Characterizing the Changes in Material Use due to Vehicle Electrification.

Modern automobiles are composed of more than 2000 different compounds comprising 76 different elements. Identifying supply risks across this palette of materials is important to ensure a smooth transition to more sustainable transportation technologies. This paper provides insight into how electrification is changing vehicle composition and how that change drives supply risk vulnerability by providing the first comprehensive, high-resolution (elemental and compound level) snapshot of material use in both conventional and hybrid electric vehicles (HEVs) using a consistent methodology. To make these contributions, we analyze part-level data of material use for seven current year models, ranging from internal combustion engine vehicles (ICEV) to plug-in hybrid vehicles (PHEVs). With this data set, we apply a novel machine learning algorithm to estimate missing or unreported composition data. We propose and apply a metric of vulnerability, referred to as exposure, which captures economic importance and susceptibility to price changes. We find that exposure increases from $874 per vehicle for ICEV passenger vehicles to $2344 per vehicle for SUV PHEVs. The shift to a PHEV fleet would double automaker exposure adding approximately $1 billion per year of supply risk to a hypothetical fleet of a million vehicles. The increase in exposure is largely not only due to the increased use of battery elements like cobalt, graphite, and nickel but also some more commonly used materials, most notably copper.

Perspectives on Cobalt Supply through 2030 in the Face of Changing Demand.

Lithium-ion battery demand, particularly for electric vehicles, is projected to increase by over 300% throughout the next decade. With these expected increases in demand, cobalt (Co)-dependent technologies face the risk of significant impact from supply concentration and mining limitations in the short term. Increased extraction and secondary recovery form the basis of modeling scenarios that examine implications on Co supply to 2030. Demand for Co is estimated to range from 235 to 430 ktonnes in 2030. This upper bound on Co demand in 2030 corresponds to 280% of world refinery capacity in 2016. Supply from scheduled and unscheduled production as well as secondary production is estimated to range from 320 to 460 ktonnes. Our analysis suggests the following: (1) Co price will remain relatively stable in the short term, given that this range suggests even a supply surplus, (2) future Co supply will become more diversified geographically and mined more as a byproduct of nickel (Ni) over this period, and (3) for this demand to be met, attention should be paid to sustained investments in refined supply of Co and secondary recovery.

Regional Heterogeneity in the Emissions Benefits of Electrified and Lightweighted Light-Duty Vehicles.

Electrification and lightweighting technologies are important components of greenhouse gas (GHG) emission reduction strategies for light-duty vehicles. Assessments of GHG emissions from light-duty vehicles should take a cradle-to-grave life cycle perspective and capture important regional effects. We report the first regionally explicit (county-level) life cycle assessment of the use of lightweighting and electrification for light-duty vehicles in the U.S. Regional differences in climate, electric grid burdens, and driving patterns compound to produce significant regional heterogeneity in the GHG benefits of electrification. We show that lightweighting further accentuates these regional differences. In fact, for the midsized cars considered in our analysis, model results suggest that aluminum lightweight vehicles with a combustion engine would have similar emissions to hybrid electric vehicles (HEVs) in about 25% of the counties in the US and lower than battery electric vehicles (BEVs) in 20% of counties. The results highlight the need for a portfolio of fuel efficient offerings to recognize the heterogeneity of regional climate, electric grid burdens, and driving patterns.

Strategic Materials in the Automobile: A Comprehensive Assessment of Strategic and Minor Metals Use in Passenger Cars and Light Trucks.

A comprehensive component-level assessment of several strategic and minor metals (SaMMs), including copper, manganese, magnesium, nickel, tin, niobium, light rare earth elements (LREEs; lanthanum, cerium, praseodymium, neodymium, promethium, and samarium), cobalt, silver, tungsten, heavy rare earth elements (yttrium, europium, gadolinium, terbium, dysprosium, holmium, erbium, thulium, ytterbium, and lutetium), and gold, use in the 2013 model year Ford Fiesta, Focus, Fusion, and F-150 is presented. Representative material contents in cars and light-duty trucks are estimated using comprehensive, component-level data reported by suppliers. Statistical methods are used to accommodate possible errors within the database and provide estimate bounds. Results indicate that there is a high degree of variability in SaMM use and that SaMMs are concentrated in electrical, drivetrain, and suspension subsystems. Results suggest that trucks contain greater amounts of aluminum, nickel, niobium, and silver and significantly greater amounts of magnesium, manganese, gold, and LREEs. We find tin and tungsten use in automobiles to be 3-5 times higher than reported by previous studies which have focused on automotive electronics. Automotive use of strategic and minor metals is substantial, with 2013 vehicle production in the United States, Canada, EU15, and Japan alone accounting for approximately 20% of global production of Mg and Ta and approximately 5% of Al, Cu, and Sn. The data and analysis provide researchers, recyclers, and decision-makers additional insight into the vehicle content of strategic and minor metals of current interest.

