Determination of molecular formulas of natural organic matter molecules by (ultra-) high-resolution mass spectrometry

Detection and Exclusion of False-Positive Molecular Formula Assignments via Mass Error Distributions in UHR Mass Spectra of Natural Organic Matter

Ultrahigh resolution mass spectrometry (UHRMS) routinely detects and identifies thousands of mass peaks in complex mixtures, such as natural organic matter (NOM) and petroleum. The assignment of several chemically plausible molecular formulas (MFs) for a single accurate mass still poses a major problem for the reliable interpretation of NOM composition in a biogeochemical context. Applying sensible chemical rules for MF validation is often insufficient to eliminate multiple assignments (MultiAs)─especially for mass peaks with low abundance or if ample heteroatoms or isotopes are included - and requires manual inspection or expert judgment. Here, we present a new approach based on mass error distributions for the identification of true and false assignments among MultiAs. To this end, we used the mass error in millidalton (mDa), which was superior to the commonly used relative mass error in ppm. We developed an automatic workflow to group MultiAs based on their shared formula units and Kendrick mass defect values and to evaluate the mass error distribution. In this way, the number of valid assignments of chlorinated disinfection byproducts was increased by 8-fold as compared to only applying 37Cl/35Cl isotope ratio filters. Likewise, phosphorus-containing MFs can be differentiated against chlorine-containing MFs with high confidence. Further, false assignments of highly aromatic sulfur-containing MFs ("black sulfur") to sodium adducts in negative ionization mode can be excluded by applying our approach. Overall, MFs for mass peaks that are close to the detection limit or where naturally occurring isotopes are rare (e.g., 15N) or absent (e.g., P and F) can now be validated, substantially increasing the reliability of MF assignments and broadening the applicability of UHRMS analysis to even more complex samples and processes.

Carbon Source in Tertiary Denitrification Regulates Dissolved Organic Nitrogen in Wastewater Effluent

With global eutrophication and increasingly stringent nitrogen discharge restrictions, dissolved organic nitrogen (DON) holds considerable potential to upgrade advanced wastewater denitrification because of its large contribution to low-nitrogen effluents and stronger stimulation effect for algae. Here, we show that DON from the postdenitrification systems dominates effluent eutrophication potential under different carbon sources. Methanol resulted in significantly lower DON concentrations (0.84 ± 0.03 mg/L) compared with the total nitrogen removal-preferred acetate (1.11 ± 0.02 mg/L) (p < 0.05, ANOVA). With our well-developed mathematical model (R2 = 0.867-0.958), produced DON instead of shared (persist in both influent and effluent) and/or removed DON was identified as the key component for effluent DON variation (Pearson r = 0.992, p < 0.01). The partial least-squares path modeling analysis showed that it is the microbial community (r = 0.947, p < 0.01) rather than the predicted metabolic functions (r = 0.040, p > 0.1) that affected produced DON. Carbon sources rebuild the microorganism-DON interaction by affecting the structure of microbial communities with different abilities to generate and recapture produced DON to finally regulate effluent DON. This study revalues the importance of carbon source selection and overturns the current rationality of pursuing only the total nitrogen removal efficiency by emphasizing DON.

Toward a More Comprehensive Approach for Dissolved Organic Matter Chemical Characterization Using an Orbitrap Fusion Tribrid Mass Spectrometer Coupled with Ion and Liquid Chromatography Techniques

Dissolved organic matter (DOM) represents one of the largest active organic carbon pools in the global carbon cycle. Although extensively studied, only <10% of DOM has been chemically characterized into individual dissolved compounds due to its molecular complexity. This study introduced a more comprehensive DOM characterization method by coupling both ion chromatography (IC) and liquid chromatography (LC) with high mass accuracy and resolution mass spectrometry. We presented a new on-the-fly mass calibration of the Orbitrap technique by utilizing the "lock mass" function in the Orbitrap Fusion Tribrid mass spectrometer (OT-FTMS), which assures high mass accuracy at every scan by a postcolumn introduction of internal labeled standards. With both IC and LC, tested unlabeled standards of amino acids, small peptides, and organic acids were consistently below 1.0 ppm mass error, giving the OT-FTMS the potential of reaching mass accuracy of the Fourier-transform ion cyclotron resonance mass spectrometer. In addition to mass accuracy, a pooled quality control sample (QC) was used to increase reproducibility by applying systematic error removal using random forest (SERRF). Using an untargeted mass spectrometry approach, estuarine DOM samples were analyzed by OT-FTMS coupled to IC in negative mode and LC in positive mode detection to cover a wide range of highly cationic to highly anionic molecules. As a proof of concept, we focused on elucidating the structures of three distinct DOM compound classes with varied acidities and basicities. In UPLC-OT-FTMS, a total of 915 compounds were detected. We putatively elucidated 44 small peptides and 33 deaminated peptides of these compounds. With IC-OT-FTMS, a total of 1432 compounds were detected. We putatively elucidated 20 peptides, 268 deaminated peptides, and 188 organic acids. Except for five compounds, all putatively elucidated compounds were uniquely detected in their corresponding chromatography technique. These results highlight the need for combining these two techniques to provide a more comprehensive method for DOM characterization. Application of the combined IC and LC techniques is not limited to DOM chemical characterization. It can analyze other complex compound mixtures, such as metabolites, and anthropogenic pollutants, such as pesticides and endocrine-disrupting chemicals, in environmental and biological samples.

Characterization of Sulfur-Rich Microbial Organic Matter in Jurassic Carbonates Using Laser-Assisted Mass Spectrometry

Laser desorption-ionization mass spectrometry (MS) shows great potential for in situ molecular analysis of planetary surfaces and microanalysis of space-returned samples or (micro)fossils. Coupled with pyrolysis gas chromatography-mass spectrometry (Py-GC-MS) in ESA's ExoMars project, this technique could help assess further the origin of sulfur-bearing organic matter (OM) recently detected on Mars. To unravel this potential, we analyzed sulfurized microbial OM from ca. 150 million year-old carbonates with laser desorption-ionization mass spectrometry (single- and two-step: LDI-MS and L2MS), in comparison with time-of-flight secondary-ion mass spectrometry (ToF-SIMS), gas chromatography-mass spectrometry (GC-MS), and Py-GC-MS. We show that LDI-MS and L2MS readily detect sulfur-bearing moieties such as (alkyl)thiophenes and (alkyl)benzothiophenes. The mineral matrix, however, made the identification of sulfur-bearing molecules challenging in our L2MS experiment. The dominance of small aromatic hydrocarbons (≤14 carbons) in the LDI-MS and L2MS of the extracted soluble and insoluble OM and of the bulk rock is consistent with the low thermal maturity of the sediment and contrasts with the predominance of larger polycyclic aromatic structures commonly observed in meteorites with these techniques. We detected inorganic ions, in particular VO+, in demineralized OM that likely originate from geoporphyrins, which derive from chlorophylls during sediment diagenesis. Finally, insoluble OM yielded distinct compositions compared with extracted soluble OM, with a greater abundance of ions of mass-to-charge ratio (m/z) over 175 and additional N-moieties. This highlights the potential of laser-assisted MS to decipher the composition of macromolecular OM, in particular to investigate the preservation of biomacromolecules in microfossils. Studies comparing diverse biogenic and abiogenic OM are needed to further assess the use of this technique to search for biosignatures.

