Eleni I. Panagopoulou

Micro-estuaries receive elevated loads of organic contaminants, yet the influence of water-column structure on their vertical distribution remains unclear. We investigated contaminant dynamics in three structurally distinct micro-estuaries during the dry season using monthly water-column and sediment sampling. Across 63 samples, 274 organic contaminants were detected. Contaminant mixtures shifted seasonally from runoff-to baseflow-dominated conditions, transitioning from pesticide-dominated profiles to more persistent industrial and effluent-derived compounds, including PFAS and sucralose. Water-column stratification strongly influenced contaminant partitioning: strongly stratified systems showed surface accumulation, while well-mixed systems exhibited uniform vertical distributions. Intermediate systems displayed partial segregation, reflecting intermittent mixing and prolonged deep-water residence times. Sediment–deep water distribution coefficients did not correlate with the sediment organic carbon content, suggesting that the dynamic estuarine conditions prevent steady-state sorption–desorption equilibrium. These findings demonstrate that stratification shapes contaminant persistence and biological exposure, underscoring the need for monitoring and risk assessments that incorporate vertical structure.

Reliable identification of contaminants in complex matrices remains hampered by low-abundance signals, complex spectra, and coeluting isobars in liquid chromatography–high-resolution mass spectrometry (LC-HRMS) analyses with data-independent acquisitions. Moreover, wide-scope target screening workflows covering hundreds to thousands of known compounds from reference standards analyses often fail to fully exploit the acquired data, leading to false positives and false negatives. Herein, trapped ion mobility spectrometry (TIMS) was integrated into LC-HRMS, and an enriched database and an analyte-specific framework were introduced for enhanced identification confidence. The database including 1948 contaminants incorporated all MS and MS/MS qualifier ions together with their CCS values and mobility filtering windows, alongside the principal ion. Specific qualifiers were designated as mandatory for the first time by evaluating their relative intensity compared to the principal ion (≥50%), with the established identification points systems being refined accordingly to increase confidence. Regarding TIMS data, ∼2500 CCS values were determined, exhibiting high repeatability (RSD ≤ 0.70%) and interinstrument reproducibility (|ΔCCS|≤ 2%). Comparison with literature data across different IMS-HRMS platforms showed CCS accuracy within 2% for 89% of the ions. In matrix spiking experiments (raptor’s eggs, human urine, wastewater), the cleaner mobility-filtered spectra resulted in improved selectivity for several contaminants’ qualifiers, which improved detection at low concentrations, minimizing false negatives. Additionally, both differentiation based on CCS values (e.g., atenolol–practolol) and mandatory detection of predefined qualifiers (e.g., prometryn–terbutryn) decreased false positives. By incorporating the TIMS dimension and mandatory qualifiers as additional identification information, this work provides a robust framework for high-throughput environmental monitoring and human exposure assessment.

Soil pollution poses a serious threat to terrestrial ecosystems and human health, yet studies often focus on a handful of pollutant classes per study. Wide-scope methodologies are necessary to account for the complexity and diversity of the soil matrix and the organic micropollutant mixture of both known and novel compounds it may contain. Thus, to facilitate comprehensive monitoring of the organic micropollutant burden in soil with gas chromatography coupled with high-resolution mass spectrometry (GC-HRMS), three wide-scope methods were developed and compared: modified QuEChERS (mQuEChERS), Accelerated Solvent Extraction (ASE), and Ultrasonic Assisted Extraction (UAE). Comparison of the three methods and the final choice of the modified QuEChERS were achieved via an examination of the performance characteristics, such as the number of analytes detected, recoveries, matrix effect, and precision, through a smart validation scheme that encompassed 38 analytes belonging to diverse pollutant classes. The mQuEChERS method was then fully validated for the simultaneous quantification of 75 analytes, including pesticides, polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), polychlorinated naphthalenes (PCNs), and organochlorine pesticides (OCPs). The method’s limits of detection (MLOD) ranged from 0.04 to 2.77 μg kg⁻¹ d.w. Linearity was demonstrated within a concentration range of 30 to 300 μg kg⁻¹ d.w. Recoveries ranged from 70 to 120%. Method precision was deemed optimal (RSD < 11%). As proof of concept, six soil samples from Greece were analyzed, with results indicative of potential temporal variations in pollutant concentration, underscoring the necessity for extensive monitoring campaigns employing GC-HRMS.

