Synergistic governance efficiency of industrial pollution and CO₂ emissions under the digital economy

Using panel data for 284 Chinese cities, this study explores the nonlinear relationship between the digital economy and the synergistic governance efficiency of industrial pollution and CO₂ emissions (SGEIPCE). The study also investigates the transmission mechanism of two-way knowledge flows within this relationship using the double fixed effect model and two-stage least square method. The results show that the digital economy has a significant U-shaped relationship on the SGEIPCE: the impact first decreases and then increases. When the level of digital economy exceeds infection point, the SGEIPCE increases. The marginal effect identified through the heterogeneity analysis indicates that Chinese cities with high innovative talent agglomeration and low industrial Internet level are the first to cross the inflection point of the U-shaped relationship, and the promoting effect of the digital economy on the SGEIPCE is greater in these two types of cites. Further, when the digital economy crosses the inflection point, it indirectly improves the SGEIPCE by increasing the level of knowledge absorption and knowledge overflow. Knowledge overflow is the most critical transmission mechanism by which China's digital economy affects SGEIPCE. These results provide empirical support and a decision-making basis for promoting the mutually beneficial cooperation between digital economy and industrial synergistic governance.