Open Access

Klaus Wiesen, Monika Wirges

• Background: Global targets for reducing resource use have been set by organizations such as the International Resource Panel and the European Commission. However, these targets exist only at the macro level, e.g., for individual countries. When conducting an environmental analysis at the micro level, resource use is often neglected as an indicator. No sum parameter indicating all abiotic and biotic raw materials has been considered for life cycle assessment, as yet. In fact, life cycle assessment databases even lack some of the specific input flows required to calculate all abiotic and biotic raw materials. In contrast, the cumulative energy demand, an input-based indicator assessing the use of energy resources, is commonly used,Background: Global targets for reducing resource use have been set by organizations such as the International Resource Panel and the European Commission. However, these targets exist only at the macro level, e.g., for individual countries. When conducting an environmental analysis at the micro level, resource use is often neglected as an indicator. No sum parameter indicating all abiotic and biotic raw materials has been considered for life cycle assessment, as yet. In fact, life cycle assessment databases even lack some of the specific input flows required to calculate all abiotic and biotic raw materials. In contrast, the cumulative energy demand, an input-based indicator assessing the use of energy resources, is commonly used, particularly when analyzing energy-intensive product systems. Methods: In view of this, we analyze the environmental relevance of the sum parameter abiotic and biotic raw material demand, which we call the material footprint. First, we show how abiotic and biotic raw material demand can be implemented in the Ecoinvent life cycle assessment database. Employing the adapted database, the material footprint is calculated for 12 individual datasets of chosen materials and crops. The results are compared to those of the cumulated energy demand and four selected impact categories: climate change, ozone depletion, acidification, and terrestrial eutrophication. Results: The material footprint is generally high in the case of extracted metals and other materials where extraction is associated with a large amount of overburden. This fact can lead to different conclusions being drawn compared to common impact categories or the cumulative energy demand. However, the results show that both the range between the impacts of the different materials and the trends can be similar. Conclusions: The material footprint is very easy to apply and calculate. It can be implemented in life cycle assessment databases with a few adaptions. Furthermore, an initial comparison with common impact indicators suggests that the material footprint can be used as an input-based indicator to evaluate the environmental burden, without the uncertainty associated with the assessment of emission-based impacts.…