In this study, biochars (BC) from potato peel residuals were synthesized at 400, 600, and 800 °C, characterized, and evaluated for the persulfate-assisted oxidation of venlafaxine (VEN). BC pyrolyzed at 800 °C demonstrated the highest catalytic activity, resulting in the degradation of 750 μg/L of VEN in the presence of 500 mg/L persulfate in less than 90 min. Acidic conditions favored VEN destruction, while the apparent kinetic constant was reduced from 0.1136 at pH 3 to 0.0389 and 0.0352 min⁻¹ for pH 7 and 9, respectively. Interestingly, the presence of inorganic ions such as bicarbonates and chlorides, as well as humic acid, only slightly reduced process efficiency. Scavenging tests and electron paramagnetic resonance spectroscopy indicate a mixed mechanism dominated by non-radical pathways, with minor radical contributions, mediated by oxygenated surface functionalities of the 800 °C biochar. Five transformation products were identified through LC-HRMS suspect and non-target approaches, and a potential degradation pathway was proposed. Most of the identified transformation products exhibited lower toxicity levels than the parent compound. Finally, life cycle analysis revealed that, despite its superior kinetics, the 800 °C biochar carries the largest environmental footprint, underscoring the need for integrated assessments that jointly optimize removal performance and environmental impacts.

Searching for new and efficient transfer hydrogenation catalysts, a series of new organometallic ruthenium(II)-arene complexes of the formulae [Ru(η⁶-p-cymene)(L)Cl][PF₆] (1–8) and [Ru(η⁶-p-cymene)(L)Cl][Ru(η⁶-p-cymene)Cl₃] (9–11) were synthesized and fully characterized. These were prepared from the reaction of pyridine–quinoline and biquinoline-based ligands (L) with [Ru(η⁶-p-cymene)(μ-Cl)Cl]₂, in 1:2 and 1:1, metal (M) to ligand (L) molar ratios. Characterization includes a combination of spectroscopic methods (FT-IR, UV-Vis, multi nuclear NMR), elemental analysis and single-crystal X-ray crystallography. The pyridine–quinoline organic entities encountered, were prepared in high yield either via the thermal decarboxylation of the carboxylic acid congeners, namely 2,2′-pyridyl-quinoline-4-carboxylic acid (pqca), 8-methyl-2,2′-pyridyl-quinoline-4-carboxylic acid (8-Mepqca), 6′-methyl-2,2′-pyridyl-quinoline-4-carboxylic acid (6′-Mepqca) and 8,6′-dimethyl-2,2′-pyridyl-quinoline-4-carboxylic acid (8,6′-Me₂pqca), affording the desired ligands pq, 8-Mepq, 6′-Mepq and 8,6′-Me₂pq, or by the classical Friedländer condensation, to yield 4,6′-dimethyl-2,2′-pyridyl-quinoline (4,6′-Me₂pq) and 4-methyl-2,2′-pyridyl-quinoline (4-Mepq), respectively. The solid-state structures of complexes 1–4, 6, 8 and 9 were determined showing a distorted octahedral coordination geometry. The unit cell of 3 contains two independent molecules (Ru-3), (Ru′-3) in a 1:1 ratio, due to a slight rotation of the arene ring. All complexes catalyze the transfer hydrogenation of acetophenone, using 2-propanol as a hydrogen donor in the presence of KOiPr. Among them, complexes 1 and 5 bearing methyl groups at the 8 and 4 position of the quinoline moiety, convert acetophenone to 1-phenylethanol quantitatively, within approximately 10 min with final TOFs of 1600 h⁻¹. The catalytic performance of complexes 1–11, towards the transfer hydrogenation of p-substituted acetophenone derivatives and benzophenone, ranges from moderate to excellent. An inner-sphere mechanism has been suggested based on the detection of ruthenium(II) hydride species.

