Abstract
Iron (Fe) is an essential trace element for the growth of phytoplankton in the ocean. Humic substances (HSs) are key components of dissolved Fe-binding organic ligands (Lt). Both Lt and HSs are widely accepted to regulate the distribution of dissolved iron (DFe) and influence its availability to marine phytoplankton and other organisms. This paper provides a concise overview of the historical progression of DFe determination and its speciation, including Lt and HSs, using electrochemical methods. It also reviews applications of these methods in examining the effects of HSs on DFe, drawing from spectroscopy, chromatography, and mass spectrometry data. Electrochemical techniques can measure the concentrations of HSs and the binding capacity of DFe, offering valuable insights into the role of HSs on DFe in marine settings. Spectroscopy, chromatography, and mass spectrometry allow for detailed characterization of the structure, properties, and types of organic ligands and HSs. These methodologies have enhanced our understanding of Lt and HSs, whether of marine or terrestrial origin, as significant ligands for DFe, influencing its concentration, distribution, and circulation. Future research should delve deeper into the mechanisms and chemical properties of Fe complexation with organic matter. Additionally, the impact of various factors on HSs complexes in relation to DFe warrants further exploration, benefiting from synchronous analysis using multiple detection methods. Such advancements would offer crucial insights into the biogeochemical cycling of Fe and enhance various research domains.
1 Introduction
Iron (Fe) is an essential trace element required for the growth of phytoplankton in the ocean. Consequently, the bioavailability of dissolved iron (DFe) significantly influences the abundance and species of phytoplankton [1,2]. The bioavailability of DFe is primarily regulated by iron-binding ligands (Lt) [3,4], which are complex with over 99.9% of DFe, making Lt fundamental to our understanding of Fe biogeochemistry [5,6]. It has been established that the organic complexation of iron plays a vital role in preventing its precipitation, promoting its transport, and modulating its reactivity and bioavailability in natural waters [7]. Despite numerous studies focusing on the spatial distribution and factors influencing Lt in seawater, the nature of Lt remains largely uncharacterized [6,8]. According to Fe speciation modeling conducted by Hassler et al. [6] using literature data, Lt are primarily divided into three critical groups: humic substances (HSs), exopolymer substances (EPS), and siderophores. The distribution and ratio of these vary regionally between coastal, offshore, and open ocean areas (Figure 1). As illustrated in Figure 1, HSs are prevalent in rivers, estuaries, nearshore waters, and deep oceans and are significant components of dissolved organic ligands [9], accounting for approximately 15–80% of DOM [10,11,12]. It has been hypothesized that land-derived HSs significantly impact the marine biogeochemical cycles of Fe [13], although this hypothesis has not yet been confirmed. Marine systems have been found to contain labile HSs of marine origin [14], which could contribute to the pool of HSs from terrestrial origin entering the ocean [15]. Moreover, HSs may exhibit weak acidic properties [16] complexed with DFe, which are abundant in phenolic-OH and carboxylic functional groups. These groups are primarily responsible for the binding of metal ions [17]. Consequently, regardless of the origin – whether marine or terrestrial – the significance of HSs for Fe in the ocean and global carbon cycling remains paramount.
![Figure 1
(a) Anticipated distribution of HSs, exopolymer substances (EPS), and siderophores concentrations, which vary with distance from the coast, offshore, and open ocean. (b) Expected HSs as iron speciation with a concentration range of 0.1–2 nmol/L DFe across four marine regions. Both figures are adapted from Hassler et al. [6].](/document/doi/10.1515/geo-2025-0812/asset/graphic/j_geo-2025-0812_fig_001.jpg)
(a) Anticipated distribution of HSs, exopolymer substances (EPS), and siderophores concentrations, which vary with distance from the coast, offshore, and open ocean. (b) Expected HSs as iron speciation with a concentration range of 0.1–2 nmol/L DFe across four marine regions. Both figures are adapted from Hassler et al. [6].
Current comprehension of DFe speciation (including Lt and HSs) in seawater relies on three fundamentally distinct approaches: first, electrochemical methods quantifying bulk properties of Lt concentrations and their conditional stability constants (log K Fe’L) [18]; second, liquid chromatography-mass spectrometry (LC-MS) methods characterizing ligands at a molecular level [19]; and third, spectroscopic methods measuring fluorescence peak intensities and qualitatively characterizing humic-like substances to identify processes linking metals [20]. Spectroscopic methods, primarily UV–vis and fluorimetric, have historically been employed for characterizing HS-like substances [21], but the results are challenging to quantify and interpret due to method selectivity and interference from other substances, particularly polysaccharides [22]. LC-MS methods require costly equipment and intricate preprocessing to determine a limited number of ligands. Conversely, electroanalytical methods, especially stripping voltammetry (SV), have facilitated the quantification of Fe and its organic speciation in seawater at nanomolar levels [5,23] and have been extensively utilized to explore the biogeochemistry of dissolved elements and their speciation in seawater over the past six decades. Only electrochemical methods can quantify both the organic and inorganic (labile) components of trace metals, providing valuable applications in kinetic studies in seawater [24]. The conditional stability and distribution of iron-binding Lt, as well as HSs, can be delineated through the use of SV, providing insights into the biogeochemistry of DFe [6]. Recent studies have capitalized on these methodological advancements to assess the complexation between DFe and ligands, aiming to elucidate the impact of HSs or Lt on the biogeochemistry of DFe [7,8,25,26].
This study provides a succinct overview of the historical development of DFe quantification and its speciation (Lt and HSs), employing electrochemical methods. It further delves into the impact of HSs on DFe in seawater, utilizing an array of techniques including spectroscopy, mass spectrometry, and electrochemical methods. This comprehensive exploration allows for a deeper understanding of the influence exerted by HSs on DFe in seawater.