Determining the parent and associated fragment formulae in mass spectrometry via the parent subformula graph

BACKGROUND

Identifying the molecular formula and fragmentation reactions of an unknown compound from its mass spectrum is crucial in areas such as natural product chemistry and metabolomics. We propose a method for identifying the correct candidate formula of an unidentified natural product from its mass spectrum. The method involves scoring the plausibility of parent candidate formulae based on a parent subformula graph (PSG), and two possible metrics relating to the number of edges in the PSG. This method is applicable to both electron-impact mass spectrometry (EI-MS) and tandem mass spectrometry (MS/MS) data. Additionally, this work introduces the two-dimensional fragmentation plot (2DFP) for visualizing PSGs.

RESULTS

Our results suggest that incorporating information regarding the edges of the PSG results in enhanced performance in correctly identifying parent formulae, in comparison to the more well-accepted "MS/MS score", on the 2016 Computational Assessment of Small Molecule Identification (CASMI 2016) data set (76.3 vs 58.9% correct formula identification) and the Research Centre for Toxic Compounds in the Environment (RECETOX) data set (66.2% vs 59.4% correct formula identification). In the extension of our method to identify the correct candidate formula from complex EI-MS data of semiochemicals, our method again performed better (correct formula appearing in the top 4 candidates in 20/23 vs 7/23 cases) than the MS/MS score, and enables the rapid identification of both the correct parent ion mass and the correct parent formula with minimal expert intervention.

CONCLUSION

Our method reliably identifies the correct parent formula even when the mass information is ambiguous. Furthermore, should parent formula identification be successful, the majority of associated fragment formulae can also be correctly identified. Our method can also identify the parent ion and its associated fragments in EI-MS spectra where the identity of the parent ion is unclear due to low quantities and overlapping compounds. Finally, our method does not inherently require empirical fitting of parameters or statistical learning, meaning it is easy to implement and extend upon.

SCIENTIFIC CONTRIBUTION

Developed, implemented and tested new metrics for assessing plausibility of candidate molecular formulae obtained from HR-MS data.

TEnvR: MATLAB-based toolbox for environmental research

With the advancements in science and technology, datasets become larger and more multivariate, which warrants the need for programming tools for fast data processing and multivariate statistical analysis. Here, the MATLAB-based Toolbox for Environmental Research "TEnvR" (pronounced "ten-ver") is introduced. This novel toolbox includes 44 open-source codes for automated data analysis from a multitude of techniques, such as ultraviolet-visible, fluorescence, and nuclear magnetic resonance spectroscopies, as well as from ultrahigh resolution mass spectrometry. Provided are codes for processing data (e.g., spectral corrections, formula assignment), visualization of figures, calculation of metrics, multivariate statistics, and automated work-up of large datasets. TEnvR allows for efficient data analysis with minimal "by-hand" manual work by the user, which allows scientists to do research more efficiently. This manuscript is supplemented with a detailed tutorial, example data, and screenshots, which collectively provide instructions on how to use all codes. TEnvR is novice-friendly and experience in programming with MATLAB is not required. TEnvR fulfills the need for a concise MATLAB-based toolbox for working with environmental data and will be updated annually to keep pace with the latest advances and needs for computational work in the environmental sciences.

Identification of low-level impurities in drug prototypes of carbocisteine by means of liquid chromatography-high-resolution mass spectrometry and general unknown comparative screening

High-resolution tandem quadrupole time-of-flight mass analysers enable new automated workflows for untargeted data evaluation of complex samples like drug products. An example of such procedure is the so-called general unknown comparative screening (GUCS), which is used for software-assisted, automated identification of components that are only present in a sample and not in a reference. The GUCS approach has been employed for the first time to detect both degradation products and reaction products in drug products. Two different carbocisteine containing syrup prototypes - one with sucrose and the other with artificial sweeteners - were selected as examples after nine months of storage at 40 °C and 75% relative humidity. The samples were analysed chromatographically using a Coresep SB mixed-mode column and high-resolution MS and MS/MS data were recorded in information dependant acquisition mode on a Sciex X500R quadrupole time-of-flight mass spectrometer. Data analysis was considerably facilitated using the corresponding placebo formulation as reference samples. With the GUCS approach two hitherto unknown degradation products of carbocisteine, i.e. the carbocisteine lactam of the sulfoxides and the disulfide between l-cysteine and thioglycolic acid, were detected at low concentrations in both of the syrup formulations. The presumed structures were confirmed by in silico analysis of the fragment spectra and high-resolution LC-MS experiments with reference substances. Two additional impurities were found in the sucrose-containing sample and identified as the N-glycosides of carbocisteine and its lactam, respectively, using binary mixtures with a 13C-labelled monosaccharide.

Investigation with ESI FT-ICR MS on sorbent selectivity and comprehensive molecular composition of landfill leachate dissolved organic matter

Molecular characterization of landfill leachate dissolved organic matter (LDOM) is essential for developing effective processing techniques. However, the molecular selectivity of extraction method and ionization modes often leads to the bias of molecular characterization of LDOM. Here, seven representative sorbents were selected and electrospray ionization negative ion mode (ESI (-)) and positive ion mode (ESI (+)) Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS) were used to investigate the molecular composition of different LDOM samples. Obvious sorbent selectivity during extraction procedure was observed, resulting in the underestimation of molecular diversity of LDOM from 32.7% to 69.3%. Totally, 14,000-18,000 unique molecules were obtained in a single sample, indicating the unprecedented molecular diversity of LDOM. Lignins, proteins and lipids are three major molecular groups in LDOM, and N or S containing molecules occupied 83%. Although much of total organic carbon was removed during biochemical treatment process, the molecular diversity of LDOM was not reduced because a considerable of bio-recalcitrant molecules was produced. The results uncover the sorbents selectivity and ionization modes selectivity in LDOM analysis and provided a comprehensive change of LDOM molecular composition during biochemical treatment, which benefits the development of accurate methods to remove organic carbon in landfill leachate.

Molecular-Scale Investigation on the Formation of Brown Carbon Aerosol via Iron-Phenolic Compound Reactions in the Dark

Brown carbon (BrC) is one of the most mysterious aerosol components responsible for global warming and air pollution. Iron (Fe)-induced catalytic oxidation of ubiquitous phenolic compounds has been considered as a potential pathway for BrC formation in the dark. However, the reaction mechanism and product composition are still poorly understood. Herein, 13 phenolic precursors were employed to react with Fe under environmentally relevant conditions. Using Fourier transform ion cyclotron resonance mass spectrometry, a total of 764 unique molecular formulas were identified, and over 85% of them can be found in atmospheric aerosols. In particular, products derived from precursors with catechol-, guaiacol-, and syringol-like-based structures can be distinguished by their optical and molecular characteristics, indicating the structure-dependent formation of BrC from phenolic precursors. Multiple pieces of evidence indicate that under acidic conditions, the contribution of either autoxidation or oxygen-induced free radical oxidation to BrC formation is extremely limited. Ligand-to-Fe charge transfer and subsequent phenoxy radical coupling reactions were the main mechanism for the formation of polymerization products with high molecular diversity, and the efficiency of BrC generation was linearly correlated with the ionization potential of phenolic precursors. The present study uncovered how chemically diverse BrC products were formed by the Fe-phenolic compound reactions at the molecular level and also provide a new paradigm for the study of the atmospheric aerosol formation mechanism.