A Methodology for Robust Comparative Life Cycle Assessments Incorporating Uncertainty.

We propose a methodology for conducting robust comparative life cycle assessments (LCA) by leveraging uncertainty. The method evaluates a broad range of the possible scenario space in a probabilistic fashion while simultaneously considering uncertainty in input data. The method is intended to ascertain which scenarios have a definitive environmentally preferable choice among the alternatives being compared and the significance of the differences given uncertainty in the parameters, which parameters have the most influence on this difference, and how we can identify the resolvable scenarios (where one alternative in the comparison has a clearly lower environmental impact). This is accomplished via an aggregated probabilistic scenario-aware analysis, followed by an assessment of which scenarios have resolvable alternatives. Decision-tree partitioning algorithms are used to isolate meaningful scenario groups. In instances where the alternatives cannot be resolved for scenarios of interest, influential parameters are identified using sensitivity analysis. If those parameters can be refined, the process can be iterated using the refined parameters. We also present definitions of uncertainty quantities that have not been applied in the field of LCA and approaches for characterizing uncertainty in those quantities. We then demonstrate the methodology through a case study of pavements.

Assessing Economic Modulation of Future Critical Materials Use: The Case of Automotive-Related Platinum Group Metals.

Platinum-group metals (PGMs) are technological and economic enablers of many industrial processes. This important role, coupled with their limited geographic availability, has led to PGMs being labeled as "critical materials". Studies of future PGM flows have focused on trends within material flows or macroeconomic indicators. We complement the previous work by introducing a novel technoeconomic model of substitution among PGMs within the automotive sector (the largest user of PGMs) reflecting the rational response of firms to changing prices. The results from the model support previous conclusions that PGM use is likely to grow, in some cases strongly, by 2030 (approximately 45% for Pd and 5% for Pt), driven by the increasing sales of automobiles. The model also indicates that PGM-demand growth will be significantly influenced by the future Pt-to-Pd price ratio, with swings of Pt and Pd demand of as much as 25% if the future price ratio shifts higher or lower even if it stays within the historic range. Fortunately, automotive catalysts are one of the more effectively recycled metals. As such, with proper policy support, recycling can serve to meet some of this growing demand.

Platinum availability for future automotive technologies.

Platinum is an excellent catalyst, can be used at high temperatures, and is stable in many aggressive chemical environments. Consequently, platinum is used in many current industrial applications, notably automotive catalytic converters, and prospective vehicle fuel cells are expected to rely upon it. Between 2005 and 2010, the automotive industry used approximately 40% of mined platinum. Future automotive industry growth and automotive sales shifts toward new technologies could significantly alter platinum demand. The potential risks for decreased platinum availability are evaluated, using an analysis of platinum market characteristics that describes platinum's geophysical constraints, institutional efficiency, and dynamic responsiveness. Results show that platinum demand for an automotive fleet that meets 450 ppm greenhouse gas stabilization goals would require within 10% of historical growth rates of platinum supply before 2025. However, such a fleet, due largely to sales growth in fuel cell vehicles, will more strongly constrain platinum supply in the 2050 time period. While current platinum reserves are sufficient to satisfy this increased demand, decreasing platinum ore grade and continued concentration of platinum supply in a single geographic area are availability risk factors to platinum end-users.

Evaluating the potential for secondary mass savings in vehicle lightweighting.

Secondary mass savings are mass reductions that may be achieved in supporting (load-bearing) vehicle parts when the gross vehicle mass (GVM) is reduced. Mass decompounding is the process by which it is possible to identify further reductions when secondary mass savings result in further reduction of GVM. Maximizing secondary mass savings (SMS) is a key tool for maximizing vehicle fuel economy. In today's industry, the most complex parts, which require significant design detail (and cost), are designed first and frozen while the rest of the development process progresses. This paper presents a tool for estimating SMS potential early in the design process and shows how use of the tool to set SMS targets early, before subsystems become locked in, maximizes mass savings. The potential for SMS in current passenger vehicles is estimated with an empirical model using engineering analysis of vehicle components to determine mass-dependency. Identified mass-dependent components are grouped into subsystems, and linear regression is performed on subsystem mass as a function of GVM. A Monte Carlo simulation is performed to determine the mean and 5th and 95th percentiles for the SMS potential per kilogram of primary mass saved. The model projects that the mean theoretical secondary mass savings potential is 0.95 kg for every 1 kg of primary mass saved, with the 5th percentile at 0.77 kg/kg when all components are available for redesign. The model was used to explore an alternative scenario where realistic manufacturing and design limitations were implemented. In this case study, four key subsystems (of 13 total) were locked-in and this reduced the SMS potential to a mean of 0.12 kg/kg with a 5th percentile of 0.1 kg/kg. Clearly, to maximize the impact of mass reduction, targets need to be established before subsystems become locked in.

