A Systematic Analysis Method for Energy Systems Characterized by Data Scarcity: A Case Study of Mongolia

Research on low-carbon transitions often neglects small developing countries due to severe data scarcity. To address this critical gap, this study introduces a novel systematic analysis framework tailored for data-constrained environments. Integrating Sankey diagram-based energy allocation analysis with a six-dimensional diagnostic framework (resources, policy, economy, technology, society, and environment), the methodology leverages publicly available International Energy Agency data to visualize complex energy flows and identify underlying drivers. To verify the framework’s efficacy, a case study of Mongolia (2016–2021) is carried out. The analysis reveals a persistent structural reliance on coal and uncovers a strategic disconnect between macro-level climate goals and micro-level implementation, primarily driven by economic dependence and technological inertia. By transforming limited public data into actionable systemic insights, this study provides a robust and reproducible tool for evidence-based policymaking. The proposed method offers a vital contribution to global decarbonization efforts, enabling other data-scarce developing countries to navigate their energy transitions effectively.