Data evaluation strategy for identification of key molecular formulas in dissolved organic matter as proxies for biogeochemical reactivity based on abundance differences from ultrahigh resolution mass spectrometry

The molecular composition of dissolved organic matter (DOM) is of relevance for global carbon cycling and important for drinking water processing also. The detection of variation of DOM composition as function of time and space from a methodological viewpoint is essential to observe DOM processing and was addressed so far. High resolution concerning DOM quality was achieved with Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS). However almost none of the existing FTICR-MS data sets were evaluated addressing the fate of single mass features / molecular formulas (MFs) abundance during experiments. In contrast to former studies we analyze the function of MF abundance of time and space for such MFs which are present in all samples and which were formerly claimed as recalcitrant in not all but a great number of studies. For the first time the reactivity of MFs was directly compared by their abundance differences using a simple equation, the relative intensity difference (δRI). Search strategies to find out the maximum δRI values are introduced. The corresponding MFs will be regarded as key MFs (KEY-MFs). In order to test this new approach data from a recent photo degradation experiment were combined with monitoring surveys conducted in two drinking water reservoirs. The δRI values varied over one order of magnitude (more than five-fold). MFs like C₉H₁₂O₆ and C₁₀H₁₄O₆ revealed high biogeochemical reactivity as photo products. Some of the KEY-MFs were identical with MFs identified as disinfection byproducts precursors in recent studies. Other KEY-MFs were oxygen-rich and relatively unsaturated (poly-phenol-like) and hence relevant to flocculation procedures.

Machine-learning assisted molecular formula assignment to high-resolution mass spectrometry data of dissolved organic matter

High-resolution mass spectrometry (HRMS) provides molecular compositional information of dissolved organic matter (DOM) through isotopic assignment from the molecular mass. However, due to the inevitable deviation of molecular mass measurement and the limitation of resolving power, multiple possible solutions frequently occur for a given molecular mass. Lowering the mass deviation threshold and adding assignment restriction rules are often applied to exclude the incorrect solutions, which generally involves time-consuming manual post-processing of mass data. To improve the result accuracy in an automated manner, we developed a molecular formula assignment algorithm based on machine-learning technology. The method integrated a logistic regression model using manually corrected isotopic composition and the peak features of HRMS data (m/z, signal-to-noise ratio, isotope type, and number, etc.) as training data. The developed model can evaluate the correctness of a candidate formula for the given mass peak based on the peak features. The method was verified by various DOM samples FT-ICR MS data (direct infusion negative mode electrospray), achieving a ∼90% accuracy (compared to the traditional approach) for formula assignment. The method was applied to a series of NOM samples and showed a significant improvement in formula assignment compared with the mass matching method.

Advances in Molecular and Microscale Characterization of Soil Organic Matter: Current Limitations and Future Prospects

Soil organic matter (SOM) comprises a continuum of organic materials from granular organic debris to small organic molecules and contains more organic carbon than global vegetation and the atmosphere combined. It has remarkable effects on soil ecological functions and the global carbon cycle as well as the fate of pollutants in the terrestrial ecosystem. Therefore, characterization of SOM is an important topic in soil science, ecology, and environmental science. Chemical complexity and spatial heterogeneity are by far the two biggest challenges to our understanding of SOM. Recent developments in analytical techniques and methods provide the opportunity to reveal SOM composition at the molecular level and to observe its distribution in soils at micro- and nanoscales, which have greatly improved our understanding of SOM. This paper reviews the outstanding advances in SOM characterization regarding these two issues from target and nontarget analyses comprising molecular marker analysis, ultrahigh-resolution mass spectrometry analysis, and in situ microscopic imaging techniques such as synchrotron-based spectromicroscopy, nanoscale secondary ion mass spectrometry, and emerging electron and optical microscopic imaging techniques. However, current techniques and methods remain far from unlocking the unknown properties of SOM. We systematically point out the limitations of the current technologies and outline the future prospects for comprehensive characterization of SOM at the molecular level and micro- and nanoscales, paying particular attention to issues of environmental concern.

Analysis of environmental organic matters by Ultrahigh-Resolution mass spectrometry-A review on the development of analytical methods

Owing to the increasing environmental and climate changes globally, there is an increasing interest in the molecular-level understanding of environmental organic compound mixtures, that is, the pursuit of complete and detailed knowledge of the chemical compositions and related chemical reactions. Environmental organic molecule mixtures, including those in air, soil, rivers, and oceans, have extremely complex and heterogeneous chemical compositions. For their analyses, ultrahigh-resolution and sub-ppb level mass accuracy, achievable using Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS), are important. FT-ICR MS has been successfully used to analyze complex environmental organic molecule mixtures such as natural, soil, particulate, and dissolved organic matter. Despite its success, many limitations still need to be overcome. Sample preparation, ionization, structural identification, chromatographic separation, and data interpretation are some key areas that have been the focus of numerous studies. This review describes key developments in analytical techniques in these areas to aid researchers seeking to start or continue investigations for the molecular-level understanding of environmental organic compound mixtures.

Discovery of Polar Ozonation Byproducts via Direct Injection of Effluent Organic Matter with Online LC-FT-ICR-MS

Effluent organic matter (EfOM), a major ozone consumer during wastewater ozonation, is a complex mixture of natural and anthropogenic organic molecules. Ozonation of EfOM adds to molecular complexity by introducing polar and potentially mobile ozonation byproducts (OBPs). Currently, nontargeted direct infusion (DI) ultrahigh resolution mass spectrometry (e.g. FT-ICR-MS) is used to study OBPs but requires sample extraction, limiting the accessible polarity range of OBPs. To better understand the impact of ozonation on EfOM and the formation of polar OBPs, nonextracted effluent was analyzed by direct injection onto a reversed-phase liquid chromatography system (RP-LC) online hyphenated with an FT-ICR-MS. Over four times more OBPs were detected in nonextracted EfOM compared to effluent extracted with solid phase extraction and measured with DI-FT-ICR-MS (13817 vs 3075). Over 1500 highly oxygenated OBPs were detected exclusively in early eluting fractions of nonextracted EfOM, indicating polar OBPs. Oxygenation of these newly discovered OBPs is higher than previously found, with an average molecular DBE-O value of -3.3 and O/C ratio of 0.84 in the earliest eluting OBP fractions. These polar OBPs are consistently lost during extraction but may play an important role in understanding the environmental impact of ozonated EfOM. Moreover, 316 molecular formulas classified as nonreactive to ozone in DI-FT-ICR-MS can be identified with LC-FT-ICR-MS as isomers with varying degrees of reactivity, providing for the first time experimental evidence of differential reactivity of complex organic matter isomers with ozone.

