This paper aims to investigate the effects of urbanization on pollutant emissions and energy intensity in selected Asian developing countries after controlling for the effects of disaggregated (renewable and non-renewable) energy consumption, trade liberalization, and economic growth. We use both linear and nonlinear panel data econometric techniques and employ recently introduced mean group estimation methods, allowing for heterogeneity and cross-sectional dependence. However, to check the robustness of our panel results, we also apply the autoregressive distributed lag (ARDL)-bound testing approach to country-level data. In addition, the relationship between affluence and CO 2 emissions is examined in the context of the Environmental Kuznets Curve (EKC) hypothesis. The estimation results identify the population, affluence, and non-renewable energy consumption as major factors in pollutant emissions in Asian countries. However, the results of the EKC hypothesis show that when countries achieve a certain level of economic growth, their emissions tend to decline. Whereas nonlinear results show that renewable energy, urbanization, and trade liberalization reduce emissions, linear estimations do not confirm these outcomes. Thus, substitution of non-renewable for renewable energy consumption, cautious and planned urbanization programs and more liberal trading regimes may be viable options for sustainable growth of these developing Asian economies.