Linking existing models to extend energy system and integrated assessment analysis is an increasingly common practice. Despite this, and unlike in the field of environmental and earth sciences, little attention has so far been paid to the details of it, to the trade-offs involved and the way in which the model linking affects the interpretation of the outcomes of the interlinked model system. Our aim in this paper is to first focus on a set of key technical and methodological problems that are common in model linking and suggest how these could be approached in different model linking contexts. We then further explore how model linking may affect the nature of the knowledge produced, and how this should be considered in the model linking process. Reflecting our literature driven assessment of the issues and possible solutions, we compile "a check list" to assist in the process of decision making for model linking.

This study presents a novel integrated modeling framework that combines the Climate-Land-Energy-Water (CLEWs) system with an Input-Output (I-O) model to assess the synergies between climate resilience, resource management, and job creation. To clarify the carbon-related impact, we note that increasing renewable energy capacity to 80 % of electricity demand reduces greenhouse gas emissions by 66 %. Applied to a water-scarce region in the Middle East, the model evaluates multiple climate adaptation scenarios, revealing that adopting water-efficient agricultural practices (e.g., replacing flood irrigation with drip and subsurface systems) can reduce water consumption by up to 30 % (132 Mm3/year). Expanding renewable energy capacity to 80 % of electricity demand cuts greenhouse gas emissions by 66 %, while creating 107,000 new jobs, of which 39,000 are in renewables, 68,000 in diversified agriculture, and 8300 in wastewater reuse. The framework also highlights that without simultaneous action on water efficiency and clean power, both emission reductions and job gains are significantly diminished. This model, applicable to diverse resource-scarce regions, demonstrates the potential for balancing sustainable development goals-enhancing resource security, decarbonizing energy systems, and promoting inclusive economic growth. The findings underscore the model's broad applicability across various geographical and policy contexts, providing a flexible decision-support tool for optimizing the nexus between water, energy, and employment in the face of climate change.

This comprehensive state-of-the-art literature review explores recent scientific developments in climate, land, energy, and water systems (CLEWs) modelling by systematically analysing 41 peer-reviewed studies published between 2020 and 2024. This research uncovered insights into the evolving interdisciplinary landscape, revealing various trends, such as approximately 74% of studies publishing their data as open-access and 50% employing an open-source analytical tool, or tools, in combination with open-access data. This study identified four areas of significance: (1) the connections between CLEWs and the sustainable development goals, (2) how the CLEWs framework is linked to capacity development, (3) the critical interplay between energy and water systems, and (4) the transformative potential for comprehensive system integration using the CLEWs modelling framework. By pinpointing promising research directions such as soft-linking CLEWs models with geographic information systems, applying robust decision making methodologies, adapting the CLEWs framework to the city level, and highlighting the need to assess real world impact of CLEWs research, the review provides a strategic roadmap for future interdisciplinary research. Notably, the analysis emphasised the urgent need for enhanced institutional coordination and collaborative communities of practice, particularly for open-source modelling tools like the open-source energy modelling system, to further accelerate knowledge dissemination and foster innovative, integrated approaches to complex systemic challenges.

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.