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The low‐carbon energy transition requires significant increases in production for many mineral commodities. Understanding demand, technological requirements, and prices associated with this production increase requires understanding the supply chain dynamics of many minerals simultaneously, and via a consistent framework. A generalized economics‐informed material flow method, global materials modeling using Bayesian optimization, captures the market dynamics of key mineral commodities. The method relies only on a limited set of widely available historical data as input, enabling quantification of economic relationships (elasticities) for supply chain components where data are sparse, and relationships cannot be obtained via traditional statistical approaches. Building upon established material flow analysis (MFA) and economic modeling techniques, Bayesian optimization was applied to fit an economics‐informed MFA model to global historical demand, supply, and price for aluminum, copper, gold, lead, nickel, silver, iron, tin, and zinc. This approach enables estimates for the evolution of ore grades, mine costs, refining charges, sector‐specific demand, and scrap collection for each commodity. Economic relationships were quantified and compared with a database compiled from the literature, including 1333 values from 213 analyses across 65 publications. Discrepancies in methods and limited coverage make use of these parameters in modeling efforts difficult. This work provides a single, homogeneous, probabilistic approach to identifying economic relationships across mineral supply chains, with uncertainty quantification, a literature database for comparison, and a modeling framework in which to use them. This article met the requirements for a Gold‐Gold JIE data openness badge described at http://jie.click/badges. [ABSTRACT FROM AUTHOR]

In the United States, polyethylene terephthalate (PET) bottle collection rates have not increased in a decade. Recycling rates remain abysmal while industry commitments and policy targets escalate the demand for recycled plastics. We investigate the PET bottle recycling system, where collection is a critical bottleneck and recycled PET supply is not meeting the expected demand. We characterize demand for recycled PET (R‐PET), analyze scenarios of expanding deposit return systems (DRS), and quantify cost barriers to improving PET bottle recycling. We find that a nation‐wide DRS can increase PET bottle recycling rates from 24% to 82%, supplying approximately 2700 kt of recycled PET annually. With stability in demand, we estimate that this PET bottle recycling system can achieve 65% bottle‐to‐bottle circularity, at a net cost of 360 USD/tonne of PET recycled. We also discuss environmental impacts, stakeholder implications, producer responsibility, and complimentary policies toward an efficient and effective recycling system. [ABSTRACT FROM AUTHOR]

Raw materials costs form an increasingly significant proportion of the total costs of renewable energy technologies that must be adopted at unprecedented rates to combat climate change. As the affordable deployment of these technologies grows vulnerable to materials price changes, effective strategies must be identified to mitigate the risk of higher input costs faced by manufacturers. To better understand potential threats to deployment, a market modeling approach was developed to quantify economic risk factors including material demand, substitutability, recycling, mining productivity, resource quality, and discovery. Results demonstrate that price changes are determined by interactions between demand growth, mining productivity, and resource quality. In the worst cases with high demand and low productivity, development of material substitutes and large recycling rates help reduce the prevalence of price risk from over 90% to under 10%. Investing in these strategies yields significant benefits for manufacturers and governments concerned about costs of materials critical to decarbonization and other advanced technologies. [ABSTRACT FROM AUTHOR]

Predictions of metal consumption are vital for criticality assessments and sustainability analyses. Although demand for a material varies strongly by region and end-use sector, statistical models of demand typically predict demand using regression analyses at an aggregated global level ("fully pooled models"). "Un-pooled" regression models that predict demand at a disaggregated country or regional level face challenges due to limited data availability and large uncertainty. In this paper, we propose a Bayesian hierarchical model that can simultaneously identify heterogeneous demand parameters (like price and income elasticities) for individual regions and sectors, as well as global parameters. We demonstrate the model's value by estimating income and price elasticity of copper demand in five sectors (Transportation, Electrical, Construction, Manufacturing, and Other) and five regions (North America, Europe, Japan, China, and Rest of World). To validate the benefits of the Bayesian approach, we compare the model to both a "fully pooled" and an "un-pooled" model. The Bayesian model can predict global demand with similar uncertainty as a fully pooled regression model, while additionally capturing regional heterogeneity in income elasticity of demand. Compared to un-pooled models that predict demand for individual countries and sectors separately, our model reduces the uncertainty of parameter estimates by more than 50%. The hierarchical Bayesian modeling approach we propose can be used for various commodities, improving material demand projections used to study the impact of policies on mining sector emissions and informing investment in critical material production. [ABSTRACT FROM AUTHOR]

