资源环境科技发展态势分析平台

Sao Paulo in Brazil has relatively relaxed regulations for ambient air pollution standards and often experiences high air pollution levels due to emissions of particulate pollutants from local sources and long-range transport of air masses impacted by biomass burning. In order to evaluate the sources of particulate air pollution and related health risks, a year-round sampling was done at the University of Sao Paulo campus (20ma.g.l.), a green area near an important expressway. The sampling was performed for PM2. 5 (<= 2: 5 mu m) and PM10 (<= 10 mu m) in 2014 through intensive (everyday sampling in wintertime) and extensive campaigns (once a week for the whole year) with 24 h of sampling. This year was characterized by having lower average precipitation compared to meteorological data, and high-pollution episodes were observed all year round, with a significant increase in pollution level in the intensive campaign, which was performed during wintertime. Different chemical constituents, such as carbonaceous species, polycyclic aromatic hydrocarbons (PAHs) and derivatives, water-soluble ions, and biomass burning tracers were identified in order to evaluate health risks and to apportion sources. The species such as PAHs, inorganic and organic ions, and monosaccharides were determined using chromatographic techniques and carbonaceous species using thermal-optical analysis. Trace elements were determined using inductively coupled plasma mass spectrometry. The risks associated with particulate matter exposure based on PAH concentrations were also assessed, along with indexes such as the benzo[a] pyrene equivalent (BaPE) and lung cancer risk (LCR). High BaPE and LCR were observed in most of the samples, rising to critical values in the wintertime. Also, biomass burning tracers and PAHs were higher in this season, while secondarily formed ions presented low variation throughout the year. Meanwhile, vehicular tracer species were also higher in the intensive campaign, suggesting the influence of lower dispersion conditions in that period. Source apportionment was performed using positive matrix factorization (PMF), which indicated five different factors: road dust, industrial emissions, vehicular exhaust, biomass burning and secondary processes. The results highlighted the contribution of vehicular emissions and the significant input from biomass combustion in wintertime, suggesting that most of the particulate matter is due to local sources, in addition to the influence of pre-harvest sugarcane burning.