2 Historical developments of Lt and HSs detection by electrochemical techniques
During the last century, voltammetry, especially utilizing mercury electrodes, has been recognized as an exceptionally robust technique for analyzing both inorganic and organic analytes. This method offers low detection and quantification limits while maintaining high reproducibility and repeatability [27,28]. Since its inception in 1963, SV has been extensively employed to determine trace metals [28,29,30,31,32]. One of the most significant advantages of electroanalytical methods is their capability to identify trace elements and their organic speciation in complex electrolytes, such as seawater, without the need for pre-separation [24]. Given that the method of determining HSs concentrations via SV is based on the speciation of DFe, it is important to review the historical development of determining trace metal concentration and their speciation (Figure 2).

General historical applications and future directions of SV on the concentration and speciation of trace metals and HSs determination. ASV: anion stripping voltammetry; CSV: cation stripping voltammetry; HMDE: hanging mercury drop electrode; AdCSV: adsorption cation stripping voltammetry; HSs: humic substances. The cited studies are shown in this references list.
2.1 Historical developments of Fe–Lt detection by electrochemical techniques
The pioneering analysis of trace metal concentration utilizing electrochemical techniques was conducted to determine zinc and cadmium in the Dead Sea through anion stripping voltammetry (ASV, Figure 2) [29]. This method was subsequently extended to other trace metals, including lead and copper (Cu) [33], and bismuth and antimony [34], pushing the detection limits far below the sensitivity of prevailing analytical procedures such as spectrophotometry, specific glass or membrane electrodes, and polarography [35]. However, due to mercury toxicity, certain regulations have constrained the advancement of mercury electrode–ASV for detecting trace metal concentrations. Consequently, since 1973, the evolution of ASV has bifurcated into two primary directions (Figure 2): one focusing on replacing mercury with alternative electrodes for trace metal detection (e.g., mercury-coated graphite electrode [34], rotating glassy carbon electrode mercury plated [36,37], mercury film electrode [38], and a twin gold disc electrode [39], and the other emphasizing the detection of low-level and organic speciation of trace metals in natural and seawaters [30,40,41,42]).
The utilization of electroanalytical methods for discerning the organic speciation of trace metals in natural water was initiated in 1974 [30]. This included the assessment of the Lt concentration, conditional stability constant (K′), and inorganic metal ions via ASV (Figure 2). Chau et al. employed differential pulse ASV (DPASV) to measure labile copper in lake water [30], while Nürnberg and Raspor used DPASV with nitrilotriacetate as a model ligand to examine dissolved organic matter (DOM) [41], estimating the Lt concentration and stability of its chelation with cadmium, zinc, and lead (Figure 2). However, ASV is limited in its ability to only identify the presence of complexation with metals and Lt and does not permit quantification of the concentrations of natural ligands and K′ in seawater.
The concentration of Fe was initially determined by adsorptive cathodic stripping voltammetry (AdCSV) starting from 1991 [43]. This method was refined for detecting processes [23,32,44] and was applied to study the distribution of Fe in various seas, including the western North Atlantic Ocean [45]. Over two decades, scientists have modified different reagents (competitive ligands and buffers) to enhance performance and adapt to various natural waters for the determination of DFe concentration [46,47,48], particularly for detecting levels lower than picomolar of DFe [49]. The use of AdCSV for detecting Fe in seawater has demonstrated significant advantages, including a very low detection limit and minimal pretreatment requirements.
The method of AdCSV with ligand competition, developed by Constant M. G. van den Berg post-1984, began to identify the complexation with metals and ligands, thereby addressing several associated problems (Figure 2) [50,51,52]. Subsequent to 1994 [5,32], the technique of competitive ligand equilibration (CLE)–AdCSV has been employed to ascertain the concentration of Fe-binding Lt and their
In an effort to elucidate the characteristics of DFe complexation and labile fractions, researchers have undertaken numerous initiatives across various domains. Initially, to classify complexation strength, DFe complexation in seawater is often divided into two primary binding site categories: strong binding sites (L1-type, log K Fe′L ≥ 12–13) and weak binding sites (L2-type, 12 ≥ log K Fe′L ≥ 10, and potentially <10) throughout the water column [5,16,25,57]. Some studies even proposed three or four binding site categories [58]. Weak binding ligands are frequently associated with HSs. Additionally, the computational methodology for CLE–AdCSV has undergone significant refinements, encompassing both the calculation procedure [59] and method intercomparisons from 15 laboratories [60]. Moreover, the assessment of DFe complexation employs a diverse range of analytical window analyses [54,61,62], all striving to closely align with the actual complexing conditions. In summary, despite challenges related to data inter-comparability arising from varied reagents (competitive ligands and buffers), instrumental configurations, and fitting models [60], a wealth of measurements has been amassed [63], revealing the basin-scale distribution of Lt across the world’s oceans.
Despite significant advancements in electrochemical methods for measuring trace metal speciation, the determination of Lt and HSs using these methods presents limitations due to their inherent constraints [64,65]. It has been found that CLE–AdCSV titrations measure the bulk properties of a heterogeneous ligand pool in seawaters, adding excess ligands rather than the actual ligands present [66]. Although there is some debate about the oversimplification of the isotherm model in the CLE–AdCSV method [53], it remains the only method for quantifying the DFe complexation situation. Over the past three decades, CLE–AdCSV has been the preferred method for studying trace metal speciation, including Lt concentrations and the
2.2 Historical developments of HSs detection by electrochemical techniques
HSs are the hydrophobic fraction of natural organic matter that is retained on XAD-8 resin and eluted by alkaline extraction [10]. This includes fulvic acid (FA), a lighter and soluble fraction obtained by centrifuging at pH 1, and humic acid (HA), the remaining part. Several methods can measure HSs in natural waters, such as electrochemical techniques [68,69], chemiluminescence [70], spectroscopy [21], and elemental analysis [71]. However, due to their variable composition and the lack of a convenient analytical method, quantifying HSs in natural waters poses challenges in terms of understanding their influence on DFe in natural water. The use of electrochemical techniques for HSs detection can provide concentration data, which has been verified with UV–vis and fluorimetric methods using the International Humic Substances Society (IHSS) Suwannee River FA [22,69].
