Hidden Role of Organic Matter in the Immobilization and Transformation of Iodine on Fe-OM Associations.

The biogeochemical processes of iodine are typically coupled with organic matter (OM) and the dynamic transformation of iron (Fe) minerals in aquifer systems, which are further regulated by the association of OM with Fe minerals. However, the roles of OM in the mobility of iodine on Fe-OM associations remain poorly understood. Based on batch adsorption experiments and subsequent solid-phase characterization, we delved into the immobilization and transformation of iodate and iodide on Fe-OM associations with different C/Fe ratios under anaerobic conditions. The results indicated that the Fe-OM associations with a higher C/Fe ratio (=1) exhibited greater capacity for immobilizing iodine (∼60-80% for iodate), which was attributed to the higher affinity of iodine to OM and the significantly decreased extent of Fe(II)-catalyzed transformation caused by associated OM. The organic compounds abundant in oxygen with high unsaturation were more preferentially associated with ferrihydrite than those with poor oxygen and low unsaturation; thus, the associated OM was capable of binding with 28.1-45.4% of reactive iodine. At comparable C/Fe ratios, the mobilization of iodine and aromatic organic compounds was more susceptible in the adsorption complexes compared to the coprecipitates. These new findings contribute to a deeper understanding of iodine cycling that is controlled by Fe-OM associations in anaerobic environments.

Activated Carbon Application Simultaneously Alleviates Paddy Soil Arsenic Mobilization and Carbon Emission by Decreasing Porewater Dissolved Organic Matter.

Flooding of paddy fields during the rice growing season enhances arsenic (As) mobilization and greenhouse gas (e.g., methane) emissions. In this study, an adsorbent for dissolved organic matter (DOM), namely, activated carbon (AC), was applied to an arsenic-contaminated paddy soil. The capacity for simultaneously alleviating soil carbon emissions and As accumulation in rice grains was explored. Soil microcosm incubations and 2-year pot experimental results indicated that AC amendment significantly decreased porewater DOM, Fe(III) reduction/Fe2+ release, and As release. More importantly, soil carbon dioxide and methane emissions were mitigated in anoxic microcosm incubations. Porewater DOM of pot experiments mainly consisted of humic-like fluorophores with a molecular structure of lignins and tannins, which could mediate microbial reduction of Fe(III) (oxyhydr)oxides. Soil microcosm incubation experiments cospiking with a carbon source and AC further consolidated that DOM electron shuttling and microbial carbon source functions were crucial for soil Fe(III) reduction, thus driving paddy soil As release and carbon emission. Additionally, the application of AC alleviated rice grain dimethylarsenate accumulation over 2 years. Our results highlight the importance of microbial extracellular electron transfer in driving paddy soil anaerobic respiration and decreasing porewater DOM in simultaneously remediating As contamination and mitigating methane emission in paddy fields.

Enrichment of Geogenic Organoiodine Compounds in Alluvial-Lacustrine Aquifers: Molecular Constraints by Organic Matter.

Organoiodine compounds (OICs) are the dominant iodine species in groundwater systems. However, molecular mechanisms underlying the geochemical formation of geogenic OICs-contaminated groundwater remain unclear. Based upon multitarget field monitoring in combination with ultrahigh-resolution molecular characterization of organic components for alluvial-lacustrine aquifers, we identified a total of 939 OICs in groundwater under reducing and circumneutral pH conditions. In comparison to those in water-soluble organic matter (WSOM) in sediments, the OICs in dissolved organic matter (DOM) in groundwater typically contain fewer polycyclic aromatics and polyphenol compounds but more highly unsaturated compounds. Consequently, there were two major sources of geogenic OICs in groundwater: the migration of the OICs from aquifer sediments and abiotic reduction of iodate coupled with DOM iodination under reducing conditions. DOM iodination occurs primarily through the incorporation of reactive iodine that is generated by iodate reduction into highly unsaturated compounds, preferably containing hydrophilic functional groups as binding sites. It leads to elevation of the concentration of the OICs up to 183 µg/L in groundwater. This research provides new insights into the constraints of DOM molecular composition on the mobilization and enrichment of OICs in alluvial-lacustrine aquifers and thus improves our understanding of the genesis of geogenic iodine-contaminated groundwater systems.

