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The Eco-Costs of Material Scarcity, a Resource Indicator for LCA, Derived from a Statistical Analysis on Excessive Price Peaks

Authors
  • vogtländer, joost
  • peck, david
  • kurowicka, dorota
Publication Date
Apr 25, 2019
Identifiers
DOI: 10.3390/su11082446
OAI: oai:mdpi.com:/2071-1050/11/8/2446/
Source
MDPI
Keywords
Language
English
License
Green
External links

Abstract

The availability of resources is crucial for the socio-economic stability of our society. For more than two decades, there was a debate on how to structure this issue within the context of life-Cycle assessment (LCA). The classical approach with LCA is to describe &ldquo / scarcity&rdquo / for future generations (100&ndash / 1000 years) in terms of absolute depletion. The problem, however, is that the long-term availability is simply not known (within a factor of 100&ndash / 1000). Outside the LCA community, the short-term supply risks (10&ndash / 30 years) were predicted, resulting in the list of critical raw materials (CRM) of the European Union (EU), and the British risk list. The methodology used, however, cannot easily be transposed and applied into LCA calculations. This paper presents a new approach to the issue of short-term material supply shortages, based on subsequent sudden price jumps, which can lead to socio-economic instability. The basic approach is that each resource is characterized by its own specific supply chain with its specific price volatility. The eco-costs of material scarcity are derived from the so-called value at risk (VAR), a well-known statistical risk indicator in the financial world. This paper provides a list of indicators for 42 metals. An advantage of the system is that it is directly related to business risks, and is relatively easy to understand. A disadvantage is that &ldquo / statistics of the past&rdquo / might not be replicated in the future (e.g., when changing from structural oversupply to overdemand, or vice versa, which appeared an issue for two companion metals over the last 30 years). Further research is recommended to improve the statistics.

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