ANOVA Funcional para evaluar la contaminación de PM2.5 en diferentes estaciones de monitoreo de Lima en el periodo 2023

Abstract

This study addresses the evaluation of PM2.5 pollution in Lima through the application of Functional ANOVA, with the objective of identifying significant differences in PM2.5 functional data measured at different monitoring stations in the city of Lima. Using collected air quality data, temporal trends and spatial variability of PM2.5 pollution were analyzed to highlight critical areas and suggest specific environmental management strategies. The results indicate significant differences in air quality in Lima, highlighting the importance of implementing mitigation policies tailored to local characteristics. This advanced statistical approach provides an effective tool for environmental assessment, allowing a better understanding of pollution problems and facilitating evidence-based decision making for the protection of public health and the environment. This work underscores the need for continuous monitoring and detailed studies to inform regulatory actions and environmental conservation initiatives aimed at improving air quality and health in urban areas.