FT-ICR MS Spectral Improvement of Dissolved Organic Matter by the Absorption Mode: A Comparison of the Electrospray Ionization in Positive-Ion and Negative-Ion Modes.

Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) in the absorption mode has a superior performance over the conventional magnitude mode. However, this improved performance for the analysis of dissolved organic matter (DOM) in negative-ion and positive-ion modes of electrospray ionization [ESI(-) and ESI(+), respectively] remains unknown. This study systemically compared the improved performance by the absorption mode for DOM FT-ICR MS spectra acquired with the low-field and high-field magnet instruments between two charge modes. The absorption mode enhanced the resolution and signal-to-noise ratio values of DOM peaks with factors of 1.88-1.94 and 1.60-1.72, respectively. The significantly higher improvement of mass resolution for the ESI(+) mode than that for the ESI(-) mode could resolve the extensive occurrence of mass doublets in the ESI(+) mode, yielding some formulas exclusively identified in the ESI(+) mode. The findings of this study have systemically demonstrated the superiority of the absorption mode in improving the spectra quality during the routine FT-ICR MS postdata analysis and highlighted its great potential in characterizing the molecular composition of DOM using the FT-ICR MS technique in both ESI(-) and ESI(+) modes.

Interpretable Machine Learning and Reactomics Assisted Isotopically Labeled FT-ICR-MS for Exploring the Reactivity and Transformation of Natural Organic Matter during Ultraviolet Photolysis.

Isotopically labeled FT-ICR-MS combined with multiple post-analyses, including interpretable machine learning (IML) and a paired mass distance (PMD) network, was employed to unravel the reactivity and transformation of natural organic matter (NOM) during ultraviolet (UV) irradiation. FT-ICR-MS analysis was used to assign formulas, which were classified on the basis of their molecular compositions and structural categories. Isotope (deuterium, D) labeling was utilized to unequivocally determine the photochemical products and examine the development of OD radical-mediated NOM transformation. With regard to the reactive molecular formulas, CHOS formulas exhibited the highest reactivity (86.5% of precursors disappeared) followed by CHON (53.4%) and CHO (24.6%) formulas. With regard to structural categories, the degree of reactivity decreased in the following order: tannins > condensed aromatics > lignin/CRAMs. The IML algorithm demonstrated that the crucial features governing the reactivity of formulas were the molecular weight, DBE-O, NOSC, and the presence of heteroatoms (i.e., N and S), suggesting that the large and unsaturated compounds containing S and N are more prone to photodegradation. The reactomics approach using the PMD network further indicated that 11 specific molecular formulas in the CHOS and CHO class served as hubs, implying a higher photoreactivity and participation in a range of transformations. The isotope labeling analyses also found that, among the reactions observed, hydroxylation (i.e., +OD) is dominant for lignin/CRAMs and condensed aromatics, and formulas containing ≤10 D atoms were developed. Overall, this study, by adopting rigorous and interpretable techniques, could provide in-depth insights into the molecular-level dynamics of NOM under UV irradiation.

Copper Safeguards Dissolved Organic Matter from Sunlight-Driven Photooxidation.

Sunlight plays a crucial role in the transformation of dissolved organic matter (DOM) and the associated carbon cycle in aquatic environments. This study demonstrates that the presence of nanomolar concentrations of copper (Cu) significantly decreases the rate of photobleaching and the rate of loss of electron-donating moieties of three selected types of DOM (including both terrestrial and microbially derived DOM) under simulated sunlight irradiation. Employing Fourier transform ion cyclotron resonance mass spectrometry, we further confirm that Cu selectively inhibits the photooxidation of lignin- and tannin-like phenolic moieties present within the DOM, in agreement with the reported inhibitory impact of Cu on the photooxidation of phenolic compounds. On the basis of the inhibitory impact of Cu on the DOM photobleaching rate, we calculate the contribution of phenolic moieties to DOM photobleaching to be at least 29-55% in the wavelength range of 220-460 nm. The inhibition of loss of electrons from DOM during irradiation in the presence of Cu is also explained quantitatively by developing a mathematical model describing hydrogen peroxide (a proxy measure of loss of electrons from DOM) formation on DOM irradiation in the absence and presence of Cu. Overall, this study advances our understanding of DOM transformation in natural sunlit waters.

