Future environmental impacts of metals: recent insights and emerging challenges

Kurzfassung

With the energy transition, the future demand for many metals is expected to sharply increase. Unless drastic measures are taken, environmental impacts caused by metal production may thus threaten climate goals. While comprehensive overviews of current environmental impacts of metal production exist, they are lacking for future impacts. We systematically reviewed studies which assessed future environmental impacts of metal supply chains. We evaluated their results regarding future impact trends, and their methods, i.e., modelling approaches, scenario variables, and data sources. Our review yielded 40 publications covering 15 metals: copper, iron, aluminium, nickel, zinc, lead, cobalt, lithium, gold, manganese, neodymium, dysprosium, praseodymium, terbium, and titanium. Metals crucial for the energy transition, e.g., lithium or neodymium, are rarely addressed, unlike major metals. Although results for future environmental impacts of metals strongly depend on scenario narratives and assumptions, we found that specific impacts (per kg) may decrease driven by, e.g., greener electricity, higher recycling shares, or novel technologies. Nevertheless, this is probably insufficient to compensate for surging demand. Thus, future demand-related impacts are still likely to increase. We identified 15 scenario variables in the reviewed studies. The most common variables are: background electricity mix, ore grade, recycling shares, demand, and energy efficiency. It is crucial to better understand future impacts of more metals, considering also impacts beyond GHG emissions and future demand developments. For this, it is required to couple supply and demand scenarios based on consistent assumptions and storylines, e.g. by linking other models to LCA models. Yet, this is hindered by the currently prevailing research practices which we found to be characterised by insufficient publication of data, untransparent and unharmonized documentation, as well as heterogeneous modelling approaches. We recommend improving research practices towards open, collaborative and more streamlined research, to enable more harmonised, reproducible, reusable and finally more accurate scenario assessments.