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Cramer C. Criscenti L. Acta, 69, A, , Curtiss L. DiChristina T. In Molecular Geomicrobiology, J. Banfield, J. Cervini-Silva, and K. East A. Elsetinow A. Felipe M. Cygan and J. Kubicki eds. Geochemical Society. Acta in press. Foresman J. Frisch et al. Gibbs G. Gilijamse J.

Gonzalez C. Goodman A. A 26 , Gordon M. Small split-valence basis sets for second-row elements. Grassian V. Guevremont J. A Reactivity of the plane of pyrite in oxidizing gaseous and aqueous environments: Effects of surface imperfections. Halgren T. Hamilton J. Hass K. B , Hellmann R. Nature , Hiemstra T. Colloid Interface Sci. Hohenberg P. Keith T. Modeling the Hydrogen Bond. Klamt A. Perkin Trans. Kohn W. Kubicki J. Acta 61, Ionic and covalent models. Acta, 57, Acta 63, A , Lasaga A. In: Lasaga A. Rev Mineral 8.

Lee C. Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density. B 37, Lee S. Lewan M. Matsumoto M. McQuarrie D. Parthiban S. Paul K. Soil Sci. Pelmenschikov A. A 6 , B 24 , Peng C.

Molecular Modeling of Geochemical Reactions : An Introduction

Israel J Chem. Perdew, J. Petersson G. The total energies of closed-shell atoms and hydrides of the 1 st -row elements. Phillips B. Prince A. Reedy B. Acta 55, Richnow H. Rimstidt J. To demonstrate how forward modelling works, the studied pond water was taken through two remediation processes, namely reaction with calcite CaCO 3 and contact with iron oxide surfaces i. These two processes were then modelled simultaneously, simulating reactions that are likely to occur in an environment where the two processes co-exist.

Calcite was added as an equilibrium phase with a saturation index of 0. The step-wise addition of calcite was carried out, with the solution assessed after each step. Minerals that became oversaturated during the addition of calcite were allowed to precipitate. The final model for the addition of calcite to pond water is presented in Figures 4 There is buffering of pH with initial additions of calcite up to just below mg, beyond which the pH increases significantly. The corresponding drop in redox potential pe at higher pH values is expected and demonstrated clearly in pe-pH diagrams.

Diaspore was the first mineral to precipitate. It continued to precipitate until all the aluminium in solution was depleted. A similar path was observed when defining Al OH 3 as the mineral, although diaspore remains supersaturated during the precipitation. Amorphous iron hydroxide precipitated early on in the profile. The iron concentration also decreased to almost complete depletion.

Manganite exhibited a similar profile. As the carbonate content and pH increased in the solution, malachite Cu 2 OH 2 CO 3 was predicted to precipitate very late in the profile just before the saturation of calcite was accomplished. Nickel hydroxide also precipitated during this step. The total concentration of the other defined elements remained unaffected. However, the speciation of elements changed with increasing pH. The addition of ferrihydrite hydrous ferric oxide HFO to the pond water was modelled.

Ions in solution adsorb onto the surface of HFO through strong and weak sites [ 19 , 23 ]. Essentially, strong sites and weak sites depict sites of high and low energy, respectively. Strong complexation of ions to HFO would occur at strong sites while there would be weak complexation at weak sites. For every 1 mmol of HFO, a total of 0. The addition of 1 g of HFO to 1 L of pond water equilibrated with oxygen and carbon dioxide was modelled. The following were input parameters for the surface: 0.

The addition of 1 g of HFO increased the pH of the solution to 5. By setting them as equilibrium phases and allowing them to precipitate, the precipitation of these minerals upon the addition of HFO can be modelled. The site occupancy of the HFO surface is summarised in Table 4. Approximately, half of the weak sites are occupied by water molecules. Sulphate and hydroxide ions take up the bulk of the remainder of weak sites. The strong sites are occupied by these oxycations, with the remainder being filled by calcium hydroxide species, hydroxide and uranyl oxide.

The sorbed fractions of the metals are summarised in Table 5. This is the percentage reduction in total soluble content of the metal after the addition of 1 g of HFO. Nearly all of the copper and uranium in the pond water has been removed from solution after the addition of HFO. Uranium is sorbed onto the strong sites and copper is split between weak and strong sites.

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The HFO had no effect on the total concentration of aluminium, chloride, iron, potassium, magnesium and sodium. By allowing minerals that become supersaturated during addition of HFO to precipitate, a different model is observed. The pH only increases to 3. As such, the speciation of metal ions is different to that discussed above. Less than 0. Water molecules occupy The models presented are based on thermodynamic principles only, no kinetics have been included.

The relative rates of adsorption onto the HFO surface and of precipitation of minerals will determine the model that better represents the chemistry of the system.

