Journal of Industrial Ecology最新文献

Digitalization appears as a lever to enhance agriculture sustainability. However, existing works on digital agriculture's own sustainability remain scarce, disregarding the environmental effects of deploying digital devices on a large scale. We propose a bottom-up method to estimate the carbon footprint of digital agriculture scenarios considering deployment of devices over a diversity of farm sizes. It is applied to two use-cases and demonstrates that digital agriculture encompasses a diversity of devices with heterogeneous carbon footprints and that more complex devices yield higher footprints not always compensated by better performances or scaling gains. By emphasizing the necessity of considering the multiplicity of devices, and the territorial distribution of farm sizes when modeling digital agriculture deployments, this study highlights the need for further exploration of the first-order effects of digital technologies in agriculture.

This work presents the PULPO (Python-based user-defined lifecycle product optimization) framework, developed to efficiently integrate life cycle inventory (LCI) models into life cycle product optimization. Life cycle optimization (LCO), which has found interest in both the process systems engineering and life cycle assessment (LCA) communities, leverages LCA data to go beyond simple assessments of a limited number of alternatives and identify the best possible product systems configuration subject to a manifold of choices, constraints, and objectives. However, typically, aggregated inventories are used to build the optimization problems. Contrary to existing frameworks, PULPO integrates whole LCI databases and user inventories as a backbone for the optimization problem, considering economy-wide feedback loops between fore- and background systems that would otherwise be omitted. The open-source implementation combines functions from Brightway2 for the manipulation of inventory data and pyomo for the formulation and solution of the optimization problem. The advantages of this approach are demonstrated in a case study focusing on the design of optimal future global green methanol production systems from captured CO₂ and electrolytic H₂. It is shown that the approach can be used to assess sector-coupling with multi-functional processes and prospective background databases that would otherwise be impractical to approach from a standalone LCA perspective. The use of PULPO is particularly appealing when evaluating large-scale decisions that have a strong impact on socioeconomic systems, resulting in changes in the technosphere on which the background system is based and which is often assumed constant in standard LCO approaches regardless of the decisions taken. This article met the requirements for a gold-gold JIE data openness badge described at http://jie.click/badges.

As environmentally extended input–output tables are increasingly used for footprint and supply chain analysis, there has been a growing demand for precise, reliable, and intertemporally consistent environmental accounts. Energy accounts are particularly relevant. As well as providing insights into embodied energy, in the case of the multi-regional input–output (MRIO) database EXIOBASE, they are the basis of the air emissions from fuel combustion. In this study we review previous methods and provide a more integrated and robust implementation for the EXIOBASE energy accounts that ensures higher levels of consistency between economic and physical data. Our results show that the new procedure significantly improves the precision of the energy use coefficients and multipliers, while reducing the number of outliers. The procedure is made publicly available for full transparency and made open source such that users and developers may raise issues and suggest improvements to the procedure. Furthermore, the procedure is standardized so it can be applied to any MRIO model with only minor adjustments to the input data.

To meet climate targets, consumption-based household emissions need to fall rapidly. An important but still poorly understood question is whether generational change could contribute to decreases in emissions. It is sometimes assumed that younger generations such as Millennials and Generation Z are more concerned about climate change and have greener lifestyles than previous generations of the Silent Generation, Baby boomers, and Generation X, but carbon footprinting analysis typically focuses on age groups rather than comparing generations over time. This paper provides a first assessment of the change in consumption-based carbon footprints of the Silent, Baby boomer, Generation X, and Millennial generations within the United Kingdom between 2001 and 2020 and a comparison of the footprints of different generational groups. The analysis is based on environmentally extended input–output analysis, using the Living Costs and Food Survey and emission data from the UK multi-regional input–output database. We find some evidence for the hypothesis that younger generations have smaller footprints than older generations as Generation X and Millennial households have smaller carbon footprints compared to the generation before them at a similar life stage. We find that factors such as decarbonization, household occupancy, total expenditure, and changing consumption patterns contribute to the UK's changing carbon consumption emissions between 2001 and 2020, and the importance of these factors varies for different generational groups. However, future research that uses a longer time series is required to assess generational differences in carbon footprints over the whole lifespan of several generations.

Recycling schemes for long-lived products are challenged by the presence of “legacy substances,” which have been used in production in the past, but are nowadays classified as substances of concern. This study quantitatively evaluates the trade-offs between phasing out legacy substances, increasing circularity levels, and reducing life cycle impacts of polyvinylchloride (PVC) window profiles recycling in Germany based on a comprehensive dynamic material and substance flow analysis coupled with a prospective life cycle assessment. Scenario results indicate that although lead had been phased out in virgin PVC by 2015, lead concentrations in end-of-life PVC window profiles will remain above 0.3% until the end of the century without a restriction of lead in recycled PVC and will be by factor 3–5 higher compared to a restriction as stipulated by EU 2023/923. However, the latter is associated with lower recycling rates and higher life cycle environmental impacts of PVC window frame waste management, which cannot be fully compensated by the introduction of new waste treatment pathways using currently available technologies. The study serves to introduce a new comprehensive modeling framework, which allows for the consideration of trade-offs between substance, material, and environmental impact dimensions as a basis for discussing and developing sustainable waste management strategies.

