Assessment of molecular diversity of lignin products by various ionization techniques and high-resolution mass spectrometry

Science of the Total Environment 713 (2020) 136573

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Assessment of molecular diversity of lignin products by various ionization techniques and high-resolution mass spectrometry Yulin Qi a,⁎, Pingqing Fu a,⁎, Siliang Li a, Chao Ma a, Congqiang Liu a, Dietrich A. Volmer b a b

Institute of Surface-Earth System Science, Tianjin University, Tianjin, China Department of Chemistry, Humboldt-Universität zu Berlin, Berlin, Germany

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• Data processing for the lignin mass spectra • Various ionization methods revealed chemical diversity of lignin. • Sulfur- and phosphorous-containing compounds as biomarkers • FT-ICR MS in-cell isolation technique for MSn

a r t i c l e

i n f o

Article history: Received 16 September 2019 Received in revised form 5 January 2020 Accepted 6 January 2020 Available online 10 January 2020 Editor: Yolanda Picó Keywords: Lignin ESI APPI APCI FT-ICR MS

a b s t r a c t Lignin is a highly complex, plant-derived natural biomass component, the analysis of which requires significant demands on the analytical platform. Fourier transform ion cyclotron mass spectrometry (FT-ICR MS) has been shown to be able to readily assess the complexity of lignin and lignin degradation products by assigning tens of thousands of compounds with elemental formulae. Nevertheless, many experimental and instrumental parameters introduce discrimination towards certain components, which limits the comprehensive MS analysis. As a result, a complete characterization of the lignome remains a challenge. The present study investigated a degraded lignin sample using FT-ICR MS and compared several atmospheric pressure ionization methods, e.g., electrospray ionization, atmospheric-pressure chemical ionization, and atmospheric-pressure photoionization. The results clearly show that the number of heteroatoms (e.g., N, S, P) in the sample greatly increases the chemical diversity of lignin, while at the same time also providing potentially useful biomarkers. We demonstrate here that FT-ICR MS was able to directly isolate isotopically pure single components from the ultra-complex mixture for subsequent structural analysis, without the time-consuming chromatographic separation. Capsule: Various ionization techniques coupled to FT-ICR MS provide a powerful tool to assess the lignome coverage. © 2020 Elsevier B.V. All rights reserved.

⁎ Corresponding authors. E-mail addresses: [email protected] (Y. Qi), [email protected] (P. Fu).

https://doi.org/10.1016/j.scitotenv.2020.136573 0048-9697/© 2020 Elsevier B.V. All rights reserved.

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Y. Qi et al. / Science of the Total Environment 713 (2020) 136573

