A quantitative framework for sustainability assessment

The present climate change crisis forced humanity to opt for sustainable development. Sustainability assessment is vital to determine the relative superiority among alternatives, characterized by multiple sustainability indicators to ensure sustainable development. Various methods, such as the Euclidean distance method, geometric mean method, and elimination et choice translating reality, have been suggested in the literature to identify the most sustainable option among alternatives. These diverse approaches adopt different normalization and aggregation formulations (the two most significant steps of any sustainability assessment), leading to conflicting results. This paper proposes a generalized sustainability framework to quantitatively identify the most suitable alternative. The proposed framework incorporates various mathematical characteristics of normalization and aggregation processes and identifies mathematical functions that satisfy these characteristics. Based on the desired characteristics, the proposed approach identifies the min-max normalization function and a novel antinorm-based aggregation function as one of the appropriate functions for a quantitative sustainability framework. To illustrate the applicability of the proposed framework, different case studies are adopted from the literature: sustainable power plants for electricity generation in Portugal, sustainable feedstocks for the biodiesel supply chain, and sustainable negative emission technologies. The results are compared with those reported in the literature, and the efficacy of the suggested framework is demonstrated. The proposed framework may be utilized for multi-criteria decision-making.