Characterization of halogenated organic compounds by the Fourier transform ion cyclotron resonance mass spectrometry: A critical review.

Halogenated organic compounds (HOCs), widely present in various environments, are generally formed by natural processes (e.g., photochemical halogenation) and anthropogenic activities (e.g., water disinfection and anthropogenic discharge of HOCs), posing health and environmental risks. Therefore, in-depth knowledge of the molecular composition, transformation, and fate of HOCs is crucial to regulate and reduce their formation. Because of the extremely complex nature of HOCs and their precursors, the molecular composition of HOCs remains largely unknown. The Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) offers the most powerful resolution and mass accuracy for the simultaneous molecular-level characterization of HOCs and their precursors. However, there is still a paucity of reviews regarding the comprehensive characterization of HOCs by FT-ICR MS. Based on the FT-ICR MS, the formation mechanism, sample pretreatment, and analysis methods were summarized for two typical HOCs classes, namely halogenated disinfection byproducts and per- and polyfluoroalkyl substances in this review. Moreover, we have highlighted data analysis methods and some typical applications of HOCs using FT-ICR MS and proposed suggestions for current issues. This review will deepen our understanding of the chemical characterization of HOCs and their formation mechanisms and transformation at the molecular level in aquatic systems, facilitating the application of the state-of-the-art FT-ICR MS in environmental and geochemical research.

Spectral Quality Assessment Strategy Based on the 13C-Isotopic Pattern for the Fourier Transform Ion Cyclotron Resonance Mass Spectra of Dissolved Organic Matter.

The interpretation of data and optimization spectral acquisition of dissolved organic matter (DOM) by ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) have been challenging due to the varied instrument performances among laboratories and the complex chemical characteristics of DOM. However, a universal spectral optimization strategy for FT-ICR MS spectra is still unavailable. The results of this study showed that the number, intensity, and resolving power of all assigned peaks increased with the ion accumulation time (IAT) and DOM concentrations within a reasonable range. The space-charge effect induced by the excess ions in the ICR cell can deteriorate the data quality of the FT-ICR MS spectra, which could be inspected by examining the mass errors and intensity deviation of the monoisotopic and 13C-isotopic peaks based on the 13C-isotopic pattern. The maximum absolute mass error and 13C-isotopic pattern-based intensity deviation are two critical criteria for inspecting the space-charge effect, which was suggested to be 2.0 ppm and 20%, respectively. Therefore, a novel strategy based on the 13C-isotopic pattern has been proposed in this study to optimize the FT-ICR MS spectra of DOM based on their wide occurrence of monoisotopic and 13C-isotopic signals. This optimization strategy has laid the fundamentals for the method development of FT-ICR MS and could be extended to different FT-ICR MS instruments and various organic complex mixtures.

Evidence for nontraditional mcr-containing archaea contributing to biological methanogenesis in geothermal springs.

Recent discoveries of methyl-coenzyme M reductase-encoding genes (mcr) in uncultured archaea beyond traditional euryarchaeotal methanogens have reshaped our view of methanogenesis. However, whether any of these nontraditional archaea perform methanogenesis remains elusive. Here, we report field and microcosm experiments based on 13C-tracer labeling and genome-resolved metagenomics and metatranscriptomics, revealing that nontraditional archaea are predominant active methane producers in two geothermal springs. Archaeoglobales performed methanogenesis from methanol and may exhibit adaptability in using methylotrophic and hydrogenotrophic pathways based on temperature/substrate availability. A five-year field survey found Candidatus Nezhaarchaeota to be the predominant mcr-containing archaea inhabiting the springs; genomic inference and mcr expression under methanogenic conditions strongly suggested that this lineage mediated hydrogenotrophic methanogenesis in situ. Methanogenesis was temperature-sensitive , with a preference for methylotrophic over hydrogenotrophic pathways when incubation temperatures increased from 65° to 75°C. This study demonstrates an anoxic ecosystem wherein methanogenesis is primarily driven by archaea beyond known methanogens, highlighting diverse nontraditional mcr-containing archaea as previously unrecognized methane sources.

