Methodological study of evaluating the traceability of neodymium based on the global substance flow analysis and Monte Carlo simulation

Abstract

Neodymium is a particularly important mineral among rare earth elements (REE) and is used in NdFeB magnets in many motors and electronic devices. In recent years, by the extremely rapid growth in the demand for neodymium, many substance flow analysis (SFA) studies have been conducted to evaluate the global flow and stock of neodymium and to analyze its recycling potential. However, illegal mining, unknown trading and end-of-life (EOL) based recycle of mineral resources such as REE cannot be quantitatively evaluated using only publicly available data. Their actual quantities involved in these activities are greatly affected by politics and production economics in countries such as China, Russia, India, etc Therefore, the lack of knowledge of the quantity of neodymium in existence is an urgent problem for the industrial sector. Accordingly, in recent years, a variety of initiatives centered in Europe have been considered to clarify its traceability.Therefore, this study aims to propose new method of SFA to clarify neodymium’s quantity of illegal mining, unknown trading and EOL based recycle in the world’s supply chain, included in the final application. The results revealed that 16–26% of neodymium used in NdFeB magnets in China contains the quantity whose production region and quantity traded are unknown. This proportion will be larger i.e., 19–28%. in final application demanded in Japan and all other countries.In addition, uncertainty analysis was conducted using Monte Carlo simulation that considered the minimum to maximum ranges of several variables, including the amount of Nd2O3 contained in rare earth deposits. From this analysis, the uncertainty of result for xEVs, conventional car, and electric bike is appeared to be lower comparing with those of other final application. This study provides important knowledge to conduct SFA considering the uncertainty which exist in the public data.