Integrating indoor/outdoor air quality monitoring and biomarker-based surveillance may improve risk assessment and support more effective protection of airport workers, while advanced predictive tools, including AI-based exposure modelling, represent a promising direction that still requires dedicated validation.
Abstract
(1) Background: Airports workers are exposed to a mixture of airborne pollutants generated by aircraft operations, ground support equipment, road traffic, and indoor microenvironments. Indoor air quality, influenced by outdoor pollutant and ventilation dynamics, represents an important, but overlooked determinant of occupational exposure. Fine and ultrafine particulate matter (PM) can induce oxidative stress, inflammation, and xenobiotic responses, affecting not only the respiratory system, but also other organs. (2) Methods: This review examines the health effects of occupational exposure among airport workers, with emphasis on indoor air pollution besides aircraft engine emissions. Studies addressing exposure characterization, biological effects, biomarkers, and risk management strategies were critically evaluated. (3) Results: Occupational exposure is driven by both combustion-derived pollutants and indoor–outdoor air exchange processes. Ultrafine particles, black carbon, polycyclic aromatic hydrocarbons, and trace metals contribute to oxidative stress, inflammatory responses, and xenobiotic pathway activation. Monitoring indoor microclimatic parameters, including temperature, atmospheric pressure, and humidity, may facilitate the identification of event-related deterioration in indoor air quality. (4) Conclusions: Indoor air pollution should be recognized as a key component of airport occupational exposure. Integrating indoor/outdoor air quality monitoring and biomarker-based surveillance may improve risk assessment and support more effective protection of airport workers, while advanced predictive tools, including AI-based exposure modelling, represent a promising direction that still requires dedicated validation.
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