Chemical Modeling of Aqueous Systems - ACS Symposium Series

Chapter 1

Chemical Modeling of Aqueous Systems An

Overview

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R. L. Bassett and Daniel C. Melchior

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Downloaded by HARVARD UNIV on April 28, 2013 | http://pubs.acs.org Publication Date: December 7, 1990 | doi: 10.1021/bk-1990-0416.ch001

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Department of Hydrology and Water Resources, University of Arizona, Tucson, AZ 85721 EBASCO Services, 3000 West MacArthur Boulevard, Santa Ana, CA 92704

Chemical modeling in hydrologic systems has become an area of active research with immediate opportunities for application to environmental problems, interpretation of diagenetic processes, and in evaluating the deposition of minerals to name a few. Researchers working in these and other areas have identified the need to quantitatively evaluate the chemical changes in geologic systems as a result of both natural and man-induced processes. To expedite these evaluations, fundamental theories of aqueous chemistry have been incorporated into computer codes along with the required constants and thermochemical data, to perform various simulations. Over the past several decades the equations and resultant codes have evolved greatly. Many of the codes that today serve as the foundations for geochemical calculations have increased in complexity both as a result of new theories in aqueous chemistry and the technical issues which needed to be resolved. The technical issues currently being addressed are often more complex in scope than originally imagined, and as a result the limits of application and the inadequacies are revealed. Researchers have evaluated the models under a wide variety of circumstances including the adequacy of the aqueous theory, usefulness for a broad range of applications, and the impact of solution-solid interactions such as is affected by mineral surface chemistry. Advancements in modeling capabilities have resulted from the work of many researchers. These give rise to new concepts in modeling such as evaluating model sensitivities, improvements to the thermodynamic and kinetic data bases, and the introduction of organic compounds to existing codes. The resulting changes have greatly enhanced the flexibility and utility of most aqueous geochemical codes. HISTORICAL F R A M E W O R K The concept of chemical modeling of natural hydrologic systems was introduced by Garrels and Thompson (1) in a paper that described the distribution of chemical species in seawater. Their approach was to construct a rigorous thermodynamically based model that was (1) mathematically but not conceptually decoupled from flow, and (2) could provide quantifiable information about the chemical processes active in an aqueous system, such as seawater or groundwater. Their initial model considered 17 species, was restricted to 25 °C and remarkably enough, clearly quantified the predominant ion and ion pair speciation in seawater. This work set the framework for a number of the computer codes used today. The historical evolution of chemical codes has not been documented nor will it be attempted here, yet several publications are available that describe the variety of codes from which to choose (2-4). One distinct trend of this past decade has been the cessation of the rapid increase in the number of models being developed; this has been replaced with a more focused effort to document and improve existing models. A small number of these codes have become the mainstay for geochemical applications. A n abbreviated pedigree of computer codes is illustrated in Figure 1. The initial conference on this subject (2) was convened during the early phase of model development, and 0097-6156/90/0416-0001 $06.00/0 c 1990 American Chemical Society

In Chemical Modeling of Aqueous Systems II; Melchior, D., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1990.


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BASSETT & MELCHIOR Overview

up to that time the focus had been on equilibrium modeling and on the expansion of the number of species in the models. Model development was rapid, machine dependent, often simultaneous and generally poorly documented. The recent emphasis in code improvement centers on issues such as more comprehensive and more complete thermodynamic data, better transportability between computer systems, the capability for evaluating systems at higher temperature, pressure and ionic strength, and more specific utility of the codes for environmental, industrial and research applications. Not surprisingly, in view of the large effort required to develop, document and calibrate these codes, only a few models have emerged which offer a reasonable possibility for surviving the scrutiny of Q A / Q C rigor, and legal qualification which will be required for future widespread use of these codes in the arenas of both research and the private sector. Issues of liability and legal defensibility are important considerations, especially in the more complex areas of geochemical and hydrochemical research such as hazardous waste, low and high level radioactive waste and groundwater contamination. The technical issues confronting researchers and applications-oriented scientists have changed dramatically over the past several decades. The current models tend to be used most frequently for critical applications and problem solving investigations as opposed to investigations of general concepts of the science. As a result of these applications-oriented approaches new concerns have evolved which have set the direction for future research (Table I). Table I. Broad categories examined at the symposium which embody the current status of chemical modeling and the potential advances A . C U R R E N T MODELS Aqueous Theory - Ion Interaction - Model Documentation Applications - Mass Transfer - Isotope Fractionation - Redox - Organic Compounds - Coupled Models Surface Chemistry

B. NEW CONCERNS Modeling Sensitivity - Sampling/Analysis - Computational - Redox/Metastability Thermodynamic and Kinetic/ Data Advancements Organic Compounds - Macromolecules - Cosolvents - Partitioning Coupled Hydrology/Chemistry

