Quantification of polycyclic aromatic sulfur heterocycles in fine airborne urban particles (PM2.5) after multivariate optimization of a green procedure

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.

Multivariate optimization of a green procedure for determination of emerging polycyclic aromatic nitrogen heterocycles in PM2.5 from sites with different characteristics

Emerging polycyclic aromatic nitrogen heterocycles (PANHs) contributes significantly to the health risk associated with inhaling polluted air. However, there is a lack of analytical methods with the needed performance to their determination. This study presents the optimization and validation for the first time of a green microscale extraction procedure for the determination of twenty-one PANHs, including carbazole, indole, and quinolone classes, in particulate matter (PM2.5) samples by gas chromatography-mass spectrometry. A simplex-centroid mixture design and full factorial design (23) were employed to optimize the following extraction parameters: type and volume of solvent, sample size, extraction time, and necessity of a cleanup step. Low limits of detection and quantification (LOD < 0.97 pg m-3 and LOQ < 3.24 pg m-3, respectively) were obtained in terms of matrix-matched calibration. The accuracy and precision of the method were adequate, with recoveries in three levels between 73 to 120% and intraday and interday relative standard deviations from 2.0 to 12.9% and 7.3 to 18.9%, respectively. The green character of the method was evaluated using the Analytical Greenness (AGREE) tool, where a score of 0.69 was obtained, indicating a great green procedure. The method was applied to PM2.5 samples collected from sites with different characteristics; the concentrations ranged from 69.3 pg m-3 (2-methylcarbazole) to 11,874 pg m-3 (carbazole) for individual PANHs and from 2306 to 24,530 pg m-3 for ∑21PANHs. Principal component analysis (PCA) and hierarchical clustering enabled discrimination of the sampling sites according to the PANHs concentrations. The score plots formed two distinct groups, one with samples containing higher concentrations of PANHs, corresponding to sites with a major influence from diesel emissions, and another group with minor PANH contents, corresponding to sites impacted by emissions from urban traffic and industrial activities.

Microscale extraction combined with gas chromatography/mass spectrometry for the simultaneous determination of polycyclic aromatic hydrocarbons and polycyclic aromatic sulfur heterocycles in marine sediments

This paper describes a novel method based on an ultrasound-assisted extraction microscale device (UAE-MSD) for the rapid and simultaneous determination of polycyclic aromatic hydrocarbons (PAH) and polycyclic aromatic sulfur heterocycles (PASH) in marine sediments. Solvent extraction conditions were optimized by applying a simplex-centroid mixture design. Optimum conditions were used to validate and determine the concentrations of 17 PAH and 7 PASH. The best conditions were obtained by extracting sediments with 500 µL of DCM:MeOH (65:35, v:v) over 23 min of sonication. Analytes were determined by gas chromatography/mass spectrometry in selective ion monitoring (GC-MS/SIM). Matrix effects were evaluated, and matrix-matched calibration was used for quantitation. Analytical method validation was carried out using the certified reference material NIST SRM 1941b, as well as sediment spiked with PASH at three concentration levels. Recoveries ranged between 70.0 ± 3.5% and 119 ± 9.1% for PAH and 80.6 ± 10.4% and 120 ± 10% for PASH. Linearity (R²) was ≥0.99 for all compounds. Method detection limits ranged from 8.8 to 30.2 ng g^-1, while limits of quantification ranged from 29.4 to 1011 ng g^-1. UAE-MSD was applied to marine sediments exposed to different anthropogenic impacts collected in Todos os Santos Bay, Brazil. PAH concentrations ranged from <LOQ to 667 ng g^-1, while PASH levels were <LOQ to 1152 ng g^-1. Dibenzothiophene was the compound presented in the highest concentration in all samples, with values up to 249 ng g^-1. The results indicated contributions of pyrogenic sources from all compounds. The developed method can potentially be applied to extract trace levels of compounds in different solid matrices to minimize extraction time and solvent consumption.