Evaluating rare earth element availability: a case with revolutionary demand from clean technologies.

The future availability of rare earth elements (REEs) is of concern due to monopolistic supply conditions, environmentally unsustainable mining practices, and rapid demand growth. We present an evaluation of potential future demand scenarios for REEs with a focus on the issue of comining. Many assumptions were made to simplify the analysis, but the scenarios identify some key variables that could affect future rare earth markets and market behavior. Increased use of wind energy and electric vehicles are key elements of a more sustainable future. However, since present technologies for electric vehicles and wind turbines rely heavily on dysprosium (Dy) and neodymium (Nd), in rare-earth magnets, future adoption of these technologies may result in large and disproportionate increases in the demand for these two elements. For this study, upper and lower bound usage projections for REE in these applications were developed to evaluate the state of future REE supply availability. In the absence of efficient reuse and recycling or the development of technologies which use lower amounts of Dy and Nd, following a path consistent with stabilization of atmospheric CO(2) at 450 ppm may lead to an increase of more than 700% and 2600% for Nd and Dy, respectively, over the next 25 years if the present REE needs in automotive and wind applications are representative of future needs.

Increasing secondary and renewable material use: a chance constrained modeling approach to manage feedstock quality variation.

The increased use of secondary (i.e., recycled) and renewable resources will likely be key toward achieving sustainable materials use. Unfortunately, these strategies share a common barrier to economical implementation - increased quality variation compared to their primary and synthetic counterparts. Current deterministic process-planning models overestimate the economic impact of this increased variation. This paper shows that for a range of industries from biomaterials to inorganics, managing variation through a chance-constrained (CC) model enables increased use of such variable raw materials, or heterogeneous feedstocks (hF), over conventional, deterministic models. An abstract, analytical model and a quantitative model applied to an industrial case of aluminum recycling were used to explore the limits and benefits of the CC formulation. The results indicate that the CC solution can reduce cost and increase potential hF use across a broad range of production conditions through raw materials diversification. These benefits increase where the hFs exhibit mean quality performance close to that of the more homogeneous feedstocks (often the primary and synthetic materials) or have large quality variability. In terms of operational context, the relative performance grows as intolerance for batch error increases and as the opportunity to diversify the raw material portfolio increases.

Evaluating the economic viability of a material recovery system: the case of cathode ray tube glass.

This paper presents an analysis of the material recovery system for leaded glass from cathode ray tubes (CRTs) using a dynamic material flow analysis. In particular, the global mass flow of primary and secondary CRT glass and the theoretical capacities for using secondary CRT glass to make new CRT glass are analyzed. The global mass flow analysis indicates that the amount of new glass required is decreasing, but is much greater than the amount of secondary glass collected, which is increasing. The comparison of the ratio of secondary glass collected to the amount of new glass required from the mass flow analysis indicates that the material recovery system is sustainable for the foreseeable future. However, a prediction of the time at which the market for secondary glass will collapse due to excess capacity is not possible at the moment due to several sources of uncertainty.

A framework for evaluating the economic performance of recycling systems: a case study of North American electronics recycling systems.

A framework for evaluating the economic performance of a recycling system is proposed, and data from four electronics recycling systems in North America (Alberta, California, Maine, and Maryland) that use different operating models are used as a preliminary test of the framework. The framework is built around a hierarchy of descriptors that clarify the function of the system components under consideration and the activities, cash flow elements, and resources within those functions; costs are incurred by specific stakeholders. Data from each system on fee and mass collection amounts and collection, processing, and management costs are used to create a matrix of several net costs for stakeholders within each system. Although all four systems are relatively new, thereby making data collection a challenge, some preliminary insights can be gleaned from comparing the systems. Processing costs vary significantly in the four systems, with Alberta and California having the highest reimbursement rates for processing. Alberta and California also have relatively high system management costs, but processors are generally quite satisfied with the systems. Maine has an additional cost for consolidation that is an implicit management cost because of the need to count incoming products by manufacturer.