From Adsorption to Precipitation of U(VI): What is the Role of pH and Natural Organic Matter?

We investigated interfacial reactions of U(VI) in the presence of Suwannee River natural organic matter (NOM) at acidic and neutral pH. Laboratory batch experiments show that the adsorption and precipitation of U(VI) in the presence of NOM occur at pH 2 and pH 4, while the aqueous complexation of U by dissolved organic matter is favored at pH 7, preventing its precipitation. Spectroscopic analyses indicate that U(VI) is mainly adsorbed to the particulate organic matter at pH 4. However, U(VI)-bearing ultrafine to nanocrystalline solids were identified at pH 4 by electron microscopy. This study shows the promotion of U(VI) precipitation by NOM at low pH which may be relevant to the formation of mineralized deposits, radioactive waste repositories, wetlands, and other U- and organic-rich environmental systems.

Organic Functional Group Chemistry in Mineralized Deposits Containing U(IV) and U(VI) from the Jackpile Mine in New Mexico.

We investigated the functional group chemistry of natural organic matter (NOM) associated with both U(IV) and U(VI) in solids from mineralized deposits exposed to oxidizing conditions from the Jackpile Mine, Laguna Pueblo, NM. The uranium (U) content in unreacted samples was 0.44-2.6% by weight determined by X-ray fluorescence. In spite of prolonged exposure to ambient oxidizing conditions, ≈49% of U(IV) and ≈51% of U(VI) were identified on U LIII edge extended X-ray absorption fine structure spectra. Loss on ignition and thermogravimetric analyses identified from 13% to 44% of NOM in the samples. Carbonyl, phenolic, and carboxylic functional groups in the unreacted samples were identified by fitting of high-resolution X-ray photoelectron spectroscopy (XPS) C 1s and O 1s spectra. Peaks corresponding to phenolic and carbonyl functional groups had intensities higher than those corresponding to carboxylic groups in samples from the supernatant from batch extractions conducted at pH 13, 7, and 2. U(IV) and U(VI) species were detected in the supernatant after batch extractions conducted under oxidizing conditions by fitting of high-resolution XPS U 4f spectra. The outcomes from this study highlight the importance of the influence of pH on the organic functional group chemistry and U speciation in mineralized deposits.

Forward modeling of metal complexation by NOM: II. prediction of binding site properties.

An a priori model of metal complexation by natural organic matter (NOM) has previously been shown to predict experimental data at pH 7.0 and 0.1 M ionic strength (Cabaniss, S. E. Environ. Sci. Technol. 2009). Unlike macroscopic models based only on stoichiometry and thermodynamics, this a priori model also predicts the ligand groups and properties of complexed (occupied) molecules. Ligand molecules with strong binding sites form complexes at low metal concentrations and have average properties (molecular weight, charge, aromaticity) which can differ significantly from the average properties of bulk NOM. Cu(II), Ni(II) and Pb(II) preferentially bind to strong amine-containing sites which are often located on small (MW < 1000), lower-aromaticity molecules. Cd(II) and Zn(II) show generally weaker binding, although they also prefer amine-containing sites to pure carboxylates and bind to smaller, less aromatic molecules. Ca(II) shows no real preference for amine over carboxylate ligand groups, preferentially binding to larger and more negatively charged molecules. Al(III) has a unique preference for phenol-containing sites and larger, more aromatic molecules. While some predictions of this model are consistent with a variety of experimental data from the literature, others await validation by molecular-level analysis.

A comparison of surface water natural organic matter in raw filtered water samples, XAD, and reverse osmosis isolates.

This research compared raw filtered waters (RFWs), XAD resin isolates (XAD-8 and XAD-4), and reverse osmosis (RO) isolates of several surface water samples from McDonalds Branch, a small freshwater fen in the New Jersey Pine Barrens (USA). RO and XAD-8 are two of the most common techniques used to isolate natural organic matter (NOM) for studies of composition and reactivity; therefore, it is important to understand how the isolates differ from bulk (unisolated) samples and from one another. Although, any comparison between the isolation methods needs to consider that XAD-8 is specifically designed to isolate the humic fraction, whereas RO concentrates a broad range of organic matter and is not specific to humics. The comparison included for all samples: weight average molecular weight (Mw), number average molecular weight (Mn), polydispersity (rho), absorbance at 280 nm normalized to moles C (epsilon280) (RFW and isolates); and for isolates only: elemental analysis, % carbon distribution by 13C NMR, and aqueous FTIR spectra. As expected, RO isolation gave higher yield of NOM than XAD-8, but also higher ash content, especially Si and S. Mw decreased in the order: RO > XAD-8 > RFW > XAD-4. The Mw differences of isolates compared with RFW may be due to selective isolation (fractionation), or possibly in the case of RO to condensation or coagulation during isolation. 13C NMR results were roughly similar for the two methods, but the XAD-8 isolate was slightly higher in 'aromatic' C and the RO isolate was slightly higher in heteroaliphatic and carbonyl C. Infrared spectra indicated a higher carboxyl content for the XAD-8 isolates and a higher ester:carboxyl ratio for the RO isolates. The spectroscopic data thus are consistent with selective isolation of more hydrophobic compounds by XAD-8, and also with potential ester hydrolysis during that process, although further study is needed to determine whether ester hydrolysis does indeed occur. Researchers choosing between XAD and RO isolation methods for NOM need to consider first the purpose of the isolation; i.e., whether humic fractionation is desirable. Beyond that, they should consider the C yield and ash content, as well as the potential for alteration of NOM by ester hydrolysis (XAD) or condensation/coagulation (RO). Furthermore, the RO and XAD methods produce different fractions or isolates so that researchers should be careful when comparing the compositions and reactivities of NOM samples isolated by these two different techniques.

