Implementation of stochastic multi attribute analysis (SMAA) in comparative environmental assessments

The selection of an alternative based on the results of a comparative environmental assessment such as life cycle assessment (LCA), environmental input-output analysis (EIOA) or integrated assessment modelling (IAM) is challenging because most of the times there is no single best option. Most comparative cases contain trade-offs between environmental criteria, uncertainty in the performances and multiple diverse values from decision makers. To circumvent these challenges, a method from decision analysis, namely stochastic multi attribute analysis (SMAA), has been proposed instead. SMAA performs aggregation that is partially compensatory (hence, closer to a strong sustainability perspective), incorporates performance uncertainty in the assessment, is free from external normalization references and allows for uncertainties in decision maker preferences. This paper presents a thorough introduction of SMAA for environmental decision-support, provides the mathematical fundamentals and offers an Excel platform for easy implementation and access

Prioritising organisational circular economy strategies by applying the partial order set theory: Tool and case study

This study presents a methodology to solve circular economy multiple indicators system decision-making problems by applying the Partial Order Set Theory (POSET). To this end, a user-friendly tool was developed to allow the prioritisation of alternative scenarios or circularity strategies based on the value that each of them takes for different circular economy indicators (both quantitative and qualitative), but avoiding processes involving aggregation and weight among the indicators. The developed tool also makes it possible to model different restrictions that facilitate its adaptation to any case study and the incorporation of the results into the decision-making process. Moreover, it allows a graphical representation of the results to be obtained by using Hasse diagrams. Finally, the developed tool was validated by means of its application to a case study with the aim of prioritising circular economy strategies in an organisation belonging to the construction sector. Specifically, this organisation presented some opportunities for improvement, mainly related to the use of recycled and recirculated materials and effluents, waste recycling, energy efficiency and the proximity of suppliers, among others. The sensitivity analysis of the considered restrictions showed not only the robustness of the results obtained with the tool but also its great influence in circular economy multiple indicators decision-making solutions.Funding for open access charge: CRUE-Universitat Jaume

The concept of stability fields and hot spots in ranking of environmental chemicals.

In contrast to conventional multi-criteria decision aids, such as the well known PROMETHEE approach, AHP or the different versions of ELECTRE, we support the basic assumption of environmetrics: let first the data speak, and then let us include subjective preferences in order to get a unique decision. In the present paper we introduce and discuss the decision support system METEOR (Method of Evaluation by Order Theory). The basis of the method is a data matrix. The rows are defined by the objects which are to be evaluated; the columns are defined by the attributes, which characterize the objects with respect to the evaluation problem. By means of the attributes a partial order is derived. In subsequent steps attributes are aggregated by a weighting procedure, allowing a high degree of participation of stakeholders and other participants of the planning process. The aim is to enrich the partial order stepwise, until the objects of interest can be compared. The software WHASSE written in Delphi is available for scientific purposes from the first author. As an example we evaluate 12 high production volume chemicals (HPVC) which have been detected in the environment by four attributes and discuss the enriched partial order after introducing some weights. It turns out that in some cases the weights have almost no influence concerning the evaluation result, whereas in some other cases slight variations of weights drastically change the evaluation result. Therefore, the metric space spanned by weights can be partitioned in so-called “stability fields” where the evaluation result is invariant and in so-called “hot spots”, where the evaluation is strongly changing. This characterisation of the space of weights is helpful for stakeholders to express their preferences