1. Introduction Lignin is a biomass component and second most abundant natural polymer behind cellulose. It is a potential source for valuable aromatic chemicals after degradation (Zakzeski et al., 2010). Structurally, lignin is a cross-linked polyphenolic polymer, composed of carbon, hydrogen, and oxygen, with molecular weight up to 10,000 Da (Tolbert et al., 2014). Lignin degradation products are usually phenols with carbon number between six to ten, which can be transferred to petroleumlike molecules via hydrodeoxygenation (Zhang et al., 2013). From an earth science point of view, lignin is a useful biomarker of land-derived organic matter due to its resistance to chemical and microbial degradation (Bugg et al., 2011). For example, lignin is a major contributor to soil organic matter (SOM) because vascular plants are exclusively terrestrial (Hedges et al., 1997). Its presence in aquatic environments can also serve as a marker of terrigenous organic matter inputs to such systems (Hedges et al., 1982). Hence, lignin in sediments has often been utilized in geochemical studies of soil, ice core, lakes and marine environments to trace the source of organic matter (Kawamura et al., 2012; Orem et al., 1997; Thevenot et al., 2010), to understand anthropogenic activities and to reconstruct the paleoenvironment (Tareq et al., 2011). In addition, lignin derivatives are ubiquitous in atmospheric aerosols from around the world (Kundu et al., 2012; Wang et al., 2006), which are mainly emitted in biomass burning processes (Chen et al., 2017; Fu et al., 2011; Simoneit et al., 2004). Prior to chemical analysis of lignin, techniques such as alkaline CuO catalyzed oxidation (Goñi and Montgomery, 2000) or the Kraft process (Chakar and Ragauskas, 2004) are often applied to break down lignin's interunit linkages into small methoxyphenyl or phenyl structural units. The major challenge in lignin studies remains the comprehensive elucidation of the individual compositions and/or discovery of chemically or geochemically-important biomarkers (Banoub et al., 2015). Recently, the term “lignome” has been introduced to describe biosynthesized lignin structures and those obtained following degradation (Morreel et al., 2010). The degraded lignin mixtures often contain tens of thousands of components (including constitutional isomers and isobars) with variable relative abundances (Banoub et al., 2007). Analytical methods such as UV/IR and nuclear magnetic resonance (NMR) only provide crude estimates of average structures and functional groups in lignin, however, information on lower abundant building blocks is often missed and sometimes analytical results are highly varied (Brinkmann et al., 2002; El Mansouri et al., 2012). High resolution mass spectrometry, such as Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), on the other hand, exhibits mass accuracy in the sub-ppm range, while consuming only very small amounts of sample. A full scan MS analysis of a lignin sample generates thousands of mass-to-charge ratio (m/z) features per sample in one measurement, and the individual compounds' elemental formula can be readily determined (Qi and Volmer, 2019a). The components of lignin degradation vary in size, functional groups, heteroatom content and acidity/basicity, depending on the degradation techniques used. Therefore, the individual components will not be equally suited to a single set of optimized instrumental parameters; for example, choice of ionization method. Electrospray ionization (ESI) is among the most widely applied ionization methods for lignin. Given the presence of significant numbers of hydroxyl, carboxyl and phenolic groups, the negative ion mode is mostly applied (Jarrell et al., 2014; Kiyota et al., 2012; Qi et al., 2016a). Atmospheric-pressure chemical ionization (APCI) is an alternative to ESI in lignin studies, which accesses small, thermally stable compounds (Banoub and Delmas, 2003; Morreel et al., 2010). Atmospheric pressure photoionization (APPI) is suitable for less polar molecules and is able to generate radical ions, with introduction of dopants, to enhance the signal intensity (Banoub et al., 2007). While mass spectrometry makes it readily possible to characterize the enormous number of compounds simultaneously,

processing the acquired data becomes a subsequent challenge. Attempts to address this problem have included the usage of the Kendrick mass defect (Hughey et al., 2001; Qi et al., 2016b), van Krevelen diagrams (Kim et al., 2003; Kosyakov et al., 2016), heat maps, double bond equivalents (DBE), and plots of carbon number versus DBE (Barrow et al., 2010; Thomas et al., 2019). The research described here is aimed at exploring the chemical diversity of an electrochemically degraded lignin sample, by systematic comparison of the spectral diversity provided by three different atmospheric-pressure ionization techniques (ESI, APCI, APPI). Due to the presence of hydroxyl groups, lignin is usually ionized by deprotonation. To obtain cationic species, in particular under positive ion ESI conditions, sodium adduct formation can be utilized, which, unfortunately, further complicates the mass spectra (Haupert et al., 2012). Furthermore, lignin will be neutralized when the attached sodium is eliminated, which makes it impossible to obtain structural information from tandem mass spectrometry (MSn). To overcome this problem, ammonium formate was added as an ionization promoter (Lu et al., 2016) in the present study to give protonated molecules [M + H]+. Ionization in positive ionization mode then allowed us to simultaneously detect side-components in the mixture such as protic phosphorus-containing compounds. A representative compound, [C12H27O4P + H]+, was chosen for MSn structural analysis. The FT-ICR MS in-cell isolation technique was utilized here to accurately select this precursor ion from a number of isobaric interferences; such an approach provides an elegant simplification of the mass analysis of the precursor ions, without the time-consuming chromatography separation.

