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Alteration of the copper-binding capacity of iron-rich humic colloids during transport from peatland to marine waters Francois Muller, and Marco Cuscov Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b05303 • Publication Date (Web): 20 Feb 2017 Downloaded from http://pubs.acs.org on February 21, 2017

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Environmental Science & Technology

Abstract Art 338x190mm (96 x 96 DPI)

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Alteration of the copper-binding capacity of iron-rich humic colloids during transport from peatland to marine waters

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François L. L. Muller*† and Marco Cuscov†

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† Environmental Research Institute, University of the Highlands and Islands, Castle Street, Thurso KW14 7JD, United Kingdom

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Corresponding author: *Dr François Muller

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E-mail: [email protected]

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Tel: +44 1837 893575

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ABSTRACT

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Blanket bogs contain vast amounts of Sphagnum-derived organic substances which can act as

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powerful chelators for dissolved iron and thus enhance its export to the coastal ocean. To

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investigate the variations in quantity and quality of these exports, adsorptive cathodic stripping

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voltammetry (CSV) was used to characterise the metal binding properties of molecular weight-

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fractionated dissolved organic matter (MW-fractionated DOM) in the catchment and coastal

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plume of a small peat-draining river over a seasonal cycle. Within the plume, both iron- and

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copper-binding organic ligands showed a linear, conservative distribution with increasing

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salinity, illustrating the high stability of peatland-derived humic substances (HS). Within the

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catchment, humic colloids lost up to 50% of their copper-binding capacity, expressed as a molar

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ratio to organic carbon, after residing for 1 week or more in the main reservoir of the catchment.

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Immediately downstream of the reservoir, the molar ratio [L2]/[Corg], where L2 was the second

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strongest copper-binding ligand, was 0.75 × 10-4 when the reservoir residence time was 5 hours

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but 0.34 × 10-4 when it was 25 days. Residence time did not affect the carbon specific iron-

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binding capacity of the humic substances which was [L]/[Corg] = (0.80 ± 0.20) × 10-2. Our

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results suggest that the loss of copper-binding capacity with increasing residence time is caused

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by intra-colloidal interactions between iron and HS during transit from peat soil to river mouth.



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INTRODUCTION

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Iron is an essential yet often growth limiting trace element for all marine organisms.1 Until now,

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the most important external source of dissolved iron to the ocean has been thought to be

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dissolution from aeolian dust.2 Additional sources include reductive and non-reductive release

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from sediments,3,4 hydrothermal venting,5,6 iceberg inputs7 and riverine inputs.8−10 The latter

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have conventionally been regarded as an almost negligible source of iron to the open ocean on

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account of the well documented pattern of iron colloid aggregation taking place in the

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freshwater-seawater mixing zone.11,12 However, new evidence has emerged to the effect that

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iron associated with humic (and fulvic) acids can survive aggregation processes and possibly

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reach the open ocean.9,13 This hitherto unsuspected behaviour has led a number of authors to

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hypothesize that peatland runoff contributes significantly to the standing stock of iron and iron-

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binding ligands in the global ocean, especially in the < 1 kDa MW fraction13,14. Both Sphagnum-

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derived humic substances (HS)14 and vascular plant degradation products such as lignin

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oligomers15 may play an important role as iron-binding ligands. Given some types of peatlands

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such as blanket bogs have close connections to coastal seas, it is clear that large quantities of

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soluble iron leaching from these landscapes might be delivered to the coastal ocean.

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One aspect of the aquatic transport of carbon and iron which has received relatively little

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attention concerns the fluvial processing of the humic-bound iron. There is little understanding

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of how and when DOM is transformed along the headstream to sea continuum, and what

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consequences this has for iron and trace element transport.

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Here we report on the results of an intensive field and laboratory study conducted from

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the headwater stream to the coastal plume of River Thurso, a humic-rich, iron-rich river linking

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the peatlands of the Flow Country, North Scotland, to the NE Atlantic Ocean. We examined

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simultaneously the seasonal variations of organic carbon (Corg), iron (Fe), copper (Cu), iron

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ligands (L) and copper ligands (L1, L2, L3) along the aquatic continuum between the headwater 3 ACS Paragon Plus Environment

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stream and the leading edge of the coastal plume. We chose our sampling dates to represent very

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different flow conditions ranging from very low (exceeded for 99% of the 40-year flow record)

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to very high (exceeded only 0.5% of the time). Our aim was then to address the following

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questions: (1) How does peatland hydrology influence the concentration and MW distribution of

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iron and iron-binding ligands associated with humic material? (2) How is this source material

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altered during its transfer from peat soils to river mouth? (3) Does the high content of humic-

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bound Fe have a competitive effect on Cu complexation by HS and, if so, can that effect be

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described in terms of changing Cu-binding parameters with time? The river-ocean system we

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chose was ideally suited to answering these questions. Indeed, the river-borne material was

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dominated by soluble or colloidal HS known to be highly resistant to flocculation10,16,17 and also

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not susceptible to co-precipitation on account of the very low concentrations of suspended

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particulate matter. In addition, the river discharge regime exhibited large seasonal variations

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which allowed us to examine a range of water transfer times spanning two orders of magnitude.

