In developing economies, there is a lack of certainty in energy and environmental economic policy. In contrast, research into the interplay between population, economic growth (GDP), renewable energy, nuclear energy, fossil fuels, and greenhouse gas (GHG) emissions has received comparatively little attention. Thus, the main motive of this exploration is to analyze the influence of population, economic growth, and various energy sources consumption on the selected South Asian economy's GHG emissions using the STIRPAT model. The period 1972–2021 is used to estimate results by considering cross-sectional dependence (CSD) and slope homogeneity (SH) tests, as well as second-generation unit root and cointegration tests. Due to the presence of SH, CSD, and mixed-order unit root problems, the cross-sectional autoregressive distributive lag (CS-ARDL) model has been used to estimate the value of selected variables. The impact of GDP and population is positive but insignificant for South Asian countries in the short run, but GDP is significant in the long run. The research also revealed that burning fossil fuels significantly contributes to atmospheric gas emissions level. In addition, renewable and nuclear energy play useful and substantial roles in reducing pollution in South Asian countries. Therefore, it is recommended that the economies of the South Asian countries maintain a uniform approach to economic policy to fully benefit from the advantages of increased green and safe energy production.