Publications

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2015
Pizeta, I, Sander SG, Hudson RJM, Omanovic D, Baars O, Barbeau KA, Buck KN, Bundy RM, Carrasco G, Croot PL, Garnier C, Gerringa LJA, Gledhill M, Hirose K, Kondo Y, Laglera LM, Nuester J, Rijkenberg MJA, Takeda S, Twining BS, Wells M.  2015.  Interpretation of complexometric titration data: An intercomparison of methods for estimating models of trace metal complexation by natural organic ligands. Marine Chemistry. 173:3-24.   10.1016/j.marchem.2015.03.006   AbstractWebsite

With the common goal of more accurately and consistently quantifying ambient concentrations of free metal ions and natural organic ligands in aquatic ecosystems, researchers from 15 laboratories that routinely analyze trace metal speciation participated in an intercomparison of statistical methods used to model their most common type of experimental dataset, the complexometric titration. All were asked to apply statistical techniques that they were familiar with to model synthetic titration data that are typical of those obtained by applying state-of-the-art electrochemical methods - anodic stripping voltammetry (ASV) and competitive ligand equilibration-adsorptive cathodic stripping voltammetry (CLE-ACSV) - to the analysis of natural waters. Herein, we compare their estimates for parameters describing the natural ligands, examine the accuracy of inferred ambient free metal ion concentrations (]M-f]), and evaluate the influence of the various methods and assumptions used on these results. The ASV-type titrations were designed to test each participant's ability to correctly describe the natural ligands present in a sample when provided with data free of measurement error, i.e., random noise. For the three virtual samples containing just one natural ligand, all participants were able to correctly identify the number of ligand classes present and accurately estimate their parameters. For the four samples containing two or three ligand classes, a few participants detected too few or too many classes and consequently reported inaccurate 'measurements' of ambient [M-f]. Since the problematic results arose from human error rather than any specific method of analyzing the data, we recommend that analysts should make a practice of using one's parameter estimates to generate simulated (back-calculated) titration curves for comparison to the original data. The root-mean-squared relative error between the fitted observations and the simulated curves should be comparable to the expected precision of the analytical method and upon visual inspection the distribution of residuals should not be skewed. Modeling the synthetic, CLE-ACSV-type titration dataset, which comprises 5 titration curves generated at different analytical-windows or levels of competing ligand added to the virtual sample, proved to be more challenging due to the random measurement error that was incorporated. Comparison of the submitted results was complicated by the participants' differing interpretations of their task. Most adopted the provided 'true' instrumental sensitivity in modeling the CLE-ACSV curves, but several estimated sensitivities using internal calibration, exactly as is required for actual samples. Since most fitted sensitivities were biased low, systematic error in inferred ambient [M-f] and in estimated weak ligand (L-2) concentrations resulted. The main distinction between the mathematical approaches taken by participants lies in the functional form of the speciation model equations, with their implicit definition of independent and dependent or manipulated variables. In 'direct modeling', the dependent variable is the measured [M-f] (or I-p) and the total metal concentration ([M](T)) is considered independent In other, much more widely used methods of analyzing titration data - classical linearization, best known as van den Berg/Ruzic and isotherm fitting by nonlinear regression, best known as the langmuir or Gerringa methods - [M-f] is defined as independent and the dependent variable calculated from both [M](T) and [M-f]. Close inspection of the biases and variability in the estimates of ligand parameters and in predictions of ambient [M-f] revealed that the best results were obtained by the direct approach. Linear regression of transformed data yielded the largest bias and greatest variability, while non-linear isotherm fitting generated results with mean bias comparable to direct modeling, but also with greater variability. Participants that performed a unified analysis of ACSV titration curves at multiple detection windows for a sample improved their results regardless of the basic mathematical approach taken. Overall, the three most accurate sets of results were obtained using direct modeling of the unified multiwindow dataset, while the single most accurate set of results also included simultaneous calibration. We therefore recommend that where sample volume and time permit, titration experiments for all natural water samples be designed to include two or more detection windows, especially for coastal and estuarine waters. It is vital that more practical experimental designs for multi-window titrations be developed. Finally, while all mathematical approaches proved to be adequate for some datasets, matrix-based equilibrium models proved to be most naturally suited for the most challenging cases encountered in this work, i.e., experiments where the added ligand in ACSV became titrated. The ProMCC program (Omanovic et al., this issue) as well as the Excel Add-in based KINETEQL Multiwindow Solver spreadsheet (Hudson, 2014) have this capability and have been made available for public use as a result of this intercomparison exercise. (C) 2015 The Authors. Published by Elsevier B.V.

Bundy, RM, Abdulla HAN, Hatcher PG, Biller DV, Buck KN, Barbeau KA.  2015.  Iron-binding ligands and humic substances in the San Francisco Bay estuary and estuarine-influenced shelf regions of coastal California. Marine Chemistry. 173:183-194.   10.1016/j.marchem.2014.11.005   AbstractWebsite

