microdata ensure that indicators can be disaggregated by socioeconomic characteristics like age, sex, income, or geographic location. Results from both methods show a right-skewed distribution of the Material Footprint in Germany and, for instance, an increasing Material Footprint with increasing household income. The methods enable researchers and policymakers to evaluate trends in resource use and to differentiate between lifestyles and along socioeconomic characteristics. This, in turn, would allow us to tailor sustainable consumption policies to household needs and restrictions.
The long-term transition towards a low-carbon transport sector is a key strategy in Europe. This includes the replacement of fossil fuels, modal shifts towards public transport as well as higher energy efficiency in the transport sector overall. While these energy savings are likely to reduce the direct greenhouse gas emissions of transport, they also require the production of new and different vehicles. This study analyses in detail whether final energy savings in the transport sector also induce savings for material resources from nature if the production of future vehicles is considered. The results for 28 member states in 2030 indicate that energy efficiency in the transport sector leads to lower carbon emissions as well as resource use savings. However, energy-efficient transport sectors can have a significant impact on the demand for metals in Europe. An additional annual demand for 28.4 Mt of metal ores was calculated from the personal transport sector in 2030 alone. The additional metal ores from semiprecious metals (e.g., copper) amount to 12.0 Mt, from precious metals (e.g., gold) to 9.1 Mt and from other metals (e.g., lithium) to 11.7 Mt, with small savings for ferrous metal ores (-4.6 Mt).
The paper describes patterns of resource use related to German households' equipment. Using cluster analysis and material flow accounting, data on socio-demographic characteristics, and expenditures on fuel, electricity and household equipment allow for a differentiation of seven different household types. The corresponding resource use, expressed in Material Footprint per person and year, is calculated based on cradle-to-gate material flows of average household goods and the related household energy use. Our results show that patterns of resource use are mainly driven by the use of fuel and electricity and the ownership of cars. The quantified Material Footprints correlate to social status and are also linked to city size, age and household size. Affluent, established and/or younger families living in rural areas typically show the highest amounts of durables and expenditures on non-durables, thus exhibiting the highest use of natural resources.
The economic assessment of low-carbon energy options is the primary step towards the design of policy portfolios to foster the green energy economy. However, today these assessments often fall short of including important determinants of the overall cost-benefit balance of such options by not including indirect costs and benefits, even though these can be game-changing. This is often due to the lack of adequate methodologies.
The purpose of this paper is to provide a comprehensive account of the key methodological challenges to the assessment of the multiple impacts of energy options, and an initial menu of potential solutions to address these challenges.
The paper first provides evidence for the importance of the multiple impacts of energy actions in the assessment of low-carbon options.
The paper identifies a few key challenges to the evaluation of the co-impacts of low-carbon options and demonstrates that these are more complex for co-impacts than for the direct ones. Such challenges include several layers of additionality, high context dependency, and accounting for distributional effects.
The paper continues by identifying the key challenges to the aggregation of multiple impacts including the risks of overcounting while taking into account the multitude of interactions among the various co-impacts. The paper proposes an analytical framework that can help address these and frame a systematic assessment of the multiple impacts.