Relation between lignin molecular profile and fungal exo-proteome during kraft lignin modification by Trametes hirsuta LE-BIN 072

The process of kraft lignin modification by the white-rot fungus Trametes hirsuta was investigated using electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI FT-ICR MS), and groups of systematically changing compounds were delineated. In the course of cultivation, fungus tended to degrade progressively more reduced compounds and produced more oxidized ones. However, this process was not gradual - the substantial discontinuity was observed between 6th and 10th days of cultivation. Simultaneously, the secretion of ligninolytic peroxidases by the fungus was changing in a cascade manner - new isoenzymes were added to the mixture of the already secreted ones, and once new isoenzyme appeared both its relative quantity and number of isoforms increased as cultivation proceeded. It was proposed, that the later secreted peroxidases (MnP7 and MnP1) possess higher substrate affinity for some phenolic compounds and act in more specialized manner than the early secreted ones (MnP5 and VP2).

Soil Organic Matter Characterization by Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR MS): A Critical Review of Sample Preparation, Analysis, and Data Interpretation

The biogeochemical cycling of soil organic matter (SOM) plays a central role in regulating soil health, water quality, carbon storage, and greenhouse gas emissions. Thus, many studies have been conducted to reveal how anthropogenic and climate variables affect carbon sequestration and nutrient cycling. Among the analytical techniques used to better understand the speciation and transformation of SOM, Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) is the only technique that has sufficient mass resolving power to separate and accurately assign elemental compositions to individual SOM molecules. The global increase in the application of FTICR MS to address SOM complexity has highlighted the many challenges and opportunities associated with SOM sample preparation, FTICR MS analysis, and mass spectral interpretation. Here, we provide a critical review of recent strategies for SOM characterization by FTICR MS with emphasis on SOM sample collection, preparation, analysis, and data interpretation. Data processing and visualization methods are presented with suggested workflows that detail the considerations needed for the application of molecular information derived from FTICR MS. Finally, we highlight current research gaps, biases, and future directions needed to improve our understanding of organic matter chemistry and cycling within terrestrial ecosystems.

Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) peak intensity normalization for complex mixture analyses

RATIONALE

Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is a preferred technique for analyzing complex organic mixtures. Currently, there is no consensus normalization approach, nor an objective method for selecting one, for quantitative analyses of FT-ICR-MS data. We investigate a method to evaluate and score the amount of bias various normalization approaches introduce into the data.

METHODS

We evaluate the ability of the Statistical Procedure for the Analysis of Normalization Strategies (SPANS) to guide the selection of appropriate normalization approaches for two different FT-ICR-MS data sets. Furthermore, we test the robustness of SPANS results to changes in SPANS parameter values and assess the impact of using various normalization approaches on downstream statistical analyses.

RESULTS

The normalization approach identified by SPANS differed for the two data sets. Normalization methods impacted the statistical significance of peaks differently, underscoring the importance of carefully evaluating potential methods. More consistent SPANS scores resulted when at least 120 significant peaks are used, where larger sets of peaks were obtained by increasing the p-value threshold. Interestingly, we show that total sum scaling and highest peak normalization, used in previous studies, underperformed relative to SPANS-recommended normalization approaches.

CONCLUSIONS

Although there is no single, best normalization method for all data sets, SPANS provides a mechanism to identify an appropriate normalization method for analyzing FT-ICR-MS data quantitatively. The number of peaks used in the background distributions of SPANS contributes more significantly to the reproducibility of results than the p-value thresholds used to obtain those peaks.

Fate of N-nitrosodimethylamine and its precursors during a wastewater reuse trial in the Llobregat River (Spain)

In summer 2019, a full-scale trial was carried out to investigate the effects in drinking water quality when tertiary treated wastewater was discharged into the Llobregat River upstream of the intake of one of the major drinking water treatment plants of Barcelona and its metropolitan area. Two scenarios were investigated, i.e. discharging the reclaimed water with and without chemical disinfection with chlorine. This study investigates the concentration of N-nitrosodimethylamine (NDMA) as the specific disinfection conditions employed in this trial may favor its formation. To this aim, both NDMA and NDMA formation potential, were measured. The river contained NDMA at very low concentrations, but the concentration of NDMA precursors was already high. The NDMA concentration was reduced from discharge to the river to drinking water intake probably due to a combined effect of dilution and photolysis. The formation potential was also reduced probably due to dilution and biodegradation. The concentration of NDMA in the drinking water was always low (<7.3 ng/L), although the formation potential was above 10 ng/L in one sample. Dissolved organic matter characterization by high resolution mass spectrometry revealed differences between the nature of the organic matter in the river before and after reclaimed water discharge.

Application of Fourier transform ion cyclotron resonance mass spectrometry in deciphering molecular composition of soil organic matter: A review

Swiftly deciphering soil organic matter (SOM) composition is critical for research on soil degradation and restoration. Recent advances in analytical techniques (e.g., optical methods and mass spectrometry) have expanded our understanding of the composition, origin, and evolution of SOM. In particular, the use of Fourier transform ion cyclotron resonance mass spectrometers (FTICR-MS) makes it possible to interpret SOM compositions at the molecular level. In this review, we discuss extraction, enrichment, and purification methods for SOM using FTICR-MS analysis; summarize ionization techniques, FTICR-MS mechanisms, data analysis methods, and molecular compositions of SOM in different environments (providing new insights into its origin and evolution); and discuss factors affecting its molecular diversity. Our results show that digenesis, combustion, pyrolysis, and biological metabolisms jointly contribute to the molecular diversity of SOM molecules. The SOM thus formed can further undergo photodegradation during transportation from land to fresh water (and subsequently oceans), resulting in the formation of dissolved organic matter (DOM). Better understanding the molecular features of DOM therefore accelerates our understanding of SOM evolution. In addition, we assess the degradation potential of SOM in different environments to better inform soil remediation methods. Finally, we discuss the merits and drawbacks of applying FTICR-MS on the analysis of SOM molecules, along with existing gaps in knowledge, challenges, and new opportunities for research in FTICR-MS applications and SOM identification.

Online Counter Gradient LC-FT-ICR-MS Enables Detection of Highly Polar Natural Organic Matter Fractions

Natural organic matter (NOM) is a highly complex mixture of natural organic molecules. The recent developments in NOM molecular characterization methods have shown that ESI-FT-ICR hyphenated with liquid chromatography (LC) is a promising approach to also obtain chemical information (such as polarity and molecular size) about NOM molecules. However, due to changing solvent composition during gradient elution in LC-FT-ICR-MS, ionization conditions also change throughout the chromatographic separation process. In this study, we applied a post-LC column counter gradient (CG) to ensure stable solvent conditions for transient ESI-MS signals. Suwanee River Fulvic Acid (SRFA) standard and a peat pore water were used as representative dissolved NOM samples for method development and validation. Our results show that in polar NOM fractions (which elute with <50% methanol) the TIC intensity and number of assigned molecular formulas were increased by 48% and 20%, as compared to the standard gradient (SG) method. Further application of a Q-isolation and selective ion accumulation for low abundance fractions revealed over 3 times more molecular formulas (especially for CHNO, CHOS, CHNOS formula classes) than in full scan mode. The number of detected highly polar NOM compounds (with elemental ratios H/C < 1, O/C > 0.6) were more than 20 times larger for CG-LC mode as compared to direct infusion (DI) (5715 vs 266 MF). We conclude that the application of a postcolumn counter gradient in LC-FT-ICR-MS analyses of NOM offers novel insight into the most polar fractions of NOM which are inaccessible in conventional DI measurements.

