Mathematics, Год журнала: 2024, Номер 12(16), С. 2591 - 2591

Опубликована: Авг. 22, 2024

This paper identifies patterns in total and per capita CO2 emissions among 208 countries considering different emission sources, such as cement, flaring, gas, oil, coal. research uses linear non-linear dimensional reduction techniques, combining K-means clustering with principal component analysis (PCA) t-distributed stochastic neighbor embedding (t-SNE), which allows the identification of distinct profiles nations. approach effective heterogeneous despite highly nature data. The optimal number clusters is determined using Calinski–Harabasz Davies–Bouldin scores, five six for emissions, respectively. findings reveal that t-SNE brings together world’s largest economies emitters, i.e., China, USA, India, Russia, into a single cluster, while PCA provides country Russia. Regarding generates cluster only one country, Qatar, due to its significant flaring byproduct oil industry, low population. study concludes international collaboration coherent global policies are crucial effectively addressing developing targeted climate change mitigation strategies.

Язык: Английский