Journal of Industrial Ecology最新文献

Graphite is a key material in electric vehicle batteries. Currently, China dominates global graphite production, and US sourcing of graphite could mitigate geopolitical supply-chain risk. We explore the feasibility of domestic natural graphite sourcing in North America by characterizing current deposits and modeling the expected demand from 2025 to 2040. The United States has 19 Mt of measured and inferred graphite resources in four deposits, and additional unevaluated resources in several other areas. We estimate that this graphite resource could produce enough natural battery-grade graphite (7.3 Mt) to meet the demand from 2025 to 2040 (1.9 Mt). Issues of concern for domestic sourcing include the fact that the US deposits have a lower average graphite content (2.4%–5.1%) than profitable graphite mines globally, and the timeline for mine development, production, and commercialization might not align with the growth of demand. Additionally, battery-grade synthetic graphite supply, derived from needle coke, might be constrained unless refineries increase production of needle coke or alternate feedstocks are commercialized. Compared to China, US natural graphite production would likely decrease greenhouse gas emissions through lower electricity grid emissions during refining, despite lower ore grades.

We present a novel statistical model for predicting Scope 1 and 2 emissions for small and medium-sized enterprises (SMEs). Trained on financial transaction data from over 100,000 UK SMEs, the model targets a business segment excluded from formal emissions reporting and often under-engaged in sustainability efforts. By leveraging scalable, objective data, our approach offers an accessible alternative to existing methods that rely on either coarse sectoral averages or detailed, resource-intensive firm-level activity data. In developing the model, we evaluate a range of predictors and find that incorporating industry-level variables beyond basic emission intensity significantly enhances predictive accuracy. We also observe diminishing returns from additional model complexity, reinforcing the value of a parsimonious, low-input design. The final model achieves RSQ values of 0.89 for Scope 1 and 0.72 for Scope 2, improves accuracy by up to 50% compared to sector-level estimates, and performs reliably on out-of-sample data. Our findings provide a simpler approach to emissions estimation for SMEs, supporting broader climate engagement among smaller actors.

The fish transport sector plays a crucial role in both domestic and export markets in India, with insulated vehicles accounting for approximately 60% of fish transit immediately after landing. These insulated vehicles, although essential for maintaining fish quality and minimizing spoilage, contribute significantly to environmental concerns, including increased greenhouse gas emissions, energy consumption, and material use, particularly given their reliance on fossil fuels. This study assessed the environmental impact of using insulated vehicles to transport 1 tonne of fish over a distance of 200 km. Using SimaPro (V9.3) for a life cycle assessment, a landing-to-consumer approach was adopted, incorporating questionnaire-based and secondary data collection. The results revealed significant impacts on human health, with vehicle operations posing high risks (1.13E-05 disability-adjusted life years) due to diesel engine emissions. The long-term global warming potential from vehicle operations was higher than that from depreciated vehicle construction, with emissions measured at 4.44 kg CO₂ equivalent per tonne per trip over 100 years. The findings indicated that emissions from insulated vehicles during fish supply contributed approximately 0.4% of global emissions, underscoring the need for environmentally sustainable transportation practices in the fish transport system. Adopting electric vehicles, hybrids, biofuels, and emission controls can enhance sustainability in fish transport. Policies like the National Green Hydrogen Mission, carbon-neutral practices, and green exports support this transition in the fish transport system.

When using discrete dynamic stock models in combination with lifetime distributions, the total amount of material transported in a period is implicitly assumed to be a spike at either the start or the end of the considered period. Depending on the choice, the residence time of materials in stock is either underestimated in the inflow-at-start approach or overestimated in the inflow-at-end approach. This paper proposes to solve this assignment problem by assuming the total mass flow to be evenly distributed over the period, using a continuous dynamic stock model, and discretizing the results afterward. It will be shown that this so-called uniform-inflow approach delivers more realistic results.