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Organic carbon was measured together with organic binding parameters for iron and

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copper in each of four MW fractions referred to as ‘low molecular weight’ (LMW < 1 kDa),

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small colloids (1−5 kDa), medium size colloids (5−30 kDa) and larger colloids or ‘higher

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molecular weight’ (HMW > 30 kDa). A separate but complementary study was conducted to

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determine if it was possible to visualise humic colloids in river water and seawater by scanning

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electron microscopy (SEM) using the WetSEM technology. Energy dispersive X-ray analyses

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of individual colloids confirmed our assumption that iron did not occur as an inorganic solid

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phase but instead was entirely bound to organic substances.

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MATERIALS AND METHODS



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Materials and reagents. Materials used in sampling, sample processing and analysis

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should neither absorb nor release the target analyte (Corg, Fe or Cu) or any substance that

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interferes with the analysis of the metal binding ligands. This was explicitly and rigorously

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tested in the processing of the samples by ultrafiltration, as described in the Supporting

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Information (S4−S7; Table S2).

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Study area, sample collection and filtration. The study area was chosen to include a

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continuum of HS transformations during water transfer from a small peat draining stream

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(transporter) to a lake (receptor zone), a river (transporter), and finally the river’s coastal plume

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(mixing zone) which underwent advection and mixing with surrounding ocean waters. Details of

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the study area, sampling and filtration procedures are summarised in the Supporting

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Information. At each site (Figure S1), 4 litres of surface water were collected in a pre-cleaned 4-

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L low density polyethylene (LDPE) bottle for same-day filtration through 0.45-µm filters.

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Sampling took place on 1 February, 25 May, 10 September and 3 November 2013,

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corresponding to river flows (measured halfway between Sites 2 and 3) of 23, 6, 0.8 and 141 m3

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s-1, respectively. An approximate residence time of water in the lake (Loch More) was

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calculated as the time it would take to empty the lake, i.e. summing up the daily river flows from

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day 0 (sampling date) and going back through time until the volume of Loch More was

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accounted for (data source: Scottish Environment Protection Agency).

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Determination of pH, TA, DOC and freshwater cations. These water quality variables were measured according to methods described in the Supporting Information (S7).

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Ultrafiltration. Separation of the colloids into three size classes (> 30 kDa, 5−30 kDa

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and 1−5 kDa) was performed using a Sartoflow CFF system (Sartorius) equipped with two

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membrane cartridges of 0.1 m2 surface area each. Ultrafiltration was carried out in cascade,

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starting with the 30-kDa ultrafiltration of 1 L of 0.4 µm filtered sample, using the permeate as

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the feed solution for the 5-kDa ultrafiltration, and so on until a final volume of about 0.8 L of 5 ACS Paragon Plus Environment

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the 1-kDa permeate was collected. Each fractionation was stopped when the retentate volume in

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the reservoir reached 50 ml. The colloids were then ‘washed’ of unwanted solutes by

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exchanging the solution with 150 ml of UV-irradiated (90 min), Chelex batch equilibrated (48

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h), ionic-strength adjusted seawater, while keeping the solution volume constant at 50 ml.

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Freshwater colloids (Sites 1−3) were exchanged with purified seawater of salinity 5 (ionic

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strength 0.1 M): this value facilitated direct comparison of the freshwater and estuarine data

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without inducing any significant aggregation of either individual macromolecules (to form

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dimers, trimers and tetramers) or small colloids which have been shown to form larger colloids

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in response to a salinity increase from 4 to 12 in this system16. A further 450 ml of the dilute

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clean seawater medium was then added to generate 500 ml of retentate fraction which was

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collected in a 500-ml FEP bottle and kept in the dark at 4°C pending analysis. Details of the full

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operating conditions and validation procedures are given in the Supporting Information (S4−S7,

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Tables S1 and S2). The isolation of colloidal matter for SEM imaging and EDX analysis was

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carried out with a 5-kDa Hydrosart membrane in the continuous diafiltration mode according

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to methods described in the Supporting Information. A relatively low ionic strength (0.01 M),

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pH 8.4 ultrapure chloride-ammonium buffer was used as the exchange medium in order to

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enhance the negative charge and thus the adsorption of the humic colloids on the Quantomix

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membrane.

