Journal of Industrial Ecology最新文献

Securing the availability of enough metals to fulfill demand is a critical societal concern. Models of metal supply systems can help enhance our understanding of these systems and identify strategies to reduce material criticality and improve resilience. In this work, we introduce a novel approach to modeling metal supply systems, using nickel as a case study. Our approach combines system dynamics modeling, in which various feedback loops influence future outcomes, with the higher sectoral and geographical detail of industrial ecology (IE) methods and data on individual mines. We also include extensive uncertainty analyses through exploratory modeling and analysis. Using this combined modeling approach, we explore the development and resilience of the global nickel supply system between 2015 and 2060 under various uncertainties and policy levers. Our results show that incorporating feedback effects leads to more realistic demand behavior and resource depletion patterns compared to traditional dynamic material flow analysis. Market feedback enhances resilience, but cannot fully offset criticality risks. Sectoral disaggregation reveals increased criticality risks due to the energy transition, which can be mitigated by increasing opportunities for substitution, product lifetime extension, recycling, exploration, capacity expansion, and by-product recovery. Geographical disaggregation highlights the resilience benefits of diverse supply sources, as well as the effects of changing regional market shares on sustainability impacts, ore grade variability, and by-product dynamics. Our combined modeling approach is a step toward prospective, dynamic criticality assessment, in which system changes and future risks are accounted for when determining material criticality and policy recommendations.

Tungsten (W), as “the teeth of modern industry,” is playing an irreplaceable role in the current industrial era due to its unique properties. Although the global primary tungsten supply is concentrated in China, the grade of such ore is deteriorating, leading to more consideration of promoting the reuse and recycling of tungsten scraps. However, the environmental impacts induced by tungsten recycling have not been investigated, which may influence the appropriate circular economy implementation along the entire tungsten industrial chain. This study aims to identify the “side effects” of tungsten recycling by comparing the pros and cons of primary/secondary tungsten production from a life cycle perspective. The environmental impacts of the primary tungsten production system (W-PPS), direct recycling system (W-DRS), and indirect recycling system (W-IRS) are estimated by using 18 mid-point indicators in human health, ecosystems, and resources categories. Results indicate that switching to W-DRS and W-IRS from W-PPS could help reduce environmental burdens in terms of major mid-point indicators, except human non-carcinogenic toxicity and terrestrial ecotoxicity. Energy and chemical raw materials input contribute the most to the above environmental impacts. Based upon these findings, we propose that serious regulations should be implemented for both primary and secondary production systems, as well as appropriate urban mine actions and sustainable industrial design schemes.

Environmental assessments of digital services currently apply an accounting perspective, and for telecommunication networks (TN) allocate electrical energy consumption in proportion to data traffic. Yet, the power draw by wired TN infrastructure is almost independent of the volume of data traffic flowing through it. Previous assessments of the effect of data traffic on energy consumption thus tended to over-estimate the short-term impact on energy consumption.

However, the growth of peak data traffic rates is a main driver of increasing TN bandwidth capacity and has an indirect impact on electrical energy consumption. This nuanced causal relationship has not been consistently represented in allocation approaches used for attributional carbon footprints.

In this text, we apply a form of consequential system expansion by considering the long-term response to peak-traffic growth. This allows us to model long-run marginal changes to product system attributes that are fixed in the short-term. The outcome illustrates a causally consistent allocation approach that avoids contradicting the short-term behavior of the engineered system.

Based on a causal inference graph of the drivers for the fixed baseload power draw by TN, we distinguish between the effects of different types of data as they contribute to traffic peaks. From this, we develop transform functions that re-allocate environmental burden to peak traffic. We present such functions for the specific case of periodically diurnal traffic in TN (including video-on-demand) and discuss the case of sporadic high-throughput events (including video streaming of life sport events and games downloads).

The allocation model incentivizes a reduction of peak demand through avoidance or demand-shifting, to decelerate the long-term expansion of TN infrastructure.

