Forecasting of hourly PM2.5 in south-west zone in Santiago de Chile

Abstract

© Taiwan Association for Aerosol Research. We present the results of a neural network model designed for the forecasting of hourly PM2.5 concentrations in Santiago, Chile. The study focuses on the observed values at two of the monitoring stations, which are located in the south-west zone of the city and are among the stations that register the highest concentrations during the period between April and August. This is the season when air quality is very often in ranges that are harmful to the population and some restrictions on emissions become useful. The forecasting model is a multilayer neural network. The input variables are observed values of hourly PM10 and PM2.5 concentrations measured at the station of interest and at a neighboring station at 7 PM of the present day and some observed and forecasted meteorological variables. NO2 concentrations during the morning and afternoon hours, which may be associated with secondary particle formation, are also used as input. The implemented