Uncovering the black box of public data: the contribution of open government data to air pollution control

Enhancing data elements to support environmental governance is a key initiative for promoting digital transformation and ecological development. This study constructs a quasi-natural experiment based on panel data of Chinese cities from 2010 to 2021, using the staggered rollout of open government data (OGD) platforms to evaluate their impact on air pollution (AP) and the underlying mechanisms. The results show that OGD significantly reduces annual average PM 2.5 concentrations by approximately 1.55 units (p < 0.01), indicating a notable improvement in air quality. Mechanism analysis suggests that government data disclosure affects AP through three pathways: enhancing environmental regulation, stimulating green innovation, and optimizing industrial structure. A one-unit increase in these mediating variables reduces PM 2.5 by approximately 0.02, 15.3, and 11.75 units, respectively (all p < 0.01). In addition, market size and market openness positively moderate the environmental effect of OGD. Heterogeneity analysis reveals regional variation. In Western China, OGD reduces PM 2.5 by about 5.61 units (p < 0.01); in Eastern China, the reduction is 1.11 units (p < 0.05), while the effect is not significant in Central China. In the Yangtze River Economic Zone, OGD leads to a reduction of 1.42 units (p < 0.01), and 1.3 units (p < 0.01) in the non-Yangtze region. These findings provide theoretical and empirical support for improving open data policies and leveraging data elements in environmental governance.