The advancement of methods for determining electroactive HSs (eHS) has followed the development of trace metal detection techniques. They are based on the complexes with molybdenum (Mo(vi)), Fe(iii), or Cu(ii) with eHS in samples, which can be adsorbed onto a mercury drop electrode to cause an electrochemical reaction [69,72,73]. The development process of determining the eHS method is presented in Table 1 and Figure 2. Beginning in 1986, Quentel et al. originally found the reduction wave of eHS-Mo(vi) [68] and developed a method to measure eHSs or refractory organic substances by complexing with Mo(vi), and it was further optimized in subsequent studies [22,72,74], as displayed in Table 1. They tried two voltammetry methods (Square-wave versus differential pulse modes), optimized measuring conditions, and studied the interferences from other metals or organic matters [22,72,74]. It was observed that high concentrations of polysaccharides could interfere with the reduction wave of eHS, which would overestimate eHS concentrations [22,74].
Summary of measurement parameters for determining HSs complexation with Fe/Mo/Cu
Standard | Complexation | Detection mode | Deposition | Reduction potential | Sensitivity (nA mg−1) | Detection condition | Detection limit | Reference |
---|---|---|---|---|---|---|---|---|
FA, obtained by lake water | Mo(vi) | SWV | −0.3 V | −0.137 V – 74 mV/(pH-2) | 120 nA mg ROM−1 L | pH 2.5, 0.5 mol/L NaCl, in the presence of phenanthroline | 2.1 μg C/L | [72,74] |
−0.458 V – 123 mV/(pH-2) | ||||||||
SRHA, SRFA | Mo(vi) | ADPV, SWV | −0.2 V | About −0.405 V | 24 nA mg ROM−1 L | pH 2 | 4.5 μg FA/L | [22,74] |
(2.3 μg C/L) | ||||||||
SRFA | Fe | AdCSV in DP mode | −0.1 V | −0.5 V | 0.67 nA mg SRFA−1 L | pH 8 in POPSO/bromate | 5 μg/L FA | [9,69] |
SRFA | Fe | AdCSV in DP mode | −0.1 V | −0.6 V | — | pH 8.2 in boric acid/bromate | — | [62] |
SRHA, SRFA | Cu | AdCSV in DP mode | +0.05 V | −0.25 V | 6 nA mg SRFA−1 L | pH 8.2 in boric acid buffer | — | [73] |
SRHA | Fe | AdCSV in DP mode | −0.2 V for Fe-HA | −0.5 V | 10 nA mg SRFA−1 L | pH 8.05 in POPSO/bromate | 4.69 μg/L HA; | [75] |
SRFA | −0.05 V for Fe-FA | 23 nA mg SRHA−1 L | 5.48 μg/L FA | |||||
SRFA | Fe | AdCSV in DP mode | −0.1 V | — | — | pH 8.3 in POPSO/bromate | 0.03 nM/(14.6 nmol Fe mg SRFA−1) | [76] |
SRHA, SRFA, Sigma-Aldrich HA | None | AdCSV in DP mode | 0 V | −0.5 V | — | Natural pH, No buffer | 0.020 mg/L SRHA | [18] |
SRHA/SRFA, Suwannee River humic and fulvic acid; SMDE, static mercury drop electrode; SWV, square-wave voltammetry; AdCSV, adsorptive cathodic stripping voltammetry; ADPV, adsorptive differential pulse voltammetry; DP, differential pulse mode. The cited studies were shown in this references list.
Research on HSs complexation with Fe was promoted by the Fe–HS method developed by Laglera and van den Berg and Laglera et al., which was catalyzed in the presence of bromate and increase the sensitivity of Fe–HS, which can measure FA and HA in natural waters including seawater directly [9,69]. The method of determining eHS complexed with DFe can offer a more relevant measure and more suitable for the Fe complexation capacity of eHS than measuring eHS at pH 2, as it can be conducted at the natural pH of seawater [22,69]. Laglera et al. confirmed that the complex stability and sensitivity of the electroactive Fe-SRFA species remain unaffected by interference from other metals and iron ligands in UV-digested seawater [69]. Based on the Fe–HS method [69], Bundy et al. and Yang et al. refined experimental parameters to study regional coastal waters [62,75]. However, the presence of a potent oxidant, such as bromate, used for catalytic reoxidation, can disrupt complexation with HSs during measurement. To address this, Laglera et al. and Sukekava et al. rearranged and expanded the initial analytical protocol [69,76]. This test method involved first collecting the natural Fe–HS complex single and then commencing the voltammetric analysis under iron saturation by the quantification of HSs standard addition that has been prepared in ultrapure water is carefully saturated with iron. This eHS method [69,76] has found extensive application in freshwater, estuarine, coastal waters, and the open ocean [25,77,78,79,80].
Cu–HS as the complex was also used to measure HSs concentration [73,81], which has been applied to study Cu and its speciation in estuary and coastal waters [82]. The interference and competition from HSs and other organic matters complexing with Fe, Cu, etc., have also been studied [73,81,83]. In the most recently updated method, the HSs in natural waters can be determined using a new, simple, and sensitive method based on their influence on the background current in a differential pulse-AdCSV, developed by Marcinek et al. [18]. The method was well correlated with classical spectrophotometry and even showed slightly better sensitivity than absorbance measurements [18]. The Mo–HS and Fe–HS methods were verified as compelling demonstrations of equivalent results by Dulaquais et al. [84]. Furthermore, Fe-binding and Cu-binding HSs in estuarine waters are the same [81]. Those HS methods have been applied to various regions to elucidate the biogeochemistry of DFe in natural waters [8,25,80].
In the determination of HSs using electrochemical techniques, the choice of HS reference standards is crucial for accurately showing the concentration of eHS. This is primarily due to the use of standard addition for quantification, which represented the real meaning of the determined eHS concentrations [22]. While carbohydrates and protein-like substances do not interfere with the measurement of individual HA or FA, different types of HA or FA standards indeed showed various results. The eHS determination needs to underline the importance of choosing the most appropriate standard. Nowadays, the IHSS supplies a few of organic matters references from different regions, while FA and HA reference materials originating from the Suwannee River are often used for the purpose of HSs method calibration and as model compound for speciation studies since 2007 [69]. In most studies about natural waters including seawater, eHS concentrations were often expressed as equivalents of Suwannee River humic and fulvic acid (SRHA and SRFA). Due to no standard extracting from seawater, thus the determination of eHS has unified SRFA as the standard references in mostly electrochemical method studies.
