Monaldi Arch Chest Dis. 2026 Sep 16. doi: 10.4081/monaldi.2026.4216. Online ahead of print.
ABSTRACT
Air pollution is a major public health risk, contributing significantly to the global burden of chronic respiratory diseases. Chronic exposure to pollutants such as PM2.5, PM10, NO₂, and O₃ is associated with documented pathogenetic mechanisms, including oxidative stress, chronic inflammation, epithelial damage, and airway remodeling, which promote the development of respiratory diseases such as asthma, COPD, and cardiovascular disease. This review examines epidemiological data at the national and regional levels, focusing on Campania, one of the Italian regions most exposed to air pollution levels above the national average. Evidence shows a significant impact on the population's respiratory health, with socioeconomic inequalities amplifying the risks for the most vulnerable communities. Analysis of environmental, epidemiological, and pathophysiological data between 2015 and 2024 confirms that, despite a slight decrease in PM10 and PM2.5 concentrations nationwide, Campania continues to record high levels, with measurable impacts on respiratory health and significant intra-regional disparities. Artificial intelligence, through machine learning models and satellite-based forecasts, offers new opportunities for improving air quality monitoring and forecasting future trends. Furthermore, the adoption of environmental justice policies could effectively target interventions in high-risk areas. To reduce the impact of air pollution, the implementation of integrated strategies that combine environmental monitoring, health policies, and advanced predictive tools, supported by artificial intelligence, is crucial for targeted and timely intervention planning.
PMID:42750629 | DOI:10.4081/monaldi.2026.4216