Dissolved iron (dFe) and organic dFe-binding ligands were determined in San Francisco Bay, California by competitive ligand exchange adsorptive cathodic stripping voltammetry (CLE-ACSV) along a salinity gradient from the freshwater endmember of the Sacramento River (salinity <2) to the mouth of the estuary (salinity >26). A range of dFe-binding ligand classes was simultaneously determined using multiple analytical window analysis, involving titrations with multiple concentrations of the added ligand,salicylaldoxime. The highest dFe and ligand concentrations were determined in the low salinity end of the estuary, with dFe equal to 131.5 nmol L-1 and strong ligand (log K-Fel, Fe'(cond) >= 12.0) concentrations equal to 139.5 nmol L-1. The weakest ligands (log K-Fel, Fe'(cond) < 10.0) were always in excess of dFe in low salinity waters, but were rapidly flocculated within the estuary and were not detected at salinities greater than 7. The strongest ligands (log K-Fel, Fe'(cond) > 11.0) were tightly coupled to dFe throughout the estuary, with average excess ligand concentrations ([L]-[dFe]) equal to 0.5 nmol L-1. Humic-like substances analyzed via both CLE-ACSV and proton nuclear magnetic resonance in several samples were found to be a significant portion of the dFe-binding ligand pool in San Francisco Bay, with concentrations ranging from 559.5 mu g L-1 to 67.5 mu g L-1 in the lowest and highest salinity samples, respectively. DFe-binding ligands and humic-like substances were also found in benthic boundary layer samples taken from the shelf near the mouths of San Francisco Bay and Eel River, suggesting estuaries are an important source of dFe-binding ligands to California coastal shelf waters. (C) 2014 Elsevier B.V. All rights reserved.

2014
Earley, PJ, Swope BL, Barbeau K, Bundy R, McDonald JA, Rivera-Duarte I.  2014.  Life cycle contributions of copper from vessel painting and maintenance activities. Biofouling. 30:51-68.   10.1080/08927014.2013.841891   AbstractWebsite

Copper-based epoxy and ablative antifouling painted panels were exposed in natural seawater to evaluate environmental loading parameters. In situ loading factors including initial exposure, passive leaching, and surface refreshment were measured utilizing two protocols developed by the US Navy: the dome method and the in-water hull cleaning sampling method. Cleaning techniques investigated included a soft-pile carpet and a medium duty 3M((TM)) pad for fouling removal. Results show that the passive leach rates of copper peaked three days after both initial deployment and cleaning events (CEs), followed by a rapid decrease over about 15days and a slow approach to asymptotic levels on approximately day 30. Additionally, copper was more bioavailable during a CE in comparison to the passive leaching that immediately followed. A paint life cycle model quantifying annual copper loading estimates for each paint and cleaning method based on a three-year cycle of painting, episodic cleaning, and passive leaching is presented.

2003
Barbeau, K, Rue EL, Trick CG, Bruland KT, Butler A.  2003.  Photochemical reactivity of siderophores produced by marine heterotrophic bacteria and cyanobacteria based on characteristic Fe(III) binding groups. Limnology and Oceanography. 48:1069-1078. AbstractWebsite

Siderophores, high-affinity Fe(III) ligands produced by microorganisms to facilitate iron acquisition, might contribute significantly to dissolved Fe(III) complexation in ocean surface waters. In previous work, we demonstrated the photoreactivity of the ferric ion complexes of several alpha-hydroxy carboxylic acid-containing siderophores produced by heterotrophic marine bacteria. Here, we expand on our earlier studies and detail the photoreactivity of additional siderophores produced by both heterotrophic marine bacteria and marine cyanobacteria, making comparisons to synthetic and terrestrial siderophores that lack the alpha-hydroxy carboxylate group. Our results suggest that, in addition to secondary photochemical reaction pathways involving reactive oxygen species, direct photolysis of Fe(III)-siderophore complexes might be a significant source of Fe(II) and reactive Fe(III) in ocean surface waters. Our findings further indicate that the photoreactivity of siderophores is primarily determined by the chemical structure of the Fe(III) binding groups that they possess-hydroxamate, catecholate, or alpha-hydroxy carboxylate moieties. Hydroxamate groups are photochemically resistant regardless of Fe(III) complexation. Catecholates, in contrast, are susceptible to photooxidation in the uncomplexed form but stabilized against photooxidation when ferrated. alpha-Hydroxy carboxylate groups are stable as the uncomplexed acid, but when coordinated to Fe(III), these moieties undergo light-induced ligand oxidation and reduction of Fe(III) to Fe(II). These photochemical properties appear to determine the reactivity and fate of Fe(III)-binding siderophores in ocean surface waters, which in turn might significantly influence the biogeochemical cycling of iron.

2001
Barbeau, K, Rue EL, Bruland KW, Butler A.  2001.  Photochemical cycling of iron in the surface ocean mediated by microbial iron(III)-binding ligands. Nature. 413:409-413.   10.1038/35096545   AbstractWebsite

Iron is a limiting nutrient for primary production in large areas of the oceans(1-4). Dissolved iron(III) in the upper oceans occurs almost entirely in the form of complexes with strong organic ligands(5-7) presumed to be of biological origin(8,9). Although the importance of organic ligands to aquatic iron cycling is becoming clear, the mechanism by which they are involved in this process remains uncertain. Here we report observations of photochemical reactions involving Fe(III) bound to siderophores-high-affinity iron(III) ligands produced by bacteria to facilitate iron acquisition(10-12). We show that photolysis of Fe(III)-siderophore complexes leads to the formation of lower-affinity Fe(III) ligands and the reduction of Fe(III), increasing the availability of siderophore-bound iron for uptake by planktonic assemblages. These photochemical reactions are mediated by the alpha -hydroxy acid moiety, a group which has generally been found to be present in the marine siderophores that have been characterized(13-15). We suggest that Fe(III)-binding ligands can enhance the photolytic production of reactive iron species in the euphotic zone and so influence iron availability in aquatic systems.