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Total metal determinations. Total Fe and Cu concentrations in the bulk samples (
30 kDa; 5−30 kDa; 1−5 kDa; < 1 kDa) were determined by

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competitive ligand equilibration cathodic stripping voltammetry (CLE-CSV) after storage for at

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least two weeks at pH 1.9 followed by either microwave digestion (which has been

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demonstrated to lead to quantitative recovery of total Fe) 9 or UV digestion (for Cu). Detailed

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information on the analysis can be found in the Supporting Information.



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Titration of Fe-binding ligands. Each sample fraction was distributed between ten

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Teflon vials (Bohlender) holding a 10-ml aliquot buffered with 10 nM borate buffer. These were

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equilibrated with Fe3+ additions to give a range of 0−50 nM Fe for the seawater samples (Site 7)

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and a range of 0−1000 nM for freshwater samples (Sites 1, 2 and 3; diluted with 0.1 M seawater

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solution). The added Fe3+ was allowed to equilibrate with the natural Fe-binding ligands for 2 h,

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at which point 2, 5, 15, 50 or 100 µM of salicylaldoxime (SA) was added to each aliquot and

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allowed to equilibrate for 12 h. Each of the ten aliquots was then analysed for labile Fe by CSV

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18,19

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the equation describing the titration curve,20 as described in the Supporting Information

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(S8−S9). This data treatment produced the Fe-binding ligand concentration, [L], and the

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conditional stability constant of the Fe-L complex, K’Fe’L, where Fe’ denotes the sum of all

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inorganic complexes of Fe3+.

in the voltammetric cell. The titration data were interpreted using a nonlinear regression to

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Titration of Cu-binding ligands. Ten 10-ml aliquots were pipetted into Teflon vials

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and each was buffered with a final concentration of borate-ammonium buffer of 10 mM and a

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final pH of 8.2. The aliquots were spiked with Cu2+ concentrations in the range of 0−5 or 0−15

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nM (depending on the initial total Cu concentration). After an equilibration time of 2 h, 2.5 µM

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SA was added to each vial and the vials were left to equilibrate for 12 h. Labile Cu was

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measured in each vial by CSV.21,22 In order to widen the detection window of Cu complexes,

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high-affinity Cu ligands were also determined in a separate, so-called ‘reverse’ titration:23 this

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titration was carried out with incremental additions of the competing ligand SA, at the natural

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concentration level of Cu. By combining the results of the forward and reverse titrations, we

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obtained two sets of Cu-binding parameters denoted ([L1], K1’) and ([L2], K2’), as described in

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the Supporting Information (S10−S12). It is important to note that unlike K’Fe’L, which is relative

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to [Fe’], K1’ and K2’ are the conditional stability constants expressed in terms of [Cu2+].


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Observation of aquatic colloids with a new analytical procedure and imaging by

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SEM. We developed a procedure to visualise individual aquatic humic colloids for the first time

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in natural waters. The main objective was to find out whether Fe was homogeneously distributed

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within the organic matrix or whether small Fe oxide entities were also present. The procedure is

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described on page S13 of Supporting Information.

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RESULTS

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The full dataset is presented in Tables S3−S10. In these tables and the following

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sections, the < 1 kDa MW fraction is the ‘truly dissolved’ or LMW fraction while the > 30 kDa

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MW fraction is referred to as the HMW fraction. The sum of the 1−5, 5−30 and > 30 kDa

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fractions is referred to as the ‘colloidal fraction’. Sample collection sites (Figure S1) are

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categorised as ‘headwater’ (Site 1), ‘river water’ (Sites 2−3) and ‘coastal’ or ‘river plume

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waters’ (Sites 4−7).

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Size distributions of Corg, Fe and Cu. These are represented as histograms in Figure 1

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Sites 1, 3 and 7 were chosen to illustrate peatland water, river water and seawater, respectively.

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Irrespective of season, Corg, Fe and Cu showed distinct size distributions. Organic carbon

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distributions among the four MW fractions showed a good deal of seasonal variability in

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freshwater samples whereas a slight maximum was evident in the 1−5 kDa range in seawater

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irrespective of season. Iron showed a local maximum between 1 and 5 kDa superimposed on a

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general increase with increasing MW. Copper was preferentially associated with the LMW

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fraction and decreased with increasing MW, except at the marine site where its distribution

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became featureless (Figure 1). These general patterns were reproducible across the four

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sampling seasons. The proportions of Corg, Fe and Cu associated with the HMW fraction were at

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their highest in February and November (high river flow). For each MW fraction, one-way 8 ACS Paragon Plus Environment


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ANOVA was carried out to study the effect of rainfall (as quantified by river flow) on the

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relative abundance of Corg, Fe, Cu and their ligands in that fraction. Proportions of Fe, Cu, L1

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and L2 decreased significantly (p < 0.05) with increasing river flow in the LMW fraction;

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proportions of Fe and L decreased significantly with increasing river flow in the 1−5 kDa

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fraction; proportions of Corg, Cu, L1 and L2 increased significantly with increasing river flow in

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the 5−30 kDa fraction; proportions of Corg, Fe and L increased significantly with increasing river

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flow in the HMW fraction (Tables S11 and S12). To summarise, whenever ANOVA detected

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differences linked with increasing river flow, these differences always corresponded to relative

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decreases of the < 1 kDa and 1−5 kDa fractions, and relative increases of the 5−30 kDa and > 30

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kDa fractions.