Researchers have proposed a family of electrochemical technologies that incorporate CO2 as a gas cathode and alkali or alkaline earth metal anodes to exploit the high reactivity of CO2 with these metals. Such proposed cells operate by converting gaseous CO2 into solid carbonate, extracting value from CO2 in the form of electricity, and fixing the CO2 in solid form. Given the increasing number of these proof‐of‐concept studies, it is timely to critically examine the potential of such emerging technologies to reduce stationary point source emissions. Environmental life cycle assessment (LCA) during early research stages can inform important design decisions. In this study, we perform LCA on electrochemical conversion processes (ECPs) involving Li, Na, Mg, or Ca as a co‐reactant with CO2 sourced from a coal plant, evaluating differing scenarios. We find that a Na‐based primary ECP configuration that integrates capture with conversion of coal plant CO2 emissions to Na2CO3 can avoid almost 28% of emissions (and 74% under best‐case conditions) that are typically associated with conventional production of the same carbonate and electricity. This represents a net emissions decrease of 435 kg CO2‐eq per 1 MWh of electricity delivered by the ECP, from a baseline of 1,105 kg CO2‐eq emitted without any mitigation strategies. In contrast, all ECPs in a rechargeable configuration result in increased emissions compared to the conventional baseline, unless the ECP system energy requirements are provided by renewables and the conventional system is assumed to have high emissions intensity. [ABSTRACT FROM AUTHOR]

Material production drives an increasingly large fraction of CO2‐equivalent emissions. Material efficiency strategies such as recycling serve to reduce these emissions. Current analyses of the effectiveness of such strategies do not include economically induced rebound effects, overestimating the associated environmental benefits. We present a dynamic supply chain simulation model for copper through 2040 incorporating inventory‐driven price evolution, dynamic material flow analysis, and life cycle assessment alongside mine‐level economic evaluation of opening, closing, and production decisions. We show that permanent increases in recycling displace ∼0.5 kilotonnes mine production per kilotonne increase in scrap supply on average, while short‐lived recycling policies can lead to increased mine production. We find evidence for supply chain evolution pathways minimizing the rebound effect and maximizing displacement of primary material, where increasing refined copper and concentrate prices and decreasing demand serve to decrease mining. However, even in best‐case scrap supply scenarios, CO2e emissions from the copper sector increase 25% by 2040 relative to 2018 due to demand growth, ore grade decline, and lower displacement among large scrap supply changes. With implementation of best available technologies across all supply chain components, we estimated 2040 CO2e emissions 10% below those of 2018 are possible, though still well short of 2°C emissions targets. We find increasing mine taxes and royalties, reclamation costs, and exploration costs further increase displacement, as does the inclusion of scrap prices on major futures exchanges. These results highlight the importance of considering the economics of the entire material supply chain when implementing material efficiency strategies. This article met the requirements for a Gold‐Gold JIE data openness badge described at http://jie.click/badges. [ABSTRACT FROM AUTHOR]

