Sustainable process design by the process to planet framework

Toward Sustainable Chemical Engineering: The Role of Process Systems Engineering

Products from chemical engineering are essential for human well-being, but they also contribute to the degradation of ecosystem goods and services that are essential for sustaining all human activities. To contribute to sustainability, chemical engineering needs to address this paradox by developing chemical products and processes that meet the needs of present and future generations. Unintended harm of chemical engineering has usually appeared outside the discipline's traditional system boundary due to shifting of impacts across space, time, flows, or disciplines, and exceeding nature's capacity to supply goods and services. Being a subdiscipline of chemical engineering, process systems engineering (PSE) is best suited for ensuring that chemical engineering makes net positive contributions to sustainable development. This article reviews the role of PSE in the quest toward a sustainable chemical engineering. It focuses on advances in metrics, process design, product design, and process dynamics and control toward sustainability. Efforts toward contributing to this quest have already expanded the boundary of PSE to consider economic, environmental, and societal aspects of processes, products, and their life cycles. Future efforts need to account for the role of ecosystems in supporting industrial activities, and the effects of human behavior and markets on the environmental impacts of chemical products. Close interaction is needed between the reductionism of chemical engineering science and the holism of process systems engineering, along with a shift in the engineering paradigm from wanting to dominate nature to learning from it and respecting its limits.

Modeling and Simulation of Energy Systems: A Review

Energy is a key driver of the modern economy, therefore modeling and simulation of energy systems has received significant research attention. We review the major developments in this area and propose two ways to categorize the diverse contributions. The first categorization is according to the modeling approach, namely into computational, mathematical, and physical models. With this categorization, we highlight certain novel hybrid approaches that combine aspects of the different groups proposed. The second categorization is according to field namely Process Systems Engineering (PSE) and Energy Economics (EE). We use the following criteria to illustrate the differences: the nature of variables, theoretical underpinnings, level of technological aggregation, spatial and temporal scales, and model purposes. Traditionally, the Process Systems Engineering approach models the technological characteristics of the energy system endogenously. However, the energy system is situated in a broader economic context that includes several stakeholders both within the energy sector and in other economic sectors. Complex relationships and feedback effects exist between these stakeholders, which may have a significant impact on strategic, tactical, and operational decision-making. Leveraging the expertise built in the Energy Economics field on modeling these complexities may be valuable to process systems engineers. With this categorization, we present the interactions between the two fields, and make the case for combining the two approaches. We point out three application areas: (1) optimal design and operation of flexible processes using demand and price forecasts, (2) sustainability analysis and process design using hybrid methods, and (3) accounting for the feedback effects of breakthrough technologies. These three examples highlight the value of combining Process Systems Engineering and Energy Economics models to get a holistic picture of the energy system in a wider economic and policy context.

Integrating Hybrid Life Cycle Assessment with Multiobjective Optimization: A Modeling Framework

By combining life cycle assessment (LCA) with multiobjective optimization (MOO), the life cycle optimization (LCO) framework holds the promise not only to evaluate the environmental impacts for a given product but also to compare different alternatives and identify both ecologically and economically better decisions. Despite the recent methodological developments in LCA, most LCO applications are developed upon process-based LCA, which results in system boundary truncation and underestimation of the true impact. In this study, we propose a comprehensive LCO framework that seamlessly integrates MOO with integrated hybrid LCA. It quantifies both direct and indirect environmental impacts and incorporates them into the decision making process in addition to the more traditional economic criteria. The proposed LCO framework is demonstrated through an application on sustainable design of a potential bioethanol supply chain in the UK. Results indicate that the proposed hybrid LCO framework identifies a considerable amount of indirect greenhouse gas emissions (up to 58.4%) that are essentially ignored in process-based LCO. Among the biomass feedstock options considered, using woody biomass for bioethanol production would be the most preferable choice from a climate perspective, while the mixed use of wheat and wheat straw as feedstocks would be the most cost-effective one.