Pontificia Universidad Católica de Chile Pontificia Universidad Católica de Chile
Jorquera H. and Barraza F. (2012)

Source apportionment of ambient PM2.5 in Santiago, Chile: 1999 and 2004 results. http://dx.doi.org/10.1016/j.scitotenv.2012.07.049

Revista : Science of the Total Environment
Volumen : 435-436
Páginas : 418-429
Tipo de publicación : ISI Ir a publicación


A receptor model analysis has been applied to ambient PM2.5 measurements taken at Santiago, Chile (33.5°S,70.7°W) in 2004 (117 samples) and in 1999 (95 samples) on a receptor site on the eastern side of the city. For both campaigns, six sources have been identified at Santiago and their contributions in 1999/2004 are: motor vehicles: 28±2.5/31.2±3.4%, wood burning: 24.8±2.3/28.9±3.3%, sulfates: 8.8±1.7/16.2±2.5%, marine aerosol: 3±2.1/9.9±1.5%, copper smelters: 1.5±1.4/9.7±3.3% and soil dust: 3.9±1.5/4.0±2.4%. Hence relative contributions are statistically the same but the absolute contributions have been reduced because ambient PM2.5 has decreased from 34.2 to 25.1 μg/m3 between 1999 and 2004 at Santiago. Similarity of results for both data sets — analyzed with different techniques at different laboratory facilities — shows that the analysis performed here is robust. Source identification was carried out by inspection of key species in source profiles, seasonality of source contributions, comparison with published source profiles and by looking at wind trajectories computed using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) from USA’s National Oceanic and Atmospheric Administration (NOAA); for the wood burning sources the MODIS burned area daily product was used to confirm wildfire events along the year. Using this combined methodology we have shown conclusively that: a) marine air masses do reach Santiago’s basin in significant amounts but combined with anthropogenic sources; b) all copper smelters surrounding Santiago — and perhaps coal-fired power plants as well — contribute to ambient PM2.5; c) wood burning is the second largest source, coming from residential wood burning in fall and winter and from regional wildfires in spring and summer.The results of the present analysis can be used to improve emission inventories, air quality forecasting systems and cost–benefit analyses at local and regional scales.