The social dimension of air quality community work: a core complement to green and digital skills

Community-engaged air quality research increasingly requires environmental, digital and social competences, yet skill classifications make social competences less visible than green and digital skills. This study was conducted to clarify the integrated competence profile needed for community-based air quality work and to assess whether the European Skills, Competences, Qualifications and Occupations taxonomy (ESCO) adequately represents that profile. It asks: (1) Which green, digital and social skills appear as emerging, episodic, expanding core and established core skills in community-based air quality work? and (2) Which gaps in existing skill classifications become visible when this work is analysed through ESCO? We analysed 169 full-text articles published from 2015 to 2025 on air quality or air pollution projects involving public, citizen or community engagement. Action-oriented sentences were extracted through a reproducible text-mining workflow and mapped to ESCO using sentence-embedding similarity. Yearly skill frequencies were then used to classify skills by temporal consistency and growth. Results show that expanding core green skills combine air quality management, pollution-prevention advice and behaviour-change functions. Expanding core digital skills support sensing, mapping, research data management and visual communication. Social skills expand around citizen participation, inclusion, community outreach, participatory research and science–policy mediation. The corpus is predominantly participatory and social rather than narrowly technical, indicating that community air quality work depends on relational competences that help make green and digital interventions trusted, meaningful and actionable. The analysis also identifies limits in ESCO: social skills are not organised as a dedicated category comparable to green and digital skills, and AI-related actions are insufficiently described for specialised air quality methods. We argue that skill taxonomies should better represent social, hybrid digital–social and AI-related competences in environmental practice.