Life Cycle Assessment and Optimization of Critical Energy Material | Yixin Liu

Field | Discipline

• Critical material
• Sustainability science
• Industrial ecology

Expertise

• Life cycle assessment
• Multiple-objective optimization
• Material flow analysis

Summary

Clean energy technologies such as solar and wind power, as well as electric vehicles, are vital for decarbonization. However, their widespread adoption intensifies the demand for critical materials, raising concerns about high supply concentration, environmental and social impacts, by-product issues, geopolitical instability, and other unsustainable factors. Addressing the complex interplay of economic, environmental, and social impacts within the energy-climate-material nexus is urgent. Moreover, the current life cycle assessments of critical material production often underestimate the impacts on climate change and other perspectives due to the limited understanding of various material flow processes. This research project aims to develop a systematic, regionalized approach for Life Cycle Assessment of both existing and future critical material production. It will involve modeling life cycle inventories for operations in leading producer countries, complemented by regionalized impact assessments. The research will focus on three main areas: (1) modeling life cycle inventories and impacts for critical materials across various scenarios of energy decarbonization and transportation electrification; (2) identifying key technological and societal factors that influence environmental impact patterns of critical materials; and (3) devising integrated strategies that meet energy and mobility needs while reducing the demand for critical materials and minimizing their environmental footprints.

This research project would involve with methodologies of dynamic material flow analysis, process-based life cycle assessment, integrated assessment model, system dynamics, big data analysis, and design of new approaches for specific themes. The objective is to leverage a synthesis of literature findings, commercial databases, and original simulation results to establish an analytical platform designed to furnish comprehensive, country-specific assessment outcomes encompassing the economic, environmental, and social implications of critical raw material production within the global battery supply chain. The Machine Learning methods will be employed to supplement missing data. The platform holds potential to address a pivotal multi-objective optimization challenge: namely, how to simultaneously minimize production costs, environmental impact, and social repercussions while aligning with low-carbon mobility and energy demands at the planetary level.

Supervision by

• Promotor: Prof. dr. K.S. (Klaus) Hubacek | Integrated Research on Energy, Environment and Society - IREES | ESRIG, University of Groningen.
• Co-promotor: Ass. Prof. dr.  X. (Xin) Sun | Integrated Research on Energy, Environment and Society - IREES | ESRIG, University of Groningen.

More information and contact details can be found on the personal profile of Yixin Liu