From Growth to Green: The Complex Interplay of Renewables, Forest Land Management and Trade on GHG Emissions

ABSTRACT Due to severe climate challenges, global economies are transitioning to green energy, specifically, the solar thermal and wind energy to attain the COP28 targets and sustainable development goals (SDGs). To fulfill energy demand, countries are investing in these sources, yet their role in the global greenhouse gas (GHG) emissions is not clearly examined. The objective of this research is to examine the linear and nonlinear implications of solar thermal and wind energy on global GHG emissions. Employing the extended STIRPAT model, this study further considers the role of forest land management, economic growth, foreign trade, and urbanization over the period 1990Q1–2021Q4. The autoregressive distributed lag model has been used to address the mixed integration order variables. The empirical results indicate that both linear and nonlinear solar thermal, forest land resources, and wind energy significantly reduce GHG emissions in the short‐ and long‐run. The influence of nonlinear solar and wind energy is stronger than their linear terms. Additionally, the forest areas are significantly correlated with the decreased emissions level. On the other hand, the environmental Kuznets curve hypothesis is valid as economic growth boosts emissions in the short run while diminishing it in the long run. In contrast, the results reveal that urbanization and international trade are the leading drivers of global GHG emissions. Based on the findings, this study recommends promoting renewable energy investment, forest conservation incentives, and carbon‐border adjustments.