Renewable energy utilization, green finance and agricultural land expansion in China

Greenhouse gas (GHG) emissions, notably carbon dioxide (CO2), are causing anthropogenic global warming, posing severe dangers to the climate, economy, and environment. The dynamic effects of economic development, Renewable Energy (RE) use, green finance, and agricultural production development on CO2 emissions in China are investigated in this study. The ARDL (Auto-regressive distributed lag) bounds testing strategy was used to test series data from 1990 to 2020, supplemented by the DOLS (Dynamic Ordinary Least Squares) method. The results of the DOLS estimate demonstrate that the macroeconomic factor is positively and significantly related to CO2 emission, implying that a 1% rise in business development is associated with a 1.64 percent increase in CO2. Furthermore, the ratio of RE usage is harmful and substantial, meaning that boosting green finance use by 1% reduces CO2 emissions by 0.25 (0.26) percent over time. Moreover, the projected long-run correlation of farmland is positive and statistically significant, indicating that a 1% increase in farm production is associated with a 0.14 (0.15) percent rise in CO2 emissions in the long run. Industrial development and farmland expansion raise Carbon intensity. However, research shows that greater use of renewable energy and green finance will reduce China's carbon emissions and improve environmental protection. Different estimation techniques, including FMOLS (Fully Modified Ordinary Least Squares) and CCR (Canonical Cointegrating Regression), provide similar findings in DOLS. To accomplish a reduction in CO2 emissions and protect the environment, this research provides policy ideas to support renewable energy usage and weather patterns farming toward a low-carbon economy.