University of Ljubljana (Slovenia) and University of Turin (Italy) researchers investigated the mechanisms behind organic contaminant transformations in water. Their findings were published in the Journal of Chromatography A (1).
Contaminants of emerging concern (CECs) are chemicals, such as medicines and personal care products, that can linger after being used and be exposed to abiotic stressors, causing degradation; this can have detrimental effects on natural species, whether in terrestrial or aquatic environments (2).
In the upper layers of aquatic ecosystems, sunlight is a key factor in starting these processes, making aquatic photochemistry critical areas of study in environmental chemistry. Direct photolysis is the primary degradation pathway, but there are still significant knowledge gaps regarding matrix-dependent indirect photodegradation in complex water matrices, where numerous phenomena are still not fully understood. Indirect photodegradation can be a more significant route than direct photolysis, especially for contaminants in complex water matrices that lack chromophore moieties. This process is more mechanistically intricate and can cause multi-stage oxidations and even ring-opening reactions.
In this study, three understudied emerging contaminants were studied: pharmaceutical ramipril (RAM), artificial sweetener neotame (NEO), and herbicide cycloxydim (CYC). Laboratory simulations of natural photoinduced transformations were done to explore direct photolysis and titanium dioxide (TiO2) photocatalyzed process, followed by analysis with tandem high-resolution mass spectrometry (HRMS). The contaminants exhibited low-to-medium degrees of photolysis, but rapid dissipation under photocatalysis. Several analytical challenges were revealed by assessing transformation products (TPs), most notably in peak detection and data management. Structural elucidation of abundant TPs was done using multi-stage MS fragmentation studies, with transformation pathways being proposed based off identified structures, evolution profiles, and polarities.
Hydroxylation (a type of chemical transformation where OH functionality is introduced into organic substrates) was the most common transformation for all contaminants, though each displayed unique additional pathways (3). RAM went through intermolecular cyclization, forming a diketopiperazine-like TP, as well as ketone formation and cleavage into low molecular mass TPs. NEO experienced ester hydrolysis, reduction (resulting in C=C bond formation), and oxidative aromatic ring-opening reactions. Finally, CYC displayed (poly)hydroxylation or transformations of its oxime ether moiety, which underwent hydrolysis, detachment, or rearrangement, leading to oxazole TPs.
To predict the toxicities of specific TPs, Ecological Structure Activity Relationships (ECOSAR) software was used. This computerized predictive system estimates aquatic toxicity by investigating a chemical’s acute (short-term) toxicity and chronic (long-term or delayed) toxicity to aquatic organisms, using computerized Structure Activity Relationships (SARs) (4). In silicotoxicity prediction showed that the hydroxylated phenolic TPs of NEO and RAM, as well as certain oxazole TP isomers of CYC, can potentially increase overall toxicity during degradation.
Overall, this study showed the importance of understanding both the transformations of contaminants and the workflows needed to manage analytical challenges for enabling comprehensive analysis of the degradation process. The research focused on the environment fate of novel and under-researched water contaminants, with many TPs being observed for the first time. Altogether, significant amounts of novel findings were contributed to the field.
(1) Kravos, A.; Cristaudo, F.; Bello, F. D.; et al. Insight into Photocatalyzed Transformations of Multiclass Organic Contaminants in Water. J. Chromatogr. A 2025, 1752, 465971. DOI:
(2) Water Resources Mission Area. Emerging Contaminants. United States Geological Survey 2019.
(3) Hydroxylation. ScienceDirect 2022.
(4) Ecological Structure Activity Relationships (ECOSAR) Predictive Model. EPA 2024.
