This study contributes to the Climate, Land, Energy, and Water system (CLEWs) framework by developing an integrated model for Kenya capturing the interdependencies between climate, land, energy, and water systems. Focusing on cooking and crop production, it examines their contributions to land use changes, mainly deforestation, and emissions. We evaluate three scenarios-BAU, SC1, and SC2- that target clean cooking transitions and reduced crop imports, covering seven crops representing 72 % of Kenya's cultivated area. We detail the challenges of gathering data to populate such a model through document examination and literature review, and we identified uncertain input parameters. Results show that forest loss from cooking varies with the fraction of non-renewable biomass (fNRB). Under BAU, forest cover loss could range from 300 km2 at an fNRB of 0.3 to 900 km2 at 0.9. Scenarios SC1 and SC2 mitigate these impacts through cleaner cooking solutions. By 2050, under the clean cooking scenario (SC2), LPG stoves could achieve up to 96 % penetration, reducing CO2 emissions to 8.3 MTon and PM2.5 to 0.8 kTon, compared to high emissions in the BAU scenario dominated by wood and charcoal stoves. In agriculture, land use expands by 56 %, 69 %, and 33 % across the scenarios, while fossil fuel use rises from 2.46 PJ to 5.9 PJ by 2050, increasing CO2 emissions, from 183 kTon to 436 kTon. The findings highlight the need for integrated policies promoting clean cooking, sustainable agriculture, and deforestation mitigation. This integrated CLEWs approach provides actional insights for reducing deforestation and emissions in energy and agriculture sectors.

Energy and transport models are powerful tools for shaping policy, development pathways, and financial decisions. However, these models often fail to account for gender equality and social inclusion (GESI), perpetuating systemic inequities and excluding the needs of marginalized communities. This perspective presents guidelines, developed through a collaborative process informed by a scoping literature review and expert consultation with modelers and social scientists, for integrating GESI into large-scale energy and transport systems modeling processes, particularly in low- and lower middle-income countries. By addressing key challenges—such as data disaggregation, the limits of current model architectures, and the complexities of quantifying social factors—we outline steps to incorporate GESI considerations throughout every stage of the modeling life cycle. While developed with energy and transport systems in mind, the principles of these guidelines are broadly applicable to other infrastructure modeling domains. Ultimately, this work demonstrates how inclusive modeling practices can produce more equitable, context-sensitive results, and foster sustainable development outcomes.

Background: Open science emphasizes the free and accessible dissemination of scholarly outputs to a wide audience, including scientists, stakeholders, and the general public. Its core principle is the open sharing of knowledge to enable reuse, replication, and uphold research integrity. Methods: Using insights from a survey designed to explore the open science practices within integrated assessment modeling (IAM) teams, as well as the challenges and barriers they face, we propose an open science protocol tailored specifically to the needs of IAMs. Results: The proposed protocol improves the transparency, accessibility, reliability, reusability, and interoperability of IAM models and results. Grounded in the findability, accessibility, interoperability, and reusability (FAIR) and transparency, responsibility, user focus, sustainability, and technology (TRUST) principles, it supports the transformation of models’ outputs into real-world applications. Conclusions: By fostering enhanced trust and engagement from policymakers, this protocol supports the broader adoption of open science in IAMs. It is complemented by a checklist and includes recommendations for open-source platforms and tools, simplifying workflows and minimizing the need for specialized expertise.

This study applies Global Sensitivity Analysis (GSA) to an optimization model for Kenya based on the Climate, Land, Energy, and Water systems (CLEWs) framework. The model provides insights into the interdependencies among energy, land, and water systems, and the sensitivity analysis allows to evaluate its ability to capture sectoral interactions and trade-offs while identifying key influential parameters shaping the overall system behavior. Using the Morris screening method, the analysis emphasizes the key role of discount rates—both global and technology- specific—influencing the energy sector, biomass use for cooking, renewable energy sources penetration, and forest land cover. The findings also show that all inputs influence forest cover, demonstrating the CLEWs model’s capacity to capture system interactions. By using a fully open methodology, this work enhances CLEWs model transparency and provides actionable insights for policymakers to address trade-offs and support resilient resource management.

