Surplus Cost Potential as a Life Cycle Impact Indicator for Metal Extraction

Marisa D.M. Vieira, Thomas C. Ponsioen, Mark J. Goedkoop and Mark A.J. Huijbregts
Additional contact information
Marisa D.M. Vieira: Radboud University Nijmegen, Faculty of Science, Department of Environmental Science, P.O. Box 9010, Nijmegen 6500 GL, The Netherlands
Thomas C. Ponsioen: PRé Consultants b.v., Stationsplein 121, Amersfoort 3818 LE, The Netherlands
Mark J. Goedkoop: PRé Consultants b.v., Stationsplein 121, Amersfoort 3818 LE, The Netherlands
Mark A.J. Huijbregts: Radboud University Nijmegen, Faculty of Science, Department of Environmental Science, P.O. Box 9010, Nijmegen 6500 GL, The Netherlands

Resources, 2016, vol. 5, issue 1, 1-12

Abstract: In the evaluation of product life cycles, methods to assess the increase in scarcity of resources are still under development. Indicators that can express the importance of an increase in scarcity of metals extracted include surplus ore produced, surplus energy required, and surplus costs in the mining and the milling stage. Particularly the quantification of surplus costs per unit of metal extracted as an indicator is still in an early stage of development. Here, we developed a method that quantifies the surplus cost potential of mining and milling activities per unit of metal extracted, fully accounting for mine-specific differences in costs. The surplus cost potential indicator is calculated as the average cost increase resulting from all future metal extractions, as quantified via cumulative cost-tonnage relationships. We tested the calculation procedure with 12 metals and platinum-group metals as a separate group. We found that the surplus costs range six orders of magnitude between the metals included, i.e ., between $0.01–$0.02 (iron) and $13,533–$17,098 (rhodium) USD (year 2013) per kilogram of metal extracted. The choice of the reserve estimate (reserves vs. ultimate recoverable resource) influenced the surplus costs only to a limited extent, i.e ., between a factor of 0.7 and 3.2 for the metals included. Our results provide a good basis to regularly include surplus cost estimates as resource scarcity indicator in life cycle assessment.

Keywords: characterization factors; endpoint; life cycle assessment; metals; mining; resource scarcity (search for similar items in EconPapers)
JEL-codes: Q1 Q2 Q3 Q4 Q5 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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