経済・人口・エネルギー指標に基づく主要温室効果ガス排出国のグループクラスタリング

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🔬研究者:国別脱炭素戦略の類型化手法とクラスタ別優先策の枠組みを、比較気候政策研究の出発点として活用できる。

🏢実務担当者:自社の拠点国が属するクラスタを把握し、Scope1-3削減目標や移行計画の実現可能性を国別文脈で再評価する材料になる。

🏛政策担当者:画一的な排出削減目標ではなく、クラスタ特性に応じた技術・規制・投資の差別化設計を検討する根拠として参照できる。

Introduction. The relevance of this work stems from the need to move away from general decarbonization plans and towards differentiated climate strategies, since countries that emit greenhouse gases (GHGs) differ in terms of their energy balance, level of industrialization, population size, carbon intensity of their economy, and the export of fuel and energy resources. The same emission reduction goals may require different technological, investment, and regulatory solutions. Unification approaches are not effective in this context. The literature mainly focuses on analyzing carbon intensity, low-carbon development scenarios, and individual energy indicators. The fragmentary nature of the known approaches prevents the creation of a typology of GHG-emitting countries based on a combination of economic, demographic, energy, and climatic characteristics. The presented scientific work fills this gap. The aim of this study was to form and interpret the typology of key GHG-emitting countries based on a comprehensive analysis of economic, demographic, energy, and climatic indicators. According to this typology, decarbonization conditions and transitional climate risks within clusters were identified. Materials and Methods. The research was based on a statistical database for more than 40 GHG-emitting countries. To ensure comparability, data preprocessing, z -score normalization of features, clustering by Ward’s hierarchical method, and the combined t-SNE + k-means approach were used. The optimal number of clusters was determined using the elbow method and the silhouette coefficient, and the clustering quality was determined by the Davies–Bouldin index. Results. Significant cross-country differences in specific greenhouse gas emissions per capita, the carbon intensity of GDP at PPP, the structure of generation capacity, and specific emissions per unit of electricity produced have been identified. Based on the results of hierarchical clustering and t-SNE + k-means , four groups of states were identified: - two largest emitters with large-scale and diversified energy production; - four exporters of fuel and energy resources; - eight carbon-intensive industrial and developing countries; - 31 relatively energy-efficient and low-carbon economies. Discussion. Cluster analysis suggested that the absolute amount of GHGs emissions was not the only factor to consider when choosing a climate strategy. Countries with similar carbon footprints could differ significantly in terms of economic scale, the proportion of coal generation, export orientation of the energy complex, industrialization level, energy efficiency, and final energy consumption structure. Each formed cluster required different priorities and approaches for adapting decarbonization strategies, namely: reduction of coal generation and modernization of networks for the largest emitters; reduction of emissions in mining and processing; CCUS and export diversification for resource economies; improvement of industrial energy efficiency and modernization of generation for industrial countries; elimination of residual emissions and accounting for imported carbon footprint for low-carbon economies. The limitations of the study were related to differences in national statistical reporting, incompleteness of some indicators, and sensitivity of clustering to the choice of variables. Conclusion. The proposed cluster approach makes it possible to move from ranking countries based on emissions to identifying groups with similar profiles of economic, demographic, energy, and climate indicators. The results of clustering can be used in further analysis of key emitting countries to identify the most suitable technologies and legislative measures for reducing greenhouse gas emissions. Additionally, the results can be used to assess the effectiveness of implementing and adapting decarbonization strategies.

• semanticscholar https://doi.org/10.23947/2541-9129-2026-10-3-206-218first seen 2026-09-13 05:09:16 · last seen 2026-09-21 05:07:30