Clean energy technologies are widely recognized as a part of the solution for a sustainable future. Unfortunately, these technologies often rely on materials that are considered critical because of their importance to the technology and their potential for supply disruptions, which often lead to drastic and unexpected price spikes. With many clean energy technologies still struggling to compete economically with incumbent technologies, it is uncertain if such material price changes could have a significant economic impact on overall clean energy technology costs. In this paper, we first estimate material intensity of critical materials for three case study clean energy technologies: proton exchange membrane (PEM) fuel cells in fuel cell electric vehicles (FCEVs), neodymium iron boron (NdFeB) permanent magnets in direct drive wind turbines, and Li-ion batteries in battery electric vehicles (BEVs). Using these data, as well as material price information, we analyze technologylevel costs under potential material price spike scenarios. By benchmarking against target costs at which each technology is expected to become economically competitive relative to incumbent energy systems, we evaluate the impact of price spikes on marketplace competitiveness. For the three case studies, technological costs could increase by between 13 and 41% if recent historical price events were to recur at current material intensities. By analyzing the economic impact of material price changes on technology-level costs, we demonstrate the need for stakeholders to push for various supply risk reduction measures, which are also summarized in this paper. Keywords Supply risk • Techno-economic analysis • Wind turbines • Li-ion batteries • Fuel cells • Rare earth elements Critical materials in clean energy technologies Electronic supplementary material The online version of this article (

No abstract

Within the response and recovery phases of the disaster management cycle, debris clean-up is a well-researched topic, around which numerous policies have been developed. However, the subcategory of electronic waste is an issue that is overlooked by existing studies. A theoretical case study of a flood of the Rhine river in Bonn, Germany is used to demonstrate that while electronic waste may be a small portion of the debris generated during a disaster (by volume), it can have disproportionately large health, economic, and environmental consequences if not effectively planned for and handled. A spatial analysis of a flooding disaster scenario in Bonn was conducted to estimate the quantity of electronic waste that could be generated from residential buildings. Further modeling was done to calculate the greenhouse gas savings, energy savings, and economic impacts that can be realized through proper recovery and recycling of the electronic waste created by the flood. One key finding is that while implementation may be difficult, ensuring that effective policy is in place prior to a disaster can enable this waste stream to be managed in a manner that mitigates negative impacts on the environment and human health and keeps valuable materials in circulation.

Clean energy technologies have been developed to address the pressing global issue of climate change; however, the functionality of many of these technologies relies on materials that are considered critical. Critical materials are those that have potential vulnerability to supply disruption. In this paper, critical material intensity data from academic articles, government reports, and industry publications are aggregated and presented in a variety of functional units, which vary based on the application of each technology. The clean energy production technologies of gas turbines, direct drive wind turbines, and three types of solar photovoltaics (silicon, CdTe, and CIGS); the low emission mobility technologies of proton exchange membrane fuel cells, permanent-magnet-containing motors, and both nickel metal hydride and Li-ion batteries; and, the energy-efficient lighting devices (CFL, LFL, and LED bulbs) are analyzed. To further explore the role of critical materials in addressing climate change, emissions savings units are also provided to illustrate the potential for greenhouse gas emission reductions per mass of critical material in each of the clean energy production technologies. Results show the comparisons of material use in clean energy technologies under various performance, economic, and environmental based units.

The capacity to utilize geographic information is a critical element of disaster risk management. Although access to and use of geographic information system (GIS) technology continues to grow, there remain significant gaps in approaches used by disaster risk management stakeholders to understand geographic information needs, sources, and information flow-ultimately limiting the efficacy of management efforts. To address this problem, we introduce the concept of geographic information capacity (GIC) to measure and analyze the ability of stakeholders to understand, access, and work with geographic information for disaster risk management. We propose a framework for assessing GIC, the GIC Profile, which we situate within a review of disaster risk managementrelevant frameworks. We evaluate the GIC Profile using two case study countries at the first (sub-national) geoadministrative boundary level. Chi-square analyses suggest GIC across equivalent regional units within each country is relatively uniform, and that this uniformity is comparable between nations despite significant difference in overall capacity. Contributions of the GIC Profile to disaster risk management research are twofold. First, this is a first attempt to develop a profile based on key indicators for quantifying GIC highlights critical areas for capacity improvement, allowing decision makers to identify and prioritize pathways to strengthen disaster risk management programs. Through this initial effort, a decision tool has been developed which may enhance decisions on how to utilize GIS in support of disaster risk management. This tool is iterative and can be updated as new events occur to maximize GIS benefits, ultimately reducing disaster risks and their potential consequences.