2. Materials and methods 2.1. Chemicals Methanol, formic acid, ammonium formate, ammonium hydroxide, and alkali lignin were purchased from Sigma-Aldrich. Electrochemical degradation was performed as described previously (Reichert et al., 2012); the resulting powder was dissolved in water/methanol (50:50 v/v) and analyzed directly without acidic or basic buffers. In positive ion ESI, ammonium formate (0.1% w/v) was added as an ionization promoter (Lu et al., 2016).

2.2. Mass spectrometry and elemental analysis Lignin was ionized using APPI and APCI in negative ion mode; ESI was used in both positive and negative ion modes (optimized experimental parameters for ESI, APCI and APPI can be found in Supplementary material, Table S1). Mass spectra were recorded using a 7-Tesla solariX 2XR FT-ICR MS instrument equipped with quadupolar detection (Bruker Daltonics, GmbH, Bremen, Germany). For full scan mass spectra, MS spectra were acquired from m/z 115 to 1000 (where most NOM measurements are conducted at) with a transient size of 8 M words using the quadrupolar detection mode, apodized with a Sine window function, and zero-filled once. A total of 200 individual transients were collected and co-added to the enhance signal-to-noise (Qi and O'Connor, 2014), resulting in a resolving power of ~700,000 at m/ z 400. For MSn analyzes, the “Sweep+Shots” function was used, with an isolation power of 18%, notch width of 0.1, and cleanup shots power of 0.25% to eject the interference ions. As a result, the monoisotopic peak of tributyl phosphate ([C12H27O4P + H]+, m/z 267.1720) could be isolated (Marshall et al., 1985; O'Connor and Costello, 2000). Subsequently, sustained off-resonance irradiation collision-induced dissociation (SORI-CID) was applied with a SORI power of 1.1% and pulse length of 0.2 s for fragmentation (Gauthier et al., 1991). The elemental analysis was performed on a Euro EA 3000 elemental analyzer (EuroVector).

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2.3. Data processing The acquired datasets were analyzed using a combination of DataAnalysis 5.0 (Bruker) and Composer 1.5.6 (Sierra Analytics) software. The full scan mass spectra were internally calibrated using a series of homologous compounds throughout the m/z range 151–927. Elemental formulae were assigned to the peaks inside the calibrated m/z range, with the following tolerances to filter the lignin compounds: composition was restricted to 12C(1–50), 1H(1−100), 16O(0−30), 32S (0–3), 14N(0–1) and 31P(0–1); double bond equivalents (DBE) ranged from 4 to 30; the acceptable mass error was set to ±1 ppm for singlycharged ions, and root-mean-square (RMS) errors for the mass assignment could be found in Table S1. Graphical visualizations were plotted using in-house Python scripts (William Kew et al., 2017). 3. Results and discussion 3.1. Role of ionization technique on lignome coverage The components of the studied alkali lignin degradation mixture were analyzed as anions under ESI, APPI, and APCI conditions using identical solvent conditions (water/methanol, no acids/bases added) in negative ion mode. The mixture was also examined in positive ion mode under ESI conditions after addition of ammonium formate (the mass spectra are summarized in the Supplementary material, Fig. S1). In theory, dimethyl sulfoxide and N,N-dimethylformamide are the optimum solvents to dissolve lignin, however, their boiling points are too high for MS analysis; the addition of dopant such as toluene in APPI can also lead to severe solubility problems. The goal of the article is to show the specific bias and selectivity of various ionization methods, rather than to explore the optimum solvent. For this reason, the most widely applied ESI solvent, i.e. water/methanol, was utilized here, while the instrumental parameters (temperature, voltage, current, gas pressure, etc.) were optimized for each measurement. Since the experimental conditions were kept consistent, the different results observed here were mostly due to differences in ionization efficiency of the

