The impact of renewable energy product trade on carbon emission spatial correlation: An analysis based on the complex network method

As global economic recovery faces severe headwinds and carbon reduction pressures, renewable energy products play a vital role in cutting carbon emissions. With deepening economic integration, the carbon emission spatial correlation has increased substantially. This study explores the structural characteristics of the renewable energy product trade network and the carbon emission spatial correlation network, and analyzes the relationship between them using an exponential random graph model. Results show that the renewable energy product trade network is characterized by high density and agglomeration, whereas the carbon emission spatial correlation network is characterized by low density and agglomeration. Renewable energy product trade increases the carbon emission spatial correlation and widens the carbon emission gap between economies. Therefore, the achievement of global low-carbon goals requires not only reasonably adjusting energy structures but also strengthening the construction of renewable energy product trade networks, promoting the efficient flow and sharing of renewable energy among various economies, facilitating the dissemination and application of relevant low-carbon technologies, and thus forming a synergistic force for carbon emission reduction.