Quantitative structure-property relationship for predicting chlorine demand by organic molecules.

Conventional methods for predicting chlorine demand (HOCl(dem)) due to dissolved organic matter (DOM) are based on bulk water quality parameters and ignore structural features of individual molecules that may better indicate reactivity toward the disinfectant. The Quantitative Structure-Property Relationship (QSPR) modeling approach can account for structural properties of individual molecules. Here we report a QSPR for HOCl(dem) based on eight constitutional descriptors. Model compounds with HOCl(dem) ranging from 0.1 to 13.4 mol chlorine per mole compound were divided into a calibration and cross-validation data set (N = 159) and an external validation set (N = 42). The QSPR was calibrated using multiple linear regression in a 5-way leave-many-out approach and has average R(2) = 0.86 and standard error of regression (StdE(reg)) = 1.24 mol HOCl per mole compound and p < 0.05. Internal cross-validation has average q(2) = 0.85 and the external validation has q(2) = 0.88, indicating a robust model. The leverage of 7 of 42 compounds in the external validation data set exceeded the critical value, suggesting that these compounds may be overextrapolated. However, root-mean-square error of prediction in the external validation was 1.17 mol HOCl per mole compound, and all compounds were predicted with +/-2.5 standardized residuals (Sresid). Application of the QSPR to model structures of NOM predicts HOCl(dem) comparable to reported measurements from natural water treatment.

Forward modeling of metal complexation by NOM: I. A priori prediction of conditional constants and speciation.

An agent-based simulation of the transformations of natural organic matter (NOM) is combined with quantitative structure-property relationships (QSPRs) for conditional metal-ligand binding constants (K'ML at pH 7.0 and ionic strength = 0.10 M) in order to predict metal binding by NOM. The resulting a priori predictions do not rely upon calibration to environmental data, but vary with the precursor molecules and transformation conditions used in the simulation. Magnitudes and distributions of K'ML are consistent with previously reported values. In a simulation starting with tannin, terpenoid, and flavonoid precursors, metal binding decreases in the order Cu(II) approximately equal to Al(III) approximately equal to Pb(II) > Zn(II) approximately equal to Ni(II) > Ca(II) approximately equal to Cd(II), whereas in simulations containing protein precursors (and thus amine-containing ligands), Al(III) is relatively less and Ni(II) and Cd(II) relatively more strongly bound. Speciation calculations are in good agreement with experimental results for a variety of metals and NOM samples, with typical root-mean-square error (RMSE) of approximately 0.1 to approximately 0.3 log units in free or total metal concentrations and typical biases of <0.2 log units in those concentrations.

Quantitative structure-property relationships for predicting metal binding by organic ligands.

Quantitative structure-property relationships (QSPRs) are developed to predict the complexation of Al(III), Ca(II), Cd(II), Cu(II), Ni(II), Pb(II), and Zn(II) by organic ligands containing carboxylate, phenol, amine, ether, and alcoholfunctional groups. These QSPRs predict conditional stability constants (K(M') at pH 7.0 and I = 0.1) over a range of ligand types with consistent uncertainties of approximately 1 log unit without requiring any steric or connectivity information. Calibration and validation data sets were constructed using 1:1 complex formation constants from the NIST Critical Stability Constants database (version 8.0). The descriptor variables are intuitive quantities conceptually related to metal binding, such as the numbers of various ligand groups, charge density, etc. The resulting calibrations have r2 = 0.87 to 0.93 and Spred = 0.67 to 1.05 log units, with positive values for all ligand count descriptor variables. The QSPRs account for 75-95% of the variability in the validation data set with RMSE of 0.74 to 1.30 log units. These QSPRs improve upon previous work by providing a tested and mechanistically reasonable method for log K(M') prediction with uncertainties comparable to or betterthan other QSPRs calibrated with groups of diverse ligands.

Reverse-phase HPLC method for measuring polarity distributions of natural organic matter.

A reverse-phase high-pressure liquid chromatography (RP-HPLC) method was developed to measure the polarity distribution of natural organic matter (NOM) samples. The polarity distribution is obtained by calibrating an octadecyl bonded silica phase column and polar eluent with compounds of known octanol-water partition coefficient (Kow) and using this calibration curve to transform NOM retention times into an equivalent Kow. Polarity distributions treat the NOM samples as a complex mixture rather than summarizing the polarity in a single number. The method is sensitive, with UV detection allowing quantitation of samples with <5 mg of C/L. Individual chromatograms are acquired in <20 min, allowing much faster analysis on smaller samples than XAD resin separation or 13C NMR. Polarity distributions of 10 representative NOM isolates and 2 whole water samples indicate that NOM is generally hydrophilic in nature (log Kow < 2), although XAD-8 isolates are more hydrophobic than RO isolates from the same source. Hydrophilicity, as indicated by recovery from the HPLC column, is correlated to the elemental oxygen/carbon ratio but does not correlate strongly with molecular weight or 13C NMR aromaticity.