Forecast of pollution by pm10 particulate material with time series - Guerrero Muñoz, Gabriela (2025)
This study aims to explain the temporal variation of PM10 particles in Quito's air quality, estimate future pollution risks, and minimize adverse health effects through the implementation of preventive measures. The research adopts a quantitative approach, focusing on data from the Quito Metropolitan Atmospheric Monitoring Network (REMMAQ) to predict PM10 pollution. The results indicate that the average particulate matter concentrations at each station for a year are acceptable based on homoscedasticity, stationarity, and normality models. The most suitable station is Guamaní, where particulate matter concentrations reach up to 38.8%. According to forecasts, air quality is considered good when it falls within the 0-50 range, where the health effects are acceptable. Guamaní consistently presents acceptable values in the range, The selected ARIMA (2, 1, 5) model, with an acceptable and appropriate fit, provides a robust alternative for managing air quality through PM10 particles using time series analysis. This study provides valuable information on air quality in Quito and the potential to address air pollution.