Complementary Elucidation of the Molecular Characteristics of Groundwater Dissolved Organic Matter Using Ultrahigh-Resolution Mass Spectrometry Coupled with Negative- and Positive-Ion Electrospray Ionization.

The formula assignment of the Fourier transform ion cyclotron resonance mass spectrometry coupled with positive-ion electrospray ionization [ESI(+)-FT-ICR MS] is challenging because of the extensive occurrence of adducts. However, there is a paucity of automated formula assignment methods for ESI(+)-FT-ICR MS spectra. The novel automated formula assignment algorithm for ESI(+)-FT-ICR MS spectra developed herein has been applied to elucidate the composition of dissolved organic matter (DOM) in groundwater during air-induced ferrous [Fe(II)] oxidation. The ESI(+)-FT-ICR MS spectra of groundwater DOM were profoundly impacted by [M + Na]+ adducts and, to a lesser extent, [M + K]+ adducts. Oxygen-poor and N-containing compounds were frequently detected when the FT-ICR MS was operated in the ESI(+) mode, while the components with higher carbon oxidation states were preferentially ionized in the negative-ion electrospray ionization [ESI(-)] mode. Values for the difference between double-bond equivalents and the number of oxygen atoms from -13 to 13 are proposed for the formula assignment of the ESI(+)-FT-ICR MS spectra of aquatic DOM. Furthermore, for the first time, the Fe(II)-mediated formation of highly toxic organic iodine species was reported in groundwater rich in Fe(II), iodide, and DOM. The results of this study not only shed light on the further algorithm development for comprehensive characterization of DOM by ESI(-)-FT-ICR MS and ESI(+)-FT-ICR MS but also highlight the importance of appropriate treatment of specific groundwater prior to use.

Development of a Gaussian-Based Alignment Algorithm for the Ultrahigh-Resolution Mass Spectra of Dissolved Organic Matter.

The alignment of ultrahigh-resolution mass spectra (UHR-MS) is critical to inspect the presence of unique and common peaks across multiple UHR-MS spectra. However, few attempts have been conducted to develop an automated alignment method. In this study, a novel automated alignment algorithm, namely, FTMSCombine, that follows a Gaussian distribution of mass errors was developed and then integrated with existing FTMSCalibrate and TRFu algorithms to establish an open-source analysis platform, namely, FTMSAnalysis, for the UHR-MS analysis of the dissolved organic matter. The developed FTMSCombine was capable of automatically aligning peaks across different UHR-MS spectra by averaging the m/z values of each peak cluster, although the alignment should be restricted to Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) spectra collected by instruments under similar conditions. The FTMSCombine exhibited an insignificant difference in the reproducibility of chemical formulae but significantly higher mass accuracy than the ICBM-OCEAN. In addition to improving the overall mass accuracy of the whole UHR-MS dataset, the FTMSCombine could effectively exclude scatters or noise peaks using an optional rule that restricts peaks (continuously) detected in at least a certain number of spectra in the UHR-MS spectra dataset. The successfully established FTMSAnalysis (freely available in the Supporting Information of this study) is of great potential in automatically analyzing UHR-MS spectra for dissolved organic matter (DOM) and will largely facilitate the elucidation of DOM chemodivesity by UHR-MS techniques including FTICR-MS.

Comprehensive understanding of DOM reactivity in anaerobic fermentation of persulfate-pretreated sewage sludge via FT-ICR mass spectrometry and reactomics analysis.

