Identificação das fontes de poluição atmosférica na cidade de São Carlos-SP.

Abstract

The quality of the atmospheric air is of great importance for the health of the population. Among the quantifiable aspects of the air quality, one can find the particulate matter (PM) concentration in the atmosphere, whose fine (PM10) and ultra-fine (PM2.5) fractions have been extensively studied, as these particle size fractions are particularly damaging for the human health. The main objective of this work was the identification of emission sources of breathable particulate matter, as well as the quantification of their relative participation in the formation of the air pollution in São Carlos/SP, with the use of the reception model. The experiments used the dichotomous sampler for the collection of the particulate matter. Samples were taken in the receptor site, at the city center, in one year period. Also, the emission profiles of local sources (soil, vehicular emission, road dust re-suspension, sugar cane burning and vegetable burning) were measured. The mass concentration was obtained by weighing the sample filters before and after collection. The filter were then submitted to XRF analysis, and 14 chemical elements were quantified (Al, Si, P, S, Cl, K, Ca, Ti, Cr, Mn, Fe, Cu, Zn, Pb). Moreover, carbon detection was carried out by the DIC (dissolved inorganic carbon) and DOC (dissolved organic carbon) techniques. These values were fed to the EPA s CMB8 computer pack that calculates the relative contributions of the sources in the reception site. The results show the seasonal dependence of the sources in São Carlos, with the important presence of the vehicular emissions in the whole year. For the fine fraction, the contribution of the sugar cane burning was significant, in the dry season. In the ultra-fine fraction, an appreciable amount of secondary sulfur was found. The comparison between the source contributions calculated from the results of these work with those calculated utilizing data from the EPA´s SPECIATE library revealed very different profiles, confirming the importance of utilizing local sources in the modeling.