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Vacuum pressure swing adsorption (VPSA) has demonstrated promising features for the upgrading of biogas to biomethane. In this study, a biogas upgrading plant, comprised of a hybrid of an N-column VPSA unit (2 ≤N≤ 6) with a combined heat and power (CHP) engine, was developed and its techno-economic characteristics were assessed via a mathematical approach. Moreover, the techno economic analysis was used for the state-of-the-art VPSA configuration (a sophisticated configuration) and compared with the developed hybrid process. The prominent parameters including feedstock transport, biogas production, desulfurization, drying, upgrading, combustion, and grid injection were considered in the analyses of the plant for the upgrading capacity in the range of 100 - 6,500 Nm3/h. Sensitivity analysis of the most influencing parameters, i.e., electricity price, gas price, and feed processing revenues, was conducted for the developed models. Beside comparing upgrading cost of the sophisticated VPSA with other upgrading technologies, a detailed comparison with the best available membrane unit for biogas upgrading was conducted. The limitations of adsorption process and VPSA in reducing the upgrading cost were also investigated. The results showed that in the absence of subsidies and requirements for CO2 capture, the hybrid plant outperforms the sophisticated VPSA units. Also, higher market price of natural gas or feedstock processing revenues were necessary in order to render the plant profitable. The results showed that, at flowrates larger than 175 Nm3/h, the sophisticated VPSA unit required a lower investment cost than the membrane unit for identical outputs. The results also show that even at the most idealistic conditions in the adsorption process, the upgrading is not economically favorable without subsidies. The findings of this study shed light on the importance of process design for biogas upgrading.

Vacuum pressure swing adsorption (VPSA) has demonstrated promising features for the upgrading of biogas to biomethane. In this study, a biogas upgrading plant, comprised of a hybrid of an N-column VPSA unit (2 ≤N≤ 6) with a combined heat and power (CHP) engine, was developed and its techno-economic characteristics were assessed via a mathematical approach. Moreover, the techno economic analysis was used for the state-of-the-art VPSA configuration (a sophisticated configuration) and compared with the developed hybrid process. The prominent parameters including feedstock transport, biogas production, desulfurization, drying, upgrading, combustion, and grid injection were considered in the analyses of the plant for the upgrading capacity in the range of 100 - 6,500 Nm3/h. Sensitivity analysis of the most influencing parameters, i.e., electricity price, gas price, and feed processing revenues, was conducted for the developed models. Beside comparing upgrading cost of the sophisticated VPSA with other upgrading technologies, a detailed comparison with the best available membrane unit for biogas upgrading was conducted. The limitations of adsorption process and VPSA in reducing the upgrading cost were also investigated. The results showed that in the absence of subsidies and requirements for CO2 capture, the hybrid plant outperforms the sophisticated VPSA units. Also, higher market price of natural gas or feedstock processing revenues were necessary in order to render the plant profitable. The results showed that, at flowrates larger than 175 Nm3/h, the sophisticated VPSA unit required a lower investment cost than the membrane unit for identical outputs. The results also show that even at the most idealistic conditions in the adsorption process, the upgrading is not economically favorable without subsidies. The findings of this study shed light on the importance of process design for biogas upgrading.

As food insecurity grows globally, foresight planning for sustainable food systems has become critical. Here we argue that history—through detailed data, case studies and methodologies—can profoundly enhance the robustness of scenario planning. By examining cases in Mozambique, Bangladesh and Holland, we illustrate how historical insights can guide interventions on local, national and transnational scales, helping to avoid unintended consequences and building resilience into future food systems.

As food insecurity grows globally, foresight planning for sustainable food systems has become critical. Here we argue that history—through detailed data, case studies and methodologies—can profoundly enhance the robustness of scenario planning. By examining cases in Mozambique, Bangladesh and Holland, we illustrate how historical insights can guide interventions on local, national and transnational scales, helping to avoid unintended consequences and building resilience into future food systems.

Abstract The aim of this study is to evaluate the incremental innovation performance of nuclear energy projects. Within this context, a novel model is generated which consists of two different stages, and large nuclear reactors are taken into consideration. Firstly, the Pythagorean fuzzy DEMATEL is used to weight the phases of technology S-Curve for nuclear energy projects. Moreover, the second stage includes the ranking two-generation technology S-curve with integer patterns for nuclear energy projects. In this framework, the best combinations are selected for innovation life cycle pattern with the integer code series. The findings demonstrate that the nuclear energy companies need to consider the two-generation technology S-Curve because continuous technological developments are occurring for nuclear power generation. It is also determined that aging in the first generation is the most significant period of two-generation technology S-Curve for nuclear energy projects. In this process, critical decisions should be made regarding future technological investments. In addition, the growth phase in the second generation is also important for the effectiveness of the nuclear energy technology. Conducting effective evaluations in these processes will contribute to increasing the efficiency of companies.

Abstract The aim of this study is to evaluate the incremental innovation performance of nuclear energy projects. Within this context, a novel model is generated which consists of two different stages, and large nuclear reactors are taken into consideration. Firstly, the Pythagorean fuzzy DEMATEL is used to weight the phases of technology S-Curve for nuclear energy projects. Moreover, the second stage includes the ranking two-generation technology S-curve with integer patterns for nuclear energy projects. In this framework, the best combinations are selected for innovation life cycle pattern with the integer code series. The findings demonstrate that the nuclear energy companies need to consider the two-generation technology S-Curve because continuous technological developments are occurring for nuclear power generation. It is also determined that aging in the first generation is the most significant period of two-generation technology S-Curve for nuclear energy projects. In this process, critical decisions should be made regarding future technological investments. In addition, the growth phase in the second generation is also important for the effectiveness of the nuclear energy technology. Conducting effective evaluations in these processes will contribute to increasing the efficiency of companies.