Searching for new and efficient transfer hydrogenation catalysts, a series of new organometallic ruthenium(II)-arene complexes of the formulae [Ru(η6-p-cymene)(L)Cl][PF6] (1–8) and [Ru(η6-p-cymene)(L)Cl][Ru(η6-p-cymene)Cl3] (9–11) were synthesized and fully characterized. These were prepared from the reaction of pyridine-quinoline and biquinoline-based ligands (L) with [Ru(η6-p-cymene)(μ-Cl)Cl]2, in 1:2 and 1:1, metal (M) to ligand (L) molar ratios. Characterization includes a combination of spectroscopic methods (FT-IR, UV-Vis, multi nuclear NMR), elemental analysis and single-crystal X-ray crystallography. The pyridine-quinoline organic entities encountered, were prepared in high yield either via the thermal decarboxylation of the carboxylic acid congeners, namely 2,2′-pyridyl-quinoline-4-carboxylic acid (pqca), 8-methyl-2,2′-pyridyl-quinoline-4-carboxylic acid (8-Mepqca), 6′-methyl-2,2′-pyridyl-quinoline-4-carboxylic acid (6′-Mepqca) and 8,6′-dimethyl-2,2′-pyridyl- quinoline-4-carboxylic acid (8,6′-Me2pqca), affording the desired ligands pq, 8-Mepq, 6′-Mepq and 8,6′-Me2pq, or by the classical Friedländer condensation, to yield 4,6′-dimethyl-2,2′-pyridyl-quinoline (4,6΄-Me2pq) and 4-methyl-2,2′-pyridyl-quinoline (4-Mepq) respectively. The solid-state structures of complexes 1–4, 6, 8 and 9 were determined showing a distorted octahedral coordination geometry. The unit cell of 3 contains two independent molecules (Ru-3), (Ru′-3) in a 1:1 ratio, due to a slight rotation of the arene ring. All complexes catalyze the transfer hydrogenation of acetophenone, using 2-propanol as a hydrogen donor in the presence of KΟiPr. Among them, complexes 1 and 5 bearing methyl groups at the 8 and 4 position of the quinoline moiety, convert acetophenone to 1-phenylethanol quantitatively, within approximately 10 minutes with final TOFs of 1600 h–1. The catalytic performance of complexes 1–11, towards the transfer hydrogenation of p-substituted acetophenone derivatives and benzophenone, ranges from moderate to excellent. An inner-sphere mechanism has been suggested based on the detection of ruthenium(II) hydride species.

Honey is a highly consumed commodity due to its potential health benefits upon certain consumption, resulting in a high market price. This fact indicates the need to protect honey from fraudulent acts by delivering comprehensive analytical methodologies. In this study, targeted, suspect and non-targeted metabolomic workflows were applied to identify botanical origin markers of Greek honey. Blossom honey samples (n = 62) and the unifloral fir (n = 10), oak (n = 24), pine (n = 39) and thyme (n = 34) honeys were analyzed using an ultra-high-performance liquid chromatography hybrid quadrupole time-of-flight mass spectrometry (UHPLC-q-TOF-MS) system. Several potential authenticity markers were revealed from the application of different metabolomic workflows. In detail, based on quantitative targeted analysis, three blossom honey markers were found, namely, galangin, pinocembrin and chrysin, while gallic acid concentration was found to be significantly higher in oak honey. Using suspect screening workflow, 12 additional bioactive compounds were identified and semi-quantified, achieving comprehensive metabolomic honey characterization. Lastly, by combining non-targeted screening with advanced chemometrics, it was possible to discriminate thyme from blossom honey and develop binary discriminatory models with high predictive power. In conclusion, a holistic approach to assessing the botanical origin of Greek honey is presented, highlighting the complementarity of the three applied metabolomic approaches.