Carbon intensity and policy uncertainties (EGPU, ESGUI & CPU) in sustainable development for China

Reducing carbon emissions is crucial for achieving sustainable development goals (SDGs). However, existing literature primarily examines carbon intensity through technical and economic factors, while the influence of policy and governance uncertainties is often overlooked. This research aims to examine the effects of three different uncertainty indicators—climate policy uncertainty (CPU), newly created sustainability uncertainty (ESGUI), and environmental governance policy uncertainty (EGPU) indices —and renewable energy generation (REN) on carbon intensity in the case of China. Fourier ARDL and Fourier Toda-Yamamoto methods are applied with quarterly data for 2015Q1–2023Q4. The findings reveal that EGPU increases carbon intensity, while CPU, ESGUI, and REN have a decreasing effect. The increasing impact of EGPU indicates that environmental policies may be rendered ineffective due to institutional weaknesses and implementation uncertainties. These results show that carbon intensity is directly related not only to energy policies but also to the quality of governance and the nature of policy uncertainties.