Polycyclic aromatic sulfur heterocycles (PASHs), such as benzothiophenes (BT), dibenzothiophenes (DBT) and benzonapthothiophenes (BNT), can be emitted from vehicular traffic and deposited in fine particles matter (PM2.5). The presence of these compounds in PM2.5 is an environmental concern due to air pollution and its toxic properties. In this study, a green microscale solid-liquid extraction method was developed to determine twenty-three PASHs in PM2.5. A simplex-centroid mixture design was applied to optimize the extraction solvent. A full factorial design was used for preliminary evaluation of the factors that influence the extraction process (extraction time, sample size, and solvent volume) and then a Doehlert design for the significant parameters. The optimal extraction conditions based on the experimental design were: sample size, 4.15 cm2; 450 μL of toluene:dichloromethane (80:20,v/v); and extraction duration, 24 min. High sensitivity (LOD < 0.66pg m-3 and LOQ < 2.21 pg m-3) and acceptable recovery (82.8-120 %), and precision (RSD 3.6-14.0 %) were obtained. The greenness of the method was demonstrated using the Analytical GREEnness (AGREE) tool. The method was applied for analyzing PASHs in PM2.5 samples collected in three time intervals per day from years with different sulfur contents in the diesel: S-500 (≤500 ppm sulfur) and S-50 (≤50 ppm sulfur). Fourteen PASHs were quantified with the highest concentrations observed for 2,8-DMDBT and 4,6-DMDBT, which are recalcitrant compounds. The ANOVA test indicated significant differences between sampling periods during the day. The reduction of diesel S-500 to S-50 corresponded to a 28 % decrease in the total sum of PASHs (∑PASHs) evaluated. Spearman's rank correlations allowed for verifying that BTs and DBTs were highly correlated, suggesting that they were derived from similar sources. A weak correlation of 2,1-BNT and 2,3-BNT with BTs and DBTs indicates that these compounds are a chemical proxy for the emission of diesel engines during the combustion process.
Keywords: Green extraction; Optimization method; PASH; Particulate matter; Urban emission.
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