RESUMO
Quantitative nontarget analysis (qNTA) for liquid chromatography coupled to high-resolution mass spectrometry enables a more comprehensive assessment of environmental samples. Previous studies have shown that correlations between a compound's ionization efficiency and a range of molecular descriptors can predict the compound's concentration within a factor of 5. In this study, the qNTA approach was further improved by considering all mass adducts instead of only the protonated ion. The model was based on a quantitative structure-property relationship (QSPR), including 216 contaminants of emerging concern (CECs), of which 80 exhibited adduct formation that accounted for >10% of the total peak intensity. When all mass adducts were included, the test set coefficient of determination improved to Q2 = 0.855 compared to Q2 = 0.670 when only the protonated ions were considered (test set median RF error factor 1.6). The inclusion of all adducts was also important to transfer the RF QSPR model reliably. It was assumed that RF variations are sequence-dependent; therefore, a second QSPR model for the prediction of the transferability factor was built for each sequence. For validation, samples were analyzed up to two years apart. The median prediction fold change was 1.74 for analytical standards (63 compounds) and 2.4 for enriched wastewater effluent samples (41 compounds), with 80% of the compounds predicted within a fold change of 2.4 and 3.3, respectively. The model was also validated on a second instrument, where 80% of the 26 compounds in wastewater effluent were predicted within a factor of 3.8.
RESUMO
Due to adverse effects of Polycyclic Aromatic Hydrocarbons (PAHs) on human health, it is important to understand how airborne PAHs, are spatially distributed within urban areas. Moss has been shown to be a suitable material for biomonitoring of airborne PAH pollution. In this study, the moss Rhytidiadelphus squarrosus was sampled throughout Tórshavn, Faroe Islands. 53 Rhytidiadelphus squarrosus samples were extracted using a matrix solid-phase dispersive extraction method and analysed for 19 parent PAHs and six groups of alkylated PAHs using gas chromatography mass-spectrometry. All PAHs were quantified in at least one Rhytidiadelphus squarrosus sample, and the sum of the EPA 16 PAHs (Æ©PAHEPA16) ranged from 0.90 to 344 µg kg-1 dry weight. Higher concentrations were found close to the harbour and the main roads. The spatial correlation was investigated for the Æ©PAHEPA16, pyrene, fluoranthene, chrysene, benzo(e)pyrene, benzo(g,h,i)perylene, C1-phenanthrenes/C1-anthracenes, and C2-phenanthrenes/C2-anthracenes using variograms. The effective range of the spatial correlation was between 500 to 700 m of all PAHs. The evaluation of diagnostic ratios of fluoranthene to pyrene, and benzo(a)anthracene to chrysene suggest that different pollution sources affect urban areas of different types. To the best of our knowledge, this is the first time airborne PAH pollution patterns were mapped in an Arctic town, and the first time, Rhytidiadelphus squarrosus was used for tracing PAH pollution sources. Rhytidiadelphus squarrosus is suitable for biomonitoring and mapping PAH pollution within urban areas since it is widespread, and suitable for mapping PAHs.
Assuntos
Fenantrenos , Hidrocarbonetos Policíclicos Aromáticos , Humanos , Hidrocarbonetos Policíclicos Aromáticos/análise , Crisenos/análise , Pirenos/análise , Antracenos , Fenantrenos/análise , Monitoramento Ambiental/métodosRESUMO
This study aimed to investigate the spatial distribution of micropollutants in wastewater related to catchment area, and their environmental risks and fate. About 24-h flow proportional effluent (n = 26) wastewater samples were collected from eight WWTPs across Denmark. From five of these WWTPs corresponding influent samples (n = 20) were collected. Samples were enriched by multi-layer solid phase and analysed by liquid chromatography-high-resolution mass spectrometry and comprehensive two-dimensional gas chromatography with high-resolution mass spectrometry detection. We detected and quantified 79 micropollutants from a list of 291 micropollutants in at least one influent or effluent wastewater sample. From this we found that 54 micropollutants decreased in concentrations during wastewater treatment, while O-desmethylvenlafaxine, carbamazepine, amitriptyline, benzothiazole, terbutryn, and citalopram increased in concentrations through the WWTP.The toxicity of effluent wastewater samples was assessed by EC50 using Raphidocelis subcapitata (R. subcapitata) and LC50 using the crustacean Daphnia magna (D. Magna), for which six micropollutants were detected above the predicted no-effect concentration. Our study demonstrates that catchment area influences the micropollutant composition of wastewater. Out of 19 pharmaceuticals, the measured concentration in influent wastewater was predicted within a factor of 10 from sale numbers and human excretion, which demonstrates the strong influence of catchment area on micropollutant composition.
Assuntos
Águas Residuárias , Poluentes Químicos da Água , Humanos , Eliminação de Resíduos Líquidos/métodos , Poluentes Químicos da Água/análise , Monitoramento Ambiental , DinamarcaRESUMO
In this study, micropollutants in wastewater effluents were prioritized by monitoring the composition of influent and effluent wastewater by liquid chromatography - high-resolution mass spectrometry (LCHRMS) non-target screening (NTS) analysis. The study shows how important data pre-processing and filtering of raw data is to produce reliable NTS data for comparison of compounds between many samples (37 wastewater samples) analyzed at different times. Triplicate injections were critical for reducing the number of false-positive detections. Intensity drift corrections within and between batches analyzed months apart made peak intensities comparable across samples. Adjustment of the feature detection threshold was shown to be important, due to large intensity variations for low abundance compounds across batches. When the threshold correction cut-offs, or the filtering of relevant compounds by the occurrence frequency, were too stringent, a high number of false positive transformation products (TPs) were reported. We also showed that matrix effect correction by internal standards can over- or under-correct the intensity for unknown compounds, thus the TIC matrix effect correction was shown as an additional tool for a retention time dependent matrix effect correction. After these preprocessing and filtering steps, we identified 78 prioritized compounds, of which 36 were persistent compounds, defined as compounds with a reduction in peak intensity between influent and effluent wastewater <50%, and 13 compounds were defined as TPs because they occurred solely in the effluent samples. Some examples of persistent compounds are 1,3-diphenylguanidine, amisulpride and the human metabolites from losartan, verapamil and methadone. To our knowledge, nine of the identified TPs have not been previously described in effluent wastewater. The TPs were derived from metoprolol, fexofenadine, DEET and losartan. The screening of all identified compounds in effluent samples from eight wastewater treatment plants (WWTPs) showed that potential drugs of abuse, anti-psychotic and anti-depressant drugs were predominant in the capital city region, whereas the anti-epileptic agents and agricultural pesticides were dominant in more rural areas.