Understanding the composition and reactivity of dissolved organic matter (DOM) at molecular level is vital for deciphering potential regulators or indicators relating to anaerobic process performance, though it was hardly achieved by traditional analyses. Here, the DOM composition, molecular reactivity and transformation in the enhanced sludge fermentation process were comprehensively elucidated using high-resolution mass spectrometry measurement, and data mining with machine learning and paired mass distance (PMD)-based reactomics. In the fermentation process for dewatered sludge, persulfate (PDS) pretreatment presented its highest performance in improving volatile fatty acids (VFAs) production with the increase from 2,711 mg/L to 3,869 mg/L, whereas its activation in the presence of Fe (as well as the hybrid of Fe and activated carbon) led to the decreased VFAs production performance. In addition to the conventional view of improved decomposition and solubilization of N-containing structures from sludge under the sole PDS pretreatment, the improved VFAs production was associated with the alternation of DOM molecular compositions such as humification generating molecules with high O/C, N/C, S/C and aromatic index (AImod). Machine learning was capable of predicting the DOM reactivity classes with 74-76 % accuracy and found that these molecular parameters in addition to nominal oxidation state of carbon (NOSC) were among the most important variables determining the generation or disappearance of bio-resistant molecules in the PDS pretreatment. The constructed PMD-based network suggested that highly connected molecular network with long path length and high diameter was in favor of VFAs production. Especially, -NH related transformation was found to be active under the enhanced fermentation process. Moreover, network topology analysis revealed that CHONS compounds (e.g., C13H27O8N1S1) can be the keystone molecules, suggesting that the presence of sulfur related molecules (e.g., cysteine-like compounds) should be paid more attention as potential regulators or indicators for controlling sludge fermentation performance. This study also proposed the non-targeted DOM molecular analysis and downstream data mining for extending our understanding of DOM transformation at molecular level.

Photochemical transformation mechanisms of dissolved organic matters (DOM) derived from different bio-stabilization sludge.

Bio-stabilization sludge contains numerous dissolved organic matter (DOM) that could enter aquatic environments by soil leaching after sludge land use, but a clear understanding of their photochemical behavior is still lacking. In this study, we systematically investigated the photoactivity and photochemical transformation of aerobic composting sludge-derived DOM (DOMACS) and anaerobic digestion sludge-derived DOM (DOMADS) by using multispectral analysis coupled with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). The results indicated that DOMACS and DOMADS have a higher proportion of highly unsaturated and phenolic compounds (HuPh)with high DBEwa, but the different polyphenols (Polyph) abundance of them, causing the different photoactivity between them. DOMACS had much higher apparent quantum yields (AQY) for triplet states of dissolved natural organic matter (3DOM*) and hydroxyl radical (•OH) but slightly lower AQY for singlet oxygen (1O2) than DOMADS under simulated sunlight conditions. As the irradiation time increased, HuPh and Polyph (associated with humic-like substances) contained in DOMACS (DOMADS) decreased by 12.0% (14.1%) and 3.0% (0.2%), respectively, with concurrent decrease in average molecular weight and aromaticity moieties, resulting in more generation of aliphatic compounds. Furthermore, based on 27 types of photochemical transformation reactions, DOMACS containing higher fractions of O10-15 and N1-3Oy class preferred dealkyl group and carboxylic acid reactions, whereas DOMADS composed of more N4Oy and S2Oy fragments preferred oxygen addition and anmine reactions. Consequently, photochemical transformations reduced the Cd (II) ion activity in the presence of DOMACS (DOMADS). This study is believed to unveil the photochemical transformation of bio-stabilization sludge-derived DOM and its impact on pollutants' fate in the aquatic environment.

Development of an Internal Calibration Algorithm for Ultrahigh-Resolution Mass Spectra of Dissolved Organic Matter.

In order to obtain a spectrum with high mass accuracy, an internal calibration of Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) is inevitable. This in turn is critical for subsequent data processing and is generally performed using the commercial instrument software DataAnalysis in the benchmark calibration mode. However, no methodological study has systemically addressed the automated internal calibration of FTICR-MS spectra for dissolved organic matter (DOM) from different sources such as terrestrial and aquatic environments. In this study, a new piecewise algorithm, FTMSCalibrate, was developed to automatically calibrate FTICR-MS spectra in both positive and negative ion modes. FTMSCalibrate was found to reproduce 91.7% ± 4.4% (referred to as the true positive ratio) of the chemical formulas obtained by calibration using manual DataAnalysis. In addition to significantly reducing the mass error, FTMSCalibrate is more accurate in terms of the molecular formula assignment for low m/z peaks than Formularity and MFAssignR. FTMSCalibrate was compatible with deprotonated ions for FTICR-MS spectra in the negative ion mode as well as protonated and adduct ions, including Na- and K-adducts, for FTICR-MS spectra in the positive ion mode. These results suggest that FTMSCalibrate publicly available herein is a robust alternative for the internal calibration of FTICR-MS spectra during postdata processing and will facilitate DOM analysis by FTICR-MS.