Electrochemical techniques have raised awareness that HSs have a strong complexation ability with DFe, which is sufficient to affect the biogeochemical action of DFe in seawater. Relevant studies have found that there are differences in the complex properties of SRHA and SRFA with Fe. Laglera and van den Berg determined the stability of the complexation of Fe with SRFA and SRHA (log
The observation of similar reduction potentials for marine eHS and SRHA or SRFA is more strongly related to the metal being reduced or oxidized than the compounds bound to metals on the mercury drop, such as the different reduction potential of eHS complexing with Mo(vi), Fe(iii), and Cu(ii) (Table 1) [69,74,81]. Therefore, it does not mean the peak of DFe–Lt complexation was single eHS [83] or mixed organic compounds or even polysaccharides [74,85]. Furthermore, our present knowledge of Lt and HSs is indirect because these ligands are complex, unknown identities and have never been isolated, recovered, and characterized. Thus, it was useful to know the weak complexation of electrochemical methods in measuring Lt and HS, which would be beneficial for the development of the terminological issues. According to existing research, some methods for determining organic matters, such as spectroscopic, chromatographic, and mass spectrometry, have supplied a lot of information on Lt or HSs, which would help analyze Lt or HSs together with AdCSV.
In future research, the application of electrochemical methods to detect trace elements in seawater is likely to diverge in two primary directions (Figure 2): the first being the development of portable or online electrochemical sensors and biosensors designed to detect heavy metals [86], and the second focusing on the mechanisms associated with complexing trace metals with ligands and HSs using multiple methods (spectroscopic, chromatography, and mass spectrometry) in seawater [26].
3 Influence of HSs on DFe distribution
3.1 Exploring the effect of HSs on DFe through electrochemical methods
Over the past decade, scientists have attempted to use electrochemical methods to determine HSs’ concentrations. It is generally believed that HSs may be an important ligand of DFe and that they have an important impact on its concentration, distribution, and circulation [9,16,20,57,87]. The author collected DFe and HS concentrations from different types of water bodies, as shown in Table 2, which exhibited similar decreasing trends from river water to estuaries, coastal seas, and oceans, like Fe speciation modeling by Hassler et al. [6] (Table 2; Figure 1).
Summary of determination of DFe and HSs concentrations using electrochemical methods for different types of water bodies
Water body | Region | DFe conc. (nmol/L) | HS conc. (μg/L) | Reference |
---|---|---|---|---|
River water | Yangtze river | 176.5 | 1712.3 | [75] |
Estuary | Penze´ estuary (NW France) | — | 0.07–4.8 mg C/L | [101] |
Mersey estuary | About 1.7–9 | About 55–350 | [9] | |
San Francisco Bay | — | 36.18–563.31 | [62] | |
Yangtze river estuary | 6.3–176.5 | 277.2–1739.8 | [75] | |
Amazon river estuary | — | 0.15–7.7 mg/L | [82] | |
Continental shelf Sea | Irish sea | — | 60–600 | [69] |
Coast off San Diego | — | 178 ± 34 | [9] | |
East China Sea | 0.10–14.2 | 81–364 for HA | [77] | |
Nearshore in Gulf of Mexico | 6.86 ± 2.32 | 202 ± 181 | [102] | |
Shelf of the South Brazil Bight | 1–5 | 0–75 | [80] | |
Open ocean | Open deep Pacific | — | 36 ± 2 | [9] |
Outside of San Francisco Bay | 6.8, 20.5 | 22.6, 39.2 | [62] | |
Atlantic sector of the Arctic Ocean | About 0.3–4.4 | About 20–285 | [76] | |
Transpolar Drift, Arctic Ocean | 0.09–4.4 | 16–446 | [94] | |
Offshore in Gulf of Mexico | 1.69 ± 0.44 | 18.9 ± 12.5 | [102] | |
GEOTRACES Atlantic GA02 | 1.15 ± 1.26 | nda | ||
200 m waters of Pacific | 0.0–0.75 | About 0–10 | [8] | |
TONGA GEOTRACES between the Melanesian basin and the South Pacific gyre | 0.45 ± 0.50 | 26.4 ± 14.2 | [25] |
Note: We only cited data for June 2015 from Mellett and Buck [102] and HA data from Yang et al. [75]. Approximate concentrations are shown for Fe and HSs because Laglera and van den Berg [9], Sukekava et al. [76], and Sato et al. [8] did plot a figure and not show the data [8,9,76].
The cited studies are shown in this references list.
HSs and DFe have similar distribution trends in the Irish Sea; thus, natural HSs may account for all ligands in offshore waters [9]. Bundy et al. reported a direct linear relationship between the HSs concentration and Fe and weak organic ligand concentrations, which play an important role in Fe distribution [62]. It was verified that HSs account for virtually all of Lt of Fe in estuarine waters [81].
For the complex water body of the estuary area in early classical studies, HSs and Fe were observed to mainly exhibit consistent behavior no matter how salinity changed [88], which attracted great attention to further studies. Recent studies have verified that HSs play an important role in stabilizing DFe in various estuaries, mainly through the combination of HSs binding to DFe and the distribution of HSs, such as in the Mersey River Estuary [9,89], Thurso Bay [90], Yangtze River Estuary [75], and a boreal river in Newfoundland, Canada [91]. Stolpe and Hassellöv found that the HSs removal ratio in estuarine areas affects the amount of Fe imported into the sea by rivers [92]. In the rich HSs in the estuary of Mercer Bay in northern Scotland, Batchelli et al. found that colloidal Fe was mainly complexed by HSs, further indicating that HSs play an important role in the distribution of Fe in nearshore waters [90]. In the process of freshwater mixing with seawater along a salinity gradient, HSs flocculation occurs and plays an important role in stabilizing a small amount of DFe [58,93]. In a study of Arctic estuaries with rich organic matter, it was found that HSs contributed greatly to complexation with Fe, but the complexation intensity was different from that of temperate estuaries [94].