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A model combining the addition of calcite with the addition of HFO can be built. These two reactions are important in situations where water remediation strategies are being considered, for example, the use of a permeable reactive barrier. For this combined model, pond water was equilibrated with oxygen and carbon dioxide and reacted with calcite until saturation of calcite was achieved. Minerals that became supersaturated were allowed to precipitate and the resulting solution brought into contact with 1 g HFO.

The final predicted water quality for this model is summarised in Table 6. The percentage reduction shown is with respect to the original solution. The pH and pe of the final modelled solution were 7. The addition of calcite increased the calcium concentration in the final solution, hence a negative value. There was a major reduction in the concentrations of aluminium, copper, iron, manganese, nickel, uranium and zinc. Chloride, potassium, magnesium, sodium and sulphate values were not significantly reduced.

Types of reaction path models include: titration, buffering, flush and kinetic reaction path models [ 11 ].

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Evaporation sequences are some of the most interesting models as they tend to reveal a wide range of possible minerals, thus complementing analytical techniques such as X-ray diffraction XRD that may come short in determining some minerals. An evaporation model of the pond water is presented as Figure The model was prepared assuming equilibration with the atmospheric gases, O 2 and CO 2. As such, the iron is speciated from the beginning of the calculation as ferric iron. The first model allowed for the dissolution of precipitated minerals as the pH changed Figure This would be relevant for a closed system, for example an evaporation experiment occurring in a beaker Figure The water would remain in contact with the precipitated minerals and as the pH decreases during evaporation, the minerals become unsaturated in solution saturation indices decrease to below zero and the precipitated minerals dissolve.

For a more environmentally relevant evaporation profile in an open system, as in the case of the pond water, the subsequent dissolution would not be allowed because the minerals that precipitate on the edge of the pond will no longer be in contact with the remaining water Figure Therefore, even though the solution becomes unsaturated with respect to the mineral, no resolubilisation occurs because the minerals have left the system.

This is not ideal for an evaporation model as we are assuming that the analysed solution is in thermodynamic equilibrium, meaning that a solution in equilibrium would have already precipitated saturated minerals. Minerals can be supersaturated in natural waters as their precipitation could be kinetically hindered. In general, it is preferable that minerals be saturated during evaporation as in the case of gypsum CaSO 4.

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Notwithstanding, the models are still useful as an indication of the type of minerals that can be precipitated from the water. The minerals presented are pure end members and in nature would precipitate as solid solution minerals, thereby removing some of the transition metals from solution. Closed system evaporation model of water a Precipitation of gypsum and b zoomed in precipitation of jarosite and precipitation and redissolution of alunite.

Open system evaporation model of water a Precipitation of gypsum and b zoomed in precipitation of jarosite and precipitation and redissolution of alunite. Inverse modelling is also known as mass balance modelling. Given the composition of two water systems along the same flow path and the mineralogy of the rock through which the water flows, inverse modelling can be used to provide a set of possible reactions that occurred to transform the first solution into the second [ 24 ].

Mass balance equations are utilised and neither thermodynamic properties nor kinetic restraints are considered [ 14 ]. Inverse modelling of the rainwater leachate is presented in Table 7. The initial solution was the blank experiment that was subjected to the same leaching and analytical methods as the leachate but did not contain any solid material.

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Table 7 summarises the phase transfers from the initial solution into and from the leachate. Phases were defined based on metal fractionation information gained from sequential extractions of the tailings material. It revealed that most of the metals discussed in this chapter exist as readily soluble phases in the oxidised tailings except for uranium which was associated with a reducible phase.

It is possible that uranium does not exist in the material as a well-defined uranyl hydroxide, but is strongly adsorbed onto the surface of the iron hydroxide. For the sake of simplicity, however, uranium has been allocated as its own phase. The defined phases were chalcanthite CuSO 4. For simplicity, chloride Cl - and nitrate NO 3 - were excluded from the model. Including these species required the definition of more phases, leading to a large number of potential models. No phase including potassium was defined. Model 1 Table 7 is the simplest model predicted by the program.

It contains the minimum number of phases. In the input file, the uncertainty parameter for each solution must be defined. In order to allow for the convergence of the initial solution, a large uncertainty was allocated for the concentrations. This is often required when attempting to apply inverse models to dilute solutions. Model 1 was generated by allowing for the adjustment of calcium, sodium and sulphate values. As such, there were no calcium or sodium containing phases in the model. Model 2 Table 7 had more phases. Only the sulphate value was adjusted by the program in order to generate the model.

As illustrated in this model, the software will use minerals as defined by the user. The iron concentration in both solutions was below the detection limit, but, despite this, melanterite and amorphous iron hydroxide were defined as phases.

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Model 2 predicts the dissolution of the ferrous sulphate mineral followed by the precipitation of ferric hydroxide. The precipitation of amorphous aluminium hydroxide in Model 1 and to an extent in Model 2 assists in lowering the pH of the initial solution to equate to that in the final solution. Forward modelling could be undertaken in order to look at the validity of each model. This would involve dissolving the predicted minerals in rainwater to see if this would yield the leachate solution.

