Because of the high levels of pollution that Santiago de Chile experiences every year in winter, the government has set up an air quality monitoring network. Information from this network is employed to alert people about the quality of air and to enforce several control strategies in order to limit pollution levels. The monitoring network has 8 stations that measure PM10, carbon monoxide (CO), sulphur dioxide (SO2), ozone (O3) and meteorological parameters. Some stations also measure nitrogen mono- and dioxide (NOx), fine particles (PM2.5) and carbon. In this study we have examined the PM10and O3data generated by this network in the year 2000 in order to determine the seasonal trends and spatial distribution of these pollutants over a year's period. The results show that concentration levels vary with the season, with PM10being higher in winter and O3in summer. All but one station, show a peak in PM10at 8:00 indicating that during the rush hour there is a strong influence from traffic, however, this influence is not seen during the rest of the day. In winter, the PM10maximum occurs at 24:00 h in all stations but Las Condes. This maximum is related to decreased wind speed and lower altitude of the inversion layer. The fact that Las Condes station is at a higher altitude than the others and it does not show the PM10increase at night, suggest that the height of the inversion layer occurs at lower altitude. Cluster analysis was applied to the PM10 and O3data, and the results indicate that the city has four large sectors with similar pollution behavior. The fact that both pollutants have similar distribution is a strong indication that the concentration levels are primarily determined by the topographical and meteorological characteristics of the area and that pollution generated over the city is redistributed in four large areas that have similar meteorological and topographical conditions. © 2006.
Gramsch, E., Cereceda-Balic, F., Oyola, P., & von Baer, D. (2006). Examination of pollution trends in Santiago de Chile with cluster analysis of PM<inf>10</inf>and Ozone data. Atmospheric Environment, 5464-5475. https://doi.org/10.1016/j.atmosenv.2006.03.062