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Polycyclic aromatic compounds (PACs) encompass a wide variety of organic analytes that have mutagenic and carcinogenic potentials for human health and are recalcitrant in the environment. Evaluating PACs levels in fuel (e.g., gasoline and diesel), food (e.g., grilled meat, fish, powdered milk, fruits, honey, and coffee) and environmental (e.g., industrial effluents, water, wastewater and marine organisms) samples are critical to determine the risk that these chemicals pose. Deep eutectic solvents (DES) have garnered significant attention in recent years as a green alternative to traditional organic solvents employed in sample preparation. DES are biodegradable, have low toxicities, ease of synthesis, low cost, and a remarkable ability to extract PACs. However, no comprehensive assessment of the use of DESs for extracting PACs from fuel, food and environmental samples has been performed. This review focused on research involving the utilization of DESs to extract PACs in matrices such as PAHs in environmental samples, NSO-HET in fuels, and bisphenols in foods. Chromatographic methods, such as gas chromatography (GC) and high-performance liquid chromatography (HPLC), were also revised, considering the sensibility to quantify these compound types. In addition, the characteristics of DES and advantages and limitations for PACs in the context of green analytical chemistry principles (GAC) and green profile based on metrics provide perspective and directions for future development.

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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.

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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.

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In this study, a green microscale solid-liquid extraction method using a miniaturized device combined with cleanup via dispersive micro-solid-phase extraction (MSLE-DµSPE) was developed for the determination by gas chromatography-quadrupole mass spectrometry (GC-MS) of n-alkanes in marine sediments. The main factors affecting the performance of this novel method were optimized using multivariate statistical tools. The MSLE-DµSPE method was validated considering the matrix-matched calibration, recovery, detection and quantification limits, ruggedness and accuracy. Under the optimum conditions, the method detection limits for n-alkanes ranged from 0.0051 to 0.0279 mg kg-1, and the quantification limits ranged from 0.0171 to 0.0930 mg kg-1. Correlation coefficients (R2) ≥0.99 were obtained for all compounds within the linear region (0.0025-0.200 mg L-1). The mean recovery for most n-alkanes ranged from 60.6 to 119%, with intraday and interday relative standard deviation (RSD) <20%. Evaluation of the MSLE-DµSPE method using Analytical Eco-Scale, Green Analytical Procedure (GAPI), and Analytical Greenness (AGREE) assessment metrics demonstrated the green potential of the developed method. Finally, the proposed method was successfully applied to marine sediment samples and the n-alkanes from C12 to C40 were detected with total concentrations in the range of 0.98-7.61 mg kg-1. This study represents the first application of a green microscale procedure to the analysis of n-alkanes in marine sediments.

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Schinus essential oils were tentatively identified by GC×GC/TOFMS, which revealed a greater number of compounds than previously reported. Eighty-six, seventy-two, and eighty-eight components were identified in Schinus lentiscifolius, Schinus molle and Schinus terebinthifolius essential oils, respectively. Compound separation due to 2 D selectivity was observed. Phytotoxic effects of Schinus essential oils were assessed on germination and initial growth of Arabidopsis thaliana. All essential oils in all tested quantities (5 µL, 10 µL, 15 µL, 20 µL, and 25 µL) affected germination rate, speed of accumulated germination, and root and shoot length of A. thaliana. Considering the mode of action of the essential oils, no differences were observed on expression of the genes ANP1 and CDK B1;1 in A. thaliana, which was analyzed by RT-qPCR. Results suggest that phytotoxic effects of Schinus essential oils seem to be explained by cellular damage rather than by induction of stress-inducible genes.

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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

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The present study compared the short-term effects of a diesel oil spill on the strucure and function of nematode and macrobenthic assemblages between tidal flats with different history of exposure to oil perturbation. A manipulative field experiment was conducted, where oil exposed treatments were contrasted with controls, during four successive times, two before and two after the oil spills. During the oil spill the death and the presence of diverse debilitated macrofaunal organisms were observed in the oil treatments. However, 24 h later no significant changes were identified, suggesting that the impacted plots were quickly recolonized. Nematode assemblages showed a decrease in overall density and an increase of r-strategist traits such as non-selective deposit feeders and colonizers at perturbed treatments from one of the historically non-perturbed tidal flats. We discuss the mechanisms responsible by distinctive patterns of response observed between the two benthic components.

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The present review reports, for the first time, various comprehensive two-dimensional gas chromatography (GC×GC) applications for different fossil fuel matrices (crude oil, heavy gas oil (HGO), light and middle distillates, coal and shale oil) for the determination of nitrogen-containing compounds. The focus is on the various types of detectors (universal and specific), and their applicability for the separation and speciation of nitrogen compounds (N-compounds) was evaluated. The capability of GC×GC to provide additional chemically specific information using different detector types, including a flame ionization detector (FID), a nitrogen chemiluminescence detector (NCD), a nitrogen-phosphorus (NPD) detector and detectors in combination with mass spectrometry (MS), is described. The coelutions (detection by MS) for various N-compounds, analytes and components of other classes, such as those that are oxygenates and hydrocarbons, are discussed.