Application of Fourier transform ion cyclotron resonance mass spectrometry to characterize natural organic matter

Advances in the ultra-high-resolution mass spectroscopy lead to a deep insight into the molecular characterization of natural organic matter (NOM). Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) has been used as one of the most powerful tools to decipher NOM molecules. In FTICR-MS analysis, the matrix effects caused by the co-occurring inorganic substances in water samples greatly affect the ionization of NOM molecules. The inherent complexity of NOM may hinder its component classification and formula assignment. In this study, basic principles and recent advances for sample separation and purification approaches, ionization methods, and the evolutions in formula assignment and data exploitation of the FTICR-MS analysis were reviewed. The complementary characterization methods for FTICR-MS were also reviewed. By coupling with other developed/developing characterization methods, the statistical confidence for inferring the NOM compositions by FTICR-MS was greatly improved. Despite that the refined separation procedures and advanced data processing methods for NOM molecules have been exploited, the big challenge for interpreting NOM molecules is to give the basic structures of them. Online share of the FTICR-MS data, further optimizing the FTICR-MS technique, and coupling this technique with more characterization methods would be beneficial to improving the understanding of the composition and property of NOM.

Mass spectrometry-based metabolomics for an in-depth questioning of human health

Today, metabolomics is becoming an indispensable tool to get a more comprehensive analysis of complex living systems, providing insights on multiple aspects of physiology. Although its application in large scale population-based studies is very challenging due to the processing of large sample sets as well as the complexity of data information, its potential to characterize human health is well recognized. Technological advances in metabolomics pave the way for the efficient biomarker discovery of disease etiology, diagnosis and prognosis. Here, different steps of the metabolomics workflow, particularly mass spectrometry-based approaches, are discussed to demonstrate the potential of metabolomics to address biological questioning in human health. First an overview of metabolomics is provided with its interest in human health studies. Analytical development and advances in mass spectrometry instrumentation and computational tools are discussed regarding their application limits. Advancing metabolomics for applicability in human health and large-scale studies is presented and discussed in conclusion.

In-situ monitoring of the unstable bacterial adhesion process during wastewater biofilm formation: A comprehensive study

The initial bacterial adhesion phase is a pivotal and unstable step in the formation of biofilms. The initiation of biofilm formation is an unstable process caused by the reversible adhesion of bacteria, which is always time-consuming and yet to be elucidated. In this study, impedance-based real time cell analysis (RTCA) was employed to comprehensively investigate the initial bacterial adhesion process. Results showed that the time required for the unstable adhesion process was significantly (p < 0.05) reduced by increasing the initial concentration of bacteria, which is mainly attributed to the large deposition rate of bacteria at high concentrations. In addition, the unstable adhesion process is also regulated by shear stress, derived in this work from orbital shaking. Shear stress improves the reversibility of unstable bacterial attachment. Furthermore, attachment characteristics during the unstable phase vary between different species of bacteria (Sphingomonas rubra, Nakamurella multipartita and mixed bacteria). The S. rubra strain and mixed culture were more prone to adhere to the substratum surface during the unstable process, which was attributed to the smaller xDLVO energy barrier and motility of species in comparison with N. multipartita. Meanwhile, the molecular composition of extracellular polymeric substances (EPS) in the initial attachment phase presented a significant difference in expressed proteins, indicating the important role of proteins in EPS that strengthen bacterial adhesion. Overall, these findings suggest that during the biofilm reactor start-up process, seed sludge conditions, including the bacterial concentration, composition and hydraulics, need to be carefully considered.

Petroleomics: Tools, Challenges, and Developments

The detailed molecular characterization of petroleum-related samples by mass spectrometry, often referred to as petroleomics, continues to present significant analytical challenges. As a result, petroleomics continues to be a driving force for the development of new ultrahigh resolution instrumentation, experimental methods, and data analysis procedures. Recent advances in ionization, resolving power, mass accuracy, and the use of separation methods, have allowed for record levels of compositional detail to be obtained for petroleum-related samples. To address the growing size and complexity of the data generated, vital software tools for data processing, analysis, and visualization continue to be developed. The insights gained impact upon the fields of energy and environmental science and the petrochemical industry, among others. In addition to advancing the understanding of one of nature's most complex mixtures, advances in petroleomics methodologies are being adapted for the study of other sample types, resulting in direct benefits to other fields.

Molecular characterization of water extractable Euglena gracilis cellular material composition using asymmetrical flow field-flow fractionation and high-resolution mass spectrometry

Asymmetrical flow field-flow fractionation (AF4) and high-resolution Orbitrap mass spectrometry (HRMS) were used to separate and characterize cellular fractions of the dark- and light-grown Euglena gracilis cellular material. Biological replicates analyzed by HRMS shared 21-73% of commonly detected m/z values. Greater variability in shared features was found in light-grown cellular fractions (p < 0.05), likely due to small variations in growth stage. Significant differences in molecular composition were observed between AF4 cellular fractions, with dark cell fractions showing a propensity towards carbohydrate-like and tannin-like compounds, and higher double-bond equivalent (DBE) and modified aromatic index (AI_mod) were associated with light-grown cell fractions. Fractionation and high-resolution mass spectrometry aided characterization demonstrated the power of the AF4 to selectively cater to certain compounds/cellular entities with distinct compositional classes and double-bond equivalents and aromaticity index characteristics. Graphical abstract.

CWPO Degradation of Methyl Orange at Circumneutral pH: Multi-Response Statistical Optimization, Main Intermediates and by-Products

The catalytic wet peroxide oxidation (CWPO) of the industrial azo-dye methyl orange (MO) activated by an Al/Fe-pillared clay catalyst was optimized by the Response-Surface Methodology (RSM). Three sequential sets of factorial 2k central composite experiments were required for the full optimization of the process; catalyst loading and stoichiometric dose of hydrogen peroxide were the experimental factors studied through different times of reaction by means of all, Dissolved Organic Carbon (DOC) removal, Total Nitrogen (TN) removal, reacted fraction of hydrogen peroxide, and decolorization as experimental responses to be maximized. The resulting single-response RSM optimums were combined in a multi-response Desirability function ruling out the differential effect of adsorption on the catalyst's surface by defining all responses per gram of clay catalyst. Former two statistical sets of experiments (DOE-1 and DOE-2) showed the CWPO degradation of MO to get favored at increasing both catalyst loading and time of reaction (up to 180 min). Afterwards, third final design of experiments (DOE-3) displayed 75% of DOC removal, 78% of TN removal, 97% of reacted H2O2, and 95% of decolorization by using a catalyst loading of 5.0 g/L of Al/Fe-PILC together with just 50% of the stoichiometric amount of H2O2. The multi-response optimum conditions based on the Desirability function showed excellent fitting explaining at least 99.3% of the optimal overall responses at 95% of confidence. A further analysis revealed that no one of the non-controllable variables under real conditions of industrial wastewater treatment (covariates): starting total organic carbon (TOC) (2.0-20 mg/L), temperature (5.0-25°C) or circumneutral pH (6.0-9.0), exhibited statistically significant effect (P > 0.05), suggesting the system to be almost insensitive against them within studied range of close to ambient conditions in the tropic. Finally, HPLC/PDA and GC/FID measurements identified phenol, cyclohexa-2,5-diene-1,4-dione, phenylamine, N-methylaniline and N,N-dimethylaniline in very low concentrations as main intermediates in the CWPO degradation of MO, which nevertheless disappeared over 90 min of treatment. Meanwhile, 4-aminobenzenesulfonic and oxalic acids were recorded as unique by-products at final time of reaction, but both of them fairly less toxic than the starting azo-dye.

