Multi-criteria screening of chemicals considering thermodynamic and life cycle assessment metrics via data envelopment analysis: application to CO2 capture. Issue 24 (14th September 2016)

• Record Type: Journal Article
• Authors: Limleamthong, P.; Gonzalez-Miquel, M.; Papadokonstantakis, S.; Papadopoulos, A. I.; Seferlis, P.; Guillén-Gosálbez, G.
• Is Part Of: Green chemistry. Volume 18:Issue 24(2016)
• Page Start: 6468
• Page End: 6481
• Publication Date: 2016-09-14
• Subjects: Environmental chemistry -- Industrial applications -- Periodicals; Environmental management -- Periodicals; 660
• DOI: 10.1039/c6gc01696k
• Languages: English
• ISSNs: 1463-9262

Abstract

Abstract : We propose a decision-support tool to assess the sustainability level of chemical products and processes. Abstract : With the growing trend of incorporating sustainability principles in the chemical industry, there is a clear need to develop decision-making tools to quantify and optimise the sustainability level of chemical products and processes. In this study, we propose a systematic approach based on Data Envelopment Analysis (DEA) for the multi-criteria screening of molecules according to techno-economic and environmental aspects. The main advantage of our method is that it does not require any articulation of preferences via subjective weighting of the assessment criteria. Furthermore, our approach identifies the most efficient chemicals (according to some sustainability criteria) and for the ones found to be inefficient it establishes in turn improvement targets that can be used to guide research efforts in green chemistry. Our method was applied to the screening of 125 amine-based solvents for CO2 capture considering 10 different performance indicators, which are relevant to technical, health, safety and environmental aspects, including CO2 solubility, molar volume, surface tension, heat capacity, viscosity, vapour pressure, mobility, fire & explosion, acute toxicity and Eco-indicator 99. Our approach eliminates 36% of the solvents (as they are found to be inefficient), identifies the main sources of inefficiency ( e.g., properties displaying poor values that should be improved) and ranks the best chemicals according to an objective criterion that does not rely on weights. Overall, our proposed DEA-based framework offers insightful guidance to make chemicals more sustainable.