Formula Assignment Algorithm for Deuterium-Labeled Ultrahigh-Resolution Mass Spectrometry: Implications of the Formation Mechanism of Halogenated Disinfection Byproducts.

Ultrahigh-resolution mass spectrometry (UHR-MS) coupled with isotope labeling has attracted significant attention in elucidating the mechanisms of the transformation of dissolved organic matter (DOM). Herein, we developed a novel formula assignment algorithm based on deuterium (D)-labeled UHR-MS, namely, FTMSDeu, for the first time. This algorithm was employed to determine the precursor molecules of halogenated disinfection byproducts (Xn-DBPs) and to evaluate the relative contribution of electrophilic addition and substitution reactions in Xn-DBP formation according to the H/D exchange of DOM molecules. Further, tandem mass spectrometry with homologous-based network analysis was used to validate the formula assignment accuracy of FTMSDeu in the identification of iodinated disinfection byproducts. Electrophilic substitution accounted for 82-98, 71-89, and 43-45% of the formation for Cl-, Br-, and I-containing Xn-DBPs, respectively, indicating the dominant role of the electrophilic substitution in chlorinated disinfection byproducts with low Br and I concentrations. The absence of putative precursors in some Xn-DBPs also suggests that Xn-DBP formation includes secondary reactions (e.g., oxidation and hydrolysis) in addition to the electrophilic addition and/or substitution of halogens. These findings highlight the significance of isotopically labeled UHR-MS techniques in revealing the transformation of DOM in natural and engineered systems.

Effects of extracellular polymeric substances on silver nanoparticle bioaccumulation and toxicity to Triticum aestivum L.

The potential effects of extracellular polymeric substances (EPS) on the behavior and toxicity of silver nanoparticle (Ag-NPs) and silver sulfide nanoparticle (Ag2S-NPs) remains ambiguous. The interaction of EPS from Bacillus subtilis with Ag2S-NPs, metallic Ag-NPs, or ionic Ag, and the associated plant safety had been examined in this study. The biological impacts of Ag-NPs and Ag2S-NPs were Ag form-dependent and highly influenced by microbial EPS. Compared with metallic Ag-NPs, Ag2S-NPs exert inert biological impacts, as revealed by 3.44 times lower Ag bioaccumulation in wheat (Triticum aestivum L.) seedlings and nearly reduce plant biomass when wheat was subjected to 1.0 mg-Ag L-1 of Ag-NPs and Ag2S-NPs with the transfer factors of 151.56-930.87 vs. 12.52-131.81, respectively. These observations were coincident with the low dissolved Ag ([Ag]diss) in the Ag2S-NPs treatment than the Ag-NPs treatment (114.0 vs. 0.0791, µg L-1). Compared with the enhanced toxicity of Ag2S-NPs to wheat, Bacillus subtilis EPS significantly alleviate the phytotoxicity of Ag-NPs, as revealed by the relative root elongation (7.15-45.40% decrease vs. 2.39-11.75% increase), and malondialdehyde (1.47-83.22% increase vs. 8.57-25.25% decrease) and H2O2 (11.27-71.78% increase vs. 5.16-36.67% decrease) contents. These constrasting plant responses of B. subtilis EPS are mainly caused by their complexation property with toxic Ag+ and nutrient elements for wheat stressed by Ag-NPs and Ag2S-NPs, respectively. Our findings highlight the importance of rhizospheric EPS in affecting the biogeochemistry and ecotoxicity of metal nanoparticles including Ag-NPs and Ag2S-NPs in agricultural systems.