Electrochemical characterization of natural organic matter by direct voltammetry in an aprotic solvent

The complex and indeterminant composition of NOM makes characterization of its redox properties challenging. Approaches that have been taken to address this challenge include chemical probe reactions, potentiometric titrations, chronocoulometry, and voltammetry. In this study, we revisit the use of direct voltammetric methods in aprotic solvents by applying an expanded and refined suite of methods to a large set of NOM samples and model compounds (54 NOM samples from 10 different sources, 7 NOM model compounds, and 2 fresh extracts of plant materials that are high in redox-active quinonoid model compounds dissolved in DMSO). Refinements in the methods of fitting the data obtained by staircase cyclic voltammetry (SCV) provided improved definition of peaks, and square wave voltammetry (SWV), performed under the same conditions as SCV, provided even more reliable identification and quantitation of peaks. Further evidence is provided that DMSO improves the electrode response by unfolding some of the tertiary structure of NOM polymers, thereby allowing greater contact between redox active functional groups and the electrode surface. We averaged experimental peak potentials for all NOM compounds and calculated potentials in water. Average values for Epa1, Epc1, and Ep1 in DMSO were -0.866 ± 0.069, -1.35 ± 0.071, and -0.831 ± 0.051 V vs. Ag/Ag+, and -0.128, -0.613, and -0.0930 V vs. SHE in water. In addition to peak potentials, the breadth of SCV peaks was quantified as a way to characterize the degree to which the redox activity of NOM is due to a continuum of contributing functional groups. The average breadth values were 1.63 ± 0.24, 1.28 ± 0.34, and 0.648 ± 0.15 V for Epa1, Epc1, and Ep1 respectively. Comparative analysis of the overall dataset-from SCV and SWV on all NOMs and model compounds-revealed that NOM redox properties vary over a narrower range than expected based on model compound properties. This lack of diversity in redox properties of NOM is similar to conclusions from other recent work on the molecular structure of NOM, all of which could be the result of selectivity in the common extraction methods used to obtain the materials.

Pushing the analytical limits: new insights into complex mixtures using mass spectra segments of constant ultrahigh resolving power

A new strategy has been developed for characterization of the most challenging complex mixtures to date, using a combination of custom-designed experiments and a new data pre-processing algorithm. In contrast to traditional methods, the approach enables operation of Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) with constant ultrahigh resolution at hitherto inaccessible levels (approximately 3 million FWHM, independent of m/z). The approach, referred to as OCULAR, makes it possible to analyze samples that were previously too complex, even for high field FT-ICR MS instrumentation. Previous FT-ICR MS studies have typically spanned a broad mass range with decreasing resolving power (inversely proportional to m/z) or have used a single, very narrow m/z range to produce data of enhanced resolving power; both methods are of limited effectiveness for complex mixtures spanning a broad mass range, however. To illustrate the enhanced performance due to OCULAR, we show how a record number of unique molecular formulae (244 779 elemental compositions) can be assigned in a single, non-distillable petroleum fraction without the aid of chromatography or dissociation (MS/MS) experiments. The method is equally applicable to other areas of research, can be used with both high field and low field FT-ICR MS instruments to enhance their performance, and represents a step-change in the ability to analyze highly complex samples.

Leachates and natural organic matter. A review of their biotreatment using fungi

Leachates have different concentrations of organic matter and levels of biodegradability, depending on the age of the landfill and they must be treated using appropriate techniques, such as fungal degradation, in order to protect the environment and water resources. Natural organic matter contains the same type of organic species as old and medium age leachates, but at lower concentrations. The present study compiles and assesses all the available literature on the biotreatment of these compounds, mainly humic acids, by fungi. It was found that the efficiency of the fungal biodegradation of these wastewaters depends on the characteristics and concentration of the organic matter in the leachate, the microorganisms selected and whether they were immobilized or not, the nutrients present in the medium and their concentrations, the experimentation time, the temperature and the pH. The influence of the mode of inoculation has only been studied in natural organic matter, but similar effects are expected in the treatment of the leachates. The interactions between these parameters are complex and the optimal conditions have to be determined by laboratory and pilot testing, employing multivariate statistical techniques and experimental design.

Orbitrap molecular fingerprint of dissolved organic matter in natural waters and its relationship with NDMA formation potential

N-nitrosodimethylamine (NDMA) is a disinfection byproduct that has been classified as probable human carcinogen by the US Environmental Protection Agency. According to the published literature, natural dissolved organic matter (DOM) can be a source of NDMA precursors in drinking water. New advances in chemical characterization of DOM with high resolution mass spectrometry (HRMS) are allowing researchers to understand these ultra-complex mixtures. The objective of this study is to investigate analytical methodologies based on HRMS to explore NDMA formation from natural waters. To this aim, different waters from drinking water reservoirs in Spain containing NDMA precursors (quantified by means of NDMA formation potential) in concentrations between 17 and 60 ng/L have been studied. The workflow includes DOM solid-phase extraction and Orbitrap analysis with and without chromatographic separation. Here, we show that the molecular composition of DOM across the studied drinking water reservoirs is correlated with the NDMA formation potential. In particular, we found that NDMA formation potential is associated with compounds with high hydrogen saturation (H/C ≥ 1.5), corresponding also to reservoirs with higher background nutrient concentrations and wastewater indicators. Further chromatographic fractionation did not allow better definition of these possible precursors as they were present in different fractions of the chromatogram, suggesting that they were isomerically complex.

Molecular characteristics, proton dissociation properties, and metal binding properties of soil organic matter: A theoretical study

Soil organic matter (SOM) is a key soil sorbent with a large number of reactive binding sites that may complex with metals, controlling their fate, transport, and bioavailability in soil. However, due to the complex and heterogeneous nature of SOM, it is not easy to probe its physical and chemical properties at the molecular level. In this study, an a priori method was developed to predict the molecular properties of SOM, which incorporated computational molecular modeling, SPARC Performs Automated Reasoning in Chemistry's (SPARC's) chemical reactivity models, and linear free energy relationships (LFERs). Specifically, the method uses SOM models simulated by molecular dynamics modeling based on the experimental elemental composition and functional group information of SOM. For the molecular characteristics, the molecular H/C and O/C ratios, molecular weight, aromatic index, and double bond equivalence of the SOM molecules were calculated. For the proton binding constants, the SPARC was used to calculate the microscopic pK_a values of every binding sites of individual molecules of the SOM model. Based on the pK_a values, the metal binding constants for individual monodentate binding sites were calculated using the Irving-Rossotti LFERs for different heavy metals. The results agreed reasonably with the default values used in the Windermere Humic Aqueous Model (WHAM) (VI) for the investigated metals. The theoretical SOM models, to some extent, represented the average properties of the investigated SOM. Overall, this study gives new quantitative and molecular insight into the structure and chemical properties of SOM. Detailed deprotonation and metal-SOM complexation information was gained for individual SOM binding sites. Such feasible and straightforward predictive scheme is useful to assess the risk of heavy metals in various aquatic and terrestrial environment involving heterogeneous natural organic matter.

