Fuzzy approach to life cycle impact assessment: An application for biowaste management systems

Background, Aims and Scope. In LCA the valuation step is very controversial since it involves value judgments. In order to strengthen the valuation step, this work establishes a new method, which includes normalization and weighting. Inspired by the proposal of Seppälä and Hämäläinen (2001), and based on the fuzzy sets theory (Zadeh 1965), this methodology permits information to be processed under uncertainty and subjectivity. The method proposed is applied to valuate five biowaste management system scenarios in the Metropolitan Area of Barcelona. Methods. The valuation methodology proposed consists of the acquisition of pattial environmental impact indicators, calculated on the basis of a characterized impact indicator (results from an LCA), an emissions inventory of the studied region, as well as the political targets and sustainability thtesholds for a given area. Next, the partial indicator obtained is transformed to obtain a fuzzy linguistic descriptor, which permits the construction of a preference order amongst a series of alternatives. Results. The proposed methodology permits the LCA normalization and weighting to be considered using a mathematically strengthened approach. It considers a semantic scale with eleven terms, which permits the gradual definition of the performance of alternatives according to their level of membership. Discussion. This consideration deals with the uncertainty and subjectivity inherent in the data used. The results reveal that the worst biowaste management option is the scenario where all biowaste is collected selectively and treated only with biological processes. The preferred biowaste management scenario is the one in which direct uses of biowaste are considered. Conclusions. The fuzzy approach considered improves the theoretical strength of the value obtained by the Distance to Target (DtT) method and its modification in accordance with Multi-Attribute Value Theories (MAVT). This permits the evaluation of complex systems, which ate frequently placed in the field of subjectivity and uncertainty. This is therefore a good method of supporting the decision-making process, based on life cycle impact assessment results. In addition, the order of preferences obtained is consistent with the characteristics of each of the scenarios analyzed. Recommendations and Perspectives. As future work, it is recommended that this methodology be applied to other situations, both in order to analyze its functionality and to compare the process defined with other fuzzy approaches, which may be appropriate for the valuation step in LCA.