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various products. And actually, using same solvent system is a proper way to compare different ionization techniques, for example, Huba et al., utilized methanol/toluene to dissolve crude oil for ESI, APPI, and APCI measurements (Huba et al., 2016); Kew et al. utilized methanol/ water to measure the Scotch Whisky samples using the three methods as well (Kew et al., 2018). Following the assignment of elemental compositions for all major species in the mass spectra, a graphical diagram is the most straightforward way to visualize the contribution of different compounds. An UpSet plot was constructed first, to display and compare the intersections of compounds detected between the ionization methods (Lex et al., 2014). Fig. 1 presents a cumulative account across the three measurements: negative ESI identified the highest number of unique formulae (5722), whereas negative APCI provided the least (1908). Negative and positive ESI also exhibited the largest number of common formulae in the pairwise intersection. Overall, there were only 365 formulae common to all the four datasets, indicating the large chemical diversity generated by the use of various ionization methods and strong role of differential ionization effects (Fig. 1). In addition to simply comparing the number of detected species, a van Krevelen diagram (Fig. 2) was plotted to study the selectivity of various ionization techniques for different compounds. The van Krevelen diagram is a widely applied graphical tool in geochemistry to study the evolution of coals and petroleum samples (Bostick and Daws, 1994), by arranging the molar ratio of hydrogen-to-carbon (H/C ratio) as ordinate and the molar oxygen-to-carbon ratio (O/C ratio) as abscissa. For complex NOM mixtures, major biogeochemical compounds (such as lignins, lipids, carbohydrates, etc.) also have their own characteristic H/C and O/C ratios (Kim et al., 2003). Overall, ESI produced the largest number of species covering a significantly larger chemical space up to m/z 900. APCI and APPI, on the other hand, generated compounds through different ionization mechanisms and ionized fewer molecules with protic functionalities. The van Krevelen diagram clearly shows that many more lignin-like compounds (O/C 0.2–0.6 and H/C 0.7–1.5) were detected via ESI. While APCI and APPI yielded similar distributions, the signals shifted slightly to lower O/C ratios, with virtually

Fig. 1. UpSet plot showing intersections of the different ionization methods. Vertical bar plots indicate the number of elemental formulae found in each exclusive intersection.

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Fig. 2. van Krevelen diagrams for each investigated ionization source. The color bar represents the m/z value of the data points.

no compounds detected above m/z 600. This was probably due to demethoxylation and water loss (both pathways eliminate oxygen) triggered by the relatively high temperatures of the two methods (Table S1), which was previously reported by Haupert et al. for a series of lignin standards (Haupert et al., 2012). It is also important to point out that for APCI and APPI more species were identified at approx. H/C 1.4 and O/C 0.2. These compounds are likely to be triterpenoid derivatives, which originate from wood extracts (Will Kew et al., 2017; Marchal et al., 2016). In the van Krevelen diagram, there are also several points, where apparent lines are extending outwards in multiple directions. For example, O/C 0.5 and H/C 1 (vanillic acid); O/C 0.2 and H/C 1.2 (eugenol); O/C 0.3 and H/C 1.2 (coniferyl alcohol), these compounds correspond to the basic structures of various lignin- and phenylpropanoid-type compounds. The trend lines in the diagram represent specific gains or losses of repeating functional groups; these lines indicate the chemical transformations of aliphatic, aromatic, oxygen and reduction states (Kim et al., 2003). 3.2. Exogenous lignin components Lignin products should, in theory, only be composed of three elements: carbon, hydrogen, and oxygen. However, elemental analysis of the alkali lignin studied here revealed that the sample contained 5.7% of sulfur and 0.3% of nitrogen. This is because the lignin studied here originated from the Kraft process (Gellerstedt, 2015). It has been reported that such a degradation process can introduce thiol groups to the structure and generates lignin sulfonate (Le Floch et al., 2015; Saiz-Jimenez and de Leeuw, 1984). Additionally, nitrogen, phosphorus, and other elements from geochemical cycling can be introduced into natural lignin due to weathering and/or geochemical processes. These heteroatoms not only increase the physicochemical diversity of lignin, but also create potential biomarkers to trace certain organic matter and anthropogenic chemicals. For example, in the positive ion ESI spectra, a phosphorus-containing compound, [C12H27O4P + H]+, was detected (peak 15 in Fig. 3). This species was suspected to be tributyl phosphate, a substance that is used as a herbicide and fungicide (Thomas et al., 1997). To confirm this hypothesis, more structural information on the suspect peak was required. Usually, tandem mass spectrometry (MSn) techniques such as collision-induced dissociation (CID) provide further insight into the possible structures. Unfortunately, due to the extreme molecular complexity of the sample, it was not possible to easily isolate the precursor ion of interest ([C12H27O4P + H]+) for effective MSn analysis. As seen from Fig. 3, the expanded region of only 0.2 m/z units from

