Multi-criteria decision-making techniques associated with (Q)SAR risk assessment for ranking surface water microcontaminants identified using LC-QTOF MS.

Contaminants of emerging concern (CECs) have been a focus of study for years, with investigations revealing the contamination of different environmental matrices (surface water, soil, air, and sediment) by diverse classes of microcontaminants. Understanding the contamination profiles requires identification and risk assessment of the microcontaminants. In the present work, analysis was made of the presence of 3250 compounds in 27 samples from the Conceição River (Rio Grande do Sul State, Brazil), using an SPE-LC-QTOF MS method. In total, 150 microcontaminants (confirmed and suspected) of different classes, especially pesticides and pharmaceuticals, were identified by an initial qualitative analysis. Subsequently, in silico predictions of eight endpoints, using quantitative structure-activity relationship ((Q)SAR) models, were employed to determine the risk of each previously screened microcontaminant. This large amount of (Q)SAR data, frequently with conflicting information in relation to the responses of the different endpoints, makes it difficult to define which microcontaminants should be prioritized for analysis. Therefore, in order to rank the identified microcontaminants by risk assessment, two multi-criteria decision-making (MCDM) ranking techniques (ToxPi and TOPSIS), associated with a weighting method, were performed to establish the order of priority for further quantitative analysis of the most hazardous microcontaminants. The two rankings were statistically similar, especially for the 20 highest priority microcontaminants. Nonetheless, sensitivity tests carried out for the ToxPi and TOPSIS outputs showed higher performance robustness of TOPSIS, compared to ToxPi. This is the first time that such an approach (screening/(Q)SAR/MCDM methods) has been performed in the context of microcontaminant environmental risk evaluation and demonstrated to be an available strategy to help rank the most concern microcontaminants identified in aqueous environment samples.

Proposal of a new, fast, cheap, and easy method using DLLME for extraction and preconcentration of diazepam and its transformation products generated by a solar photo-Fenton process.

This work evaluated the formation of transformation products (TPs) during the degradation of diazepam (DZP) by a solar photo-Fenton process. Six TPs were identified, three of them for the first time. After elucidation of the TPs, a new, cheap, fast, and easy method was employed to extract and preconcentrate DZP and its TPs, using dispersive liquid-liquid microextraction (DLLME). The method was optimized using factorial and Doehlert designs, with the best results obtained using acetonitrile as disperser solvent and chloroform as extraction solvent, with volumes of 1000 and 650 µL, respectively. When DZP degradation was performed in ultrapure water, the extraction/preconcentration of DZP and its TPs by DLLME was very similar to the results obtained using a traditional SPE method. However, when hospital wastewater was used as the matrix, more limited extraction efficiency was obtained using DLLME, compared to SPE. Meanwhile, all the TPs extracted by SPE were also extracted by the DLLME technique. Furthermore, DLLME was much less expensive than SPE, besides being faster, easier, and requiring only small amounts of organic solvents. This work reports a new and very important tool for the extraction and preconcentration of TPs formed during degradation using techniques such as advanced oxidation processes (AOPs), since without this step it would not be possible to identify all the TPs formed in some complex wastewater matrices.

Investigation of pharmaceuticals and their metabolites in Brazilian hospital wastewater by LC-QTOF MS screening combined with a preliminary exposure and in silico risk assessment.

This work evaluates the occurrence of pharmaceuticals, with special emphasis on their metabolites, in raw hospital wastewater (HWW) using wide-scope screening based on liquid chromatography coupled to high resolution mass spectrometry. The applied strategy uses an extended purpose-built database, containing >1000 pharmaceuticals and 250 metabolites. Raw HWW samples from a hospital located in south Brazil were collected over six months, with a monthly sampling frequency. Accurate-mass full-spectrum data provided by quadrupole-time of flight MS allowed the identification of 43 pharmaceuticals and up to 31 metabolites in the samples under study. Additionally, other four metabolites not included in the initial database could be identified using a complementary strategy based on the common fragmentation pathway between the parent compound and its metabolites. Nine metabolites derived from four pharmaceuticals were identified in the raw HWW samples, whereas their parent compounds were not found in these samples. The results of this work illustrate the importance of including not only parent pharmaceuticals but also their main metabolites in screening analysis. Besides, the inclusion of in silico QSAR predictions allowed assessing the environmental fate and effect of pharmaceuticals and metabolites in terms of biodegradability, as possible Persistent, Bioaccumulative and Toxic (PBT) compounds, and their potential hazard to the aquatic environment.

Degradation of pharmaceuticals in different water matrices by a solar homo/heterogeneous photo-Fenton process over modified alginate spheres.

A solar homo/heterogeneous photo-Fenton process using five materials (Fe(II), Fe(III), mining waste, Fe(II)/mining waste, and Fe(III)/mining waste) supported on sodium alginate was used as a strategy to iron dosage for the degradation of eight pharmaceuticals in three different water matrices (distilled water, simulated wastewater, and hospital wastewater). Experiments were carried out in a photoreactor with a capacity of 1 L, using 3 g of iron-alginate spheres and an initial hydrogen peroxide concentration of 25 mg L-1, at pH 5.0. All the materials prepared were characterized by different techniques. The Fe(III)-alginate spheres presented the best pharmaceutical degradation after a treatment time of 116 min. Nineteen transformation products generated during the solar photo-Fenton process were identified by liquid chromatography coupled to quadrupole time-of-flight mass spectrometry, using a purpose-built database developed for detecting these transformation products. Finally, the transformation products identified were classified according to their toxicity and predicted biodegradability.