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The present research is focused on the development of a flow-modulated comprehensive two-dimensional gas chromatography-triple quadrupole mass spectrometry (FM GC × GC-MS/MS) method for the determination of classes of aromatic organic sulphur compounds (benzothiophenes, dibenzothiophenes, and benzonaphthothiophene) in heavy gas oil (HGO). The MS/MS instrument was used to provide both full-scan and multiple-reaction-monitoring (MRM) data. Linear retention index (LRI) ranges were used to define the MRM windows for each chemical class. Calibration solutions (internal standard: 1-fluoronaphthalene) were prepared by using an HGO sample, depleted of S compounds. Calibration information was also derived for the thiophene class (along with MRM and LRI data), even though such constituents were not present in the HGO. Linearity was satisfactory over the analyzed concentration range (1-100 mg/L); intra-day precision for the lowest calibration point was always below 17%. Accuracy was also satisfactory, with a maximum percentage error of 3.5% (absolute value) found among the S classes subjected to (semi-)quantification. The highest limit of quantification was calculated to be 299 µg/L (for the C1-benzothiophene class), while the lowest was 21 µg/L (for the C4-benzothiophene class).

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Comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC×GC/TOFMS) has shown great skill in analyzing complex mixtures such as fossil fuels, especially for compounds at low concentrations. The analysis of N-polyaromatic compounds (NPAC) in coal and crude oil is a great challenge for analytical chemistry due to its environmental and technological importance, and also its diversity of concentration in the matrix. This study is the first report in the applicability of GC×GC/TOFMS for detection of NPAC in a coal tar sample with no fractionation. Normally these compounds are analyzed after sample treatment, making the process expensive and time consuming. However, the higher separation power of GC×GC/TOFMS, compared to 1D-GC, produces cleaner mass spectra in complex samples, which helps in identification of analytes with no pre-fractionation. In this paper, the main objectives were to demonstrate the applicability of GC×GC/TOFMS in the speciation and separation between basic and neutral NPAC from coal tar sample derived from fast pyrolysis, without prior sample fractionation. The methodology used here consisted of chromatographic injection of the diluted sample using a conventional columns set and data analysis by ChromaTOF/Excel™ software. Some basic compounds (pyridines and quinolines) and neutral ones (carbazoles and indoles) were detected with good chromatographic separation and spectral similarity. Tools like spectral deconvolution, extracted ion chromatogram (EIC) and dispersion graphics allowed greater security on the identification and separation of NPAC in this complex sample of coal tar, with no pre-treatment.

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This work studied fast pyrolysis as a way to use the residual fiber obtained from the shells of coconut ( Cocos nucifera L. var. Dwarf, from Aracaju, northeastern Brazil). The bio-oil produced by fast pyrolysis and the aqueous phase (formed during the pyrolysis) were characterized by GC/qMS and GC×GC/TOF-MS. Many oxygenated compounds such as phenols, aldehydes, and ketones were identified in the extracts obtained in both phases, with a high predominance of phenolic compounds, mainly alkylphenols. Eighty-one compounds were identified in the bio-oil and 42 in the aqueous phase using GC/qMS, and 95 and 68 in the same samples were identified by GC×GC/TOF-MS. The better performance of GC×GC/TOF-MS was due to the possibility of resolving some coeluted peaks in the one-dimension gas chromatography. Semiquantitative analysis of the samples verified that 59% of the area on the chromatogram of bio-oil is composed by phenols and 12% by aldehydes, mainly furfural. Using the same criterion, 77% of the organic compounds in the aqueous phase are phenols. Therefore, this preliminary assessment indicates that coconut fibers have the potential to be a cost-effective and promising alternative to obtain new products and minimize environmental impact.

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Separation of polycyclic aromatic sulfur heterocycles among themselves and also from interferents in petrochemical matrices is a challenging task because of their low concentration, matrix complexity, and also due to the presence of polyaromatic hydrocarbons, as they present similar physico-chemical properties. Therefore, the objective of this work was preparation, characterization, and application of a stationary phase for separation of these compounds in a heavy gas oil sample and their identification by comprehensive two-dimensional gas chromatography. The stationary phase was prepared by grafting mercaptopropyltrimethoxisilane onto a silica surface, followed by palladium(II) chloride immobilization. Elemental analysis, thermogravimetry, nitrogen adsorption-desorption isotherms, infrared analysis, and scanning electron microscopy were performed to characterize this solid phase. Sulfur compounds were separated in an open column packed with the stationary phase and analyzed by comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometric detection. The number of compounds tentatively identified was 314 and their classes were thiophenes, benzotiophenes, dibenzothiophenes, naphthothiophenes, benzonaphthothiophenes, and dinaphthothiophenes. Separation among sulfur compounds and polyaromatic hydrocarbons was successful, which is a difficult goal to achieve with the traditionally employed solid phases. Some recalcitrant compounds (dibenzothiophenes with substituents of two and four carbons) were fully separated and tentatively identified.