In emerging economies like India, infrastructure development is expected to grow in the coming decades. Buildings, an important infrastructural asset and anthropogenic material source, need adequate exploration as potential raw material repositories. This study introduces a novel “Material FLow and market Behavior Assessment (MaLBA)” model to evaluate building material circularity prospects while integrating dynamic stock modeling for material flow and the Bass diffusion model for market maturity. The MaLBA model studies the feasibility of construction and demolition waste (CDW) recycling at the regional scale for Thane City, India, and highlights the influence of marketing mechanisms such as advertisement and word of mouth in recycled CDW product adoption at the regional scale. The model predicts a 20% decadal increase in CDW generation in the region, while the material required for new construction activities in Thane is expected to correspondingly rise by 13% between 2024 and 2050. Considering the present Indian policies focus on CDW recycling as the major CDW management strategy, the MaLBA model suggests that expanding Thane's recycling capacity from 300 to 700 Mt/Day can prove counterproductive to meet the national targets as the technical limitations of recycled material usage and limited user acceptance might lead to an oversupply of recycled CDW products by 2050. Therefore, this study recommends focusing on market development by doubling efforts to advertise recycled products and expand recycling infrastructure in alignment with regional infrastructure growth. Additionally, this study also suggests diversifying the CDW management approach by including strategies such as reduce and reuse for long-term benefits.

Understanding the trends and distribution of greenhouse gas (GHG) emissions embodied in household consumption is pivotal to developing climate-change mitigation strategies that are just and effective. While household GHG footprints inequality is increasingly investigated, less is known about its temporal dynamics across product groups. For the case of Austria, we (1) develop a database for household GHG footprints from 2000 to 2020 by combining multi-regional input–output modeling with household budget surveys, (2) investigate temporal trends across consumption categories and income groups, and (3) explore socio-economic explanatory variables. We find that the sum of Austrian household GHG footprints declined from 73 Mt CO2eq in 2000 to 67 Mt CO2eq in 2020. In 2005, when Austrian GHG emissions peaked, the highest income decile induced 3.5 times more GHG emissions than the lowest income decile. This factor remained similarly high at 3.4 until 2020, particularly due to trends in the consumption categories mobility and goods. The most notable GHG reduction was achieved in housing/heating, where carbon inequality was less pronounced. Beyond income, floor space, car ownership, the heating system, household size, and the number of vacations significantly affect GHG footprints. Our findings suggest that reducing stubbornly high carbon inequality, particularly in the consumption of mobility and goods, can contribute to more effective climate-change mitigation.

This study provides a comparative analysis of the biophysical economic structures of four developed economies—Sweden, the United States, the United Kingdom, and Canada. We draw upon results from input–output models to map and analyze capital, energy, and carbon relationships in each economy. The capital stock of each country is divided into four sectors: (i) energy production and distribution, (ii) production of goods and services for consumption, (iii) residential, and (iv) construction and manufacture of capital. The findings reveal diverse strengths and challenges in decarbonization efforts across the countries. Sweden excels in “energy production and distribution” and “residential” sectors, owing to its commitment to renewable energy and energy efficiency, but requires attention in goods and services production where carbon intensity is high. The United Kingdom stands out for its high greenhouse gas intensity in residential capital stock and in the consumption of goods and services, underscoring the need for targeted low-carbon investments. The United States and Canada display high GHG intensities across all sectors, necessitating a more robust transition toward renewable and low-carbon energy solutions. In particular, the United States’ carbon intensity in its energy sector and Canada's industry dominated by fossil fuel extraction offer specific areas for intervention. The study concludes that focusing on sectors with the highest carbon intensity and adopting both sector-specific and broader strategies can significantly accelerate each country's decarbonization efforts, thereby contributing to global climate change mitigation. This article met the requirements for a gold-gold JIE data openness badge described at http://jie.click/badges.

