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Summary: The emergence of increasingly complex data in industrial ecology (IE) has caused scholarly interest in interactive visualization (IV). IV allows users to interact with data, aiding in processing and interpreting complex datasets, processes, and simulations. Consequently, IV can help IE practitioners communicate the complexities of their methods and results, shed light on the underlying research assumptions, and enable more transparent monitoring of data quality and error. This can significantly increase the reach and impact of research, promote transparency, reproducibility, and open science, as well as improve the clarity and presentation of IE research. A review of current IV applications reveals that, while data exploration has received some attention among IE practitioners, IV applications in scientific communication are clearly lacking. With the help of a working example, we explore the value of IV, discuss its operationalization, and highlight challenges that the IE community must face during IV uptake. Such challenges include technical and knowledge limitations, limits on user interaction, and implementation strategies. With these challenges in mind, we outline key aspects needed to lift the IE field to the forefront of scientific communication in the coming years. Among these, we draft the basic principles of a "Hub for Interactive Visualization in Industrial Ecology" (HIVE), a point of encounter where IE practitioners could find an array of data visualization tools that are geared toward IE datasets. IV is here to stay, and its inceptive stage presents many opportunities to IE practitioners to shape its operationalization and benefit from early adoption. [ABSTRACT FROM AUTHOR]

Summary: The divide between attributional and consequential research perspectives partly overlaps with the long‐standing methodological discussions in the life cycle assessment (LCA) and input‐output analysis (IO) research communities on the choice of techniques and models for dealing with situations of coproduction. The recent harmonization of LCA allocations and IO constructs revealed a more diverse set of coproduction models than had previously been understood. This increased flexibility and transparency in inventory modeling warrants a re‐evaluation of the treatment of coproduction in analyses with attributional and consequential perspectives. In the present article, the main types of coproductions situations and of coproduction models are reviewed, along with key desirable characteristics of attributional and consequential studies. A concordance analysis leads to clear recommendations, which call for important refinements to current guidelines for both LCA/IO practitioners and database developers. We notably challenge the simple association between, on the one hand, attributional LCA and partition allocation, and on the one hand, consequential LCA and substitution modeling. [ABSTRACT FROM AUTHOR]

The complexity of data and methods in industrial ecology (IE) keeps growing, and the demand for comprehensive and interdisciplinary assessments increases. To keep up with this development, the field needs a data infrastructure that allows researchers to annotate, store, retrieve, combine, and exchange data at low cost, without loss of information, and across disciplines and model frameworks. A consensus-building debate about how to describe the common object of study, socioeconomic metabolism (SEM), is necessary for the development of practical data structures and databases. We review the definitions of basic concepts to describe SEM in IE and related fields such as integrated assessment modeling. We find that many definitions are not compatible, are implicit, and are sometimes lacking. To resolve the conflicts and inconsistencies within the current definitions, we propose a hierarchical system of terms and definitions, a practical ontology, for describing objects, their properties, and events in SEM. We propose a typology of object properties and use sets to group objects into a hierarchical, mutually exclusive, and collectively exhaustive (H-MECE) classification. This grouping leads to a general definition of stocks. We show that a MECE representation of events necessarily requires two complementary concepts: processes and flows, for which we propose general definitions based on sets. Using these definitions, we show that the system structure of any interdisciplinary model of SEM can be formulated as a directed graph. We propose guidelines for semantic data annotation and database design, which can help to turn the vision of a powerful data infrastructure for SEM research into reality. [ABSTRACT FROM AUTHOR]

The production of waste creates both direct and indirect environmental impacts. A range of strategies are available to reduce the generation of waste by industry and households, and to select waste treatment approaches that minimize environmental harm. However, evaluating these strategies requires reliable and detailed data on waste production and treatment. Unfortunately, published Australian waste data are typically highly aggregated, published by a variety of entities in different formats, and do not form a complete time-series. We demonstrate a technique for constructing a multi-regional waste supply-use (MRWSU) framework for Australia using information from numerous waste data sources. This is the first MRWSU framework to be constructed (to the authors' knowledge) and the first sub-national waste input-output framework to be constructed for Australia. We construct the framework using the Industrial Ecology Virtual Laboratory (IELab), a cloud-hosted computational platform for building Australian multi-regional input-output tables. The structure of the framework complies with the System of Environmental-Economic Accounting (SEEA). We demonstrate the use of the MRWSU framework by calculating waste footprints that enumerate the full supply chain waste production for Australian consumers. [ABSTRACT FROM AUTHOR]