Modelling the effect of calcite and HFO on pond water chemistry as it leaches through a medium containing these best exemplifies a reactive transport model. For this purpose, a permeable reactive barrier PRB containing calcite and HFO was considered conceptualized in Figure 13 , with initial conditions defined as follows:. Division of different areas into compartments as follows: zone 1 containing pond water; zone 2 containing 9 cells that had the same amount of calcite and HFO and zone 3 containing 3 cells that have only rainwater in them.

The simulation was such that a band of pond water was allowed to flow through the PRB, with the final predicted water quality represented in zone 3. The assumption was that pond water flowed through the zones followed by rainwater. Simulation of the transport of iron through the zones gave the results presented in Figure Iron was found to be transported conservatively, with concentrations remaining just above 4 x 10 -5 mol L This is as a result of no precipitation minerals being defined. The speciation of iron changed with change in pH and pe, but the total concentration remained constant.

The results for transportation of manganese are presented in Figure Manganese was found to bind to the surface of HFO. Initially, there is a large decrease in manganese concentration with most of it being captured by HFO sites at the front of the barrier as shown by step 4 in Figure However, as rainwater flowed through after the pond water, it was shown to leach off manganese from the adsorptive sites, resulting in increased concentrations in subsequent solutions as shown by step 8 in Figure Thereafter, the manganese concentration is spread out in the barrier as it adsorbs onto HFO and is then slowly leached off step 16 and step 20 in Figure The effects of strong and weak HFO sites on the binding of manganese are shown in Figures 1 6 and 17 , respectively.

Weak sites had higher initial manganese a magnitude higher than for strong sites adsorbed onto them and this decreased to lower than for strong sites following flushing with rainwater. Strong sites showed a high resistance to desorption of manganese adsorbed onto them as shown by the almost constant adsorbed concentration Figure 16 while weak sites, on the other hand, showed a low resistance to desorption of manganese by rainwater Figure The desorption steps showed that the adsorbed concentrations decreased over time, evidence that manganese was lost from solid surface to the water column.

This increased manganese content in water is the sustained content observed in Figure 15 as explained before. The observed decrease in manganese concentration on weak sites could be attributed to competition for these sites by calcium and magnesium contained in rainwater owing to contact with calcite. Geochemical modelling is an important tool for predicting reactions. However, there are some limitations to its capability that should be considered. For instance, the quality of the data used for modelling influences the quality of the models obtained. While some manipulations can be done on the data during the modelling process, the best practice requires that analytical data be as accurate and relevant as possible.

Another limitation is the availability and suitability of databases. This is encountered when modelling of solutions of high ionic strengths, e. The other challenge is that of a general lack of literature containing kinetic data for a number of important mineral reactions. Geochemical modelling has been shown to be a useful tool in making predictions of contaminant behaviour in the aqueous environment. This has been demonstrated by modelling the same water samples using various models.

Molecular Modeling of Geochemical Reactions : James D. Kubicki :

While it may have some limitations, geochemical modelling remains a robust method that gives a better understanding of contaminants and that can be used for decision making such as in proposing appropriate remediation strategies for contaminated water, predicting potential impacts of contaminants on the environment and for general risk assessment. It can be used to complement analytical techniques, revealing important information where the latter tend to fail. Licensee IntechOpen.

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Downloaded: Introduction Water quality has become more and more important over the years owing to increased demand for water by the growing population. Materials and methods Solid material was sampled from the oxidised zone of the TSF a depth of up to 1 m. Data treatment and basis for modelling The above two samples, namely leachate from oxidised tailings and pond water composite will be discussed and utilised in the case studies related to different geochemical models.

Table 1. Analysed pond water and artificial rainwater leachate of oxidised tailings. Results and discussion This section presents and discusses the results for the different models obtained from simulating the evolution of the above water samples. Speciation-solubility models The chemical analysis of a sample will generally only provide total concentrations of the elements in the solution. Table 2. Species distribution of iron in pond water. Table 3. Selected mineral saturation indices for the pond water sample.

Forward models In forward modelling, the final composition of a solution after a reaction or equilibration is calculated [ 11 ]. Modelling of the addition of calcite to the pond water was undertaken as follows: The pond water was equilibrated with atmospheric gases oxygen and carbon dioxide Calcite was added as an equilibrium phase with a saturation index of 0.

Table 4. Surface complexes formed after addition of 1 g HFO to 1 L of tailings pond water. Element Percentage sorbed Ca 0. Table 5. Percentage of total elements adsorbed after addition of 1 g HFO to 1 L of pond water. Table 6. Final quality of pond water after addition of 1 g HFO to 1 L initial pond water. Inverse models Inverse modelling is also known as mass balance modelling. Table 7. Inverse modelling of rainwater leachate.