The Air Quality Data–Policy Gap: Institutional, Political, and Behavioral Barriers to Effective Decision-Making

Air pollution remains a critical public health and environmental challenge, despite significant advancements in monitoring technologies and the widespread availability of high-resolution air quality data. This study examines a persistent paradox: why improved data availability does not consistently translate into effective policy action. Adopting a qualitative synthesis approach, the research analyzes evidence from multiple Asian contexts, including China, India, Pakistan, and Southeast Asia, to investigate the structural factors shaping the data–policy relationship. The study develops a conceptual framework that positions air quality data as a necessary but insufficient condition for effective policymaking, emphasizing the mediating role of institutional, political, and behavioral factors. The findings reveal that fragmented governance structures, weak enforcement mechanisms, limited administrative capacity, and misaligned political incentives systematically constrain the translation of data into action. In several cases, data is underutilized, selectively interpreted, or overshadowed by short-term policy priorities and socioeconomic considerations. Additionally, trust deficits and limited technical expertise further weaken the effectiveness of data-driven decision-making processes. The analysis demonstrates that the gap between knowledge and action is fundamentally a governance challenge rather than a technical one. Addressing this gap requires a shift from data-centric approaches toward strengthening the institutional and political conditions under which data is interpreted and applied. The study contributes to the literature by advancing a theoretically grounded framework for understanding the data–policy gap and offers policy-relevant insights for improving air quality governance in complex, multi-level contexts. Beyond air quality governance, the findings have broader implications for climate policy implementation and green economy transitions, highlighting the importance of institutional capacity, governance coherence, and stakeholder trust in translating environmental data into effective policy action.