Functional analysis of variance of air pollution caused by fine particles

Abstract

Environmental pollution is harmful to human health, as it can lead to chronic respiratory diseases. In particular, fine particles suspended in the air (PM2.5) count among the most aggressive air pollutants. PM2.5 levels vary depending on local conditions. The goal of this work was to compare year-round airborne PM2.5 readings from three air quality surveillance stations in Cali (Colombia) to determine whether these show significant spatial and temporal variation. We subjected the obtained PM2.5 dataset to a functional analysis of variance. We observed that PM2.5 levels vary significantly among the three measurement sites on a temporal scale. Whereas in the morning hours PM2.5 levels among the three sites differed most, in the afternoon and evening hours, the corresponding PM2.5 levels were not significantly different.