Summary: Many advanced energy and environmentally relevant technologies rely on metals that have been identified as critical, or whose availability may be limited. Several of these elements are produced mostly as by‐products of mining other base metals (carriers). This by‐product dependence has been proposed as a significant supply‐risk indicator by the materials criticality community. This article provides new quantitative evidence that, in several cases, by‐product metals' availability may not be directly limited by carrier supply. We perform an assessment based on characteristics essential to by‐product metals, including physical concentration, market value of metals, and extraction technology efficiency. We analyze 40 carrier/by‐product pairs and identify five 'high‐by‐product' pairs. We assess the supply responsiveness of these metals. Our analysis suggests that rather than limited primary production of carrier, lack of incentive for improving recovery efficiency may limit availability of the by‐product. This behavior is found in the zinc‐indium and copper‐selenium systems. For germanium, on the other hand, we instead propose influence from the by‐product market itself leading to price inelasticity of supply. As a complement to other quantitative methods developed for material systems, such as material flow analysis, we provide an essential technoeconomic analysis of the by‐product metals problem by employing cluster analysis and econometric modeling. This approach provides insight into supply‐risk mitigation strategies related to extraction efficiency and supply‐chain structure. [ABSTRACT FROM AUTHOR]

Summary: Life cycle thinking plays an important role in sustainable development in the building sector. However, the complexity of data collection and scope definition limits life cycle assessment (LCA) applications. Even if the inventory data have already been collected, tabulated, and indexed, the method is still time‐consuming, which may be discouraging for designers. This study demonstrates how the LCA of buildings can be robustly streamlined using structured underspecification of impact data combined with an effective and efficient triage of the data collection. Tests were conducted with a series of building typologies that were analyzed with a cradle‐to‐gate approach. The probabilistic triage approach was tested to identify selected activities requiring detailed specification because they contribute most to total impact, thereby reducing data gathering effort. Impacts such as global warming, acidification, eutrophication, and smog creation were assessed, and results showed that 40% to 46% of the bill of materials components represent 75% of total impacts of single‐family houses and multifamily buildings. By specifying only a prioritized subset of the bill of materials to the highest level of specificity, results proved to be reasonably accurate and obtainable with less effort. [ABSTRACT FROM AUTHOR]

This research incorporates waste boiler ash into masonry construction materials using alkali-activation. The boiler ash, derived from three different Indian pulp and paper mills, has many undesirable characteristics for alkali-activation, including varying shape, large particle sizes ranging from 5 to 600 μm, loss on ignition between 8 and 35%, and less than 4% alumina. When combined with supplementary materials in the form of clay and lime, high compressive strengths are observed in the bricks made with all three ashes, demonstrating the robustness of the proposed mix design. A brick formulation with a solids phase weight ratio of ash(70):clay(20):lime(10), liquid to solid ratio of 0.45, and 2 M NaOH produces bricks with compressive strengths between 11 and 15 MPa after 28 days curing at 30 °C. Furthermore, early strength development is observed, as more than 55% of the 28 day strength is achieved after one day curing. An economic and environmental analysis indicates that these bricks can be produced for similar costs as the clay fired brick with reduced environmental impact, making them a viable alternative in the market. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the guest editors discuss the theme of the issue, the circular economy (CE) alternative to a traditional linear economy.

As design for recycling becomes more broadly applied in material and product design, analytical tools to quantify the environmental implications of design choices will become a necessity. Currently, few systematic methods exist to measure and direct the metallurgical alloy design process to create alloys that are most able to be produced from scrap. This is due, in part, to the difficulty in evaluating such a context-dependent property as recyclability of an alloy, which will depend on the types of scraps available to producers, the compositional characteristics of those scraps, their yield, and the alloy specification itself. This article explores the use of a chance-constrained based optimization model, similar to models used in operational planning in secondary production today, to (1) characterize the challenge of developing recycling-friendly alloys due to the contextual sensitivity of recycling, (2) demonstrate how such models can be used to evaluate the potential scrap usage of alloys, and (3) explore the value of sensitivity analysis information to proactively identify effective alloy modifications that can drive increased potential scrap use. These objectives are demonstrated through two cases that involve the production of a broad range of alloys utilizing representative scraps from three classes of industrial end uses. [ABSTRACT FROM AUTHOR]