• Energy Research

Abstract Purpose This research aims to develop a critical understanding of the employment of digital technologies (DTs) for LCA studies, outlining both the opportunities and challenges associated with circular strategies. Two research questions are thus addressed: (1) What circular loops and aspects are addressed when digital technologies are integrated in the development of a Life Cycle Inventory? (2) Which trade-offs are revealed in the integration of digital technologies in Life Cycle Inventory development addressing circularity along a life cycle? Methods This study is based on the problematisation approach, which critically examines existing assumptions in the LCA literature, structured into six principles: defining a domain of investigation, articulating and evaluating assumptions, developing alternative perspectives, involving the audience through qualitative interviews, and assessing the alternative assumptions. A systematic literature review (SLR) and semi-structured interviews with experts were conducted to explore these issues and suggest future research directions. Results and discussion It emerges that the DTs are mainly integrated in the Life Cycle Inventory phase capturing closing and narrowing loops, whereas a limited number of cases investigate slowing loops with different aspects investigated. However, even if DTs can facilitate and improve the trustworthiness of the inventory, they can also lead to an increase in complexity because more competencies are needed, it is more difficult to control data collection and elaboration, and more social interactions along the supply chain are needed. At the same time, DTs can reduce flexibility because further improvements are blocked, interfaces can be rigid to connect, and technical and normative updates can be more difficult to implement. Conclusions DTs improve the development of the Life Cycle Inventory phase, particularly in the context of the circular economy. However, they also introduce new complexities and challenges. The use of blockchain, digital twins, and IoT sensors, for instance, has significantly improved data transparency and traceability, which are critical for circular economy practices, but complexity and training requirements can limit their benefits, so careful consideration must be given to their implementation to maximise benefits and minimise drawbacks.

Abstract Sustainability of industrial processes has been a hot spot and draws the attentions of more and more stakeholders, because determining the synthetic sustainability index can help the decision-makers/stakeholders to make informed decisions towards sustainable industrial processes, especially for selecting the most sustainable industrial process among multiple alternatives. This study aims to develop an interval reference point technique for the prioritization of industrial processes under uncertainties. The hierarchy best-worst method which can determine the weights of the criteria, the local weights of the sub-criteria and the global weights of the sub-criteria simultaneously was employed for weights determination. An interval reference point technique which allows the users to set the aspiration point (the level of acceptance) and the reservation point (the level of desirable expectation) was developed to determine the dual synthetic sustainability indexes, and both the weak synthetic sustainability index (compensatory sustainability index) and the strong synthetic sustainability index (non- compensatory sustainability index) were used to prioritize the industrial processes. A case study with five alternative energy storage technologies has been studied to illustrate the developed framework, and the results reveal that the developed framework is feasible and efficient for sustainability assessment and prioritization of industrial processes.

The interest of scientists and companies in understanding the business implications of environmental investment is timely; however, a dilemma remains at the firm level: is the environment a “strategic competitive factor”, as in the “Porter point of view”, or is it a “luxury good”, as in the “Wagner point of view”? Our research contributes to this debate through a review of the papers published in scientific journals between 2000 and 2015 that discussed the direction of the relationship between the environmental and business performances of enterprises. The objectives of the research are: (a) to verify if there is an agreement in the scientific literature of the last 15 years about the “Porter–Wagner dilemma” when focusing at the firm level; (b) to underline the prevalent cause and effect directions of the relationship between environmental and business performance; and (c) to investigate the reasons for any disagreements in this topic among the scientists. The results show that the main agreement regards the positive bi-directional relationship, as a virtuous cyclic approach with mutual effects between business and environmental performance; nevertheless, more complex hypotheses emerge, such as nonlinear and/or conditional relationship, that need to be further explored. On the other hand, the Porter–Wagner dilemma remains, and the main reason for the non-agreement among scientists can be due to the several non-homogeneous variables considered in the analyses. Thereafter, as lesson for scientists, the priority is to share univocal methods to measure firms’ environmental and business performances.

The biomass poultry litter and sewage sludge co-gasification is a good thermochemical method to produce hydrogen energy meanwhile to mitigate the consumption of fossil fuels. However, the operation optimization in the complex process system is important while computationally difficult because of high nonlinearity and many first-principle constraints. To address the optimization of this biohydrogen production process, a methodology framework for achieving the optimal operations is thus presented. The complete process system is first simulated and decomposed into upstream gasification process and downstream hydrogen purification for reducing computational complexity through the thermodynamic equilibrium-based simulation.

A comprehensive introduction to the benefits and challenges of life cycle assessment for sustainable development

Urban sewage treatment is an irreplaceable part of environment protection and public health. In order to help the stakeholders choose the best scenario for urban sewage treatment, alternative technologies are proposed to wastewater treatment in cities by developing a novel sustainability decision support framework. The proposed methodology is used to study the illustrative case which includes four urban sewage treatment technologies. The results show that the anaerobic–oxidation ditch technology performs highest for sustainability for urban sewage treatment, following by anaeroxic–anoxic–oxic, sequencing batch reactor, and triple oxidation ditch in the descending order. The proposed method can be extended and applied to help stakeholders to decide the most sustainable wastewater treatment technology alternatives.

Abstract The purpose of this study is to develop a method for prioritizing and classifying the sustainability of hydrogen supply chains and assist decision-making for the stakeholders/decision-makers. Multiple criteria for sustainability assessment of hydrogen supply chains are considered and multiple decision-makers are allowed to participate in the decision-making using linguistic terms. In this study, extension theory and analytic hierarchy process are combined to rate the sustainability of hydrogen supply chains. The sustainability of hydrogen supply chains could be identified according to the synthesis correlation degrees to each classical domain. Finally, an illustrative case is studied by the proposed method, and the results show that the proposed method is feasible for prioritizing and classifying the sustainability of hydrogen supply chains.

A tri-generation-based sustainable poultry litter (PL) valorization process has been developed in this study. To make the proposed process economically viable and energy efficient, the primary gasification process of PL is further enhanced to convert syngas into dimethyl ether (DME). According to our energy analysis, the current tri generation process exhibits 57% energy efficiency, which is 12% higher than that of PL gasification (45%). A particle swarm optimization (PSO)-based algorithm was applied to optimize the gasification and DME production process. According to PSO results, the optimum operating conditions are 667 ◦C, 2 bar, and 1.78 air ratio in the gasification process, while using reaction temperatures of 400 and 100 ◦C in the DME reactors leads to 242.6 kg/ ton DME with 4414.6 kJ/s net heat. On the contrary, only 190.8 kg/ton DME with 4642.2 kJ/s net heat can be generated in the base process. The optimized process is economically viable to achieve an 80% plant operational efficiency with an internal rate of return (IRR) of 16.3% when compared with the base process, which becomes infeasible when the plant efficiency is <90%. A sustainability index (SI) was developed, and the results show that the optimized process was more sustainable (0.290) than the base process (0.279). Therefore, our optimized DME process is more economically viable and eco-friendly