Heating and cooling activities account for nearly half of the European Union's total energy use, yet only 23 % of this demand is met by renewable sources. As reliance on fossil fuels declines and waste suitable for incineration diminishes, alternative renewable and excess heat (EH) sources become essential. In Sweden, approximately 4.7 TWh of industrial EH is recovered annually, contributing 12 % of available EH and 9 % of the district heating (DH) supply. Despite projections that EH utilisation will rise from 22 TWh in 2015 to 33 TWh by 2050, lowtemperature levels and economic viability challenges have limited Urban Excess Heat (UEH) integration into DH systems. This study develops a spatial-techno-economic optimisation framework to support long-term UEH integration in DH networks. The framework, composed of three open-source tools for spatial network optimisation, long-term planning, and short-term operational optimisation, was applied to the City of Stockholm's DH system, where over 80 % of buildings are DH-connected. Results indicate that UEH sources within a 5-km radius of primary DH pipelines have the highest feasibility for integration. Economic analyses revealed that investment sensitivity is highest with fluctuations in electricity prices, emphasising the cost implications of energy markets on UEH feasibility. Scenarios with varying grid temperatures demonstrated that lower temperatures improve UEH uptake but require adaptive network designs for efficiency. Iterative linking of long-term and highresolution operational models highlighted differences between cost-optimal plans and operational realities, suggesting refinement needs. This framework offers robust pre-feasibility insights for stakeholders, enhancing strategic planning for sustainable urban heating across municipal and regional levels.

Background

Article 12 of the Paris Agreement summons the signing parties to co-operate in improving the education of their citizens on climate change and related matters. The article thereby acknowledges the importance of citizens’ support and understanding of climate change and needed measures to fight climate change. This work aims to inform European citizens on how climate change-related policies affect the power sector in Europe. For this purpose, a serious game, based on sound principles of energy systems analysis, has been developed to allow players to explore how key policy decisions affect capacity mix, investment needs, and electricity costs.

Results

The game is based on more than 1700 scenarios run through an open-source and accessible, yet technologically detailed, myopic energy system optimisation model for the electricity supply in the EU27 + 3. The game allows the user to take the role of a decision-maker and make decisions in 2020, 2030, and 2040 regarding the usage of CCS, biomass imports, cross-border electricity transmission and the pace of emission reductions. The user is then presented with economic, social, and environmental impacts of these choices. These impacts are, for example, measured and illustrated in the development of accumulated CO2 emissions per capita, levelised cost of electricity, and investment need per citizen.

Conclusion

The Power Decisions Game provides a first-of-its-kind open-source infrastructure that allows non-modellers to explore the impact of key decisions and preferences on the design of the future European power system. Furthermore, it provides insights on the consequences of short-sighted decision making. The game can be used to facilitate policy-science discussions.

This paper presents an innovative approach to addressing critical global challenges in long-term energy planning for low- and middle-income countries (LMICs). The paper proposes and tests an international enabling environment, a delivery ecosystem, and a community of practice. These components are integrated into workflows that yield four self-sustaining capacity-development outcomes. Planning long-term energy strategies in LMICs is particularly challenging due to limited national agency and poor international coordination. While outsourcing energy planning to foreign experts may appear to be a viable solution, it can lead to a reduction in government agency (the ability of a government to make its own informed analysis and decisions). Additionally, studies commissioned by external experts may have conflicting terms of reference, and a lack of familiarity with local conditions can result in misrepresentations of on-the-ground realities. It is argued here that enhancing national agency and analytical capacity can improve coordination and lead to more robust planning across line ministries and technical assistance (TA) providers. Moreover, the prevailing consulting model hampers the release and accessibility of underlying analytics, making it difficult to retrieve, reuse, and reconstruct consultant outputs. The absence of interoperability among outputs from various consultants hinders the ability to combine and audit the insights they provide. To overcome these challenges, five strategic principles for energy planning in LMICs have been introduced and developed in collaboration with 21 international and research organizations, including the AfDB, IEA, IRENA, IAEA, UNDP, UNECA, the World Bank, and WRI. These principles prioritize national ownership, coherence and inclusivity, capacity, robustness, transparency and accessibility. In this enabling environment, a unique delivery ecosystem consisting of knowledge products and activities is established. The paper focuses on two key knowledge products as examples of this ecosystem: the open-source energy modeling system (OSeMOSYS) and the power system flexibility tool (IRENA FlexTool). These ecosystem elements are designed to meet user-friendliness, retrievability, reusability, reconstructability, repeatability, interoperability, and audibility (U4RIA) goals. To ensure the sustainability of this ecosystem, OpTIMUS is introduced—a community of practice dedicated to maintaining, supporting, expanding, and nurturing the elements within the ecosystem. Among other ecosystem elements, training and research initiatives are introduced, namely the Energy Modelling Platform for Africa, Latin America and the Caribbean, and Asia-Pacific as well as the ICTP Joint Summer School on Modelling Tools for Sustainable Development. Once deployed via workflows, the preliminary outcomes of these capacity-development learning pathways show promise. Further investigation is necessary to evaluate their long-term impacts, scalability, replication, and deployment costs.