Development and Application of a High-Precision Algorithm for Nontarget Identification of Organohalogens Based on Ultrahigh-Resolution Mass Spectrometry.

Brominated and/or chlorinated organic compounds (referred to as organohalogens) are frequently detected in natural and engineered environments. However, ultrahigh-resolution mass spectrometry (UHR-MS)-based nontargeted identification of organohalogens remains challenging because of the coexistence of a vast number of halogenated and nonhalogenated organic molecules. In this study, a new algorithm, namely, the NOMDBP code, was developed to simultaneously identify organohalogens and non-organohalogens from the UHR-MS spectra of natural and engineered waters. In addition to isotopic patterns, for the first time, three optional filter rules [i.e., selection for minimum nonoxygen heteroatoms, inspection of the presence of newly formed halogenated disinfection byproducts (Xn-DBPs), and of their precursors] were incorporated into our code, which can accurately identify DBP-associated peaks and further elucidate Xn-DBP generation and transformation mechanisms. The formula assignment ratio against 2815 previously reported organohalogens, and their 11,583 isotopologues exceeded 97%. Application of our algorithm to disinfected natural organic matter indicated that oxygen-containing Xn-DBP species accounted for a majority of the Xn-DBPs. Furthermore, brominated Xn-DBPs (Br-DBPs) were characterized by a higher degree of unsaturation compared to chlorinated Xn-DBPs. In addition to electrophilic substitution and electrophilic addition reactions, the decomposition/transformation pathway was found to be another important mechanism in Br-DBP formation. The results of this study highlight the superior potential of our code for the efficient detection of yet unknown organohalogens (including organohalogens bearing nonoxygen heteroatoms) in a nontargeted manner and for the identification of their generation mechanism occurring during the disinfection process.

Development and comparison of formula assignment algorithms for ultrahigh-resolution mass spectra of natural organic matter.

Increasing number of application of ultrahigh-resolution mass spectrometry (UHR-MS) to natural organic matter (NOM) characterization requires an efficient and accurate formula assignment from a number of mass data. Herein, we newly developed two automated batch codes (namely TRFu and FuJHA) and assessed their formula assignment accuracy together with frequently used open access algorithms (i.e., Formularity and WHOI). Overall assignment accuracy for 8719 NOM-like emerging chemicals with known molecular formulae (mass range from 68 Da to 1000 Da) was highest (94%) for TRFu. Further, TRFu showed up to 99.1% formula assignment ratio for a total 76,880 UHR-MS peaks from 35 types of NOM (e.g., aquatic, soil/sediment, biochar). Therefore, as a reliable and practically feasible tool, the automated batch TRFu (freely available at ChemRxiv, https://doi.org/10.26434/chemrxiv.9917399) can precisely characterize UHR-MS spectra of various NOM and could be extended to non-target screening of NOM-like emerging chemicals in natural and engineered environments.

Iron uptake by bloom-forming freshwater cyanobacterium Microcystis aeruginosa in natural and effluent waters.

Studies on Fe uptake by phytoplankton have been often conducted using artificial culture media. However, Fe chemistry in freshwater can be influenced by riverine anthropogenic impacts and other factors causing water quality changes. In this study, therefore, Fe uptake in natural (river and reservoir) and effluent waters was investigated for the notorious bloom-forming freshwater cyanobacterium Microcystis aeruginosa. To investigate the Fe uptake mechanism, a short-term incubational assay was conducted in the presence of light, Fe(II) ligand and Fe(III) reductant, with results consistently indicating that unchelated Fe(III) is the major substrate for Fe uptake by M. aeruginosa. Further assays using various freshwater samples indicated that Fe uptake is lower in natural waters compared to that of effluent waters and, interestingly, Fe uptake was found to be limited in natural waters. These results suggest that Fe limitation can be alleviated by the inflow of effluent waters. Statistical analysis with various water quality variables indicated that Fe availability is significantly influenced by concentrations of dissolved Fe and organic matter as well as specific UV absorbance (an index of aromaticity). Overall, findings of this study highlight that watershed anthropogenic activities exert important roles in Fe uptake by freshwater cyanobacteria via alteration of Fe speciation.