Tracing water-soluble, persistent substances in the Black Sea

Transport and dispersion of PFOA and PFOS in the Black Sea

A 3-D transport and dispersion model was applied to study the recent past and future dynamics of perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) concentrations in the Black Sea for the 2016-2030 period. The modelled surface concentrations show a distinct seasonal behaviour, shaped by winter to spring convective mixing. A significant increasing long-term trend in PFOS concentrations is established, with concentrations in water layers 200 m below the surface increasing at 4-8% per year. Driving mechanisms for PFOA and PFOS transport and accumulation in the subsurface and deeper layers are the cooling of the surface water in winter and the transport of water masses from the North Western Shelf (NWS) of the Black Sea. A simulated 50% phase-out of PFOA and PFOS from 2020 to 2030 shows a 21% reduction in PFOA, while PFOS continues to increase.

Biodegradation characteristics and mechanism of terbuthylazine by the newly isolated Agrobacterium rhizogenes strain AT13

Terbuthylazine (TBA) is an emerging environmental contaminant that poses moderate to high risk to non-target organisms. In this study, a newly TBA-degrading strain, Agrobacterium rhizogenes AT13, was isolated. This bacterium degraded 98.7% of TBA (100 mg/L) within 39 h. Based on the six detected metabolites, three novel pathways of strain AT13, including dealkylation, deamination-hydroxylation, and ring-opening reactions, were proposed. The risk assessment demonstrated that most degradation products might be substantially less harmful than TBA. Whole-genome sequencing and RT-qPCR analysis revealed that ttzA, which encodes S-adenosylhomocysteine deaminase (TtzA), is closely related to TBA degradation in AT13. Recombinant TtzA showed 75.3% degradation of 50 mg/L of TBA within 13 h and presented a K_m value of 0.299 mmol/L and a V_max value of 0.041 mmol/L/min. The molecular docking results indicated that the binding energy of TtzA to TBA was -32.9 kcal/mol and TtzA residue ASP161 formed two hydrogen bonds with TBA at distances of 2.23 and 1.80 Å. Moreover, AT13 efficiently degraded TBA in water and soil. Overall, this study provides a foundation for the characterization and mechanism of TBA biodegradation and may enhance our understanding of the TBA biodegradation by microbes.

Multiple machine learning algorithms assisted QSPR models for aqueous solubility: Comprehensive assessment with CRITIC-TOPSIS

As an essential environmental property, the aqueous solubility quantifies the hydrophobicity of a compound. It could be further utilized to evaluate the ecological risk and toxicity of organic pollutants. Concerned about the proliferation of organic contaminants in water and the associated technical burden, researchers have developed QSPR models to predict aqueous solubility. However, there are no standard procedures or best practices on how to comprehensively evaluate models. Hence, the CRITIC-TOPSIS comprehensive assessment method was first-ever proposed according to a variety of statistical parameters in the environmental model research field. 39 models based on 13 ML algorithms (belonged to 4 tribes) and 3 descriptor screening methods, were developed to calculate aqueous solubility values (log K_ws) for organic chemicals reliably and verify the effectiveness of the comprehensive assessment method. The evaluations were carried out for exhibiting better predictive accuracy and external competitiveness of the MLR-1, XGB-1, DNN-1, and kNN-1 models in contrast to other prediction models in each tribe. Further, XGB model based on SRM (XGB-1, C = 0.599) was selected as an optimal pathway for prediction of aqueous solubility. We hope that the proposed comprehensive evaluation approach could act as a promising tool for selecting the optimum environmental property prediction methods.