Global carbon dioxide (CO2) emissions reached a record high of over 37 billion tonnes in 2023. Identifying the specific drivers behind this environmental impact is essential for informed, data-driven decision-making. This study utilizes the STIRPAT framework to evaluate the complex correlations between CO2 emissions and four variables: total population, urbanization, gross domestic product (GDP), and the human development index (HDI). The research methodology involves a statistical analysis conducted with JMP® software, examining a dataset spanning 143 countries from 1990 to 2022 through four distinct sensitivity analyses (Studies A--D). A unique aspect of this research is the application of HDI as an affluence factor, offering a broader measure of socioeconomic well-being compared to traditional GDP-focused models. Findings demonstrate that GDP, HDI, population and urbanization significantly impact emissions, though their influence varies based on how nations are grouped. Study A emerged as the most robust model for capturing cross-national variation. These results emphasize the importance of tailored national strategies and suggest that countries can benefit from adopting strategies that have proven effective in reducing CO2 emissions in comparable contexts, particularly considering the challenging climate targets set for the coming years.
Prado et al. (Wed,) studied this question.