The Contribution of Coniferous Canopy to the Molecular Diversity of Dissolved Organic Matter in Rainfall

Rainwater interacts with tree canopies in forest ecosystems, which greatly influence its quality. However, little information is available regarding how tree canopies influence dissolved organic matter (DOM) in rainwater. To examine this, we collected bulk deposition (rainfall) and throughfall in a conifer (Chamaecyparis obtusa) plantation, western Japan, during a rain event, and analyzed their DOM molecular compositions using ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry. The dissolved organic carbon flux and the number of DOM molecular species detected were approximately seven times and three times higher in throughfall than in rainfall, respectively. We found that the average proportion of molecular species shared between five sample replicates was larger in throughfall (69%) than in rainfall (50%). Nonmetric multidimensional scaling revealed that the molecular species were significantly differentiated between throughfall and rainfall, and the dissimilarity among the replicates was much smaller in throughfall. This indicates that the quality of DOM in rainwater became spatially homogeneous due to contact with tree canopies. The number of lignin-like molecules was larger than those of any other biomolecular compounds in throughfall and seven times larger than in rainfall, suggesting that many of plant-derived DOM molecules were dissolved into rainwater.

Atmo-ecometabolomics: a novel atmospheric particle chemical characterization methodology for ecological research

Aerosol particles play important roles in processes controlling the composition of the atmosphere and function of ecosystems. A better understanding of the composition of aerosol particles is beginning to be recognized as critical for ecological research to further comprehend the link between aerosols and ecosystems. While chemical characterization of aerosols has been practiced in the atmospheric science community, detailed methodology tailored to the needs of ecological research does not exist yet. In this study, we describe an efficient methodology (atmo-ecometabolomics), in step-by-step details, from the sampling to the data analyses, to characterize the chemical composition of aerosol particles, namely atmo-metabolome. This method employs mass spectrometry platforms such as liquid and gas chromatography mass spectrometries (MS) and Fourier transform ion cyclotron resonance MS (FT-ICR-MS). For methodology evaluation, we analyzed aerosol particles collected during two different seasons (spring and summer) in a low-biological-activity ecosystem. Additionally, to further validate our methodology, we analyzed aerosol particles collected in a more biologically active ecosystem during the pollination peaks of three different representative tree species. Our statistical results showed that our sampling and extraction methods are suitable for characterizing the atmo-ecometabolomes in these two distinct ecosystems with any of the analytical platforms. Datasets obtained from each mass spectrometry instrument showed overall significant differences of the atmo-ecometabolomes between spring and summer as well as between the three pollination peak periods. Furthermore, we have identified several metabolites that can be attributed to pollen and other plant-related aerosol particles. We additionally provide a basic guide of the potential use ecometabolomic techniques on different mass spectrometry platforms to accurately analyze the atmo-ecometabolomes for ecological studies. Our method represents an advanced novel approach for future studies in the impact of aerosol particle chemical compositions on ecosystem structure and function and biogeochemistry.

Facet-Mediated Adsorption and Molecular Fractionation of Humic Substances on Hematite Surfaces

Interactions between dissolved organic matter (DOM) and iron oxyhydroxides have important environmental and geochemical implications. The present study employed two hematite nanocrystals to investigate the adsorption and molecular fractionation of two typical humic substances (HSs) using electrospray ionization coupled with Fourier transform ion cyclotron resonance mass spectrometry (ESI-FT-ICR-MS). Hematite with a predominant exposure of {100} facets induced more pronounced adsorption and molecular fractionation of HSs than {001} facets, indicating that the interfacial adsorptive fractionation process of HSs was mediated by exposed facets of hematite. Further exploration of the surface OH groups of the two hematite nanocrystals confirms that the facet-mediated molecular fractionation of HSs was attributable to the abundance of singly iron-atom coordinated -OH sites on the hematite surfaces. Molecules with a high oxidation state and high aromaticity such as oxidized black carbon, polyphenol-like, and tannic-like compounds preferentially formed ligand-exchange complexes with singly coordinated -OH groups on the hematite surfaces, inducing the selective binding and molecular fractionation of HSs at the mineral-water interface. These results demonstrate that singly iron-atom coordinated -OH sites determine DOM adsorption and mediate molecular fractionation on hematite surfaces, and this contributes substantially to our understanding of the molecular mechanisms of iron oxyhydroxide-mediated molecular exchange of DOM in soils and/or sediments.

Optical and molecular characterization of dissolved organic matter (DOM) in the Arctic ice core and the underlying seawater (Cambridge Bay, Canada): Implication for increased autochthonous DOM during ice melting

Sea ice contains a large amount of dissolved organic matter (DOM), which can be released into the ocean once it melts. In this study, Arctic sea ice DOM was characterized for its optical (fluorescence) properties as well as the molecular sizes and composition via size exclusion chromatography and Fourier transformation ion cyclotron resonance mass spectrometry (FT-ICR MS). Ice cores were collected along with the underlying seawater samples in Cambridge Bay, an Arctic area experiencing seasonal ice formation. The ice core samples revealed a marked enrichment of dissolved organic carbon (DOC) compared to the seawater counterparts (up to 6.2 times greater). The accumulation can be attributed to in situ production by the autotrophic and heterotrophic communities. Fluorescence excitation emission matrices (EEMs) elaborated with parallel factor analysis (PARAFAC) evidenced the prevalence of protein-like substances in the ice cores, which likely results from in situ production followed by accumulation in the ice. Size exclusion chromatography further revealed the in situ production of all DOM size fractions, with the exception of the humic substance fraction. The majority of DOM in both the ice and seawater consists of low molecular weight compounds (<350 Da) probably derived by the microbial degradation/transformation of freshly produced DOM. Molecular characterization also supported the in situ production of DOM and highlighted the marked difference in molecular composition between sea ice and seawater. This study provides new insights into the possible role of sea ice DOM in the Arctic carbon cycle under climate change.

Molecular transformation of natural and anthropogenic dissolved organic matter under photo-irradiation in the presence of nano TiO2

Photochemical transformation of dissolved organic matter (DOM) plays a very important role in the cycling of organic carbon in aquatic systems. Increasing release of photoactive nanoparticles such as titanium dioxide nanoparticles (nano TiO₂) into surface water may impact this process. The present study employed Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) to examine the molecular transformation of natural DOM (peat DOM, DOM_p) and anthropogenic DOM (sludge-derived DOM, DOM_s) under photo-irradiation as affected by nano TiO₂. Differences in molecular components between DOM_p and DOM_s were observed. DOM_s contained more heteroatom formulas (76%) with low aromaticity and low carbon oxidation state than did DOM_p (22%). The presence of nano TiO₂ resulted in significant decreases in both DOM content and molecular diversity under photo-irradiation. Consistent alterations were observed between DOM_p and DOM_s such that high molecular weight compounds, high aromaticity and/or heteroatom S-containing compounds were more easily photodegraded in the presence of nano TiO₂; whereas the average carbon oxidation state decreased in DOM_p but increased in DOM_s, likely due to the significant differences in O abundance, especially in the contents of carboxyl moieties, between DOM_p and DOM_s. The findings of the present study suggest that the release of nano TiO₂ into aquatic environment will accelerate the consumption of dissolved organic carbon and the attenuation of molecular diversity for both DOM in waters.

