RESUMO
Impacts associated with land use are increasingly recognized as important aspects to consider when conducting Life Cycle Assessment (LCA). Across the existing models accounting for land use activities in life cycle impact assessment, a balance is yet to be found between complexity and comprehensiveness on one hand, and applicability on the other hand. This work builds on the LANd use indicator value CAlculation (LANCA®) model, assessing the impacts of land use activities on five soil properties, and aims at developing an aggregated index to improve its applicability. First a statistical analysis is conducted, leading to the shortlisting of the four most significant soil quality indicators. Then two options for aggregating the selected indicators are presented: the soil quality index (SQI), based on linear aggregation, and the normalisation-based soil quality index (NSQI), where the aggregation process involves normalisation integrated into the characterisation step. Country-specific and global average characterisation factors (CFs) are calculated for 57 land use types considering both land occupation and land transformation interventions with the two suggested approaches. The two indices present similar ranking of land use types but the relative contribution of the separate indicators to the aggregated index varies according to the approach adopted. The differences between the aggregation approaches suggested are discussed, together with the limitations related to both the LANCA® model and the aggregation approaches. This work represents a first step towards the widespread application of a comprehensive and robust land use model at midpoint level in LCA. Finally, a number of recommendations for the future development of the LANCA® model and of the related soil quality models are provided.
RESUMO
Over the last few decades, the systematic approach of knowledge transfer from biological concept generators to technical applications has received increasing attention, particularly because marketable bio-derived developments are often described as sustainable. The objective of this paper is to rationalize and refine the discussion about bio-derived developments also with respect to sustainability by taking descriptive, normative and emotional aspects into consideration. In the framework of supervised learning, a dataset of 70 biology-derived and technology-derived developments characterised by 9 different attributes together with their respective values and assigned to one of 17 classes was created. On the basis of the dataset a decision tree was generated which can be used as a straightforward classification tool to identify biology-derived and technology-derived developments. The validation of the applied learning procedure achieved an average accuracy of 90.0%. Additional extraordinary qualities of technical applications are generally discussed by means of selected biology-derived and technology-derived examples with reference to normative (contribution to sustainability) and emotional aspects (aesthetics and symbolic character). In the context of a case study from the building sector, all aspects are critically discussed.