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Fe speciation in the bulk and size-fractionated samples. Iron concentrations, Fe-

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binding ligand concentrations (expressed as molar Fe equivalents) and conditional stability

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constants of Fe complexes with organic ligands are presented in Tables S7-S10. One ligand

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class was detected throughout, referred to simply as L. Iron and Fe-binding ligand

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concentrations, denoted [FeT] and [L] respectively, co-varied along the freshwater-seawater

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continuum, ranging from 5000−20,000 nM in the peatland stream to 80−200 nM in the far-field

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plume. Previous studies19,23 had led us to expect an insignificant effect of ionic strength on K’

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over the range 0.1−0.7 M, as was indeed the case. The degree of association of L with LMW

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components generally increased from freshwater (7−22%) to seawater (18−34%), except in the

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November survey where it was 7−11% throughout. The relative importance of the LMW

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fraction recorded at any given point downstream of Loch More increased with decreasing river

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flow. This trend was most pronounced at Site 2, near the outlet of Loch More, where the

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proportion of iron-binding ligands associated with the LMW fraction was 25% on 10 Sep (base

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flow), 17% on 25 May (near average flow) and 10−11% on 1 Feb and 3 Nov (high flow).

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Finally, a significant negative relationship (r2 = 0.49, p < 0.05, n = 12) was found between the 9 ACS Paragon Plus Environment

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percentage of LMW ligands in river samples and the value log K’ for the complex formation

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between Fe and the total ligand pool (Figure S2). This dependence of log K’ on %[L]LMW

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suggested a stronger association of Fe to the HMW than to the LMW components of HS.

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However, speciation analyses of the isolated fractions could not validate this theory. Instead, log

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K’ values measured on the isolated fractions showed no significant dependence on the MW cut-

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off of the ultrafiltration membranes: log K’ = 10.93 ± 0.34 (< 1 kDa), log K’ = 10.90 ± 0.27

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(1−5 kDa), log K’ = 11.01 ± 0.27 (5−30 kDa) and log K’ = 11.05 ± 0.24 (> 30 kDa).

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Cu speciation in the bulk and size-fractionated samples. Copper speciation results are

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presented in Tables S7-S10. Up to three ligands falling into distinct log K’ classes were detected

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in the headwater stream (Site 1): these ligands were denoted L1 (15.1 < log K1’< 15.7), L2 (12.2

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< log K2’< 13.0) and L3 (10.2 < log K1’< 11.0). Two ligands were detected in the plume waters

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(Sites 4−7); their log K’ values were aligned with the above Class 1 and Class 2 and as such

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these ligands are also referred to as L1 and L2. In all the surveys, L1 decreased linearly from [L1]

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= 4−12 nM at S = 0 to [L1] = 0.7−1.3 at S = 35 throughout the coastal plume. By contrast,

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variations of L2 showed non-linearity in the plot between S = 0 and S = 35, except in the

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September survey (Figure S3). Concerning the distribution of Cu-binding ligands among the

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different size classes, a relative shift towards LMW with decreasing river flow was recorded at

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Sites 1−3. All sites combined, the proportion of L1 associated with the LMW fraction was

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54−64% on 10 Sep (base flow), 42−62% on 25 May (near average flow), 24−39% on 1 Feb

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(high flow) and 19−23% on 3 Nov (very high flow). The proportion of L2 associated with the

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LMW fraction was 47−62% on 10 Sep (base flow), 42−58% on 25 May (near average flow),

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33−59% on 1 Feb (high flow) and 33−44% on 3 Nov (very high flow). Finally, there was no

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significant dependence of log K’ values measured on isolated fractions on the MW cut-off.

