Dynamic Life Cycle Assessment for Critical Energy Materials: Developing a New Framework for Integrated Industrial Ecology Methods

1337095 (Kendall)。到2050年，与能源相关的温室气体排放量预计将翻一番，导致全球气候变暖6度或更多。需要迅速和广泛地部署可再生能源和节能技术来改变这些排放的过程。这种部署将增加对清洁能源技术重要材料的需求，导致一些材料成为关键的能源材料。国家和国际机构越来越强调关键能源材料在实现气候变化减缓目标和发展美国清洁能源经济方面的作用。供应、需求和矿物开采延迟、障碍或激励之间复杂的相互作用将导致关键材料的各种资源限制和环境影响。因此，需要一种动态和前瞻性的方法来模拟材料的可用性和环境影响，以便技术开发人员选择对环境有利的材料，并支持战略性清洁能源政策。本研究将建立一个综合生命周期评估（LCA）和物料流分析（MFA）框架，以创建一个动态的材料可持续性评估方法。LCA从整体上分析了技术的环境绩效，但目前的LCA方法即使在评估未来技术时也依赖于静态生命周期清单数据。本研究将结合产业生态学的两种方法：LCA和MFA，发展前瞻性和动态的研究方法。这种耦合产生了动态LCA的新框架，该框架承认采矿和精炼影响的空间变异性，并预测材料的可用性和环境影响随时间的变化。该框架将适用于被视为临界、接近临界或观察名单的四种金属：两种稀土，钕和镝；锂;和镁。这四个都是生产电动汽车的必要条件，电动汽车是一种重要的清洁能源技术。以未来电动汽车的动态LCA为例，说明了该方法的可行性。生成的模型和数据集将有助于改进该特定技术的生命周期设计、规划和材料选择，并为开发其他技术和材料的类似工具和数据提供框架。本研究将通过解决LCA中未解决的问题，包括长寿命产品中材料的回收分配实践，以及未来LCA中合作生产的处理，为工业生态学的其他方法进步做出贡献。当可回收材料在长寿命产品中绑定时，二次材料可用性的延迟代表了回收分配的一个有趣案例。此外，由于许多关键的能源材料是作为副产物生产的，因为它们共同出现在地质矿床中，因此将解决副产物分配问题。采用改进的生命周期分析方法有助于避免意想不到的后果，并提高减缓气候变化战略的有效性。这项研究将允许清洁能源技术开发人员预测在设计中选择特定材料对环境的长期负面影响，促进产品开发早期阶段的生命周期决策。这项研究还将帮助决策者和工业界预测确定替代材料和资源以及发展强大的回收基础设施所需的时间。研究方法和结果将被纳入教育课程研究，还应该帮助政策制定者和工业界预测识别替代材料和资源以及发展强大的回收基础设施所需的时间。研究方法和成果将纳入研究生和本科课程的教育课程，使学生了解定量可持续发展方法和当前问题。此外，项目研讨会将针对教育背景不利的一年级本科生和考虑或已注册工程领域的社区大学转校生。研讨会将利用环境可持续性主题的工程设计问题，帮助学生将工程职业与社会相关主题联系起来。此外，6-12年级的学生将通过教师培训材料成为目标。该项目将全年资助一名博士生，并提供两名本科生暑期研究经历。

1337095 (Kendall). Energy-related greenhouse gas emissions are expected to double by 2050, leading to warming of the global climate by 6 degrees or more. Rapid and extensive deployment of renewable and energy-efficient technologies is required to change the course of these emissions. This deployment will increase demands for materials important for clean energy technologies, leading to some becoming critical energy materials. National and international agencies have increasingly emphasized the role of critical energy materials in meeting climate change mitigation goals and for developing a vibrant economy for clean energy in the U.S. The complex interactions of supply, demand, and mineral extraction delays, barriers, or incentives will lead to varying resource restrictions and environmental impacts for critical materials over time. Thus, a dynamic and prospective approach to modeling material availability and environmental impacts is required for environmentally preferable material selection by technology developers, and to support strategic clean energy policies. This research will develop an integrated life cycle assessment (LCA) and material flow analysis (MFA) framework to create a dynamic approach for material sustainability assessment. LCA holistically analyzes the environmental performance of technologies, yet current LCA methods rely on static life cycle inventory data even in assessments of future technologies. This research will develop a prospective and dynamic approach by coupling two methods from industrial ecology: LCA and MFA. This coupling results in a new framework for dynamic LCA, one that acknowledges spatial variability in mining and refining impacts, and anticipates changes in a material's availability and environmental impacts over time. The framework will be applied to four metals considered critical, near critical, or watch list: two rare earths, neodymium and dysprosium; lithium; and magnesium. All four are essential for producing electric vehicles, an important clean energy technology. A dynamic LCA of future electric vehicles will serve as an illustrative case for this new method. The models and datasets generated will contribute to improved life cycle design, planning, and material selection for this particular technology, and provide a framework for developing similar tools and data for other technologies and materials. This research will contribute to other methodological advancements in industrial ecology by addressing unresolved issues in LCA, including recycling allocation practices for materials in long-lived products, and the treatment of co-production in prospective LCAs. The delay in secondary material availability when recyclable materials are bound in long-lived products represents an interesting case for recycling allocation. In addition, co-product allocation issues will be addressed because many critical energy materials are produced as co-products because they co-occur in geologic deposits. Application of enhanced LCA methods can help avert unintended consequences and improve the effectiveness of climate change mitigation strategies. This research will allow clean energy technology developers to anticipate long-term negative environmental consequences of selecting a particular material in a design, facilitating life cycle decision-making at the earliest stages of product development. This research will also help policymakers and industry anticipate the timing required for identifying alternative materials and resources, and for developing robust recycling infrastructure. The research methods and outcomes will be incorporated into educational curricula research and should also help policymakers and industry anticipate the timing required for identifying alternative materials and resources, and for developing robust recycling infrastructure. The research methods and outcomes will be incorporated into educational curricula for graduate and undergraduate courses, exposing students to quantitative sustainability methods and current issues. In addition, project-based seminars will be developed to target first year undergraduates from educationally disadvantaged backgrounds and community college transfer students considering or enrolled in engineering fields. Seminars will use engineering design problems with environmental sustainability themes to help students connect careers in engineering with socially relevant themes. In addition, students in grades 6-12 will be targeted through teacher training materials. The project will support one doctoral student in all years and provide two undergraduate summer research experiences.