Industrial assets or fixed capital stocks are at the core of the transition to a low-carbon economy. They represent substantial accumulations of capital, bulk materials, and critical metals. Their lifetime determines the potential for material recycling and how fast they can be replaced by new, more efficient facilities. Their efficiency determines the coupling between useful output and energy and material throughput. A sound understanding of the economic and physical properties of fixed capital stocks is essential to anticipating the long-term environmental and economic consequences of the new energy future. We identify substantial overlap in the way stocks are modeled in national accounting, dynamic material flow analysis, dynamic input-output (I/O) analysis, and life cycle assessment (LCA) and we merge these concepts into a common framework for modeling fixed capital stocks. We demonstrate the usefulness of the framework for simultaneous accounting of capital and material stocks and for consequential LCA. We apply the framework to design a demand-driven dynamic I/O model with dynamic capital stocks, and we synthesize both the marginal and attributional matrix of technical coefficients (A-matrix) from detailed process inventories of fixed assets of different age cohorts and technologies. The stock modeling framework allows researchers to identify and exploit synergies between different model families under the umbrella of socioeconomic metabolism. [ABSTRACT FROM AUTHOR]

Sustainable development and digital transformation profoundly re-shape industrial societies but have been studied largely independently. In light of pressing global environmental and social challenges, both transformations need to be well aligned with each other to achieve multiple objectives such as listed under the UN Sustainable Development goals (SDGs). Quantitative research on interlinkages, energy and material implications, and co-dependencies between the different digital transformation (DT) and sustainable development (SD) strategies is emerging and has so far focused on estimating the overall potential and on life cycle assessment (LCA). To frame the problem systematically, we developed a hierarchy of system levels for studying society's material and energy use, including the four levels: product/process, process cluster, life cycle/material cycle, and economy-wide. We mapped major DT strategies and the SDGs to the hierarchy and found a wide gap in system coverage: While most DT strategies focus on the product, process and process cluster levels, the SDGs predominantly target the economy-wide level. Socio-metabolic and industrial ecology research is needed to inform decision makers on how the two transformations can be aligned to reach overarching societal goals, such as the SDGs, expanding on and moving beyond LCA. Future research needs to assess combinations of multiple DT and SD strategies. It needs to study how DT can help decouple human wellbeing from negative environmental and social impacts. Research needs to focus on the strategies' deployment potential, infrastructure needs, impacts on material cycles, and potential to transform both service demand and industrial production. [Display omitted] • Sustainable development and digital transformation will profoundly reshape society. • Both transformations must be aligned to achieve multiple objectives like the SDGs. • Digital strategies focus on products and processes, SDGs target the system level. • Strategies and supporting policies need to be co-designed across multiple domains. • We propose a detailed agenda for socio-metabolic and industrial ecology research. [ABSTRACT FROM AUTHOR]

Identifying strategies for reducing greenhouse gas emissions from steel production requires a comprehensive model of the sector but previous work has either failed to consider the whole supply chain or considered only a subset of possible abatement options. In this work, a global mass flow analysis is combined with process emissions intensities to allow forecasts of future steel sector emissions under all abatement options. Scenario analysis shows that global capacity for primary steel production is already near to a peak and that if sectoral emissions are to be reduced by 50% by 2050, the last required blast furnace will be built by 2020. Emissions reduction targets cannot be met by energy and emissions efficiency alone, but deploying material efficiency provides sufficient extra abatement potential. [ABSTRACT FROM AUTHOR]

