Uncovering transformation products of four organic contaminants of concern by photodegradation experiments and analysis of real samples from a local river

Toxicological and environmental risks of enalapril and their possible transformation products generated under phototransformation reactions

Pharmaceutical active compounds (PACs) in the concentration range of hundreds of ng/L to μg/L have been identified in urban surface water, groundwater, and agricultural land where they cause various health risks. These pollutants are classified as emerging and cannot be efficiently removed by conventional wastewater treatment processes. The use of nano-enabled photocatalysts in the removal of pharmaceuticals in aquatic systems has recently received research attention owing to their enhanced properties and effectiveness. In the current study, toxicological and environmental risks of enalapril (ENL) and their possible transformation products (TPs) generated under phototransformation processes (e.g., photolysis and photocatalysis reactions) were assessed. In photolysis reaction, removal of ENL was incomplete (< 16 %), while mineralization degree was negligible. In contrast, total removal of ENL was achieved through the photocatalytic process and its maximum mineralization ratio was 66 % by using natural radiation. Proposed transformation pathways during the phototransformation of ENL include hydroxylation and fragmentation reactions generating transformation products (TPs) such as hydroxylated TPs (m/z 393) and enalaprilat (m/z 349). Potential environmental risks for aquatic organisms were not observed in the concentrations of both ENL and enalaprilat contained in surface water. However, the acute and chronic toxicities prediction of TPs such as m/z 409, 363, and 345 showed toxic effects on aquatic organisms. Thus, more studies regarding TPs monitoring for both ENL and PhACs with the highest occurrence worldwide are necessary for the creation of a database of the concentrations contained in surface water and groundwater for the assessment of the potential environmental risk for aquatic organisms.

Identifying organic micropollutants' transformation products from the soil dissipation experiment by non-targeted high-resolution mass spectrometry approach: Can we gain more than transformation product identity?

Risk assessment of environmental hazards originating from xenobiotics extensively used worldwide (e.g., pharmaceuticals, bisphenols, or preservatives) requires a combined study of their effects, mobility, dissipation mechanisms, and subsequent transformation product identification and evaluation. We have developed an efficient accelerated solvent extraction method for a broad range of micropollutants of variable physical-chemical properties in soils to enable more accurate hazard characterisation. Micropollutant recoveries from freeze-dried soils were 60-120%, with the exception of atorvastatin, fexofenadine, and telmisartan, which had reduced recoveries (40-66%). The observed matrix effect ranged from -26% to 17% and was corrected by the matrix matching standard for quantitative analysis. The method allows sensitive and reliable determination of a wide range of analytes in soil samples and, consequently, qualitative analysis of transformation products (TP) with variable physicochemical properties. We identified TPs of five compounds (venlafaxine, telmisartan, valsartan, atorvastatin, and sertraline) by applying suspect and non-targeted data analyses. To our knowledge, the transformation product of atorvastatin was reported for the first time. All others were found in soil or other matrices. Valsartan (formed valsartan acid) and atorvastatin (transformed probably by oxidative decarboxylation of beta, delta dihydroxy heptanoic acid chain to propionic acid) were modified to a relatively large extent. All other compounds identified were only hydroxylated (sertraline and telmisartan) or demethylated (venlafaxine). We estimated the stability and presence of the identified TPs based on the constructed time trends and the ratio between TP formation and degradation rates. We demonstrated how valuable a non-targeted approach can be for complex evaluation of the fate and effect of soil pollutants.

Identifying congeners and transformation products of organic contaminants within complex chemical mixtures in impacted surface waters with a top-down non-targeted screening workflow

Over 350,000 compounds are registered for production and use including a high number of congeners found in complex chemical mixtures (CCMs). With such a high number of chemicals being released in the environment and degraded into transformation products (TPs), the challenge of identifying contaminants by non-targeted screening (NTS) is massive. "Bottom-up" studies, where compounds are subjected to conditions simulating environmental degradation to identify new TPs, are time consuming and cannot be relied upon to study the TPs of hundreds of thousands of compounds. Therefore, the development of "top-down" workflows, where the structural elucidation of unknown compounds is carried directly on the sample, is of interest. In this study, a top-down NTS workflow was developed using molecular networking and clustering (MNC). A total of 438 compounds were identified including 176 congeners of consumer product additives and 106 TPs. Reference standards were used to confirm the identification of 53 contaminants among them lesser-known pharmaceuticals (aliskiren, sitagliptin) and consumer product additives (lauramidopropyl betaine, 2,2,4-trimethyl-1,2-dihydroquinoline). The MNC tools allowed to group similar TPs and congeners together. As such, several previously unknown TPs of pesticides (metolachlor) and pharmaceuticals (gliclazide, irbesartan) were identified as tentative candidates or probable structures. Moreover, some congeners that had no entry on global repositories (PubChem, ChemSpider) were identified as probable structures. The workflow worked efficiently with oligomers containing ethylene oxide moieties, and with TPs structurally related to their parent compounds. The top-down approach shown in this study addresses several issues with the identification of congeners of industrial compounds from CCMs. Furthermore, it allows elucidating the structure of TPs directly from samples without relying on bottom-up studies under conditions discussed herein. The top-down workflow and the MNC tools show great potential for data mining and retrospective analysis of previous NTS studies.