Journal of Industrial Ecology最新文献

Bio-based polymers may present a sustainable, circular way to reduce the environmental impact of plastics because they are produced from biomass that absorbs CO₂ during its growth. However, sourcing (type of biomass used and cultivation location), production, and end-of-life affect the environmental impact of bio-based plastics. We assessed the effect of sourcing and end-of-life options on the environmental impact of bio-based high-density polyethylene (bio-HDPE) in 31 sourcing scenarios and five end-of-life options. Our study found that careful consideration of biomass sourcing (biomass type and production location) and end-of-life is needed to optimize the environmental impact of bio-based plastics. If these aspects are not considered, the environmental impact of bio-HDPE may exceed that of its petrochemical-based counterpart. The direct availability of fermentable sugars indicated a lower environmental impact. The production location affected the resources needed for biomass cultivation and the environmental impact of processing due to the energy mix. Recently published guidelines do not allow biogenic carbon to be accounted for during the production stage, but only upon the incineration of the plastic. Our results show that this way of attributing biogenic carbon results in an apparent disadvantage for bio-based plastics compared to petrochemical-based plastics. Furthermore, it disadvantaged mechanical recycling of bio-based plastics compared to incineration, a result out of line with circular economy principles.

As the largest producer and consumer of copper, China is facing enormous challenges from carbon peaking and neutrality. This article adopts “bottom-up” and “top-down” methods to construct a more accurate model, to predict the CO₂ emissions of China's copper smelting industry, and explores its potential for carbon reduction in the future from three scenarios as the baseline scenario (BAU), the general low-carbon (NLC), and the enhanced low-carbon (ELC). The results show that the CO₂ emissions can achieve a peak in 2028 either in NLC or ELC scenarios, with a peak range of 14.9–16.88 million tonnes. Prior to reaching the peak, the contributions of energy adjustment, material substitution, and process selection to carbon reduction have significantly improved, and the contribution rates increased from 30.91%, 4.11%, and 1.46% to 42.7%, 32.07%, and 15.63% in ELC scenario. After the peak, the contribution of energy adjustment gradually slows down, while the material substitution continues to increase, and the contribution rates increased from 21.25% and 32.07% to 29.38% and 40.01% in NLC and ELC scenarios. In the future, concentrate oxygen-enriched bottom-blowing smelting and direct refining from waste copper anode furnaces show ideal potential for carbon reduction before 2025, increasing the proportion of recycled copper production, and adjusting energy structure will be more effective from 2025 to 2035. The conclusions of this study can provide a scientific basis for formulating policy recommendations for green and low-carbon development of the copper industry in China and all over the world in the future.

A systemic understanding of the use of wood resources is required to defossilize society and promote bio-based developments. This study provides a novel approach to represent a comprehensive material flow analysis (MFA) spanning the entire wood value chain; encompassing wood harvest to products, use in society, collection, reuse, recycle, energy generation, and trade. By recognizing wood as a complex material, with changing properties throughout its lifespan, we developed a method where we employed a color-coded system for processes (27 boxes) and 110 flows to symbolize distinct life stages and the dynamic characteristics, including 23 different trade flows. The wood processes and flows are categorized (11 categories) into different wood types (e.g., softwood and hardwood) and harmonized to include all available data on each single step of the wood life cycle, improving data traceability and visualization, and allowing for replicable analysis with respective data noted for each process and flow. Methodological obstacles due to different units, uncertainty of flows, and discrepancies in data are addressed and adjustments proposed. Switzerland was chosen as a case study as a large number of various types of data were available to perform the analysis. The categorized and harmonized flows of woody biomass mapped and analyzed in the MFA provide a comprehensive basis to identify and recommend avenues to increase cascading use of wood as a carbon sink, by considering relevant aspects like the network of flows and processes, the quality and availability of the woody biomass, and the organization of the industry.

Building stock models can provide information on the current and future environmental impacts of buildings. Therefore, these models are useful tools for identifying trajectories that are compatible with the objectives of the Paris Agreement. However, the models often lack detail, which can lead to underestimations of the actual impacts of national building stocks, resulting in misinformed decision-making. This study presents the steps needed to create an archetype-based bottom-up building stock model that uses Python and Brightway2. Prospective environmental assessments, including circularity assessments, can be performed by combining life cycle assessment (LCA) with material flow analysis (MFA). An important facet of this model is that it supports the development of a practical and easily reproducible method for the high-precision modeling of a building stock. This model is open source, is readily adaptable to other countries, and does not require programming knowledge. This combined LCA-MFA method can be used to assess the potential to reduce greenhouse gas (GHG) emissions from the Austrian building stock in five future scenarios involving sufficiency, energy, material, and design-related measures. The results show different reduction potentials for embodied and operational GHG emissions depending on the set of measures taken. In all scenarios, mineral and synthetic materials contribute the most to embodied GHG emissions. Finally, the issue of validating building stock models is addressed, and numerous cross-evaluations are proposed to ensure the reliability of results.

The decarbonization of transport is a key goal facing climate change. The electrification of the powertrain for passenger cars is part of this goal to reduce carbon emissions. This involves a big change in the global supply chain, specifically in countries with a high weight of the traditional automotive sector, such as Spain, where above 10% of the GDP comes from this industry. There is a forecasted shift from the sector of traditional automotive parts to the electric sector, where batteries and electric components will be the major part of the powertrain. This work evaluates socioeconomic and environmental impacts of the changes in the car industry from the ramp-up of the electric vehicles market in Spain, and also in the European Union and the rest of the world. To do it, we use an environmentally extended multiregional and multi-sectoral input–output model. Our simulations include the technological change and demand shifts estimated to achieve the penetration of electric vehicles up to 2030 and 2050. The results show significant impacts on employment and economic indicators by 2050, when the share of electric vehicles is expected to increase up to a relevant level.