The DFe-binding capacity of HSs can explain why they play an important role in stabilizing the concentration and controlling the distribution of Fe [9]. Yang et al. reported that the Fe-binding capacity of HSs decreases exponentially with increasing salinity [75], which may be due to changes in the structure of HSs with increasing salinity [95]. In offshore waters, such as the Irish Sea and San Francisco Bay, the DFe-binding capacity at individual stations is lower than that measured under laboratory conditions, which indicates that HSs, as excess ligands, can form complexes with most of the DFe [9,58]. Similarly, according to data on the DFe-binding capacity of HSs in the East China Sea, HSs in most regions were also excess ligands for complexed DFe, although the concentration of DFe in the Yangtze River estuary was excessively high due to land-based inputs [75]. Therefore, Fe–HS complexes serve as the primary source of terrestrial iron reaching ocean waters [7,75].
Although HSs have been confirmed to play a pivotal role in stabilizing DFe, recent studies have offered alternative explanations for the complexation of DFe in specific seawater conditions [80]. The correlation between DFe and iron ligand concentrations in coastal waters has consistently been observed [96,97]. However, discrepancies have been noted between DFe and ligands in shelf and slope upwelling areas. Unlike expected, eHS concentrations did not display decreasing horizontal gradients from land to ocean. Instead, eHS were found to be iron–humic complexes that play a crucial role in complexing with DFe in upwelled waters [80]. This raises the need for further research into the sources or sinks that influence the distribution of HSs, ligands, and DFe in upwelling waters and other unique regions.
In open oceans, over 99% of the Fe is complexed with organic ligands, which increase iron solubility and microbial availability in early studies [96,98]. HSs’ concentrations were found to co-vary with DFe in the North and Northwest Atlantic, Southern Ocean, and Northeast Pacific [87]. In the Lau Basin of the western tropical south, including areas near hydrothermal vents [99], a substantial fraction of DFe is complexed by humic-like ligands (mean of approximately 30%). It has been confirmed that eHS can solubilize a substantial portion of freshly formed Fe-oxyhydroxides; however, this ability decreases rapidly as the inorganic particles age. Using an ocean circulation model, Misumi et al. [100] simulated how the distribution of weak ligands in the ocean controls the concentration of DFe. The model results showed that HSs play an important role in the Fe cycle in the ocean, which is consistent with some field research results [100]. Recent research has found that eHS accounted for only 20 ± 13% of Lt in the mixed layer and 8 ± 6% in deep waters within the western tropical South Pacific Ocean [25].
In the upper water column of open oceans, HSs may constitute only a fraction of the ligand pool (<20%, Figure 1), which includes terrestrial humic material and is supplemented by microbes originating from generic cellular debris as marine detritus [6]. In some open ocean studies, the eHS, as determined by electrochemical methods, had no correlation with the humic-like substance measured via fluorescence. This highlights the disparity in the detection of HSs using the two methods, illustrated by studies conducted from the central Pacific Ocean to the Bering Sea. However, a strong positive correlation between the concentrations of eHS and chlorophyll a suggests their biological origins [8], implying that the sources of eHS and DFe may differ in open oceans.
The latest research indicates that the electrochemical method not only quantifies eHS concentrations but also sheds light on the role of HSs in the marine iron cycle. This is achieved by examining the ligand exchange in a ternary SRHS-Fe-DFOB (desferrioxamine B, a type of siderophore), leading to the hypothesis that DFe complexed with various ligands might operate on a “first come, first served” basis [7]. These electrochemical techniques are not limited to measuring HSs’ concentrations and the binding capacity of DFe; they also facilitate our understanding of the competition among different ligands for DFe. Consequently, electrochemical approaches offer insights into the impact of HSs on DFe in marine settings.
3.2 Exploring the effect of HSs on DFe through other techniques
HS from marine or terrestrial sources or DOM in cool temperate zones to subtropical and tropical wetland systems have various compositions and structures, which may affect the effect of humic-like substances on iron in different rivers [103]. Spectroscopic, chromatographic, and mass spectrometry, as well as their hyphenated techniques, have been widely used to distinguish the structures, properties, and types of Lt and HSs [104,105,106]. Those methods can help us to know Lt and HSs from marine or terrestrial sources and can be used to trace the influence of terrestrial materials on seawater.
Therefore, an increasing number of scientists have focused on the role of humic-like substances and ligands in the Fe cycle of marine environments [20,86,107,108,109]. Many field studies have focused on humic-like fluorescent dissolved organic matter (FDOM) using optical methods [106,110]. In the nearshore area of the Yukon Estuary, humic-like FDOM was found to be correlated with DFe and play an important role in the transportation of DFe complexed with natural organic ligands to the continental shelf of the Bering Sea [111]. In the central sea area of the North Pacific, the DFe concentrations are strongly and linearly correlated with the fluorescence intensity of humic-like FDOM [112,113]. In recent spectral studies, the influence of humic-like FDOM not only occurred from the river plume to seas but also to open oceans. For example, terrigenous HSs are a regulator of the concentrations of DFe from the Gaoping River plume to seas [20]; marginal seas have been found to be important external sources of DFe in the North Pacific through the circulation of intermediate water, according to humic-like FDOM over the North Pacific [106]; DFe correlated with the humic-like FDOM in the western tropical South Pacific Ocean [25]; vascular plant and algal derived humic-like CDOM play a contributed role on DFe-ligand pool in the Laptev Sea and major Arctic basins [114].