This study investigates opportunities to reduce carbon emissions in the telecommunication sector in India by extending the analytical scope beyond operational activities to include equipment installation and service delivery within the telecom supply chain. A three-step methodology framework is employed to comprehensively account for emissions across Scopes I, II, and III. The first step comprises a systematic literature review, identifying 62 carbon reduction initiatives across the telecom supply chain. Factor and regression analysis are used to evaluate the contributions of equipment, operations, and channel partners to carbon mitigation. The next step applies material flow cost accounting (MFCA) to telecom infrastructure, identifying multiple quantity centers to measure electricity consumption and carbon emissions by equipment type. These insights are integrated with findings from the literature review to trace year-on-year emission trends and identify potential reductions. The contribution of technological interventions to improve overall efficiency is also assessed. In the final step, MFCA outcomes are linked with enterprise resource planning systems to enhance organizational decision-making. Results reveal that operational activities account for the smallest share of emissions reduction potential (30.49%) while significant opportunities exist in the equipment installation phase and at service delivery partner sites, representing a potential improvement of up to 227%.

Understanding the dynamics of building material stocks and flows, including the turnover processes of building stock, is important for promoting sustainable resource use in cities. This study provides high-resolution, integrated mapping of building material stocks and flows across various cities and regions in Japan, offering a detailed view of the country's spatial material metabolism. This research combines bottom-up estimates of material stocks and flows with spatial analysis using material metabolism indicators, examining how patterns of material stock turnover vary across Japan. Spatial variations in material stock turnover highlight regional factors that influence stock–flow dynamics and offer insights into local resource use and policy development tailored to specific regional contexts. In this study, the national stock turnover rate in 2020 is estimated to be 1.16%/year for inflow and 0.64%/year for outflow, with more active metabolism observed in the central areas of large metropolitan regions and lower levels in low-density rural areas. Additionally, distinct patterns of material metabolism were observed across districts, associated with redevelopment and urban sprawl. This study illustrates how spatially detailed approaches can support the analysis of stock–flow dynamics across the country and contribute to the development of sustainable resource use strategies tailored to local conditions.

Policies targeting cross-border industrial decarbonization, such as carbon tariffs, may risk exacerbating the structural inequity between countries/regions regarding climate responsibility and economic benefits. As a typical representative, the EU's Carbon Border Adjustment Mechanism (CBAM) is introduced to combat carbon leakage and promote global industrial decarbonization. However, the implications of CBAM on trade-related carbon inequity remain underexplored. Using international trade data of the primary CBAM-targeted sectors (cement, fertilizers, iron and steel, and aluminum), we apply the Carbon Gini coefficient and the Trade Carbon Inequity (TCI) index to assess the effects of carbon tariffs with various revenue recycling mechanisms on trade-related carbon inequities at both global and national/regional levels. The results reveal that implementing CBAM, without revenue recycling, significantly intensifies carbon inequity, as indicated by increased Carbon Gini coefficients and higher percentage increases in developing economies’ TCI indices. Moreover, revenue recycling—whether based on national/regional historical climate damage or per-capita income—partially mitigates these effects, yet carbon inequities remain above the pre-CBAM baselines. In contrast, our proposed TCI-based allocation criterion reduces the Carbon Gini coefficients below pre-CBAM levels and offsets CBAM-related TCI increases in developing economies such as Turkey and India. These findings emphasize that CBAM design needs to integrate justice-oriented revenue recycling to harmonize decarbonization efforts with equity goals in pursuing a globally carbon-neutral economy while reconciling Sustainable Development Goals—specifically, “SDG13-Climate Action” and “SDG10-Reduced Inequalities.”

