This study explores the complex relationship between pollution sources and human development over a 30-year timespan, to yield comparative results between ‘high’ and ‘low’ level pollution emission countries. The four independent variables used in this study is namely, GHG emissions, air pollution, water pollution, and urbanization. The dependent variable applied is the three key components of Human Development Index (HDI), GNI per capita, education, and life expectancy. A panel data of 34 countries, where stratification is performed to divide the countries accordingly into groups of 17 ‘high’ and 17 ‘low’ emissions polluting countries. Multivariate multiple regression analysis and Toda- Yamamoto Causative Analysis were used to generate results to answer the developed research questions and hypothesis.
The revealed outcomes found that GHG emissions, air pollution, and urbanization is positively associated to the HDI components for ‘high’ polluting countries, whereas water pollution is negatively associated. Alternatively, all the environmental factors (GHG emissions, air pollution, water pollution) are negatively associated to the HDI components for ‘low’ polluting countries, whereas urbanization is positively associated. The findings reinforced our theoretical idea on Environmental Kuznets Curve and Public Goods Theory, underscoring the complex yet imperative dynamics between pollution and human development on different polluting level countries. Nonetheless, this study provides a foundation for understanding pollution's impact on human development and informs sustainable policymaking
