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Nonregenerative Natural Resources in a Sustainable System of Energy Supply

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Bradshaw,  Alexander M.
Max Planck Institute for Plasma Physics;
Theory, Fritz Haber Institute, Max Planck Society;

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引用

Bradshaw, A. M., & Hamacher, T. (2012). Nonregenerative Natural Resources in a Sustainable System of Energy Supply. ChemSusChem: chemistry & sustainability, energy & materials, 5(3), 550-562. doi:10.1002/cssc.201100563.


引用: https://hdl.handle.net/11858/00-001M-0000-0010-76E8-7
要旨
Following the lead of the European Union in introducing binding measures to promote the use of regenerative energy forms, it is not unreasonable to assume that the global demand for combustible raw materials for energy generation will be reduced considerably in the second half of this century. This will not only have a favourable effect on the CO(2) concentration in the atmosphere, but will also help preserve fossil fuels-important as raw materials in the chemical industry-for future generations. Nevertheless, associated with the concomitant massive shift to regenerative energy forms, there will be a strong demand for other exhaustible raw materials, in particular metals, some of which are already regarded as scarce. After reviewing the debate on mineral depletion between "cornucopians" and "pessimists", we discuss the meaning of mineral "scarcity", particularly in the geochemical sense, and mineral "exhaustion". The expected drastic increase in demand for mineral resources caused by demographic and societal pressures, that is, due to the increase in in-use stock, is emphasised. Whilst not discussing the issue of "strong" versus "weak" sustainability in detail, we conclude that regenerative energy systems-like nearly all resource-consuming systems in our society-do not necessarily satisfy generally accepted sustainability criteria. In this regard, we discuss some current examples, namely, lithium and cobalt for batteries, rare earth-based permanent magnets for wind turbines, cadmium and tellurium for solar cells and copper for electrical power distribution.