Episodic air quality degradation due to particles occurs in multiple cities in central and southern Chile during the austral winter reaching levels up to 300-800 mu g/m(3) hourly PM2.5, which can be associated with severe effects on human health. An air quality prediction system is developed to predict such events in near real time up to 3days in advance for nine cities with regular air quality monitoring: Santiago, Rancagua, Curico, Talca, Chillan, Los angeles, Temuco, Valdivia, and Osorno. The system uses the Weather Research and Forecasting with Chemistry model configured with a nested 2km grid-spacing domain to predict weather and inert tracers. The tracers are converted to hourly PM2.5 concentrations using an observationally based calibration which is substantially less computationally intensive than a full chemistry model. The conversion takes into account processes occurring in these cities, including higher likelihood of episode occurrence during weekends and during colder days, the latter related to increased wood-burning-stove activity for heating. The system is calibrated and evaluated for April-August 2014 where it has an overall skill of 53-72% of episodes accurately forecasted (61-76% for the best initialization) which is better than persistence for most stations. Forecasts one, two, and three days in advance all have skill in forecasting events but often present large variability within them due to different meteorological initializations. The system is being implemented in Chile to assist authority decisions not only to warn the population but also to take contingency-based emission restrictions to try to avoid severe pollution events.