Humic-like ligands are ubiquitous in the Lau Basin of the western tropical South Pacific Ocean and organic Arctic boreal soils, as well as proximate to hydrothermal vents, underpin the bioavailability and stabilization of DFe in oceans [99,108]. Sakata et al. found that humic-like substances in aerosol particles and surface water could control Fe solubility in size-fractionated aerosol particles in the Pacific Ocean using X-ray absorption–fine structure spectroscopy [115]. The latest laboratory experiments have provided new evidence of the importance of HSs in preserving DFe in estuaries and tidal flat wetlands [116,117]. Small aquatic humic ligands produced by organic soils in the Arctic boreal region also play a critical role in relieving the Fe limitation of phytoplankton in rivers and oceans [108]. Heerah and Reader identified the Fe-binding ligands present in a boreal river in Canada using Fourier-transform infrared spectroscopy, which verified the importance of the influence of humic-like ligands on the remaining DFe along an artificial salinity gradient [91]. Sato et al. found high amounts of humic-like substances in low-salinity surface waters between the outer edge of the Changjiang diluted water plume and a branch of the Kuroshio Current, which may have been influenced by microbial activity or photolytic degradation [118].
Except for exploring the influence of humic-like FDOM on the distribution of DFe in natural water samples, it was necessary to identify some kinds of matters of Lt and HSs and study interactions of DFe with them by chromatographic and mass spectrometry, as well as their hyphenated techniques at a molecular level. Waska et al. have found that the equilibration of DFe and artificial ligands can be investigated by electrospray-ionization mass spectrometry (ESI-MS) and Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS), which may be as a representative tool to study interactions between trace metals and DOM [119,120]. Some kinds of chromatographic separation technologies, such as liquid chromatography (LC), immobilized-metal affinity (iMAC), and solid-phase extraction (SPE), would help ESI-MS and FT-ICR-MS supply more information about Lt complexing with DFe [105,121,122,123]. For example, siderophores in the eastern tropical North Pacific oxygen-deficient zone were exactly isolated and identified by LC-ESI-MS [104]; Gledhill et al. determined elemental stoichiometries of aluminum, iron, copper, nickel, zinc, cobalt, and manganese associated with a fraction of the DOM pool isolated by SPE-LC coupled to inductively coupled plasma mass (ICP-MS) [124]. Furthermore, isotope exchange LC−ICP-MS supplied us another technique for understanding Lt and HS, which can bridge molecular-level ligand identification with kinetic and thermodynamic metal-binding properties [19,125].
Therefore, the measurement of HSs by electrochemical methods, spectroscopic methods, chromatographic methods, and mass spectrometry, as well as their hyphenated techniques, have provided much information on the distribution and correlation of HSs complexed with DFe. In most estuaries, coastal waters, and open oceans, HSs or humic-like substances have a correlation with DFe; however, some special regions may have other influencing factors. This needs to explore deeply and widely on the source or sink, or other factors.
4 Possible future research
The biogeochemical cycling of Fe is crucial to many environmental processes, and DFe and its speciation are important in the marine environment. Over the past three decades, numerous and intricate interactions between DFe and Lt in seawaters have been uncovered by researchers [6,16]. Electrochemical methods, especially AdCSV, have provided substantial insights into Fe complex speciation, encompassing both ligands and eHS [86]. However, there are still unresolved issues with the use of electrochemical methods for determining Lt and eHS. For instance, these methods can only separately quantify a maximum of two to four different types of Lt based on variations in
In terrestrial, estuarine, and marine ecosystems, the distributions of DFe and eHS in river water, estuaries, coastal waters, offshore waters, and open oceans are similar (Table 2). This similarity stems from their common origins in terrestrial sources (such as lignin plant degradation), anthropogenic activities, atmospheric sources [115], and marine sources (like algae degradation). However, in specific regions, DFe and eHS may exhibit different distribution trends [80]. A more comprehensive understanding requires further research, including investigations into the water column, phytoplankton, microorganisms, aerosols, etc., or incubation experiments. Such studies can determine whether eHS are directly produced by phytoplankton or released through relevant biological processes like grazing, bacterial composition changes, and viral lysis [8,25]. They can also shed light on the differences between the sources and sinks of DFe and HSs in seawater. Recent findings indicate that interactions between Fe and various ligands in seawater are complex. These interactions involve competition among ligands to form complexes with DFe, affecting the physicochemical properties or binding characteristics of iron complexes in seawater [7]. In some open oceans, eHS and humic-like FDOM have been observed to follow different distribution trends [80,126]. It has been confirmed that the results for humic-like FDOM and eHS show either overlapping or distinct fractions of the humic pool. Given that humics account for only 5–20% and EPS account for more than 50% (Figure 1), the electroactive fraction of humics might be interfaced [22,74]. This observation aligns with the fact that AdCSV cannot distinguish more than two similar peak positions [25,86].
While electrochemical methods can provide a wealth of information about the speciation of iron (Fe) complexes and HSs, there is a need for further differentiation of these ligands in terms of their structural or chemical characteristics related to their sources and sinks [6,8]. Therefore, the current understanding of DFe, Lt, and HSs in seawater is based on fundamentally different approaches, including electrochemical methods that measure the bulk properties of a heterogeneous ligand pool, spectroscopy that determines the structure and properties of HSs, and chromatographic separation technologies coupled to ESI-MS and ICP-MS methods that characterize ligands at the molecular level. For instance, preliminary laboratory experiments have demonstrated that the complex of organic ligands on Fe would influence the initial kinetic isotope fractionation of δ 56Fe [26,127]. As can be seen from the foremost points, different HS testing methods are used with different research foci. At present, those methods have been used to explore the interaction between DFe and its speciation [8,25,121], as well as copper [82], which have obtained some important information, but mechanism and chemical properties of Fe complexing with organic matters are still needed more research [26].
In the future, if multiple detection methods can be applied in synchronous field research, the understanding of the mechanism and importance of HSs complexation with DFe would be much more comprehensive and in-depth; the sources and sinks of DFe and ligands and HSs in marine environment need to study more deeply and widely; research should be conducted on different types of marine environments, such as bridge molecular-level ligand identification with kinetic and complex group sites, as well as thermodynamic metal-binding properties.
Interestingly, the process of Fe complexation with HA could potentially enhance the removal of pollutants in environments of low salinity [128]. This discovery provides a guiding principle for future applied research on Fe complexation with HSs.