The understanding of the transboundary impact of Climate Change on hydropower is not well-established in the literature, where few studies take a system perspective to understand the relative roles of different technological solutions for coordinated water and energy management. This study contributes to addressing this gap by introducing an open-source, long-term, technologically-detailed water and energy resources cost-minimisation model for the Drin River Basin, built in OSeMOSYS.The analysis shows that climate change results in a 15-52% annual decline in hydro generation from the basin by mid-century. Albania needs to triple its investments in solar and wind to mitigate the risk of climate change. Changing the operational rules of hydropower plants has a minor impact on the electricity supply. However, it can spare significant storage volume for flood control.

Islands all over the world face common challenges connected to energy costs and greenhouse gas emissions. Thus, islands have been identified as perfect sites for implementing and testing innovative solutions to boost the green energy transition towards a sustainable and clean energy system. The supply of clean water is a major issue that affects small islands, and desalination, particularly Reverse Osmosis, represents a valid solution to this challenge. In this research, an energy system model is used to analyse long-term water and energy supply strategies of the tourist island of Favignana, Italy. The model is built with the Open Source long-term energy modelling tool OSeMOSYS at an hourly resolution. It considers both the potential synergies offered by Reverse Osmosis Desalination and the use of water storage to store the excess electricity when needed. The indirect emissions for the maritime transportation of goods and fuels (i.e., water and diesel) to the island are also accounted for. Different energy policies are compared to understand how a carbon tax, a limit on emissions and no policy would impact the long-term energy strategy of the island. The results show that a carbon tax that covers also the maritime transportation sector would lead to the lowest overall cumulative emissions. They additionally reveal that the contribution of emissions for maritime transportation of goods and fuels is relevant and cannot be neglected if a full decarbonisation has to be achieved. On the technological side, investment in a desalination plant is the most viable option in all cases. Finally, for the first time, OSeMOSYS is applied with hourly resolution and the results are compared with those obtained with lower time resolution showing that inaccuracies are found both for overall values and for the dispatching strategies.

With increasing heating and cooling demands, decarbonisation of the heating and cooling sectors is key to achieving a carbon-neutral energy system. Using industrial excess heat in heating systems helps offset emissions by reducing the use of fossil fuels. While several studies have analysed the temperature of heat availability, the cost of extending or constructing the heating network and techno-economic feasibility, it is important to consider all aspects together to achieve a comprehensive design of industrial excess heat recovery. This study proposes a method to link an energy system optimisation tool with a spatial analysis tool and an exergy analysis tool to achieve a comprehensive design. An iterative soft link is implemented between the energy system model and the spatial analysis tool for high spatial and temporal resolution. The developed method is applied to a case study of an industrial park in Greece. Scenarios are developed to assess the robustness of the developed method and the system profitability of excess heat recovery. The scenarios indicated that the profitability of excess heat depends heavily on the price of natural gas with the share of excess heat increasing from 10% to 45% with a 20% increase in natural gas prices in cases where heat pumps are needed for temperature boosting. In cases where heat pumps are not needed, excess heat indicates higher system profitability with a share of around 40% and reduces the emissions by around 50 times. The method provides robust results in considered scenarios with convergence within four iterations.