Showing papers by "Markus Berger published in 2011"

The anthropogenic stock extended abiotic depletion potential (AADP) as a new parameterisation to model the depletion of abiotic resources

Abstract: Raw material availability is a cause of concern for many industrial sectors. When addressing resource consumption in life cycle assessment (LCA), current characterisation models for depletion of abiotic resources provide characterisation factors based on (surplus) energy, exergy, or extraction–reserve ratios. However, all indicators presently available share a shortcoming as they neglect the fact that large amounts of raw materials can be stored in material cycles within the technosphere. These “anthropogenic stocks” represent a significant source and can change the material availability significantly. With new characterisation factors, resource consumption in LCA will be assessed by taking into account anthropogenic material stocks in addition to the lithospheric stocks. With these characterisation factors, the scarcity of resources should be reflected more realistically. This study introduces new characterisation factors—the anthropogenic stock extended abiotic depletion potentials—for the impact category depletion of abiotic resources. The underlying characterisation model is based on the conventional model but substitutes ultimate reserves by resources and adds anthropogenic material stocks to the lithospheric stocks. A fictional life cycle inventory, consisting of 1 kg of several metals, was evaluated using different characterisation factors for depletion of abiotic resources. Within this analysis it is revealed that materials with relatively large anthropogenic stocks, e.g. antimony and mercury, contribute comparatively less to abiotic depletion when using the new characterisation factors. Within a normalized comparison of characterisation factors, the impact of anthropogenic stock results in relative differences between −45% and +65%, indicating that anthropogenic stocks are significant. With the new parameterisation of the model, depletion of abiotic resources can be assessed in a meaningful way, enabling a more realistic material availability analysis within life cycle impact assessment. However, a larger set of characterisation factors and further research are needed to verify the applicability of the concept within LCA practice.

Correlation analysis of life cycle impact assessment indicators measuring resource use

Abstract: Even though the necessity of a sustainable use of natural resources is widely accepted, there is neither consensus on how “resource use” is clearly defined nor how it should be measured. Depending on the definition, it can comprise raw material consumption only or the consumption and pollution of natural resources. Consequently, lots of indicators can be applied, and the result of a life cycle assessment study aiming to quantify resource use seems to depend on the selection of impact categories. Therefore, this paper aims at analyzing life cycle impact assessment results obtained by means of several indicators to check if different indexes lead to similar results and if the number of indicators can be reduced. Life cycle impact assessment results of 100 materials from the GaBi and ecoinvent databases were compiled using the GaBi 4.3 software. The results obtained by different resource- and emission-oriented as well as single-score indicators were compared by means of correlation analysis to check for potential dependencies between indicators. The analyses revealed large differences regarding the correlations between indicators. While no significant correlations were found between emission-oriented indexes (R 2 = 0.40–0.62), strong linear regressions were identified between indicators assessing raw material consumption (R 2 = 0.65–0.98). This can be explained by the facts that all indicator results are dominated by the consumption of fossil fuels and that characterization models of correlating indexes rely on net calorific values when computing characterization factors for fossil energy carriers. In material groups that consist of energy carriers themselves, like monomers and polymers, significant linear regressions were identified between all resource-oriented indicators (R 2 = 0.78–1.00). Depending on the definition, different life cycle impact assessment indicators can be used for measuring resource use. Following the broader definition, a wide range of impacts has to be evaluated as no significant correlations between indexes assessing resource consumption and pollution were identified. In contrast, since strong linear regressions were revealed among some resource-oriented indicators, the number of indexes can be reduced when defining resource use in a conventional sense.