Environmental quality and climate change have become hot topics among academics in all scientific fields in recent decades due to their impact on human health and economic development. Hence, this paper investigates the key factors of carbon dioxide emissions in India from 1970–2020 through the Bayer-Hanck test and Augmented ARDL framework on an augmented STIRPAT model, introducing uncertainty and globalization. We employ a set of unit-root tests and a combination of cointegration techniques (DOLS and FMOLS), which permit us to estimate the long-run and short-run relationships. Empirical findings confirmed that the series is I(1) series and there is the existence of a long-run relationship between our variables using three cointegration tests, meaning that the variables have the same behavior in the long run term. The findings revealed that India has an inverse U shape of the Environmental Kuznets curve (EKC) due to the positive association between GDP per capita and CO2 emissions until reaching a threshold, after which the link becomes inverse due to the negative impact of GDP square on CO2 emissions. Furthermore, the findings demonstrated a positive influence of uncertainty and a negative impact of globalization on long-term environmental degradation. Besides, energy consumption and population density are positively associated with CO2 emissions in the long and short run. We advocate for policies that promote more trade openness by entering new markets and cooperating with new trading partners.