Can extreme rainfall associated with landslides affect air quality? A case study in a coastal city (São Sebastião, São Paulo State, Brazil)

Abstract This study investigated the impact of an extreme precipitation event and the subsequent landslides that occurred in São Sebastião municipality (São Paulo State, Brazil) in February 2023 on particulate matter (PM 10 and PM 2.5 ) concentration. Hourly air quality and meteorological data from December 2021 to February 2025 were analyzed. The methodology combined cluster analysis (CA) using the k -means algorithm to classify meteorological patterns and the Openair package for spatio-temporal assessment. CA identified a specific group of days associated with anomalous behavior during the extreme event. Analyses using bivariate polar plots and variation in time plots revealed that, while intense rainfall initially promoted wet scavenging of pollutants, the post-landslide period was characterized by a 124% increase in PM 10 concentrations and a 93.3% increase in PM 2.5 concentrations. Two additional high precipitation events were examined for comparison, showing that PM also decreased during intense rainfall, while the post-rainfall recovery differed among events. These results indicate that the February 2023 increase cannot be explained by landslide occurrence alone and may have reflected the combined influence of meteorological conditions, changes in local activities, and potential particle resuspension . Overall, the findings highlight the importance of adequate monitoring networks in place for understanding the secondary environmental effects of extreme rainfall and disaster events in vulnerable coastal areas.