the mass spectrum exhibited a total of 20 assigned features in such a small segment. In most mass spectrometers, a quadrupole-based isolation device is responsible for precursor ion selection, which can isolate precursor ions only within a minimum mass window of ~0.5 m/z unit. For this reason, subsequent MSn experiments on this mass window would include all the 20 precursor ions shown in Fig. 3, thus making proper structural interpretation of the single compounds of interest impossible. To overcome this problem, pre-separation methods such as liquid chromatography or capillary electrophoresis can be utilized. Here, we used a different strategy, based on the ability of FT-ICR MS, to effectively isolate ions of interest in the ion cyclotron resonance cell itself (“in-cell isolation”). This technique has been shown to enable the isolation of individual isotope peaks from complex proteins (O'Connor and McLafferty, 1995) or a single peak in a very complex natural organic matter spectrum (Witt et al., 2009). As a result of this procedure, all fragment ions are isotopically “pure”. This approach therefore allows an unambiguous assignment of all fragment ions. Fig. S2 in the Supplementary material illustrates this approach for the [C12H27O4P + H]+ ion, by using the so-called “Sweep+Shots” function (Heck and Derrick, 1997; Wills and O'Connor, 2014) of the FT-ICR MS instrument used here. An m/z window as small as ~0.005 m/z units can be achieved to select the single isotope peak of the [C12H27O4P + H]+ ions. Thus, the structure of tributyl phosphate was unambiguously

Fig. 3. Precursor ion isolation of the suspected tributyl phosphate ion species (marked with ▼) using the quadrupole isolation device: all the shown isobaric interferences inside the above window were included in the subsequent MSn analysis. A full list of peak assignments can be found in Tables S2.

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confirmed via a series loss of C4H8 groups in the following SORI-CID experiment (Fig. S2, bottom). The presence of tributyl phosphate in the lignin sample indicates that lignin may contain other exogenous substances, even from anthropogenic activities. Possible sources of the phosphorous contamination include agricultural effluent, leaks from chemical plants or waste dumps from manufacturers. The region where the lignin was collected might be repeatedly affected by contamination. For this reason, the phosphorus-containing compounds in lignin could potentially be used as a biomarker to evaluate the terrestrial ecosystem. 3.3. Lignin-related species The van Krevelen diagrams and the recovery of compounds containing heteroatoms (e.g., N, S, P) discussed in the previous sections provided an overview of the chemical diversity of the lignin sample and indicated the potential role of external contributors from the natural environment. In this section, only the lignin-related components were further investigated using the elemental ratios in the van Krevelen diagram (O/C 0.2–0.6 and H/C 0.7–1.5). To provide further insight, a new UpSet plot was generated based on the lignin-like compounds, to represent the size of exclusive intersections across the various ionization methods (Fig. 4). Overall, there were only 124 common compounds in the four investigated ionization techniques, pointing out the large differences of chemical structures and physicochemical properties. Negative ion ESI exhibited the largest number of unique assigned formulae (4201) and the widest m/z coverage, whereas APCI and APPI provided the smallest number (159 and 387 formulae, respectively). The apparent inefficiency of APCI and APPI was likely caused by the used solvent system, which was not optimized specifically for each technique. This was purposely done, however, to rule out possible contaminations, chemical reactions and adduct formation from the additional chemicals. Thus, the simplest solvent system (water and methanol) was applied without added acids, bases and dopants to facilitate the ionization process.

