ORIGINAL RESEARCH article
Front. Environ. Sci.
Sec. Environmental Policy and Governance
Volume 13 - 2025 | doi: 10.3389/fenvs.2025.1580362
This article is part of the Research TopicAdvancing Carbon Reduction and Pollution Control Policies Management: Theoretical, Application, and Future ImpactsView all 38 articles
Uncovering the black box of public data: the contribution of open government data to air pollution control
Provisionally accepted
- Minzu University of China, Beijing, Beijing Municipality, China
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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 PM2.5 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 oneunit increase in these mediating variables reduces PM2.5 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 PM2.5 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.
Keywords: Open government data, Air Pollution, Mechanism analysis, Regional heterogeneity, Difference-in-differences
Received: 20 Feb 2025; Accepted: 30 Apr 2025.
Copyright: © 2025 Zhou, Wang and Han. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Ruotong Wang, Minzu University of China, Beijing, 100081, Beijing Municipality, China
Mingyang Han, Minzu University of China, Beijing, 100081, Beijing Municipality, China
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