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Morphology, size and composition of isolated aquatic colloids. SEM images of

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colloidal matter isolated from Site 3 (Figure S4a, 1 Feb; Figure S4c, 3 Nov) and Site 6 (Figure 10 ACS Paragon Plus Environment


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S4b, 1 Feb; Figure S4d, 3 Nov) revealed a disperse population of very similar, almost spherical

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particles with diameter between 100 and 400 nm. No significant degree of aggregation to

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produce particles larger than 0.45 µm could therefore be inferred from these images, despite the

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lengthy CFF processing which had resulted in retentate colloidal concentrations 10 times (Site

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3) or 80 times (Site 6) greater than ambient concentrations. Conversely, colloids smaller than

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100 nm, expected to be very abundant, could not be seen on these images because the SEM

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resolution of low-contrast material such as DOM was in the region of 100 nm. With this

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observation in mind, and also bearing in mind that DOM preconcentration must have induced

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agglomeration of some of the LMW species, it must be stressed that the images in Fig. S4 do not

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reflect the ‘true’ DOM size distribution. EDX analyses produced spectra (Figure S4) which

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were indistinguishable from those of complexes formed between humic substances and Fe.24

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DISCUSSION

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Positioning the freshwaters of this study in terms of their [Fe]/[Corg] molar ratio

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with respect to other boreal bog-draining surface waters. To put this work in a broader

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perspective, it is worth comparing the range of [Fe]/[Corg] values recorded in the 0.45-µm

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filtered samples throughout our catchment (0.5−2.0 × 10-2) with those reported in other peatland

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streams and ponds of the northern hemisphere, i.e. Alaska (0.3−1.8 × 10-2),25 Canada (0.2−3.3 ×

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10-2),26 Austria (1.4−2.8 × 10-2),27 southern Sweden (2.6−5.1 × 10-2),28 Finland (3.4 × 10-2)29 and

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NW Russia (0.3−6.2 × 10-2).30,31 It is interesting to note that our range overlaps with those of

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studies where filterable Fe occurred in part as (oxyhydr)oxide nanoparticles and nanoparticulate

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aggregates. Even so, our Fe speciation results or SEM images (discussed below) produced no

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evidence that Fe (oxyhydroxide) minerals were present.


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Season- and hydrology-dependent changes in the size distribution and metal

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binding properties of headstream DOM. In natural waters where both organic carbon and iron

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are abundant, Fe-rich nano-oxides may be coprecipitated with organic matter or organic matter

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may be adsorbed on the mineral surfaces.32−34 Either way, the surface charge density of the

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colloids is likely to be dictated by the presence of humic and fulvic acid groups.35 Therefore,

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organic-Fe colloids would be expected to develop a negative surface charge at the pH (8.4) used

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in our medium exchange treatment. As such they would be expected to attach to the poly-l

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lysine coated membrane and thus be wet-imaged by SEM. However, EDX analyses of the

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membrane-adsorbed colloids (Figure S4) never suggested that solid inorganic phases of Fe were

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present in the colloids. Although their existence in the inner core of the colloids cannot be

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totally ruled out,36 we believe it much more likely that Fe was homogeneously distributed inside

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the organic matter matrix. This assumption is supported by the similarity of the mean size and

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composition of our isolated colloids to the sizes and compositions reported for ‘blended’

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organic-Fe colloids known to comprise organically complexed Fe 37−39 (and possibly Fe-bridged

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entities)40,41 rather than organic-coated Fe oxides. It is further supported by the fact that the

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partitioning of Fe into colloidal and soluble pools corresponded closely to the partitioning of

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ligands (r2 = 0.95, n = 16, freshwater samples only; r2 = 0.89, n = 28, all samples): a discrepancy

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between the two would have been detected if part of the colloidal Fe had been a solid inorganic

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phase.42

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In order to successfully describe fluvial reprocessing of the Fe-rich DOM, we need a

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quantitative understanding of what influences the quality of the source DOM exported from

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peatland soils. The quantity of DOM released is not, in itself, a good indicator of its size

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distribution or metal binding properties. Indeed, several authors have investigated the influence

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of DOC concentration in experiments performed with aquatic NOM. They observed no

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significant concentration-dependent changes in the size distribution of UV-absorbing DOM 26,43



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or that of metals (Fe, Cu, Zn).44 In our catchment, variations in MW fractionation appear to be

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mainly driven by hydrological conditions. Figure 1 shows that at each site, the concentrations of

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Corg and Fe in the highest MW fraction (> 30 kDa) were higher in Feb and Nov than in May or

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Sep, whereas Corg and Fe measured in the other fractions do not show this trend. This is

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consistent with a rise in the water table under wetter conditions (Figure 2) since recently fixed

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HMW organic carbon is more abundant in the top layer of the peat soil,45,46.

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Decrease in the Cu-binding capacity of DOM brought about by fluvial processing.

