Revisiting the Cumulative Grade-Tonnage Relationship for Major Copper Ore Types

Gerst, Michael D.

doi:10.2113/gsecongeo.103.3.615

Cited by 61 publications

(49 citation statements)

References 23 publications

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“…Gerst [42] estimated that mining operations have to become deeper than the current open pit mining operations. Furthermore, different ores have different characteristics and moving from one to the other may result in substantially different mining conditions and, as a result, in different operating costs [43]. The cost and tonnage data used to derive the cumulative cost-tonnage curves, however, does not contain information on the mine type and ore type.…”

Section: Limitationsmentioning

confidence: 99%

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

et al. 2016

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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.

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Section: Limitationsmentioning

confidence: 99%

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

et al. 2016

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“…Due to a lack of geological data, both parties acknowledge that an empirical proof is still needed. Gerst (2008) concludes that he can neither confirm nor refute these two hypotheses. Based on worldwide data on copper deposits over the past 200 years, he finds evidence for a log-normal relationship between copper production and average ore grades.…”

Section: Geological Abundance and Distribution Of The Elements In Thementioning

confidence: 95%

Non-Renewable Resources, Extraction Technology, and Endogenous Growth

Stuermer

Schwerhoff

2015

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We add an extractive sector to an endogenous growth model of expanding varieties and directed technological change. Firms increase their economically extractable stocks of non-renewable resources through R&D investment in extraction technology and reduce their stocks through extraction. We show how the geological distribution of the non-renewable resource interacts with technological change. Our model accommodates long-term trends in non-renewable resource markets -namely stable prices and exponentially increasing extractionfor which we present data going back to 1792. The model suggests that over the long term, development of new extraction technologies neutralizes the increasing demand for non-renewable resources in industrializing countries such as China.JEL classification: O30, O41, Q30

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“…In a recent empirical study, Gerst (2008) concludes that he can neither confirm nor refute these two hypotheses. Based on worldwide data on copper deposits over the past 200 years, he finds evidence for a log-normal relationship between copper production and average ore grades.…”

Section: Geological Abundance and Distribution Of The Elements In Thementioning

confidence: 95%

Technological Change in Resource Extraction and Endogenous Growth

Stuermer

Schwerhoff

2013

SSRN Journal

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Revisiting the Cumulative Grade-Tonnage Relationship for Major Copper Ore Types

Cited by 61 publications

References 23 publications

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

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

Non-Renewable Resources, Extraction Technology, and Endogenous Growth

Technological Change in Resource Extraction and Endogenous Growth

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