Surplus Cost Potential as a Life Cycle Impact Indicator for Metal Extraction
2. Methods and Data
2.1. Cause-Effect Pathway
2.2. Cumulative Cost-Tonnage Relationships
2.3. Characterization Factors
2.4. Sensitivity Analysis
2.5. Data Selection and Fitting
|Metal||Cumulative Metal Extracted||Maximum Metal Extracted|
|CMEtotal (kgx)||MMER (kgx)||MMEURR (kgx)|
|Copper||5.92 × 1011||1.28 × 1012||5.22 × 1012|
|Iron||3.41 × 1013||1.15 × 1014||6.49 × 1015|
|Lead||2.35 × 1011||3.24 × 1011||3.04 × 1012|
|Manganese||5.80 × 1011||1.15 × 1012||1.28 × 1014|
|Molybdenum||6.62 × 109||1.76 × 1010||1.89 × 1011|
|Nickel||5.53 × 1010||1.29 × 1011||7.82 × 1012|
|Palladium||5.15 × 106||2.83 × 107||8.25 × 107|
|Platinum||6.97 × 106||3.82 × 107||1.12 × 108|
|Rhodium||7.36 × 105||4.04 × 106||1.18 × 107|
|Silver||1.13 × 109||1.65 × 109||2.11 × 1010|
|Uranium||2.71 × 109||5.23 × 109||4.33 × 1011|
|Zinc||4.58 × 1011||7.08 × 1011||1.16 × 1013|
|Platinum-Group Metals||1.47 × 107||8.07 × 107||2.36 × 108|
2.5.1. Cumulative Cost-Tonnage Relationships
- Typically, deposits contain various metals but there is often a main metal that justifies the operation of a mine exploring that deposit. As such, the operating costs of a mine are to be shared by all outputs with a market value. In the World Mine Cost Data Exchange , the costs were allocated across all mine products in proportion to their production (monetary) value to the mine operator.
- Each table includes data in U.S. dollars valued in the year it represents, e.g., the costs for 2004 are expressed in constant USD valued in 2004. The CPI Inflation Calculator  was used to convert all costs into U.S. dollars for 2013 (USD2013).
- For each mine, the weighted average costs per amount of metal produced, calculated on basis of the operating costs per metal in that mine each year and the production tonnages for the same years, and the total metal extracted in the period covered for that mine were calculated.
- The mines were then ranked in increasing order of costs per amount of metal extracted and the cumulative metal extracted for each mine was calculated by adding the metal extracted of that mine to that of all previous mines with lower operating costs.
- A log-logistic fit was applied to the inverted costs for every mine with the software R for statistical computing  to derive the scale parameter α and the shape parameter β, including their 95% confidence interval (95% CI). The R square (R2) of the log-logistic fit was also determined. For the derivation of α and β, the total tonnage of metal extracted Ax was set equal to the total metal extracted as reported in the WMCDE database between 2000 and 2012 or 2013, depending on the metal .
2.5.2. Characterization Factors
3.1. Cumulative Cost-Tonnage Relationships
3.2. Characterization Factors
4.1. Comparison with other Indicators
Supplementary FilesSupplementary File 1
Conflicts of Interest
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Vieira, M.D.M.; Ponsioen, T.C.; Goedkoop, M.J.; Huijbregts, M.A.J. Surplus Cost Potential as a Life Cycle Impact Indicator for Metal Extraction. Resources 2016, 5, 2. https://doi.org/10.3390/resources5010002
Vieira MDM, Ponsioen TC, Goedkoop MJ, Huijbregts MAJ. Surplus Cost Potential as a Life Cycle Impact Indicator for Metal Extraction. Resources. 2016; 5(1):2. https://doi.org/10.3390/resources5010002Chicago/Turabian Style
Vieira, Marisa D.M., Thomas C. Ponsioen, Mark J. Goedkoop, and Mark A.J. Huijbregts. 2016. "Surplus Cost Potential as a Life Cycle Impact Indicator for Metal Extraction" Resources 5, no. 1: 2. https://doi.org/10.3390/resources5010002