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Some of the abovementioned differences in the binding of Fe and Cu with aquatic HS were

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expected. For example, it was likely that the triple-charged Fe(III) ions would form stronger

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complexes with the more acidic hydrophilic fulvic acids than with the less acidic and more

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hydrophobic humic acids.40,41 Since the large concentration of ionised groups in fulvic acids

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favours the formation of intermolecular bridges,41 it follows that Fe tends to be present in larger-

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size aggregates than Cu. Conversely, Cu(II) is known to form stronger complexes with humic

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than with fulvic acids, including aromatic structures of humic acids; 47 these are stabilised by

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only weak hydrophobic interactions and thus end up as smaller entities than the Fe-bridged

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fulvic aggregates. In addition, a recent study has revealed that Fe binding in humic samples is

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entirely dependent on oxygen-containing HS functional groups, such as carboxyl and phenolic,39

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which is not the case for Cu.

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Notwithstanding the different distributions of Fe and Cu (Figure 1) and their respective

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ligands (Figure 2) among the size classes, it nevertheless remains the case that both elements

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(and their respective ligands) were distributed across the full size spectrum. Such a broad

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distribution is consistent with our established knowledge about humic colloids consisting of

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supramolecular associations of relatively small molecules loosely bound together by hydrogen

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bonds, cation bridges (e.g. with Ca2+, Fe3+ or Al3+), and weak hydrophobic interactions.16,41,43,48

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It is also consistent with our previous observations that the vast majority of Fe- and Cu-binding 13 ACS Paragon Plus Environment

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ligands in this catchment are humic. A recent study showed that Fe and Cu occurring in similar

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concentrations competed for the same HS binding ligands so that the ligand concentrations for

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Fe and Cu were the same.23 In the present study, the concentration of Fe-binding ligands, [L],

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was of a similar magnitude to that of the Cu-binding ligands, [L1] + [L2], at the marine site only:

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[L] = 1−4 × ([L1] + [L2]) throughout the year. At the freshwater sites, [L] was up to two orders

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of magnitude higher than [L1] + [L2]. The explanation for the diverging values in freshwater

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must be related to the fact that Fe was a main component of the freshwater samples whereas Cu

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was a trace component. Indeed, the molar ration FeT/CuT was in the range 750−5000 at Sites 1

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to 3, compared to 36−65 at the marine site. Therefore, the most likely explanation for changes in

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Cu-binding properties is that Fe originating from the mineral subsoil of the peatlands 32,43,46 was

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able to modify the properties of aquatic organic colloids as they were carried along the

310

stream.48,49 A second possibility, i.e. that Cu-binding ligands were selectively broken down by

311

biological or photochemical transformations is very unlikely because of (i) the scarcity of

312

biologically-produced ligands in this catchment and (ii) the relative uniformity of log K1’ and

313

log K2’ values between Site 1 and Site 3. The log K1’ and/or log K2’ values would be expected to

314

shift in response to a decrease in the proportion of Cu-selective, biologically produced ligands.

315

Since organic carbon is a passive tracer throughout the river catchment and estuary,16

316

variations in binding site density ([L]/[Corg], [L1]/[Corg] or [L2]/[Corg]) with time or with distance

317

from the source are likely to provide information about internal transformations of the DOM. At

318

Site 1, the Fe-binding ligand content (mol L/mol Corg) of the freshly formed Fe-OM material

319

(Site 1) was 0.3−0.7 × 10-2 in the < 1 kDa fraction but 2−8 × 10-2 in the > 30 kDa fraction.

320

Conversely, the Cu-binding ligand contents of the DOM sampled at Site 1 were [L1]/[Corg] =

321

0.6−2.0 × 10-5 and [L2]/[Corg] = 1.0−1.2 × 10-4 in the < 1 kDa fraction, but [L1]/[Corg] = 0.4−1.8

322

× 10-5 and [L2]/[Corg] = 0.2−0.5 × 10-4 in the > 30 kDa fraction. Downstream of Loch More

323

(Sites 2 and 3), a further distinction can be made for Cu (but not Fe) ligands between high flow 14 ACS Paragon Plus Environment


Page 16 of 33

324

and low flow conditions: at high flow, the carbon specific Cu-binding capacity of the DOM was

325

unchanged from that measured upstream of Loch More whereas it declined significantly at low

326

flow conditions. This is clearly visible in Figure 3, where metal binding capacities of each size

327

fraction recorded at Site 2 and 3 are plotted against the calculated residence time of water in

328

Loch More. It can be seen from Figure 3 that (i) an increase in residence time leads to a loss of

329

Cu-binding (but not Fe-binding) site density and (ii) the loss from any colloidal fraction is

330

proportionally greater than that from the soluble fraction. Thus, colloids lost up to 50% of their

331

L2 site density after residing for 1 week or more in Loch More while the truly dissolved material

332

lost only 28%. Taking into account previous work on the Fe and Cu binding properties of

333

HS,23,51,52 it can be concluded that a kinetic process involving colloidal Fe and Corg must be

334

responsible for the gradual inhibition of Cu-HS complexation.