5 Conclusion
This study provides a comprehensive review of the historical progression of determining DFe and its speciation in seawater using electrochemical methods. It also discusses the impact of HSs on DFe, as explored through electrochemical methods, spectroscopy, chromatography, and mass spectrometry. Electrochemical methods have not only been employed to quantify Fe complexing speciation, HS concentrations, and the binding capacity of DFe, but they have also enhanced our understanding of the competition between different ligands for DFe. Moreover, the use of spectroscopic, chromatographic, and mass spectrometry techniques, including their hyphenated applications, has offered valuable insights into the distribution and correlation of HSs complexed with DFe. These studies suggest that further research is needed to understand the mechanisms and chemical properties of Fe complexing with organic matter. Therefore, despite multiple detection methodologies, the influence of HS complexation on DFe still warrants additional investigation. This includes synchronous analysis in diverse environments such as oceans, various types of estuaries, and coastal waters. It also considers differences in HS sources and the impact of various factors on the influence of HSs on Fe. This would contribute to our understanding of the mechanisms and significance of the biogeochemical cycling of Fe.
Acknowledgments
This study was supported by the National Natural Science Foundation of China (Grant nos. 42090043 and 42106168). This research was also funded by the Research Project of China Three Gorges Corporation (Grant no. 202103552]. The author appreciated Prof. Jing Zhang for supporting important suggestions and funding. The author also thank the anonymous reviewers and editor for the constructive comments.
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Funding information: This study was supported by the National Natural Science Foundation of China (Grant nos. 42090043 and 42106168). This research was also funded by the Research Project of China Three Gorges Corporation (Grant no. 202103552).
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Author contributions: Study conception and design, as well as reference collections, were all conducted by Han Su.
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Conflict of interest: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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- Assessing the effectiveness of utilizing low-cost inertial measurement unit sensors for producing as-built plans
- Analysis of the formation process of a natural fertilizer in the loess area
- Machine learning methods for landslide mapping studies: A comparative study of SVM and RF algorithms in the Oued Aoulai watershed (Morocco)
- Chemical dissolution and the source of salt efflorescence in weathering of sandstone cultural relics
- Molecular simulation of methane adsorption capacity in transitional shale – a case study of Longtan Formation shale in Southern Sichuan Basin, SW China
- Evolution characteristics of extreme maximum temperature events in Central China and adaptation strategies under different future warming scenarios
- Estimating Bowen ratio in local environment based on satellite imagery
- 3D fusion modeling of multi-scale geological structures based on subdivision-NURBS surfaces and stratigraphic sequence formalization
- Comparative analysis of machine learning algorithms in Google Earth Engine for urban land use dynamics in rapidly urbanizing South Asian cities
- Study on the mechanism of plant root influence on soil properties in expansive soil areas
- Simulation of seismic hazard parameters and earthquakes source mechanisms along the Red Sea rift, western Saudi Arabia
- Tectonics vs sedimentation in foredeep basins: A tale from the Oligo-Miocene Monte Falterona Formation (Northern Apennines, Italy)
- Investigation of landslide areas in Tokat-Almus road between Bakımlı-Almus by the PS-InSAR method (Türkiye)
- Predicting coastal variations in non-storm conditions with machine learning
- Cross-dimensional adaptivity research on a 3D earth observation data cube model
- Geochronology and geochemistry of late Paleozoic volcanic rocks in eastern Inner Mongolia and their geological significance
- Spatial and temporal evolution of land use and habitat quality in arid regions – a case of Northwest China
- Ground-penetrating radar imaging of subsurface karst features controlling water leakage across Wadi Namar dam, south Riyadh, Saudi Arabia
- Rayleigh wave dispersion inversion via modified sine cosine algorithm: Application to Hangzhou, China passive surface wave data
- Fractal insights into permeability control by pore structure in tight sandstone reservoirs, Heshui area, Ordos Basin
- Debris flow hazard characteristic and mitigation in Yusitong Gully, Hengduan Mountainous Region
- Research on community characteristics of vegetation restoration in hilly power engineering based on multi temporal remote sensing technology
- Identification of radial drainage networks based on topographic and geometric features
- Trace elements and melt inclusion in zircon within the Qunji porphyry Cu deposit: Application to the metallogenic potential of the reduced magma-hydrothermal system
- Pore, fracture characteristics and diagenetic evolution of medium-maturity marine shales from the Silurian Longmaxi Formation, NE Sichuan Basin, China
- Study of the earthquakes source parameters, site response, and path attenuation using P and S-waves spectral inversion, Aswan region, south Egypt
- Source of contamination and assessment of potential health risks of potentially toxic metal(loid)s in agricultural soil from Al Lith, Saudi Arabia
- Regional spatiotemporal evolution and influencing factors of rural construction areas in the Nanxi River Basin via GIS
- An efficient network for object detection in scale-imbalanced remote sensing images
- Effect of microscopic pore–throat structure heterogeneity on waterflooding seepage characteristics of tight sandstone reservoirs
- Environmental health risk assessment of Zn, Cd, Pb, Fe, and Co in coastal sediments of the southeastern Gulf of Aqaba
- A modified Hoek–Brown model considering softening effects and its applications
- Evaluation of engineering properties of soil for sustainable urban development
- The spatio-temporal characteristics and influencing factors of sustainable development in China’s provincial areas
- Application of a mixed additive and multiplicative random error model to generate DTM products from LiDAR data
- Gold vein mineralogy and oxygen isotopes of Wadi Abu Khusheiba, Jordan
- Prediction of surface deformation time series in closed mines based on LSTM and optimization algorithms
- 2D–3D Geological features collaborative identification of surrounding rock structural planes in hydraulic adit based on OC-AINet
- Spatiotemporal patterns and drivers of Chl-a in Chinese lakes between 1986 and 2023
- Land use classification through fusion of remote sensing images and multi-source data
