Pilar Swart

Abiotic Resource Use

Abiotic resource use in life cycle assessment (LCA) deals with the environmental concerns due to the use of resources such as metals, minerals, fossil energy, nuclear energy, atmospheric resources (e.g. argon), and flow energy resources (e.g. wind energy). Land and water may also be considered as abiotic resources, but these are dealt with elsewhere in the book series in dedicated chapters (Chap. 11 Land use by Llorenc Mila i Canals and Laura de Baan and Chap. 12 Water use by Stephan Pfister). Methods that evaluate ‘abiotic resource use’ in LCA were divided in three categories: (1) Resource accounting methods, which are methods that account for the overall natural resource use along the life cycle of a product; (2) Resource depletion methods at the midpoint level, which are methods that address the scarcity of resources (and therefore damage to the area of protection Resources), but at a midpoint level; and (3) Resource depletion methods at the endpoint level, which are methods that address the scarcity of resources at an endpoint level. Numerous methods are presented in this chapter, with different concepts and approaches. However, several gaps still exist in the evaluation of abiotic resource use in LCA, and more research is needed.

Modeling fossil energy demands of primary nonferrous metal production: the case of copper.

The methodologies for life cycle impact assessment (LCIA) of metal resources are rather diverse. Some LCIA methods are based on ore grade changes, but they typically do not consider the impact of changes in primary metal extraction technology. To characterize the impact of technology changes for copper, we modeled and analyzed energy demand, expressed in fossil energy equivalents (FEE) per kilogram of primary copper, taking into account the applied mining method and processing technology. The model was able to capture variations in reported energy demands of selected mining sites (FEE: 0.07 to 0.84 MJ-eq/kg ore) with deviations of 1 to 30%. Applying the model to a database containing global mine production data resulted in energy demand median values of around 50 MJ/kg Cu irrespective of the processing route, even though median values of ore demands varied between processing routes from ca. 35 (underground, conventional processing) to 200 kg ore/kg Cu (open pit, solvent-extraction, and electrowinning), as high specific ore demands are typically associated with less energy intensive extraction technologies and vice versa. Thus, only considering ore grade in LCIA methods without making any differentiation with regard to employed technology can produce misleading results.