335

Iron-rich humic substances are formed underground upon reaction of Fe with HS and 46

336

subsequently transported to the stream via either surface runoff or groundwater seepage

337

Given the transient conditions they experience, it is therefore not surprising that they should

338

undergo changes with time. The nature of these changes is likely dependent on the

339

physicochemical forms of Fe and organic matter and their mutual interactions.30,32,34 In turn,

340

these depend on the [Fe]/[Corg] molar ratio.33,34,53 Natural and synthetic Fe-HS colloids formed

341

from Fe(II) titration of HS are generally modelled as agglomerates of HS molecular units of

342

hydrodynamic diameter 1.5−3.0 nm, interspersed with Fe2+, Fe3+ or Fe oxide entities depending

343

on the [Fe]/[Corg] ratio.54,55 In this study, the [Fe]/[Corg] ratio measured in bulk samples at Sites 1

344

to 3 was in the range 0.7−2.3 × 10

345

formation of Fe-HS coprecipitates 32,34,56 but large enough to allow the possibility that Fe oxide

346

nanoparticles or small polynuclear structures of hydrolysed Fe(III) may be distributed inside the

347

humic matrix. At the [Fe]/[Corg] ratio prevailing in this study, such polynuclear Fe species would

348

be typically 1 nm diameter in size.54 The existence of such small polynuclear Fe species may

-2

.

mol/mol. These values are too small to allow for the


Page 17 of 33


349

explain why we were unable to detect any Fe-bearing mineral phases by SEM/EDXA. The slow

350

decomposition of these hypothetical polynuclear Fe species and their subsequent dispersion

351

throughout the humic colloids may have led to Fe outcompeting any trace metals for

352

complexation with humic ligands.49 Such a mechanism has been shown to halve the

353

complexation capacity of humic colloids towards Eu(III) over a timescale of 2 days.50 Indeed we

354

found that about one half of the original Cu-binding ligand concentration [L2] has been excluded

355

from humic complexation over a similar timescale (Figure 3). However, caution should be

356

exercised in attributing our results to this mechanism, not least because it was established in the

357

presence of 100 µM Fe, i.e. 10 times our [FeT] values, as well as 10 times our [Fe]/[Corg] values.

358

An alternative mechanism to explain the in-stream alteration of Cu-binding properties is that

359

they were influenced by the molecular architecture of the HS, which in turn was governed by

360

their Fe content and the time they spent in the aquatic system.

361

Fe and Cu speciation in riverine versus marine waters. A linear relationship was

362

generally found between each chemical variable and salinity, which corroborates previous

363

observations that physical mixing is the main driver in this plume environment.9,16,51 The only

364

exception to conservative mixing was for Cu (Figure S5) and L2 (Figure S3) in the > 5 kDa

365

fractions at times of high river flow. Most of the time, coagulation was not a factor as Fe and Cu

366

species travelled into coastal waters. In the absence of any significant estuarine or coastal

367

processing, our objective is to compare riverine (Site 3) and marine samples (Site 7).

368

Comparing the carbon specific Fe and Cu contents of the DOM pool reveals some

369

striking differences. The molar ratio [Fe]/[Corg] in coastal ocean waters (0.05−0.10 × 10-2) was

370

systematically 10 ± 4 times lower than in the freshwater outflow (0.53−0.85 × 10-2). By contrast,

371

the molar ratio [Cu]/[Corg] in marine waters (0.10−0.23 × 10-4) was systematically 1.7 ± 0.4

372

times higher than in the freshwater outflow (0.07−0.16 × 10-4). The same argument can be made

373

for their respective ligands. These findings clearly support the view that peatland-derived Fe16 ACS Paragon Plus Environment


374

rich humic substances transported by River Thurso are responsible for a significant flux of Fe

375

and Fe-binding ligands to marine waters but not a significant flux of Cu or Cu-binding ligands.

376

Finally, the MW distributions of Corg, Fe and Cu in freshwater were strikingly different

377

from one another although the differences were not so great in seawater (Figure 1). Taking the

378

LMW fraction as an example, it comprised 23−32% of the total dissolved Corg (Tables S3−S6;

379

Figure 1), 10−20% of Fe and 42−68% of Cu (Tables S7−S10; Figure 1) measured at Site 3, the

380

exact value depending on time of year. By contrast, the percentages of Corg, Fe and Cu

381

associated with the LMW fraction at Site 7 were 17−28%, 13−30% and 14−36%, respectively.