- Nexus between renewable energy, technological innovation, and carbon dioxide emissions in Saudi Arabia
- Analysis of the spillover effects of green organic transformation on sustainable development in ethnic regions’ agriculture and animal husbandry
- Factors impacting spatial distribution of black and odorous water bodies in Hebei
- Large-scale shaking table tests on the liquefaction and deformation responses of an ultra-deep overburden
- Impacts of climate change and sea-level rise on the coastal geological environment of Quang Nam province, Vietnam
- Reservoir characterization and exploration potential of shale reservoir near denudation area: A case study of Ordovician–Silurian marine shale, China
- Seismic prediction of Permian volcanic rock reservoirs in Southwest Sichuan Basin
- Application of CBERS-04 IRS data to land surface temperature inversion: A case study based on Minqin arid area
- Geological characteristics and prospecting direction of Sanjiaoding gold mine in Saishiteng area
- Research on the deformation prediction model of surrounding rock based on SSA-VMD-GRU
- Geochronology, geochemical characteristics, and tectonic significance of the granites, Menghewula, Southern Great Xing’an range
- Hazard classification of active faults in Yunnan base on probabilistic seismic hazard assessment
- Characteristics analysis of hydrate reservoirs with different geological structures developed by vertical well depressurization
- Estimating the travel distance of channelized rock avalanches using genetic programming method
- Landscape preferences of hikers in Three Parallel Rivers Region and its adjacent regions by content analysis of user-generated photography
- New age constraints of the LGM onset in the Bohemian Forest – Central Europe
- Characteristics of geological evolution based on the multifractal singularity theory: A case study of Heyu granite and Mesozoic tectonics
- Soil water content and longitudinal microbiota distribution in disturbed areas of tower foundations of power transmission and transformation projects
- Oil accumulation process of the Kongdian reservoir in the deep subsag zone of the Cangdong Sag, Bohai Bay Basin, China
- Investigation of velocity profile in rock–ice avalanche by particle image velocimetry measurement
- Optimizing 3D seismic survey geometries using ray tracing and illumination modeling: A case study from Penobscot field
- Sedimentology of the Phra That and Pha Daeng Formations: A preliminary evaluation of geological CO2 storage potential in the Lampang Basin, Thailand
- Improved classification algorithm for hyperspectral remote sensing images based on the hybrid spectral network model
- Map analysis of soil erodibility rates and gully erosion sites in Anambra State, South Eastern Nigeria
- Identification and driving mechanism of land use conflict in China’s South-North transition zone: A case study of Huaihe River Basin
- Evaluation of the impact of land-use change on earthquake risk distribution in different periods: An empirical analysis from Sichuan Province
- A test site case study on the long-term behavior of geotextile tubes
- An experimental investigation into carbon dioxide flooding and rock dissolution in low-permeability reservoirs of the South China Sea
- Detection and semi-quantitative analysis of naphthenic acids in coal and gangue from mining areas in China
- Comparative effects of olivine and sand on KOH-treated clayey soil
- YOLO-MC: An algorithm for early forest fire recognition based on drone image
- Earthquake building damage classification based on full suite of Sentinel-1 features
- Potential landslide detection and influencing factors analysis in the upper Yellow River based on SBAS-InSAR technology
- Assessing green area changes in Najran City, Saudi Arabia (2013–2022) using hybrid deep learning techniques
- An advanced approach integrating methods to estimate hydraulic conductivity of different soil types supported by a machine learning model
- Hybrid methods for land use and land cover classification using remote sensing and combined spectral feature extraction: A case study of Najran City, KSA
- Streamlining digital elevation model construction from historical aerial photographs: The impact of reference elevation data on spatial accuracy
- Analysis of urban expansion patterns in the Yangtze River Delta based on the fusion impervious surfaces dataset
- A metaverse-based visual analysis approach for 3D reservoir models
- Late Quaternary record of 100 ka depositional cycles on the Larache shelf (NW Morocco)
- Review Articles
- Humic substances influence on the distribution of dissolved iron in seawater: A review of electrochemical methods and other techniques
- Applications of physics-informed neural networks in geosciences: From basic seismology to comprehensive environmental studies
- Ore-controlling structures of granite-related uranium deposits in South China: A review
- Shallow geological structure features in Balikpapan Bay East Kalimantan Province – Indonesia
- A review on the tectonic affinity of microcontinents and evolution of the Proto-Tethys Ocean in Northeastern Tibet
- Special Issue: Natural Resources and Environmental Risks: Towards a Sustainable Future - Part II
- Depopulation in the Visok micro-region: Toward demographic and economic revitalization
- Special Issue: Geospatial and Environmental Dynamics - Part II
- Advancing urban sustainability: Applying GIS technologies to assess SDG indicators – a case study of Podgorica (Montenegro)
- Spatiotemporal and trend analysis of common cancers in men in Central Serbia (1999–2021)
- Minerals for the green agenda, implications, stalemates, and alternatives
- Spatiotemporal water quality analysis of Vrana Lake, Croatia
- Functional transformation of settlements in coal exploitation zones: A case study of the municipality of Stanari in Republic of Srpska (Bosnia and Herzegovina)
- Hypertension in AP Vojvodina (Northern Serbia): A spatio-temporal analysis of patients at the Institute for Cardiovascular Diseases of Vojvodina
- Regional patterns in cause-specific mortality in Montenegro, 1991–2019
- Spatio-temporal analysis of flood events using GIS and remote sensing-based approach in the Ukrina River Basin, Bosnia and Herzegovina
- Flash flood susceptibility mapping using LiDAR-Derived DEM and machine learning algorithms: Ljuboviđa case study, Serbia
- Geocultural heritage as a basis for geotourism development: Banjska Monastery, Zvečan (Serbia)
- Assessment of groundwater potential zones using GIS and AHP techniques – A case study of the zone of influence of Kolubara Mining Basin
- Impact of the agri-geographical transformation of rural settlements on the geospatial dynamics of soil erosion intensity in municipalities of Central Serbia
- Where faith meets geomorphology: The cultural and religious significance of geodiversity explored through geospatial technologies
- Applications of local climate zone classification in European cities: A review of in situ and mobile monitoring methods in urban climate studies
- Complex multivariate water quality impact assessment on Krivaja River