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Rising concentrations of atmospheric carbon dioxide are causing acidification of the oceans. This results in changes to the concentrations of key chemical species such as hydroxide, carbonate and bicarbonate ions. These changes will affect the distribution of different forms of trace metals. Using IPCC data for pCO2 and pH under four future emissions scenarios (to the year 2100) we use a chemical speciation model to predict changes in the distribution of organic and inorganic forms of trace metals. Under a scenario where emissions peak after the year 2100, predicted free ion Al, Fe, Cu, and Pb concentrations increase by factors of up to approximately 21, 2.4, 1.5, and 2.0 respectively. Concentrations of organically complexed metal typically have a lower sensitivity to ocean acidification induced changes. Concentrations of organically complexed Mn, Cu, Zn, and Cd fall by up to 10%, while those of organically complexed Fe, Co, and Ni rise by up to 14%. Although modest, these changes may have significance for the biological availability of metals given the close adaptation of marine microorganisms to their environment.

Concentrations of Al, Fe, Mn, Ni, Cu, Cd, Pb, and Zn were measured using DGT (diffusive gradients in thin-films) devices deployed in situ in 34 headwater streams in Northern England. Mean values of filtered samples analyzed by ICP-MS (inductively coupled plasma mass spectrometry) were used, along with DOC (dissolved organic carbon), pH and major ions, to calculate the distribution of metal species using the speciation code WHAM. DGT-measured concentrations, [Me]DGT, of Zn and Cd were generally similar to concentrations in filtered samples, [Me]filt. For the other metals, [Me]DGT was similar to or lower than [Me]filt. Calculation of the maximum dynamic metal from the speciation predicted using WHAM showed that most of the lower values of [Cu]DGT could be attributed to the dominance of Cu-fulvic acid complexes, which diffuse more slowly than simple inorganic species. Similar calculations for Al, Pb, and Mn were consistent with appreciable proportions of these metals being present as colloids that are not simple complexes with humic substances. Differences between WHAM predictions and the measured [Ni]DGT indicated that WHAM used with the default binding parameters underestimates Ni binding to natural organic matter. Plots of [Me]DGT versus the ratio of bound metal to DOC provided slight evidence of heterogeneous binding of Pb and Cu, while results for Mn, Cd, and Zn were consistent with weak binding and complete lability.

Humic acid was isolated from three contrasting organic-rich soils and acid-base titrations performed over a range of ionic strengths. Results obtained were unlike most humic acid data sets; they showed a greater ionic strength dependency at low pH than at high pH. Forward- and back-titrations with the base and acid revealed hysteresis, particularly at low pH. Previous authors attributed this type of hysteresis to humic acid aggregates-created during the isolation procedure-being redissolved during titration as the pH increased and regarded the results as artificial. However, forward- and back-titrations with organic-rich soils also demonstrated a similar hysteretic behavior. These observations indicate (i) that titrations of humic acid in aggregated form (as opposed to the more usual dissolved form) are more representative of the acid-base properties of humic acid in soil and (ii) that the ionic strength dependency of proton binding in humic acid is related to its degree of aggregation. Thus, the current use of models based on data from dissolved humic substances to predictthe acid-base properties of humic acid in soil under environmental conditions may be flawed and could substantially overestimate their acid buffering capacity.

The aim of the present work is to model iron speciation during its interaction with natural organic matter. Experimental data for iron speciation were achieved with an insolubilised humic acid used as an organic matter analogue for 30microM to 1.8 mM total iron concentrations and 2< or = pH< or = 5.5. IHA was found to be able to impose its redox potential to the solution and therefore the Fe(ll)/Fe(lll) ratio. Model VI and the NICA-Donnan model have been adjusted to experimental results of acid-base titrations, total iron measurements, and redox speciation in solution. They both describe well pH and concentration dependence of iron adsorption. For high iron concentration, Fe(lll) solution activity is limited by precipitation of a poorly ordered Fe oxyhydroxide with a higher solubility (log Ks = 5.6-5.7) than ferryhydrite described in the litterature.

We present a method to calculate critical limits of cationic heavy metals accounting for variations in soil chemistry. We assume the free metal ion concentration (Mfree) to be the most appropriate indicator of toxicity, combined with a protective effect of soil cations (e.g., H+, Ca2+). Because soil metal cations tend to covary with pH, the concentration of Mfree exerting a given level of toxic effect (Mfree,toxic) can be expressed as a function of pH alone. We use linear regression equations to derive Mfree,toxic in toxicity experiments from soil pH, organic matter content, and endpoint soil metal. Chronic toxicity data from the literature, for plants, invertebrates, microbial processes, and fungi are interpreted in terms of an average log Mfree,toxic together with distributions of species sensitivity. This leads to critical limit functions to protect 95% of species, of the form log Mfree,CRIT = (pH + gamma. Appreciable effects of soil pH upon log Mfree,CRIT are found, with alpha = -1.21 (Cu), -0.34 (Zn), -0.43 (Cd), and -0.83 (Pb). Critical limit functions in terms of the geochemically active soil metal (Msoil,CRIT), that pool of metal which controls the free ion concentration, have also been derived, with soil pH and organic matter content as variables. The pH effect on Msoil,CRIT is relatively small, with slopes of 0.05 (Cu), 0.19 (Zn), 0.16 (Cd), and 0.20 (Pb), since the effect of pH on Mfree,CRIT is countered by the variation of Mfree with pH.