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The separation of the organic sulfur compounds (OSC) of petroleum or its heavy fractions is a critical step and is essential for the correct characterization of these compounds, especially due to similar physical and chemical properties of polycyclic aromatic sulfur heterocycles (PASH) and polycyclic aromatic hydrocarbons (PAH). This similarity results in coelutions among PAH and PASH and for this reason former steps of fractionation are required before gas chromatographic analysis. The objective of this study was to evaluate the potential of GC×GC for the separation and identification of OSC in a heavy gas oil sample without fractionation, after pre-fractionation in an alumina column and also after fractionation process. This last one was performed with a modified stationary phase manufactured and characterized in the laboratory, called Pd(II)-MPSG, where palladium is chemically linked to silica through mercaptopropyl groups. The fractions obtained from both procedures were analyzed by GC×GC/TOFMS, which was effective to separate and identify various classes of OSC. A hundred and thirty-five compounds were tentatively identified in the sample that was only pre-fractionated. However, when the fractionation was also performed with the Pd(II)-MPSG phase, a larger number of sulfur compounds were found (317). Results have shown that the analysis of a pre-fractionated sample by GC×GC/TOFMS is suitable when the goal is a general characterization of classes of compounds in the sample, while a more detailed analysis of PASH can be performed, using also the fractionation Pd(II)-MPSG phase. GC×GC/TOFMS played a major role in the comparison of samples obtained from pre-fractionation and fractionation steps due to its high peak capacity, selectivity, organized distribution of chromatographic peaks and resolution.

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The determination of organic sulfur compounds (OSC) in coal is of great interest. Technically and operationally these compounds are not easily removed and promote corrosion of equipment. Environmentally, the burning of sulfur compounds leads to the emission of SO(x) gases, which are major contributors to acid rain. Health-wise, it is well known that these compounds have mutagenic and carcinogenic properties. Bitumen can be extracted from coal by different techniques, and use of gas chromatography coupled to mass spectrometric detection enables identification of compounds present in coal extracts. The OSC from three different bitumens were tentatively identified by use of three different extraction techniques: accelerated solvent extraction (ASE), ultrasonic extraction (UE), and supercritical-fluid extraction (SFE). Results obtained from one-dimensional gas chromatography (1D GC) coupled to quadrupole mass spectrometric detection (GC-qMS) and from two-dimensional gas chromatography with time-of-flight mass spectrometric detection (GC × GC-TOFMS) were compared. By use of 2D GC, a greater number of OSC were found in ASE bitumen than in SFE and UE bitumens. No OSC were identified with 1D GC-qMS, although some benzothiophenes and dibenzothiophenes were detected by use of EIM and SIM modes. GC × GC-TOFMS applied to investigation of OSC in bitumens resulted in analytical improvement, as more OSC classes and compounds were identified (thiols, sulfides, thiophenes, naphthothiophenes, benzothiophenes, and benzonaphthothiophenes). The roof-tile effect was observed for OSC and PAH in all bitumens. Several co-elutions among analytes and with matrix interferents were solved by use of GC × GC.

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Coal is a non renewable fossil fuel, used mainly as a source of electrical energy and in the production of coke. It is subjected to thermal treatment, pyrolysis, which produces coke as a main product, in addition to a condensed liquid by-product, called tar. Tar is a complex mixture of organic compounds which contains different chemical classes, presenting aromatic and sulphur heterocyclic compounds. In general, identification of these compounds requires steps of isolation and fractionation, mainly due to co-elution of these compounds with polyaromatic hydrocarbons (PAH). The objective of this work is to characterize the sulphur compounds present in the coal tar obtained via pyrolysis, using comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry detector (GC×GC/TOFMS). Coal samples from the State of Paraná, Brazil were subjected to laboratorial scale pyrolysis. Several experimental conditions were tested, such as sample weight (5, 10 and 15g), heating ramp (10, 25 and 100°C/min) and final temperature (500, 700 and 900°C). Samples were analyzed by one dimensional gas chromatography (1D-GC) coupled to a quadrupole mass spectrometry detector (GC/qMS) and two-dimensional gas chromatography with time-of-flight mass spectrometry detector (GC×GC/TOFMS). The higher amount of sulphur compounds was obtained at a final temperature of 700°C and a heating ramp of 100°C/min. The main classes observed in the color plot were thiophenes, benzothiophenes and alkylated dibenzothiophenes. GC×GC/TOFMS allowed the identification of the greater number of compounds and the separation of several sulphur compounds from one another. Moreover, separation of sulphur compounds from polyaromatic hydrocarbons and phenols was achieved, which was not possible by 1D-GC. Comparing GC×GC/TOFMS and 1D-GC (SIM mode) also showed that 1D-GC, one of the most employed quantification tools for sulphur compounds, can be misleading for detection, identification and quantification, as the number of isomers of sulphur compounds found was greater than theoretically possible.

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