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Under positive ESI conditions, it was expected that deprotonation of the hydroxyl groups would suppress overall detection of lignin components, in particular for those species of higher oxygen content. Hence, ammonium formate was added as a charge carrier, which facilitated the protonation process. During ionization, [M + NH4]+ adducts were initially generated, followed by release of NH3 to give [M + H]+. A similar approach was previously used for analyzes of flavonoids (Zhao et al., 2008), lipids (Cai and Syage, 2006), and aromatic compounds (Lu et al., 2016). It is important to reiterate that the two ESI methods provided the largest number of common formulae in their pairwise intersections (1389 of the 1708 compounds in positive ESI were also observed under negative ESI conditions). The unique formulae assigned in positive ESI were mostly phosphorus-containing compounds such as tributyl phosphate (McDonald et al., 2016), highlighting the possibility of using the positive ion ESI mode to additionally cover the exogenous lignin components. The identified lignin-like compounds were further classified according to the oxygen class. A histogram representing the count of O2 to O20 components in the APCI, APPI, positive and negative ESI mass spectra is shown in Fig. 5. Overall, formulae were assigned up to O20 for the four ionization pathways; however, only compounds seen in negative ESI extended above O16, and the histogram was truncated accordingly. ESI clearly covered the broadest O range and presented a normal distribution. It appears that signals of oxygen-rich compounds were enhanced in ESI, as additional hydroxyl groups increased the possibility of deprotonation. In contrast, APCI and APPI were less effective and mostly detected compounds with a number of oxygen atoms below five, as multiple oxygen atoms can increase compounds' vaporization points. Given this low number of oxygens, the compounds detected by APCI and APPI were likely lignin monomers, i.e., compounds featuring the phenol core with methoxy groups. Interestingly, the relative ratio of the O2, O3, and O4 compounds remained almost the same (1:6:10) for all four investigated ionization techniques, suggesting that these lignin compounds with low oxygen content might be less sensitive to experimental and environmental

Fig. 4. UpSet plot showing intersections of the different ionization methods for the lignin-like species. Vertical bar plots indicate the number of elemental formulae found in each exclusive intersection.

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Fig. 5. Histogram of the number of formulae identified for oxygen classes ranging from O2 to O20 for APCI, APPI and ESI mass spectra of lignin.

changes. This feature may make them possible biomarkers to track the origin of lignin species in the environmental matrix. 3.4. Sulfur-containing species Not only did ESI produce more unique elemental formulae than the other investigated ionization techniques, but it also enabled the detection of a large number of sulfur-containing species, which were also observed by the other methods (Qi and Volmer, 2019b). Due to weathering processes, sulfur and other elements from geochemical cycling can be introduced into natural lignin and sulfur-containing species have been frequently reported in lignin analyzes (Braaten et al., 2003; Fredheim et al., 2002; Raghuraman et al., 2005), as well as in atmospheric aerosols (Li et al., 2018; Wan et al., 2019; Zhu et al., 2019). Sulfur can be inserted into the aromatic ring, to form thiophenic and benzothiopenic species, or into the alkane-type chains to form thioethers. To gain further insight into the sulfur-containing lignin, DBE versus carbon number diagrams were plotted. As shown in Fig. 6, the lignin-like species observed in negative ESI exhibited a large carbon and DBE number distribution range. For comparison, the contribution of the OnS compound class as a function of DBE was plotted separately. The distribution of sulfur-containing lignin was much shallower along with lower oxygen numbers. This suggests that these compounds should have a lower overall DBE value, indicating that they have longer, alkane-type chains in the structures. Sulfur is more likely to form thiol group (low DBE) rather than to link to the aromatic core (high DBE). To further support this hypothesis, a planar limit study (Purcell et al., 2010) was conducted. The planar limit is defined as the slope for a given carbon number in a plot of DBE versus carbon number (Fig. 6), which was initially proposed to better understand the molecular structure of compounds in petroleomics. It has been reported that the slope varies from a saturated to an asphaltene fraction of crude oil, with reported slope values of ~0.3 and ~0.9, respectively (Arenas-Diaz et al., 2017). These values indicate the presence of more condensed structures as the subfraction become heavier. The slope of the OnS class was much smaller, pointing to less condensed structures and evidence of long, saturated chains. Moreover, thiol deprotonates easily, while the thiophenic compounds can stabilize free radicals due to delocalization throughout the aromatic framework. Therefore, the presence of thiol groups explains the significant number of sulfur–containing lignin compounds detected in ESI as opposed to APPI. If the sulfur were inserted into the aromatic rings, the resulting thiophenic and benzothiopenic species should be readily observed under APPI conditions.

