<p>Air pollution represents a major global concern with significant repercussions on public well-being, health, and environmental quality. Mitigating air pollution is necessary for ensuring sustainable ecosystems. This study aims to identify, analyse, and develop a hierarchical structural model to map mitigation enablers for overcoming air pollution. It employs a mixed-method approach utilising thematic analysis (qualitative) with in-depth interviews to identify key mitigation enablers. These themes were subsequently validated and expanded through an extensive literature review and consultations with a panel of experts. The identified enablers were then utilised to construct an Interpretive Structural Modelling (ISM) model (quantitative), facilitating a deeper understanding of their interrelationships and hierarchies. The result identifies political support as the foundational driver influencing all enablers, followed by stringent regulatory measures that steer economic and technological measures. Mid-level variables, such as economic, technological, and environmental interventions, mutually reinforce one another in driving systemic change. Socio-behavioural factors emerge as the most dependent outcomes, reflecting how public engagement ultimately consolidates the effectiveness of pollution mitigation. This empirical research integrates both qualitative insights and expert validation with quantitative modelling, offering a comprehensive and nuanced perspective on mitigation strategies that lay the groundwork for informed interventions and sustainable solutions. It is written to appeal to a broad interdisciplinary audience concerned with sustainability, human–environment interaction, and policy-making.</p>