The emerging issue of carbon dioxide (CO2) emissions is highly affecting global sustainable and economic development endeavors. Countries with high population growth, rapid industrialization, and significant energy needs find themselves in this bracket. This study, based on data from 1960 to 2018, evaluates carbon emissions using principal component analysis (PCA). The findings indicate that two leading principal components (C.1 and C.2) had the greatest impact as they accounted for seventy-seven percent (77%) of the total variance. The eigenvalues of both components were greater than one, signifying their significance. C.1 shows a strong connection for CO2 emissions, total population, and production of electric energy through various sources. C.2 is more connected to the growth of industries. The scree plot confirms this by finding them to be dominant. This emphasizes the interaction between electricity production, specifically from coal, and the demographic data. The results highlight how PCA can be utilized to distinguish drivers that cause the emission of carbon to provide an understanding that might be used in managing the environment and setting relevant policies.
Qureshi et al. (Thu,) studied this question.
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