382

As already mentioned, two factors contributed to the large percentage of Cu found in the LMW

383

fraction at Site 3. The first was the affinity of Cu for the smaller, more hydrophobic components

384

of HS. The second was the partial exclusion of Cu from the larger, more hydrophilic

385

components of HS to which Fe was strongly and extensively associated. Such fractionation of

386

Cu towards the LMW fraction was not observed in marine waters (Figure 1). The explanation

387

can be found in Figure 4, which clearly points to a marine, probably biological source51,57−59 of

388

L2 type ligands. These L2 ligands are associated here with the 5−30 and > 30 kDa colloidal

389

fractions (Figure 4), hence the dramatic shift in the size distribution of Cu from riverine to

390

marine waters. We conclude that the peatland-derived, Fe-rich humic colloids that are

391

responsible for transporting significant amounts of Fe and Fe-binding ligands to the coastal

392

ocean do not necessarily play this role for Cu and other trace metals. Instead, the degree of Cu

393

complexation by Fe-rich humic colloids may be limited as a result of (i) direct competitive

394

effects of Fe(III) or (ii) structural changes induced by Fe(III) within the humic colloids. It

395

remains to be seen whether the blocking effect of Fe on Cu complexation by terrestrial HS is

396

directly responsible for triggering in situ biological production of Cu-binding ligands in coastal

397

waters.

398 17 ACS Paragon Plus Environment

Page 18 of 33

Page 19 of 33


399

ASSOCIATED CONTENT

400

Supporting Information

401

Detailed descriptions of (i) the study area and sampling methods, (ii) CFF procedures, cleaning

402

procedures, calibrations and mass balance calculations, (iii) determination of water quality

403

variables, (iv) Fe speciation calculations, (v) Cu speciation calculations, and (vi) SEM imaging

404

of large colloids: pages S2−S13. Retention coefficients of standard macromolecules (Table S1)

405

and recovery of elements through the successive CFF stages (Table S2): pages S6−S7. Water

406

quality and metal speciation dataset (Tables 3−10): pages S15−S22. Proportions of Corg, Fe, Cu

407

and ligands present in each of the four size fractions of DOM: page S23. Figures S1−S5: pages

408

S24−S28.

409

410

AUTHOR INFORMATION

411

Corresponding Author

412

*Email: [email protected]

413

Note

414

The authors declare no competing financial interest.

415

416

ACKNOWLEDGMENTS

417

We thank Sophie Tankéré-Muller (Caithness Kayak Club) for collecting water samples in

418

Thurso Bay, Andrew Skinner and Graham Thompson (Royal Society for the Protection of

419

Birds) for providing us with water table information, Ian Reynard (Scottish Environmental

420

Protection Agency) for providing the daily mean flow dataset for River Thurso, and Russell 18 ACS Paragon Plus Environment


421

Garvie (ISS Group Services Ltd) for patiently resolving our SEM technical problems. We

422

acknowledge a Small Grant (SG88) from MASTS and financial support from the European

423

Regional Development Fund under the MaREE Project.


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Figure 1. Distribution of dissolved organic carbon, Fe and Cu among the four isolated size

617

fractions at Sites 1, 3 and 7 on 1 Feb, 25 May, 10 Sep and 3 Nov 2013.

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Figure 2. Relationships between water table levels monitored at a site situated 1.5 km NNW of

619

Site 1 and corresponding percentages of DOC and ligand concentrations measured in the HMW

620

fraction (> 30 kDa) of DOM at Site 1.

621

Figure 3. Carbon-normalised concentrations of (a) Fe-binding ligands, (b) stronger Cu-binding

622

ligands and (c) weaker Cu-binding ligands detected at Sites 2 and 3, plotted as a function of the

623

residence time of water in Loch More.

624

Figure 4. Carbon-normalised concentrations of (a) Fe-binding ligands, (b) stronger Cu-binding

625

ligands and (c) weaker Cu-binding ligands detected at Sites 3 to 7, plotted as a function of

626

salinity.

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Distribution of dissolved organic carbon, Fe and Cu among the four isolated size fractions at Sites 1, 3 and 7 on 1 Feb, 25 May, 10 Sep and 3 Nov 2013. 177x146mm (300 x 300 DPI)


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Figure 2. Relationships between water table levels monitored at a site situated 1.5 km NNW of Site 1 and corresponding percentages of DOC and ligand concentrations measured in the HMW fraction (MW > 30 kDa) at Site 1. 89x124mm (300 x 300 DPI)



Figure 3. Carbon-normalised concentrations of (a) Fe-binding ligands, (b) stronger Cu-binding ligands, and (c) weaker Cu-binding ligands detected at Sites 2 and 3, plotted as a function of the residence time of water in Loch More. 87x159mm (300 x 300 DPI)


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Figure 4. Carbon-normalised concentrations of (a) Fe-binding ligands, (b) stronger Cu-binding ligands, and (c) weaker Cu-binding ligands detected at Sites 3 to 7, plotted as a function of salinity. 88x159mm (300 x 300 DPI)


Alteration of the Copper-Binding Capacity of Iron ... - ACS Publications

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