An extensive investigation, aimed to study the fine fraction of airborne particulate matter (FAPM) in the Mexico City Metropolitan Area (MCMA), started in 2003, after the FAPM sampling network of the Environmental Secretariat of the Federal District Government (Secretaría del Medio Ambiente del Gobierno del Distrito Federal, SMA-GDF) was put into operation. Formerly, several research institutions in Mexico, in collaboration with the local government, made continuous efforts during the last two decades, in order to improve air quality in the MCMA. Samples have been collected using US-EPA designated samplers, following the same agency protocols. In this study, 922 samples were analyzed by PIXE in order to determine the elemental concentrations (ng/m3) of the FAPM. The samples were collected every three days by the Atmospheric Sampling Network (Red Automática de Monitoreo Atmosférico, RAMA) of the SMA-GDF, starting by the end of 2003 and along 2004 on three sites, and during the whole 2005 to the beginning of 2006 in seven stations, taking samples every six days during this last stage. The sample collection has continued up to date at the latter pace. The results obtained have allowed determining the sulfur (S) spatial distribution over the area, showing a reasonable uniformity in space, but well marked time variability. The S spatial distribution has also showed similar patterns between equivalent seasons from year to year, although not a strict periodicity. Compared to other elements found consistently in the samples, S is mainly distributed over the area by a large amount of mobile (mainly transportation) sources, fairly distributed over it, while other elements come from fixed sources located at industrial or urban areas. Comparisons were also made among the sampling sites, and among the three climatic seasons (drycold, dry-hot and rain) from year to year. Correlations between temporal variations of pairs of sampling sites were also calculated for S and other elements, in order to support these conclusions.
COAST: COntrollable Arbitrary-Sampling NeTwork for Compressive Sensing