A total of 171 datasets of literature and experimental data for metal-ion binding by fulvic and humic acids have been digitized and re-analyzed using the NICA-Donnan model. Generic parameter values have been derived that can be used for modeling in the absence of specific metalion binding measurements. These values complement the previously derived generic descriptions of proton binding. For ions where the ranges of pH, concentration, and ionic strength conditions are well covered by the available data,the generic parameters successfully describe the metalion binding behavior across a very wide range of conditions and for different humic and fulvic acids. Where published data for other metal ions are too sparse to constrain the model well, generic parameters have been estimated by interpolating trends observable in the parameter values of the well-defined data. Recommended generic NICA-Donnan model parameters are provided for 23 metal ions (Al, Am, Ba, Ca, Cd, Cm, Co, CrIII, Cu, Dy, Eu, FeII, FeIII, Hg, Mg, Mn, Ni, Pb, Sr, Thv, UVIO2, VIIIO, and Zn) for both fulvic and humic acids. These parameters probably represent the best NICA-Donnan description of metal-ion binding that can be achieved using existing data.

The complexation of heavy metals with dissolved organic matter (DOM) in the environment influences the solubility and mobility of these metals. In this paper, we measured the complexation of Cu, Cd, Zn, Ni, and Pb with DOM in the soil solution at pH 3.7-6.1 using a Donnan membrane technique. The results show that the DOM-complexed species is generally more significant for Cu and Pb than for Cd, Zn, and Ni. The ability of two advanced models for ion binding to humic substances, e.g., model VI and NICA-Donnan, in the simulation of metal binding to natural DOM was assessed by comparing the model predictions with the measurements. Using the default parameters of fulvic and humic acid, the predicted concentrations of free metal ions from the solution speciation calculation using the two models are mostly within 1 order of magnitude difference from the measured concentrations, except for Ni and Pb in a few samples. Furthermore, the solid-solution partitioning of the metals was simulated using a multisurface model, in which metal binding to soil organic matter, dissolved organic matter, clay, and iron hydroxides was accounted for using adsorption and cation exchange models (NICA-Donnan, Donnan, DDL, CD-MUSIC). The model estimation of the dissolved concentration of the metals is mostly within 1 order of magnitude difference from those measured except for Ni in some samples and Pb. The solubility of the metals depends mainly on the metal loading over soil sorbents, pH, and the concentration of inorganic ligands and DOM in the soil solution.

The binding of americium (Am) by peat humic acid (PHA) has been investigated at Am concentrations between 10(-1) and 10(-7) M at pH approximately 2.6 in the presence and absence of Cu as a competing ion. Cu-PHA binding was also investigated in order to derive independent binding constants for use in modeling the competitive binding studies. Humic ion-binding model VI was used to compare the acquired data with previously published binding data and to investigate the importance of high-affinity binding sites in metal-PHA binding. Am was not observed to bind to high-affinity, low-concentration binding sites. The model VI parameter deltaLK2 takes into accountthe small number of strong sites in PHA and was found to be important for Cu-PHA binding but not for Am-PHA binding, regardless of whether Cu was present. Analysis of the PHA sample revealed that it contained a considerable quantity of Fe not removed by the extraction procedure, much of which is believed to be present as Fe(III). Model VI was then used to investigate the possible importance of the presence of Fe(III) in the Am-PHA binding experiments. When Fe(III) was assumed to be present, improved descriptions of the data by model VI were obtained by assuming that all of the metals [Am, Cu, and Fe(III)] undergo strong binding. This highlights the importance of Fe(III) competition in metal-PHA binding studies and possible shortcomings in the extraction procedure used to extract PHA.

Forty-nine datasets consisting of literature and experimental data for proton binding by fulvic and humic acids have been analyzed using the NICA-Donnan model. The model successfully described the behavior of the individual datasets with a high degree of accuracy and highlighted the differences in site density and binding affinity between fulvic acids (FA) and humic acids (HA) while demonstrating their strong similarities. The data have also been used to derive generic model descriptions of proton binding by FA and HA that can be used for modeling in the absence of specific parameter sets for the particular humic substance of interest. These generic parameters can provide estimates of the amount of proton binding by a wide variety of humic substances to within approximately +/- 20% under any given conditions. The maximum site density for protons was 7.74 and 5.70 equiv kg-1 for a generic FA and HA, respectively. The recommended generic NICA-Donnan parameter values for FA are b = 0.57, Qmax1,H = 5.88, log KH1 = 2.34, mH1 = 0.38, Qmax2,H = 1.86, log KH2 = 8.6, and mH2 = 0.53; for HA the values are b = 0.49, Qmax1,H = 3.15, log KH1 = 2.93, mH1 = 0.50, Qmax2,H = 2.55, log KH2 = 8.0, and mH2 = 0.26.