Greenhouse Gas Emission Clustering: Advancing Net Zero Goals through Data-Driven Analysis

This study analyzes greenhouse gas (GHG) emissions (carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O)) from 108 countries (1990–2020) using k-means clustering with a Dynamic Time Warping (DTW) metric, identifying high, medium, and low emission clusters based on total and per capita emissions. CO2, driven by fossil fuel use in energy, industry, and transportation, dominates emissions, with China and the U.S. accounting for 44% globally. Methane from agriculture and fossil fuel extraction disproportionately affects India, Brazil, and Turkmenistan, while N2O, linked to nitrogen-based fertilizers, shows high per capita contributions from Australia, New Zealand, and parts of Africa. Tailored mitigation strategies addressing regional and sector-specific drivers are critical, emphasizing energy transitions, sustainable agriculture, and land-use management. Clustering provides policymakers with a framework for targeted climate action, aligning emission profiles with solutions. Future research should focus on sectoral emissions, real-time monitoring, and mitigation impacts to advance global net-zero goals.