It is the intent of this paper to discuss several relevant details of the models currently used and to indicate some of the most pressing research problems that will most likely be pursued in the near future. C U R R E N T MODELS Aqueous Theory Ion-Association and Ion-Hvdration. Aqueous solutions of electrolytes have been chemically described using a variety of theories. The original theoretical approach used by geochemists to model aqueous systems was based on the concept of ion-pairing or ion-association. The ion association approach as described by Garrels and Thompson (1) accurately depicted the speciation of seawater and later many other aqueous solutions. This approach was subsequently found to be inadequate for defining the chemistry of more complex and more concentrated aqueous solutions or those solutions near the critical point of water. This deficiency led to the use of other theoretical approaches to describe these systems, such as the ion-interaction, mean salt, and ion-hydration theories. The ion-association concept relies on the use of Debye-Huckel based activity coefficients to calculate aqueous activities and is one that is employed most frequently in the models used today. A primary assumption of this approach is the use of the Maclnnes convention such that for an aqueous solution containing equimolal concentrations of K and CI", their activities and hence activity coefficients are equivalent. This approach and convention were reexamined by Parkhurst in this volume, who explored the issue of mean salt based activity coefficients and the apparent +


CHEMICAL MODELING OF AQUEOUS SYSTEMS II


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discrepancies between values calculated by each method. This enlightened examination merits further evaluation in the future as new approaches to calculating electrolyte activity coefficients are addressed. The ion-hydration approach for describing electrolyte chemistry has been described here by Wolery and Jackson. This alternative approach is based on some of the pioneering work done by Stokes and Robinson (43) and attempts to examine electrolyte speciation in terms of the degree of solvation. Since this approach and concept is relatively new, it remains a question whether these methods can be applied to modeling natural systems. Modeling of natural systems is indeed more complex than those prepared in a laboratory setting. Geochemists recognize that many variables will influence the chemistry of natural aqueous systems and minerals present. The importance of temperature and pressure on aqueous chemistry is well recognized. Aggarwal discusses in this volume the significance of pressure effects on aqueous thermodynamics and presents an approach for addressing this issue. Glynn presents a thermodynamic framework for evaluating the effect of mineral solid-solutions and aqueous solution compositions in Chapter 6. The ion-interaction theory in contrast to the above was developed by Pitzer (42) as an outgrowth of work done by Guggenheim (44). This phenomenological methodology was based on the concept that ions electrostaticly interact in solution and that these interactions were based on a statistical likelihood of collision, hence the ionic strength dependency. Several papers in this volume discuss aspects of the importance of this approach to modeling the chemistry of complex systems. Ion Interaction. Ion-interaction theory has been the single most noteworthy modification to the computational scheme of chemical models over the past decade; this option uses a virial coefficient expansion of the Debye-Huckel equation to compute activities of species in high ionic strength solutions. This phenomenological approach was initially presented by Pitzer (42) followed by numerous papers with co-workers, and was developed primarily for laboratory systems; it was first applied to natural systems by Harvie, Weare and co-workers (45-47). Several contributors to the symposium discussed the ion interaction approach, which is available in at least three of the more commonly used codes; SOLMNEQ.88, PHRQPITZ, and E Q 3/6 (Figure 1). The ion-interaction model is a theoretically based approach that uses empirical data to account for complexing and ion pair formation by describing this change in free ion activity with a series of experimentally defined virial coefficients. Several philosophical difficulties have resulted from the introduction of this approach: the lack of extensive experimental database for trace constituents or redox couples, incompatibility with the classical ion pairing model, the constant effort required to retrofit solubility data as the number of components in the model expand using the same historical fitting procedures, and the incompatibility of comparing thermodynamic solubility products obtained from model fits as opposed to solubility products obtained by other methods. A controversy exists between the proponents of ion-association versus the ion-interaction approach. This controversy usually revolves around the issue of chemical realism since many known ion pairs such as CaSO^ were not explicitly defined by the ion-interaction approach. However, the impact of the strong iomc interaction can be reflected in the magnitude of the virial coefficient terms. More recently, this deficiency has been addressed for the carbonate system, however, questions still remain whether mixed methodologies reflect the true solution chemistry or are simply forced fits of experimental data. Clearly the ion-interaction methodology is superior to the ion-pairing approach at high ionic strength, and can also be used at low-ionic strengths as well. With this formulation, it is possible to compute the activities of many electrolytes up to 20 m. Pabalon and Pitzer illustrated the utility of this approach by examining salt solutions from moderate concentrations to fused salts (this volume). Clegg and Brimblecombe have employed the model in combination with Henry's Law constants to calculate gas solubilities for several volatile electrolytes (this volume). The ion interaction approach is limited by the available experimental data, both in terms of elements considered and the availability of data for fitting solubility of solid phases at elevated temperature. Another caution discussed here by Plummer and Parkhurst is the requirement to not only be internally consistent with the interaction parameters used in the model, but to be consistent with the choice of the activity coefficient scale, if measured pH values are used. For solution compositions in which the virial coefficients are well defined, the mineral phase boundaries, ionic activity, and the activity of water, can be modeled remarkably well. Numerous applications are already benefiting from the existing database, such as the ability to predict the solubility of minerals in brine environments. Despite the advancement in the description of high ionic strength solutions, the incompatibility of the ion-pairing model and the semi-empirical 0