The circular economy (CE) challenges the traditional linear economic model by emphasizing the importance of resource efficiency, recycling, and regeneration in society. However, the role of gender in CE practices remains underexplored. This article presents a systematic literature review on how gender dynamics intersect with CE, highlighting the implications of gendered labor distribution, access to resources, and decision-making processes. Women, often pivotal in household and community resource management, are underrepresented in policy and research. Gender perspectives are therefore crucial for addressing social, environmental, and justice dimensions within CE. The study employs the lens of care labor to reveal power imbalances and the exclusion of marginalized groups, advocating for inclusive policies to achieve socially sustainable and equitable CE futures. The review identifies the overrepresentation of women in undervalued, informal activities and the dominance of men in highly valued, technologically advanced CE roles. It also underscores the benefits of gender diversity in corporate governance, which enhances sustainability practices. The article calls for a deeper examination of gender's impact on CE, suggesting a research agenda to integrate gender perspectives, enhance CE effectiveness, and promote equity. The findings indicate that addressing gender inequalities in CE is essential to prevent replicating the shortcomings of the linear economy and to foster innovative, inclusive, and sustainable development.

Material flow analysis (MFA) is used to quantify and understand the life cycles of materials from production to end of use, which enables environmental, social, and economic impacts and interventions. MFA is challenging as available data are often limited and uncertain, leading to an under-determined system with an infinite number of possible stocks and flows values. Bayesian statistics is an effective way to address these challenges by principally incorporating domain knowledge, quantifying uncertainty in the data, and providing probabilities associated with model solutions. This paper presents a novel MFA methodology under the Bayesian framework. By relaxing the mass balance constraints, we improve the computational scalability and reliability of the posterior samples compared to existing Bayesian MFA methods. We propose a mass-based, child and parent process framework to model systems with disaggregated processes and flows. We show posterior predictive checks can be used to identify inconsistencies in the data and aid noise and hyperparameter selection. The proposed approach is demonstrated in case studies, including a global aluminum cycle with significant disaggregation, under weakly informative priors and significant data gaps to investigate the feasibility of Bayesian MFA. We illustrate that just a weakly informative prior can greatly improve the performance of Bayesian methods, for both estimation accuracy and uncertainty quantification.

Construction activities are a major driver of greenhouse gas emissions worldwide. However, the majority of construction-driven emissions are indirect, meaning that these emissions occur during the manufacturing and transport of construction materials. This is in contrast with direct emissions, which are directly emitted from construction machinery. These indirect impacts are represented as embodied emissions and are difficult to quantify at scale, limiting the effectiveness of climate policymaking in the building sector. This paper presents results from a comprehensive account of embodied emissions within the Canadian construction sector, at a resolution far higher than existing global accounts, as well as novel analyses of flows and intensities of embodied emissions. It has the specific goal of serving as a baseline for future analyses of decarbonization scenarios and the more general goal of highlighting the importance of a consumption-based approach to climate policymaking in the sector. The accounts are produced via an environmentally extended input–output analysis based on Canadian supply–use tables for the year 2018, and results are presented for the 13 provinces and territories as well as 19 categories of buildings and infrastructure. Results show that demand from construction drives 13% of Canada's consumption-based emissions, residential construction is by far the largest driver of emissions, and at 0.28 kgCO_2eq per Canadian dollar of GDP, the efficiency of Canadian construction is roughly in line with the OECD average. A disproportionate share of emissions is driven by construction in provinces that are growing fast in terms of their populations, feature significant extractive industries, and feature higher emissions intensities. The construction sectors of western provinces are highly interconnected and receive a disproportionate proportion of embodied emissions from Alberta, whose high level of emissions promises to complicate decarbonization efforts. This article met the requirements for a gold-gold JIE data openness badge described at http://jie.click/badges

As the European Union transitions to the circular use of plastics, robust life cycle assessments are crucial in understanding and preparing for this new economy. Additives are essential to the production of all plastics but were reported as missing from life cycle assessments (LCAs) of plastic materials a decade ago. This study expands upon previous research by investigating if plastic additive impacts are now included in LCAs of recycled plastic materials or if they are still absent. In part I, we conduct a systematic literature review of 93 LCAs on plastics, including mechanical recycling pathways, and distinguish if plastic additive impacts are considered in (i) in-text discussions and (ii) the life cycle inventories (LCIs) of each study. We then compare the types of additive inclusion within the corpus to ascertain whether author knowledge or data availability dictates additive inclusion in plastic LCAs. We find that data disclosure and detailed discussions of specific additive impacts are missing across the corpus due to poor transparency in LCI disclosure or overly generic disclosures of additives. The lack of detailed and transparent discussions and disclosure indicates that additive impacts are missing from LCAs of recycled plastic materials, leading to incomplete analyses of their impacts. Until addressed, such a gap may lead to inaccurate or incomplete circular plastic material LCAs. In part II, we assess the quality of generic disclosures and explore how database quality and transparency have contributed to additive omissions in LCAs.