Name: Elson Silva Galvão
Type: PhD thesis
Publication date: 30/08/2018

Name Rolesort ascending
Jane Meri Santos Advisor *

Examining board:

Name Rolesort ascending
Jane Meri Santos Advisor *

Summary: Epidemiological studies have shown the association of airborne particulate matter (PM) size and chemical composition with health problems affecting the cardiorespiratory and central nervous systems. Therefore, PM source identification is an important step in air quality management programs. Receptor models are frequently used for PM source apportionment studies to identify the contribution of local sources. Despite the benefits of using receptor models for air quality management, limitations such as collinearity effects in which sources have similar chemical profiles restrict their application or compromise the accurate separation of sources. For highly correlated sources, the identification of specific markers is still the best way for more accurate source apportionment. There are several works using different analytical techniques in PM chemical and physical characterization to supply information for source apportionment models. The choice among available techniques depends on: particles physical properties, sampling and measuring time, access to facilities and the costs associated to equipment acquisition, among other considerations. Despite the numerous analytical techniques described in the literature for PM characterization, laboratories are normally limited to in-house available techniques, which raises the question if a given technique is suitable for the purpose of a specific experimental work. In this work, the state of art on available technologies for PM characterization is stablished and a guide to choose the most appropriate technique(s) for a specific study is proposed. A new approach is also proposed to identify the most appropriated sources associated to the factors revealed by the Positive Matrix Factorization modelling by characterizing inorganic and organic chemical species and using pollutant roses. PM samples were collected in a coastal, urban/industrialized region in Brazil and analyzed by EDXRF, TD-GC-MS and TOC for the characterization of metals, PAHs, EC and OC. This region presents an atypical iron-rich atmosphere due to the presence of pelletizing and steelmaking industries. The proposed methodology revealed that consolidated markers for vehicular: elemental carbon (EC) and organic carbon (OC), sea salt: chloride (Cl) and sodium (Na), and industrial: iron (Fe) sources, were also associated to other sources. Cl, a typical marker of sea salt, was also attributed to industrial sintering activities. Some PMF factors showed high OC loadings, a typical marker for both vehicular exhaust and coal burning. The definition of the most appropriate source for those factors was only possible due to the assessment of the pollutant roses. Potassium (K), a usual marker of biomass burning, was predominantly associated to winds from an industrial park placed at Northeast of the sampling sites and, therefore, most likely associated to sintering emissions. Some PAHs such as naphtalene, chrysene, phenanthrene, fluorine and acenaphtylene were key markers allowing the apportionment of sources with similar inorganic chemical profiles, among them the industrial sintering, pelletizing and biomass burning. Results showed that combining both organic and inorganic chemical markers with pollutant roses for identification of the directionality of predominant sources improved the interpretation of PMF factor numbers in source apportionment studies.
In addition, the Resonant Synchrotron X-ray Diffraction (RSr-XRD) technique was conducted at the Laboratório Nacional de Luz Synchrotron (LNLS) in Campinas, Brazil, to analyze settleable particles (SP), total suspended particulate matter (TSP), PM10, and PM2.5 samples showing high levels of iron-based crystalline phases. In comparison to the use of chemical elemental species, the identification of the crystalline phases provided an enhanced approach to classify specific iron-based source markers. α-Fe2O3, metallic Fe, FeS2 and K2Fe2O4 are associated, respectively, to iron ore, pelletizing, and sintering; blast furnaces and steelmaking; coal deposits; and sintering emissions. The attribution of crystal rather than elemental composition in the identification of sources improved the accuracy of source apportionment studies. Compounds such as K2Fe2O4 and NH4ClO4 are specifically linked to the sintering process, mainly formed during raw materials furnace roasting. Uncommon sulfates crystals such as FeAl2(SO4)4.22H2O and (NH4)3Fe(SO4)3 present in the PM2.5 samples showed the high influence of α-Fe2O3 in the atmospheric photo-reduction of Fe into sulfates. Results also showed high influence of other sources than sea with a high Cl contribution, such as sintering and coke ovens. Therefore, we believe that the use of receptor models in tandem with source profiles defined by crystalline phases, elemental species, and organic compounds, such as the PAHs, can improve distinction of highly correlated sources.

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