As the world's largest CO2 emitter and steel producer, China has set the ambitious goal of establishing a circular economy which aims at reconciling economic development with environmental protection and sustainable resource use. This work applies dynamic material flow analysis to forecast production, recycling, and iron ore consumption in the Chinese steel cycle until 2100 by using steel services in terms of in-use stock per capita as driver of future development. The whole cycle is modeled to determine possible responses of the steel industry in light of the circular economy concept. If per-capita stock saturates at 8-12 tons as evidence from industrialized countries suggests, consumption may peak between 2015 and 2020, whereupon it is likely to drop by up to 40% until 2050. A slower growing in-use stock could mitigate this peak and hence reduce overcapacity in primary production. Old scrap supply will increase substantially and it could replace up to 80% of iron ore as resource for steel making by 2050. This would require advanced recycling technologies as manufacturers of machinery and transportation equipment would have to shift to secondary steel as well as new capacities in secondary production which could, however, make redundant already existing integrated steel plants. [ABSTRACT FROM AUTHOR]

The IPCC Forth Assessment Report postulates that global warming can be limited to 2 °C by deploying technologies that are currently available or expected to be commercialized in the coming decades. However, neither specific technological pathways nor internationally binding reduction targets for different sectors or countries have been established yet. Using the passenger car stock in China as example we compute direct CO2 emissions until 2050 depending on population, car utilization, and fuel efficiency and compare them to benchmarks derived by assuming even contribution of all sectors and a unitary global per capita emission quota. Compared to present car utilization in industrialized countries, massive deployment of prototypes of fuel efficient cars could reduce emissions by about 45%, and moderately lower car use could contribute with another 33%. Still, emissions remain about five times higher than the benchmark for the 2 °C global warming target. Therefore an extended analysis, including in particular low-carbon fuels and the impact of urban and transport planning on annual distance traveled and car ownership, should be considered. A cross-sectoral comparison could reveal whether other sectors could bear an overproportional reduction quota instead. The proposed model offers direct interfaces to material industries, fuel production, and scrap vehicle supply. [ABSTRACT FROM AUTHOR]

Different options for a reform of the EU Emissions Trading System are discussed to ensure carbon price incentives for mitigation options in the basic materials sector, while minimizing carbon leakage risks. This paper quantifies carbon leakage risks, distributional implications, and additional revenues associated with an import-only border carbon adjustment (BCA), a symmetric (import and export) BCA, and an excise for embodied emissions at a fixed benchmark level in combination with continued free allocation. We estimate the product-level carbon intensities for 4400 commodity groups, compute maximal implied price changes due to full carbon pricing, and calculate cost increases relative to gross value added to assess the scale of carbon leakage risks. We show, first, that around 10% of EU exports and 5% of all domestic manufacturing sales meet the criteria for carbon leakage risk under an incomplete BCA at a carbon price of 30 EUR/t. Second, the distributional implications of consistent carbon pricing of basic materials are small and progressive. Finally, an excise could generate revenues of around 20 billion euros that may be used towards climate action. Our results on potential carbon leakage risks and their mitigation can inform responsible policy making to shape the EU pathway towards climate neutrality. • Embodied emissions of basic materials in 4400 commodity groups quantified. • Effects of border carbon adjustments and excise duty on key economic variables. • Substantial carbon leakage risks along the value chain and in export markets. • Limited and slightly progressive effect of material carbon pricing on consumers. • Fiscal revenues under border carbon adjustments and excise duty estimated. [ABSTRACT FROM AUTHOR]