Extending multi-regional input–output (MRIO) models with spatially explicit life cycle impact assessment (LCIA) models allows practitioners to quantify biodiversity impacts at every step of global supply chains. Inconsistencies may be introduced, however, when high-resolution characterization factors (CFs) are aggregated so as to match the low spatial granularity of MRIO models. These aggregation errors are greater when CFs are aggregated via proxies, such as ecoregion land shares, instead of based on spatially explicit elementary stressor flows. Here, we describe our approach to tailoring application-specific CFs for use in MRIO studies. We apply a global agricultural production model, Spatial Production Allocation Model (MapSPAM), with the LCIA database, LC-IMPACT, to create crop-specific national CFs. We investigated i) if the differing aggregation approaches and the increased spatial explicitness of the constructed CFs deviate substantially from those in LC-IMPACT, and ii) what the resulting consequences for national production and consumption-based biodiversity footprints are when combining the tailor-made CFs with the EXIOBASE MRIO model. For the year 2020, we observe an increase in global production-based biodiversity impacts of 23.5% for land use when employing crop-specific CFs.

In response to pressing societal challenges, scholars are increasingly focusing on research aimed at fostering sustainable futures. We contribute to that discussion by theorizing the circular economy (CE) as an “ecology of practices.” The ecology of practices concept helps to make sense of a developing field that has been heavily practitioner-driven. Through an analysis of the diverse CE practices in analytical and operational contexts, we investigate the roles, disciplinary influences, and visions for the future and categorize their trajectories. Drawing on the sociology of expectations, we consider the articulations of CE in practice, advocating for inclusive dialogue among stakeholders and collective engagement with ontological multiplicity in shaping CE futures. We propose a framework that contributes to broader debates in organization and management studies, emphasizing the significance of everyday practices in shaping sustainable futures beyond the realm of CE. In so doing, we focus on unpicking how sustainable futures are variously enacted as a way of enabling collaboration that might otherwise be hindered by disciplinary obligations.

Biodiversity loss is one of the planetary boundaries that is most urgently in need of action. However, very little is known about the consumers’ willingness to pay (WTP) for products with higher (or lower) levels of biodiversity performance. Therefore, this research was conducted to investigate how consumers’ WTP is influenced by a product's impact on biodiversity. To address this question, we collected representative data from 524 German consumers in a survey-based experiment. Drawing on prospect theory, we identified the shape of the WTP reaction function for a given product in relation to its biodiversity performance. We demonstrate that consumers with sufficiently high levels of education and concern about biodiversity loss are willing to pay more for products with above-average biodiversity performance and less for products with below-average biodiversity performance. However, the extent to which a product outperforms the industry average does not influence consumers’ increased WTP. From a sustainable development perspective, these observed patterns highlight the problematic contrast between the pressing need for substantial improvements in product biodiversity performance and the limited incentives provided by consumers. Consequently, the findings suggest that the incentives that consumers currently provide for corporate biodiversity management are insufficient to assist in staying within the planetary boundaries.

Increasing social, economic, and political pressure causes many companies to pledge to decarbonize. A common measure involves the use of Energy Attribute Certificates (EAC), such as the European Guarantees of Origin (GO), to reduce emissions from electricity procurement (Scope 2). However, previous studies find no effect on additional renewable energy capacity. Focusing on Norway and Germany as dominant contributors to net GO exports and imports, this study examines the GO trade alongside corporate carbon accounting data to answer the research question: Does the decarbonization of corporate electricity procurement using Guarantees of Origin contribute to the expansion of renewable electricity generation capacity in Norway and Germany? The analysis of CDP and Association of Issuing Bodies data reveals Norway's consumption mix is more carbon intensive than Germany's because Norway exports GO and imports fossil electricity attributes. German companies report predominantly market-based approach, mainly using green tariffs and GO for zero emission claims, while Norwegian companies favor the location-based approach. The largest share of GO issued in Norway comes from hydropower plants aged 41 to 70 years. The results highlight the urgency to revise corporate carbon accounting standards. GO lack additionality due to double counting of renewable attributes. Potential solutions include additionality criteria, GO trade restrictions based on physical capacities, and age limits for eligible power plants. This study's novelty is linking CDP data with GO trade, to assess the integrity of corporate decarbonization strategies. It contributes valuable insights to ongoing discourse on the role of EAC.

Residential and non-residential buildings are a major contributor to human well-being. At the same time, buildings cause 30% of final energy use, 18% of greenhouse gas emissions (GHGE), and about 65% of material accumulation globally. With electrification and higher energy efficiency of buildings, material-related emissions gain relevance. The circular economy (CE) strategies, narrow, slow, and close, together with wooden buildings, can reduce material-related emissions. We provide a comprehensive set of building stock transformation scenarios for 10 world regions until 2060, using the resource efficiency climate change model of the stock–flow–service nexus and including the full CE spectrum plus wood-intensive buildings. The 2020–2050 global cumulative new construction ranges from 150 to 280 billion m² for residential and 70-120 billion m² for non-residential buildings. Ambitious CE reduces cumulative 2020–2050 primary material demand from 80 to 30 gigatons (Gt) for cement and from 35 to 15 Gt for steel. Lowering floor space demand by 1 m² per capita leads to global savings of 800-2500 megatons (Mt) of cement, 300-1000 Mt of steel, and 3-10 Gt CO₂-eq, depending on industry decarbonization and CE roll-out. Each additional Mt of structural timber leads to savings of 0.4-0.55 Mt of cement, 0.6-0.85 Mt of steel, and 0.8-1.8 Mt CO₂-eq of system-wide GHGE. CE reduces 2020–2050 cumulative GHGE by up to 44%, where the highest contribution comes from the narrow CE strategies, that is, lower floorspace and lightweight buildings. Very low carbon emission trajectories are possible only when combining supply- and demand-side strategies. This article met the requirements for a gold-gold JIE data openness badge described at http://jie.click/badges.