This paper investigates future energy requirements; amounts of carbon dioxide needed, emitted, or captured; and capital and operating expenses in Germany's process industries derived from a techno-economic evaluation of production methods under various scenarios. These methods include maintaining conventional production, adopting direct electrification, or implementing hydrogen-based technologies. Scenarios vary the assumptions on hydrogen and carbon dioxide emission allowance prices for 2035 and 2045. Which production methods are cost-effective, and therefore assumed to be implemented in the scenarios, depends on marginal abatement costs of carbon dioxide emissions across industries. For 2035, results show that only very low hydrogen prices and emission allowance prices above €200 per metric ton drive significant adoption of low-carbon production methods, with hydrogen demand ranging from nearly zero to 238 TWh and electricity demand from 54 to 197 TWh. Scenarios for 2045 assume full defossilization, with hydrogen demand ranging between 267 and 419 TWh and electricity requirements between 163 and 301 TWh. Across all scenarios analyzing 2045, 263 TWh of hydrogen are used as a reactant, a reductant, or for metallurgical purposes, making this demand portion, given the lack of other defossilization options, unavoidable when aiming for complete defossilization while maintaining domestic production. Additionally, the paper regionalizes selected scenario results based on site-specific data. The regionalization reveals a strong concentration of high hydrogen demands for use as a reactant and reductant at only a few sites, posing challenges for integration into the energy infrastructure, while hydrogen used for process heating shows a more decentralized distribution.

The simplest method for treating liquid digestate, which involves directly spreading it over local agricultural land, is facing scrutiny due to the challenges of transporting large volumes and the environmental risks posed by nitrogen and phosphorus pollutants. Improvements in liquid digestate treatment are necessary to mitigate these threats and support a growing circular economy. This study evaluates an advanced digestate treatment method that decouples hydraulic retention time (HRT) and solid retention time (SRT) in high-rate algal/bacterial ponds (HRABPs). By combining life cycle assessment (LCA) with high-fidelity modeling for HRABPs, this study simulates productivity and removal efficiencies under realistic climatological conditions, providing life cycle inventories for numerous large-scale scenarios. To minimize environmental impacts while maximizing algal productivity and nitrogen intake in the algal biomass, 36 scenarios were simulated, considering different HRT, SRT, alkalinity addition, winter storage, and biomass post-treatment hypotheses. The results demonstrate that microalgae treatment makes sense for valorizing liquid digestate, proving to be less impactful than direct land application. However, the LCA results also highlight the complexity of the issue. Low HRT (HRT = 5 days < SRT = 10 days), including winter storage, requires the smallest production area, resulting in high productivity and low environmental impacts. Conversely, high HRT (HRT = 90 days > > SRT = 15 days) achieves the highest efficiency in nitrogen and phosphorus recycling but necessitates large production areas, leading to high environmental impacts. Mathematical modeling, coupled with LCA, can resolve these trade-offs and guide the optimization and scaling-up of climatology-dependent systems.

Bioeconomy is often cited as one pathway toward sustainable materials and a circular economy in an urban–rural context. This study conducts a life cycle sustainability assessment (LCSA)—life cycle assessment, social life cycle assessment, and life cycle costing (LCC)—to assess the benefits and impacts of substituting fossil polymer-based products with biogenic alternatives through two product systems: drinking cups and insulation boxes. In detail, we assess the environmental impacts, social hotspots, and societal costs subject to various product characteristics. The latter comprises, among others, different materials (fossil-based polymers, first-generation and second-generation biomass), allocation scenarios, electricity mixes, use cycles, and end-of-life (EoL) quotas. The LCSA is conducted with primary data provided by industry partners and secondary data from ecoinvent, the social hotspots database, and the literature. The results show that the drinking cup from second-generation bio-polyethylene (bio-PE) performs best in most environmental impact categories, followed by the fossil-based polypropylene (PP) cup. When substituting PP cups with bio-PE cups, 32% of CO₂ eq. emissions and 37% of water can be saved, while land use and particulate matter emissions increase by 37% and 7%, respectively. Due to low recycling rates in the status quo, cups made of polylactide acid—a first-generation bio-based polymer—often have higher environmental impacts than fossil-based ones. Governance and health and safety are the most prominent social categories and are especially linked with raw materials transportation. Similar trends are observed for the insulation box product system. The study identifies improvements in EoL practices, using biomass as-is, and regional sourcing as essential for enhancing bio-based materials' sustainability.