ABSTRACT Climate change and rising global temperatures are significantly affecting energy consumption patterns and carbon emissions. This study directly contributes to the United Nations Sustainable Development Goals (SDGs), particularly SDG 13 (Climate Action), SDG 7 (Affordable and Clean Energy), and SDG 12 (Responsible Consumption and Production). This study investigates the relationship between temperature and energy‐related emissions from coal, diesel, electricity, and natural gas using panel data from eight Chinese provinces covering the period 1990–2022. Advanced econometric techniques including Panel Autoregressive Distributed Lag (ARDL), Panel Generalized Method of Moments (GMM), Panel Least Squares (PLS), and Panel Quantile Regression (PQR) are employed to analyze the temperature‐emission dynamics. The ARDL long‐term results indicate a significant and positive relationship between temperature and electricity‐driven emissions, while a negative association is observed for coal‐ and diesel‐driven emissions. However, natural gas‐driven emissions exhibit more complex behavior, showing a negative long‐term relationship with temperature but a positive short‐term effect. The ARDL findings are consistent with the results obtained from GMM, PLS, and PQR models, and this consistency strengthens the reliability and robustness of the results. The findings suggest that although fossil fuel consumption is a major driver of rising temperatures, temperature alone does not lead to immediate changes in energy consumption patterns. The study underscores the need for robust policy measures aimed at promoting energy efficiency, accelerating the transition to renewable energy, and developing climate‐resilient energy systems to mitigate the impact of rising global temperatures on energy demand and emissions.
Ahmad et al. (Wed,) studied this question.