4. Conclusions Only ultra-high resolution mass spectrometry currently has the ability to resolve thousands of compounds present in complex mixtures. In this work, a 7 T FT-ICR MS was coupled to ESI, APCI and APPI sources and utilized in both positive and negative ion modes to analyze a lignin sample. Using of negative-ion ESI led to the observation of the greatest number of components, while APCI yielded the fewest. It is clear that the number of observed components is significantly influenced by the

Fig. 6. DBE versus carbon number plots for all lignin-like species and only the OnS species assigned from negative ESI mass spectra, with planar limit lines (red) and slopes labelled. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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ionization techniques, with consequences for environmental forensics. When attempting to interpret a lignin sample, comprehensive ionization methods should be applied to ensure a broader characterization and to prevent erroneous interpretation. This statement also holds true for other multi-component analyzes. On the other hand, it is important to consider what type of chemical structures are being measured, and caution should be exercised for choosing the proper ionization method. Different ionization methods revealed the chemical complexity of lignin degradation products and also allowed for the observation of heteroatom-containing compounds (e.g., S and P), which might serve as a potential marker to track the anthropogenic activity. Observation of the phosphorous-containing compound may indicate contamination from other anthropogenic sources, including agricultural effluent and industrial chemicals, suggesting that there may have been continuous pollution from anthropogenic sources. The FT-ICR MS “in-cell isolation” technique used here allowed the selection of the isotopically pure single monoisotopic ions from the highly complex mixture without prior chromatography separation. This procedure greatly simplified the interpretation of the subsequent MSn spectrum, as possible contributions of isotopes (e.g., 13C and 34S) were eliminated. Structural elucidation has always been a major problem for complex natural organic samples, but the approach shown here enabled rapid and unambiguous characterization of compounds from highly complex samples, such as soil, lake and marine sediments, as well as atmospheric aerosols. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements This work was jointly funded by the National Natural Science Foundation of China [Nos. 41625014 and 41861144026], the National Key Research and Development Program of China [grant number 2016YFA0601002], starting grant from Tianjin University (390/ 0701321010), and the German Research Foundation (DFG VO 1355/4-3). Author contributions YLQ and PQF designed the study. The manuscript was written through contributions of all authors. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.scitotenv.2020.136573. References Arenas-Diaz, J.P., Palacio Lozano, D.C., Ramirez, X., Cabanzo, R., Guzman, A., Mejia-Ospino, E., 2017. Chemical characterization of polar species in Colombian vacuum residue and its supercritical fluid extraction subfractions using electrospray ionization FT-ICR mass spectrometry. Chem. Eng. Trans. 57, 1603–1608 SE-Research Articles. https:// doi.org/10.3303/CET1757268. Banoub, J., Delmas, G.-H., Joly, N., Mackenzie, G., Cachet, N., Benjelloun-Mlayah, B., Delmas, M., 2015. A critique on the structural analysis of lignins and application of novel tandem mass spectrometric strategies to determine lignin sequencing. J. Mass Spectrom. 50, 5–48. https://doi.org/10.1002/jms.3541. Banoub, J.H., Delmas, M., 2003. Structural elucidation of the wheat straw lignin polymer by atmospheric pressure chemical ionization tandem mass spectrometry and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. J. Mass Spectrom. 38, 900–903. https://doi.org/10.1002/jms.503. Banoub, J.H., Benjelloun-Mlayah, B., Ziarelli, F., Joly, N., Delmas, M., 2007. Elucidation of the complex molecular structure of wheat straw lignin polymer by atmospheric pressure photoionization quadrupole time-of-flight tandem mass spectrometry. Rapid Commun. Mass Spectrom. 21, 2867–2888. https://doi.org/10.1002/rcm.3159.

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