Recognition of the molecular characterization and mechanisms of heterogeneously formed organic pollutants from metallurgical industries by FT-ICR-MS and GC/Q-TOF-MS

Toward a comprehensive understanding of alicyclic compounds: Bio-effects perspective and deep learning approach

The escalating use of alicyclic compounds in modern industrial production has led to a rapid increase of these substances in the environment, posing significant health hazards. Addressing this challenge necessitates a comprehensive understanding of these compounds, which can be achieved through the deep learning approach. Graph neural networks (GNN) known for its' extraordinary ability to process graph data with rich relationships, have been employed in various molecular prediction tasks. In this study, alicyclic molecules screened from PCBA, Toxcast and Tox21 are made as general bioactivity and biological targets' activity prediction datasets. GNN-based models are trained on the two datasets, while the Attentive FP and PAGTN achieve best performance individually. In addition, alicyclic carbon atoms make the greatest contribution to biological activity, which indicate that the alicycle structures have significant impact on the carbon atoms' contribution. Moreover, there are terrific number of active molecules in other public datasets, indicates that alicyclic compounds deserve more attention in POPs control. This study uncovered deeper structural-activity relationships within these compounds, offering new perspectives and methodologies for academic research in the field.

Overlooked impacts of natural organic matter conversion in a Fe(II)-induced peroxymonosulfate activation system for river water remediation

The peroxymonosulfate (PMS) process may be hindered severely due to natural organic matter (NOM) conversion in the treatment of emerging pollutants from river water, becoming a critical engineering and technical issue. In this study, a Fe(II)-induced river water (RW)/PMS catalytic system was constructed for investigating molecular transformation of NOM and related influence mechanism to sulfamethoxazole (SMX) degradation. Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) analysis indicated that NOM molecules containing no more than one heteroatom in river may be attacked by hydroxyl radicals (OH) and then polymerized, converting into molecules with two or three heteroatoms during PMS oxidation. Based on the correlation analysis, CHONP-NOM, CHOSP-NOM and CHONSP-NOM showed a significant inhibition against SMX degradation, while CHONS-NOM exhibited a moderate inhibitory effect. Besides, more condensed aromatic structures, carbohydrates and tannins were generated via reactive species (OH and sulfate radicals (SO₄^-)) oxidation, radical addition and polymerization reactions. Notably, condensed aromatic structures, carbohydrates and tannins presented weak, modest and strong inhibition to SMX degradation, respectively. Based on the current results, the inhibition of target pollutants degradation would be mitigated via regulation of NOM molecules in a Fe(II)-induced PMS activation system, providing valuable information to reduce NOM impact. In addition, this study paves the way to achieve efficient removal of emerging pollutants from river water.

Molecular insights towards changing behaviors of organic matter in a full-scale water treatment plant using FTICR-MS

The changing behavior of organic matter in a full-scale water treatment process was characterized based on the three-dimensional excitation-emission matrix (3D-EEM) and Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). Polyaluminum chloride (PAC) as a coagulant can help to effectively remove soluble microbial by-products-like and aromatic protein-like substances during coagulation and sedimentation, corresponding to tannin and coagulated aromatic regions. The leakage of soluble microbial products during sand filtration resulted in an increase in the intensity of biomass-like regions. Nitrogen-containing compounds have higher weighted average value of double bond equivalents (DBE_w) and the modified aromaticity index (AI_mod-w) than nitrogen-free compounds. Water treatment can preferentially remove unsaturated nitrogen-containing compounds with more O atoms and higher-oxidation-state carbon. The dissolved organic carbon (DOC) and UV₂₅₄ were not correlated well with changes in nitrogen-containing compounds due to the preferential removal of nitrogen-containing compounds. This study revealed the specificity of organic matter removal during water treatment, and it was helpful in optimizing treatment processes for various raw water to ensure water quality.

Dissolved organic matter in complex shale gas wastewater analyzed with ESI FT-ICR MS: Typical characteristics and potential of biological treatment

Knowledge on the composition and characteristics of dissolved organic matter (DOM) in complex shale gas wastewater (SGW) is critical to evaluate environmental risks and to determine effective management strategies. Herein, five SGW samples from four key shale gas blocks in the Sichuan Basin, China, were comprehensively characterized. Specifically, FT-ICR MS was employed to provide insights into the sources, composition, and characteristics of SGW DOM. Organic matter was characterized by low average molecular weight, high saturation degree, and low aromaticity. Notably, the absence of correlations between molecular-level parameters and spectral indexes might be attributed to the high complexity and variability of SGW. The unique distribution depicted in van Krevelen diagrams suggested various sources of DOM in SGW, such as microbially derived organics in shales and biochemical transformations. Moreover, linear alkyl benzene sulfonates, as well as associated biodegraded metabolites and coproducts, were identified in SGW, implying the distinct anthropogenic imprints and abundant microbial activities. Furthermore, high DOC removal rates (31.42-79.23 %) were achieved by biological treatment, fully supporting the inherently labile nature of SGW and the feasibility of biodegradation for SGW management. Therefore, we conclude that DOM in SGW is a complex but mostly labile mixture reflecting both autochthonous and anthropogenic sources.

Identification of emerging organic pollutants from solid waste incinerations by FT-ICR-MS and GC/Q-TOF-MS and their potential toxicities

Emissions from the incineration of solid waste are a global public health concern, but little attention has been paid to previously unrecognized chemical compounds that are generated by waste incineration and released into the atmosphere. We conducted nontarget analysis of organic chemicals formed during waste incineration by Fourier-transform ion cyclotron resonance mass spectrometry and gas chromatography-quadrupole time-of-flight mass spectrometry. Using toxicity data in the ToxCast library and predicted toxicity data for traditional priority polycyclic aromatic hydrocarbons and 2,3,7,8-tetrachlorodibenzo-p-dioxin, we prioritized 13 compounds including hexachloro-1,3-butadiene, 9 of which are reported here for the first time as constituents of emissions from the incineration of solid waste and hexachloro-1,3-butadiene was included in the Stockholm Convention in 2017. The predicted activity of these pollutants to androgen receptors and to the aryl hydrocarbon receptor were comparable to, or higher than, the 2,3,7,8-tetrachlorodibenzo-p-dioxin and benzo[a]pyrene. In addition, some alkylated polycyclic aromatic hydrocarbons and heteroatom polycyclic aromatic hydrocarbons were also identified in solid waste incineration processes, peak areas of which were 1-2 orders of magnitude higher than dioxins and 1-3 orders of magnitude lower than their parent polycyclic aromatic hydrocarbons. Our study can provide information for better recognizing and regulating the emissions of organic pollutants formed by the incineration of solid waste.