A new approach for evaluating transformations of dissolved organic matter (DOM) via high-resolution mass spectrometry and relating it to bacterial activity

Streams are important sites of transformation of dissolved organic matter (DOM). The molecular characterization of DOM-quality changes requires sophisticated analytical evaluation techniques. The goal of our study was to link molecular DOM transformation with bacterial activity. We measured the degradation of leaf leachate over a gradient of bacterial production obtained by different rates of percolation of sediments in seven experimental flumes on five sampling dates. We developed a new strategy for evaluating molecular formula data sets obtained by ultra-high resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS), in which the time-dependent change of component abundance was fitted by a linear regression model after normalization of mass peak intensities. All components were categorized by calculating the slope (change of percent intensity per day) in each of the seven flumes. These slopes were then related to cumulative bacterial production. The concentration of DOM decreased quickly in all flumes. Bacterial activity was higher in flumes with percolated sediment than in those without percolation, whereas plankton bacterial activity was higher in flumes without percolation or without sediment. There were no differences in molecular-DOM characteristics between flumes, but there were distinct changes over time. Positive slopes, i.e. increasing intensities over time, were found for small molecules (MW < 450 Da) and high O/C ratios, whereas decreasing intensities were observed less often and only for large molecules and low O/C ratios. The positive slopes of produced components showed a positive relationship to bacterial production for small and for oxygen-rich components. The negative slopes of degraded components were negatively related to bacterial production for large and for oxygen-deficient molecules. Overall, the approach provided new insights into the transformation of specific molecular DOM components.

The effect of advanced secondary municipal wastewater treatment on the molecular composition of dissolved organic matter

There is a growing interest in water reuse and in recovery of nutrients from wastewater. Because many advanced treatment processes are designed to remove organic matter, a better understanding of the composition of dissolved organic matter (DOM) in wastewater is needed. To that end, we assessed DOM in the Nine Springs Wastewater Treatment Plant in Madison, Wisconsin by UV-visible spectroscopy and Fourier transform-ion cyclotron resonance mass spectrometry. Samples were collected from the influent and effluent of two different secondary treatment processes and their respective secondary clarifiers, the UV disinfection unit, and an Ostara treatment system, which produces struvite via chemical precipitation. The optical properties reveal that DOM throughout the plant is relatively aliphatic and is low in molecular weight compared to DOM in freshwater systems. Furthermore, the DOM is rich in heteroatoms (e.g., N, S, P, and Cl) and its molecular formulas are present in the lipid-, protein-, carbohydrate-, and lignin-like regions of van Krevelen diagrams. Secondary treatment produces DOM that is more aromatic and more complex, as shown by the loss of highly saturated formulas and the increase in the number of CHO, CHON, and CHOP formulas. The two secondary treatment processes produce DOM with distinct molecular compositions, while the secondary clarifiers and UV disinfection unit result in minimal changes in DOM composition. The Ostara process decreases the molecular weight of DOM, but does not otherwise alter its composition. The optical properties agree with trends in the molecular composition of DOM within the main treatment train of the Nine Springs plant.

Mass Defect from Nuclear Physics to Mass Spectral Analysis

Mass defect is associated with the binding energy of the nucleus. It is a fundamental property of the nucleus and the principle behind nuclear energy. Mass defect has also entered into the mass spectrometry terminology with the availability of high resolution mass spectrometry and has found application in mass spectral analysis. In this application, isobaric masses are differentiated and identified by their mass defect. What is the relationship between nuclear mass defect and mass defect used in mass spectral analysis, and are they the same? Graphical Abstract ᅟ.

Comparing the Spectroscopic and Molecular Characteristics of Different Dissolved Organic Matter Fractions Isolated by Hydrophobic and Anionic Exchange Resins Using Fluorescence Spectroscopy and FT-ICR-MS

Despite the environmental significance of dissolved organic matter (DOM), characterizing DOM is still challenging due to its structural complexity and heterogeneity. In this study, three different chemical fractions, including hydrophobic acid (HPOA), transphilic acid (TPIA), and hydrophilic neutral and base (HPIN/B) fractions, were separated from bulk aquatic DOM samples, and their spectral features and the chemical composition at the molecular level were compared using both fluorescence excitation emission matrix-parallel factor analysis (EEM-PARAFAC) and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). The HPIN/B fraction was distinguished from the two acidic fractions (i.e., HPOA and TPIA) by the EEM-PARAFAC, while the TPIA fraction was discriminated by using the molecular parameters derived from the FT-ICR MS analyses. Statistical comparison suggests that the spectral dissimilarity among the three chemical fractions might result from the acido-basic properties of DOM samples, while the differences in molecular composition were more likely to be affected by the hydrophobicity of the DOM fractions. The non-metric multidimensional scaling map further revealed that the HPOA was the most heterogeneous among the three fractions. The number of overlapping formulas among the three chemical fractions constituted only <5% of all identified formulas, and those between two different fractions ranged from 2.0% to 24.1%, implying relatively homogeneous properties of the individual chemical fractions with respect to molecular composition. Although employing chemical fractionation achieved a lowering of the DOM heterogeneity, prevalent signatures of either acido-basic property or the hydrophobic nature of DOM on the characteristics of three chemical isolated fractions were not found for this study.

Photochemically Induced Bound Residue Formation of Carbamazepine with Dissolved Organic Matter

More than 400 new nitrogen containing products were detected upon experimental sunlight photolysis of the pharmaceutical carbamazepine (CBZ) in the presence of dissolved organic matter (DOM) by Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). These products were presumably formed through covalent binding of CBZ phototransformation products with DOM molecules. About 50% of these newly formed bound residues contained one nitrogen atom and had a molecular mass between 375 and 525 Da, which was 150 to 200 Da higher than for an average DOM molecule. In addition, a previously unknown CBZ phototransformation product, 3-quinolinecarboxylic acid (3-QCA), was identified by liquid chromatography high resolution tandem mass spectrometry (LC-HRMS/MS). 3-QCA was likely formed through oxidative ring cleavage and subsequent decarboxylation of acridine, a well-known phototransformation product of CBZ. Collision induced dissociation experiments and Kendrick mass defect analyses corroborated that about 160 of the new products were formed via covalent binding of 3-QCA with DOM molecules of above-average O/C and H/C ratios. Experiments at lower CBZ concentration suggested that the importance of bound residue formation increases with increasing DOM/CBZ ratios. Photochemically induced bound residue formation of polar contaminants with DOM in the aqueous phase is thus a disregarded pathway along which contaminants can be transformed in the environment. The method presented here offers a new possibility to study the formation of bound residues, which may be of relevance also for other transformation processes in natural waters where radical intermediates are generated.