Spatial–temporal evolution, drivers, and pathways of the synergistic effects of digital transformation on pollution and carbon reduction in heavily polluting enterprises

Under the "dual carbon" goals, heavily polluting enterprises face dual pressures to reduce both pollution and carbon emissions, necessitating the urgent exploration of effective pathways for coordinated emission reductions. This study investigates the potential of digital transformation in enterprises to achieve synergistic emission reductions. First, the entropy method is employed to measure enterprise digitalization and pollutant levels, and the spatial-temporal evolution characteristics of regional coordinated emission reductions are analyzed. Subsequently, using panel data from heavily polluting enterprises in the Yangtze River Economic Belt, the study examines the impact of digital transformation on pollution and carbon reduction, its underlying mechanisms, and the moderating effects of environmental policies on these relationships. Robustness tests confirm the synergy between carbon and pollution emissions. The findings reveal that digital transformation contributes to the synergistic reduction of carbon and pollutant emissions in enterprises, primarily through two pathways: the coordinated integration of internal innovation resources and the collaborative engagement in external innovation networks. Furthermore, air pollution control policies and low-carbon city initiatives significantly enhance the synergistic emission reduction effects of digitalization. Interestingly, heavily polluting enterprises located in the downstream regions of the Yangtze River, those with smaller operational scales, or those facing strong financing constraints, demonstrate more pronounced synergistic emission reduction effects through digital transformation. Based on these conclusions, we recommend that governments focus on strengthening either "pollution reduction" or "carbon reduction" policies, as either alone can yield dual emission reduction benefits. Additionally, tailoring regional emission reduction policies to local conditions can maximize economic and environmental benefits.