Material stocks of infrastructure, buildings, and machinery are the biophysical basis of production and consumption. They are a crucial lever for resource efficiency and a sustainable circular economy. While material stock research has proliferated over the last years, most studies investigated specific materials or end‐uses, usually not embedded into an economy‐wide perspective. Herein, we present a novel version of the economy‐wide, dynamic, inflow‐driven model of material inputs, stocks, and outputs (MISO2), and present a global, country‐level application. Currently, MISO2 covers 14 supply chain processes from raw material extraction to processing, trade, recycling, and waste management, as well as 13 end‐uses of stocks. The derived database covers 23 raw materials and 20 stock‐building materials, across 177 countries from 1900 to 2016. We find that total material stocks amount to 1093 Gt in 2016, of which the majority are residential (290 Gt) and non‐residential buildings (234 Gt), as well as civil engineering (243 Gt), and roads (313 Gt). The other nine end‐uses covering stationary and mobile machinery, as well as short‐lived products, amount to 13 Gt. Material stocks per capita are highly unequally distributed around the world, with one order of magnitude difference between low‐ and high‐income countries. Results agree well with similar global country‐level studies. Low data quality for some domains, especially for lower‐income countries and for sand and gravel aggregates, warrant further attention. In conclusion, the MISO2 model and the derived database provide stock‐flow consistent perspectives of the socio‐economic metabolism around the world, enabling multiple novel and policy relevant research opportunities. This article met the requirements for a silver‐gold JIE data openness badge described at http://jie.click/badges. [ABSTRACT FROM AUTHOR]

• The tungsten cycle in China from 1949 –2017 has been quantified for the first time. • China's tungsten dominance only exists in low value-added products which face over-capacity issues. • China's future tungsten supply will be constrained by the declining tungsten ore quality. • China is a net-exporter of tungsten products, but has high dependence on tech-intensive tungsten products from other nations. Tungsten is deemed a critical raw material by many nations, given its irreplaceable use in industrial and military applications. In particular, much concern has been drawn to China's high share in global tungsten supply. While various studies have focused on the criticality of tungsten, few have specifically explored how tungsten is produced, consumed, and traded. In this paper, the dynamic material flow analysis is applied to quantify China's annual tungsten cycle from 1949 – 2017. It is estimated that total tungsten mined from ores in China over the past 68-year period is ~2500 kilo-tons (kt). Among those, ~750 kt of tungsten has been exported to other countries, and around 970 kt tungsten is domestically consumed. It is noted ≈1720 kt has been lost from mining, production, and end-of-life stage, and merely ~130 kt has been recycled as end-of-life scrap. Our material flow analysis further refined China's tungsten dominance. Although China currently dominates the global production of tungsten, this dominance will not extend too far into the future given China's limited share of world tungsten reserves and its declining ore quality. Our trade flow analysis reveals that China imported ~35 kt of high value-added downstream tungsten products from outside manufacturers, whose mineral resource was originally imported from China. At present, China by itself is experiencing overcapacity issues in the primary production, which discourages the recycling of at end-of-life (EoL) stage and makes the EoL recycling rate only 10%. It is noted that the percentage of Chinese tungsten for domestic consumption has been increasing in the past few years. This highlights the need for systematic measures from stakeholders along the tungsten cycle to promote sustainable practices for efficient tungsten production, use, and recycling in China. Meanwhile, the results also suggest the importance of monitoring the criticality of tungsten and other critical minerals from a dynamic and material cycle perspective. Image, graphical abstract [ABSTRACT FROM AUTHOR]

Carbon neutrality requires systematic transformations of both energy and metal systems. These transformations are not isolated but rather interlinked and interdependent, such that trade-offs between different strategies exist. Herein, we explore the critical interlinkages between energy and metal systems and further propose a circular metal-energy nexus to advance global coordinated actions towards a carbon-neutral future., Competing Interests: The authors declare that they have no conflicts of interest in this work., (© 2022 The Authors. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd.)

Material production accounts for a quarter of global greenhouse gas (GHG) emissions. Resource-efficiency and circular-economy strategies, both industry and demand-focused, promise emission reductions through reducing material use, but detailed assessments of their GHG reduction potential are lacking. We present a global-scale analysis of material efficiency for passenger vehicles and residential buildings. We estimate future changes in material flows and energy use due to increased yields, light design, material substitution, extended service life, and increased service efficiency, reuse, and recycling. Together, these strategies can reduce cumulative global GHG emissions until 2050 by 20-52 Gt CO 2 -eq (residential buildings) and 13-26 Gt CO 2 e-eq (passenger vehicles), depending on policy assumptions. Next to energy efficiency and low-carbon energy supply, material efficiency is the third pillar of deep decarbonization for these sectors. For residential buildings, wood construction and reduced floorspace show the highest potential. For passenger vehicles, it is ride sharing and car sharing., (© 2021. The Author(s).)

