Plant-to-planet analysis of CO 2 -based methanol processesOur society demands more sustainable chemicals, fuels and products to fulfil carbon neutrality. This Analysis introduces a systems engineering approach that for the first time quantifies the sustainability level of chemicals in global terms by extending state-of-the-art process assessment with the concept of planetary boundaries, thus providing more sensible guidance in research and policy-making. Focusing on methanol synthesis, we show that replacing the fossil-derived CO and H 2 feedstock with captured CO 2 and renewable H 2 shall help us to operate within ecological Earth limits of climate change that are currently transgressed. Registered charity number: 207890 rsc.li/ees As featured in: PAPER Tao Cheng, Yanguang Li et al . Weakening hydrogen adsorption on nickel via interstitial nitrogen doping promotes bifunctional hydrogen electrocatalysis in alkaline solution

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This article addresses the design of sustainable chemical supply chains in the presence of uncertainty in the life cycle inventory associated with the network operation. The design task is mathematically formulated as a bi-criterion stochastic mixed-integer nonlinear program (MINLP) that simultaneously accounts for the maximization of the net present value and the minimization of the environmental impact for a given probability level. The environmental performance is measured through the Eco-indicator 99, which incorporates the recent advances made in Life Cycle Assessment. The stochastic model is converted into its deterministic equivalent by reformulating the probabilistic constraint required to calculate the environmental impact in the space of uncertain parameters. The resulting deterministic bi-criterion MINLP problem is further reformulated as a parametric MINLP, which is solved by decomposing it into two sub-problems and iterating between them. The capabilities of the proposed model and solution procedure are illustrated through two case studies for which the set of Pareto optimal, or efficient solutions that trade-off environmental impact and profit, are calculated. These solutions provide valuable insights into the design problem and are intended to guide the decision maker towards the adoption of more sustainable design alternatives.

The objective of this work is to present a quantitative tool to support decision-making in the area of optimal design of supply chains (SC) for the combined production of sugar and ethanol. The problem is formulated as a multiobjective mixed-integer linear program that seeks to optimize simultaneously the economic and environmental performance of the production chain. The advantages of the approach presented are illustrated through its application to a case study, in which a trade-off exists between the economic and environmental performance of the network. Our method provides valuable insight into the problem and a guide to adopt more sustainable strategic alternatives in the design of SCs with embedded biorefineries.