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The REpowerEU plan prioritizes combining electrification with low-carbon hydrogen for a green energy shift. However, uncertainties surrounding the future hydrogen market and its supply costs impede the establishment of its value chain. Without definite plans for hydrogen production and infrastructure, investing in low-carbon hydrogen industrial processes is risky. Simultaneously, the absence of solid market interest poses challenges in deploying a hydrogen backbone. In recent years, European gas Transmission System Operators (TSOs) in Belgium, Netherlands, and Germany, have introduced various roadmaps for their prospective national hydrogen network. Despite the infrastructure proposals, detailed quantitative scenario analysis for the future hydrogen supply chain is still missing. This paper presents a hydrogen infrastructure model that employs Mixed Integer Linear Programming (MILP) for investment and operational cost optimization at detailed spatiotemporal resolution. A regionalization method is proposed to allocate the potential hydrogen consumption in different industrial sectors across various clusters within a country, represented as the prospective hydrogen demand nodes. The model assesses extreme supply scenarios to examine the robustness of the resulting network infrastructure and compare the system-levelized cost of hydrogen. A real-life case study focusing on the potential Belgian hydrogen supply chain showcases the model's capabilities and outputs. • Regionalization of the industrial hydrogen consumption derived from a national-scale energy system model. • MILP cost optimization model for hydrogen infrastructure design. • Comparative analysis of diverse extreme low-carbon hydrogen supply scenarios. • In-depth case study focusing on the prospective Belgian hydrogen backbone. [ABSTRACT FROM AUTHOR]

The coexistence of the need to improve economic conditions and the conscious use of environmental resources plays a central role in today's sustainable development challenge. In this study, a novel integrated framework to evaluate the impact of new technological interventions is presented and an application to smallholder coffee farms and their supply chains in Kenya is proposed. This methodology is able to combine multiple information through the joint use of three approaches: supply chain analysis, input-output analysis, and energy system modeling. Application to the context of the Kenyan coffee sector enables framework validation: shading management measures, the introduction of eco-pulpers, and the exploitation of coffee waste biomass for power generation were compared within a holistic high-level perspective. The implementation of shading practices, carried out with fruit trees, shows the most relevant effects from the economic point of view, providing farmers with an additional source of income and generating $903 of work for every million of local currency (about $9k) invested in this solution. The same investment would save up to 1.46 M m3 of water per year with the eco-pulpers technology. Investing the same amount in coffee-biomass power plants would displace a small portion of production from heavy-duty oil and avoid importing a portion of fertilizer, saving up to 11 tons of CO2 and around $4k per year. The results suggest the optimal allocation of a $100m budget, which can be affected by adding additional constraints on minimum environmental or social targets in line with sustainable development goals. [ABSTRACT FROM AUTHOR]