Understanding the link between well-being and carbon emissions is crucial, as demand-side emission reduction efforts should not compromise living standards. While a nonlinear, threshold-based relationship between well-being and carbon emissions has been identified at the national level, empirical evidence at the household or individual level remains limited. Using data from the China Family Panel Studies, this study develops a multidimensional indicator framework to measure household well-being and empirically assesses its relationship with per capita carbon emissions. The results indicate an inverted U-shaped relationship, where carbon emissions are initially associated with improvements in well-being. However, beyond a certain threshold, further increases in carbon emissions are no longer linked to significant gains in well-being. Specifically, the decoupling threshold is estimated at 15.4 tons of CO₂ annually per capita in the absence of technological progress, and is reduced to 9.7 tons when technological improvements are taken into account. However, the available carbon budget is insufficient for all individuals to reach these decoupling points, and sample households could only reduce emissions by 1.4% without sacrificing overall well-being. Moreover, prioritizing limited carbon allowances for low-income groups may maximize societal well-being, since their carbon intensity of human well-being is comparatively lower. These findings underscore the importance of technological progress and population heterogeneity in designing fair and effective policies that balance well-being with emission reductions.

Comprehensive methods for estimating mismanaged waste accumulation in the environment are limited, especially in the Global South, and new technologies are urgently needed. Here, we applied the Azure system, a physical floating barrier designed to retain and extract river floating waste while providing observational data of mismanaged waste, comparing results with a modeling tool that uses material flow analysis to provide estimates of mismanaged waste, incorporating environmental and socioeconomic factors. The Azure system was installed at the Portoviejo River (Ecuador), and anthropogenic litter was removed, extracted, weighed, and classified. Approximately 13.8 tonnes (t) of litter were collected over 2 years of sampling, of which 87% were plastic bags containing domestic waste. About 45% of the total waste collected, that is, 6.2 t, was estimated to be plastic waste. In contrast, modeled mismanaged plastic waste estimates for the Portoviejo River varied between 148 and 1858 t per year, at least two orders of magnitude higher than field data. These results highlight the discrepancy that can occur between observational data and waste estimates. The factors that contribute to this are discussed here to help understand riverine waste sources and transport to the ocean. The results emphasize the need for a better understanding of socioeconomic and environmental aspects in the Global South to help the development of better modeling tools. Our findings of domestic deposition as a major source of riverine contamination in the Portoviejo watershed emphasize the importance of waste management for tackling river contamination. Effective monitoring tools, such as the Azure system, could help improve this.

China is actively committed to mitigating carbon emissions through its “Dual Carbon” and “Zero-Waste Cities” strategies. Hazardous waste (HW) treatment, a significant source of greenhouse gas (GHG) emissions, plays a crucial role in achieving carbon reduction targets. This study systematically assessed the carbon emissions and low-carbon pathways of a representative multi-HW treatment park in Qingdao using life cycle assessment and life cycle cost methodologies. In 2020, the total net GHG emissions of the HW park were 49,669.3 t CO₂-eq, with an average emission intensity of 1181.1 kg CO₂-eq per tonne of HW. Among the various treatment systems, medical waste (MW) incineration exhibited the highest GHG emission intensity (1377.6 kg CO₂-eq/t MW), followed by industrial hazardous waste (IHW) incineration (1076.4 kg CO₂-eq/t IHW), fly ash/slag treatment (9.7 kg CO₂-eq/t HW), and physicochemical treatment (8.5 kg CO₂-eq/t HW). Three integrated low-carbon pathways demonstrated that utilizing waste heat for heating exhibited the highest carbon mitigation potential, achieving up to −403.6 kg CO₂-eq/t IHW, followed by technological improvement and resource recycling. The combined low-carbon scenario could achieve a 49.5% reduction in total carbon emissions compared to the baseline scenario. Furthermore, economic performance improved, with treatment benefits increasing from 3431.3 RMB/t IHW to 3948.5 RMB/t IHW due to enhanced energy efficiency and resource recovery. This study provides a framework for assessing multi-HW parks’ carbon footprints and offers strategic insights for low-carbon, resource-efficient waste management. The findings also support sustainable multi-HW management and contribute to climate and decarbonization efforts.