In the absence of data on the destination industry of international trade flows most multi-regional input-output (MRIO) tables are based on the import proportionality assumption. Under this assumption imported commodities are proportionally distributed over the target sectors (individual industries and final demand categories) of an importing region. Here, we quantify the uncertainty arising from the import proportionality assumption on the four major environmental footprints of the different regions and industries represented in the MRIO database EXIOBASE. We randomise the global import flows by applying an algorithm that randomly assigns imported commodities block-wise to the target sectors of an importing region, while maintaining the trade balance. We find the variability of the national footprints in general below a coefficient of variation (CV) of 4%, except for the material, water and land footprints of highly trade-dependent and small economies. At the industry level the variability is higher with 25% of the footprints having a CV above 10% (carbon footprint), and above 30% (land, material and water footprint), respectively, with maximum CVs up to 394%. We provide a list of the variability of the national and industry environmental footprints in the Additional files so that MRIO scholars can check if an industry/region that is important in their study ranks high, so that either the database can be improved through adding more details on bilateral trade, or the uncertainty can be calculated and reported., Supplementary Information: The online version contains supplementary material available at 10.1186/s40008-021-00250-8., Competing Interests: Competing interestsThe authors declare that they have no competing interests., (© The Author(s) 2021.)

This study provides scenarios toward 2050 for the demand of five metals in electricity production, cars, and electronic appliances. The metals considered are copper, tantalum, neodymium, cobalt, and lithium. The study shows how highly technology-specific data on products and material flows can be used in integrated assessment models to assess global resource and metal demand. We use the Shared Socio-economic Pathways as implemented by the IMAGE integrated assessment model as a starting point. This allows us to translate information on the use of electronic appliances, cars, and renewable energy technologies into quantitative data on metal flows, through application of metal content estimates in combination with a dynamic stock model. Results show that total demand for copper, neodymium, and tantalum might increase by a factor of roughly 2 to 3.2, mostly as a result of population and GDP growth. The demand for lithium and cobalt is expected to increase much more, by a factor 10 to more than 20, as a result of future (hybrid) electric car purchases. This means that not just demographics, but also climate policies can strongly increase metal demand. This shows the importance of studying the issues of climate change and resource depletion together, in one modeling framework.

Substantial amounts of post-consumer scrap are exported to other regions or lost during recovery and remelting, and both export and losses pose a constraint to desires for having regionally closed material cycles. To quantify the challenges and trade-offs associated with closed-loop metal recycling, we looked at the material cycles from the perspective of a single material unit and trace a unit of material through several product life cycles. Focusing on steel, we used current process parameters, loss rates, and trade patterns of the steel cycle to study how steel that was originally contained in high quality applications such as machinery or vehicles with stringent purity requirements gets subsequently distributed across different regions and product groups such as building and construction with less stringent purity requirements. We applied MaTrace Global, a supply-driven multiregional model of steel flows coupled to a dynamic stock model of steel use. We found that, depending on region and product group, up to 95% of the steel consumed today will leave the use phase of that region until 2100, and that up to 50% can get lost in obsolete stocks, landfills, or slag piles until 2100. The high losses resulting from business-as-usual scrap recovery and recycling can be reduced, both by diverting postconsumer scrap into long-lived applications such as buildings and by improving the recovery rates in the waste management and remelting industries. Because the lifetimes of high-quality (cold-rolled) steel applications are shorter and remelting occurs more often than for buildings and infrastructure, we found and quantified a tradeoff between low losses and high-quality applications in the steel cycle. Furthermore, we found that with current trade patterns, reduced overall losses will lead to higher fractions of secondary steel being exported to other regions. Current loss rates, product lifetimes, and trade patterns impede the closure of the steel cycle.