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phenomenological model is an unresolved issue and will need to be resolved for a unified theoretical description of the solution for many applications. Model Documentation. Geochemical computer codes have increased in complexity over the past decade, as options were added and as theoretical developments were incorporated. Several of the more widely used models have now been updated and documented (EQ3/6, PHRQPITZ, SOLMNEQ.88, MINTEQ, WATEQ4F). Little change has occurred with respect to the more standard computations such as: speciation to determine single ion activities, distribution of redox species based of the "system Eh," or based on specified redox couples, and the determination of the degree of saturation of a water with respect to a predetermined table of minerals. The principal components present in most geochemical codes are illustrated in Figure 2. Additionally, some of the most common options which have been incorporated into the more generally used models during this past decade and the major evolutionary changes that have been observed are also given in Figure 2. Detailed descriptions of many of these options can be found elsewhere in the users manuals of specific codes. Other options, such as water mixing subroutines, incorporation of adsorption submodels, organic ligand complexation, and transportability of codes to run on a microcomputer are now available. In the future, subroutines that incorporate algorithms for computing the solubility of anthropogenic organic compounds and partitioning of dissolved organic species between phases, will be of great interest to environmental scientists. A Computer Workshop was convened during the 1988 ACS Symposium on this topic, during which time software related to the conference theme was demonstrated. Participants provided brief descriptions of these models which are given in the Appendix. Applications Mass transfer or reaction path modeling probably represents the most extensive evolutionary change in the past decade. The first code that had the capability to model mass transfer, by simulating the change in solution composition as minerals dissolve or precipitate was P A T H . This complex model was cumbersome and was restricted to mainframe computers. Reaction path modeling is now routinely performed using new codes such as P H R E E Q E , PHRQPITZ, EQ3/6, PATH, SOLMNEQ.88 and MINTEQ, which now are executable on microcomputers and workstations. The ability to simulate the evolution of a water composition for points along a flow path, provides information about reaction mechanisms and the thermodynamic reaction state of the solution, without being bound to the rigorous constraints of the flow equations. Papers by Steefel and Lasaga, Janeky, Toran, Longmire, Striegl and Healy, and Carnahan in this volume, describe this process which now also includes the computation of isotope fractionation, redox speciation and even coupling to flow and transport models. Surface Chemistry The modeling of mineral/solution-interfacial reactions represents an area of geochemistry which has been shown to be critical in understanding the mobility of elements in natural systems. A recent ACS Symposium (48) focused on this topic and provided an excellent summary of advances in the field. Several key aspects of interfacial chemistry are presented in this volume by Stollenwerk and Kipp; Rea and Parks; Machesky; and Anderson and Benjamin. Submodels to the large aqueous speciation codes now go far beyond early attempts at simulating surface chemical reactions (ion exchange, Freundlich, Langmuir, etc.), by incorporating sophisticated adsorption subroutines, such as the constant capacitance or the triple-layer model (15.39,40). The modeling of the partitioning of inorganic species between the aqueous solution and a single solid phase is well documented. Adsorptive additivity for multiple phases is, however, not experimentally observed; therefore, the predictive simulation of sorption on natural materials such as soils and sediments using surface complexation concepts is at present unworkable. Anderson and Benjamin do, however, propose an explanation for the non-additive behavior in the binary suspensions of A l or Fe hydroxides and amorphous silica, by attributing the non-additive aspects of sorption to surface coverage of silica. This stands along side the assumptions of Honeyman (49) which attribute the non-ideality to particle interaction. Numerous research efforts are currently underway to rigorously model sorption in aqueous suspensions with multiple adsorbents. The adjustment of adsorption parameters with respect to changing temperature is generally not addressed in most modeling exercises, owing to the uncertainty of the adsorption modeling


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START

THERMODYNAMIC DATABASE

MATRIX INVERSION OR ITERATIVE SOLUTION: ALGORITHM


INPUT CHEMICAL DATA

SECONDARY COMPUTATIONS S a t u r a t i o n Index Computed C a t i o n / A n i o n B a l a n c e Geothermometers Percentage Species D i s t r i b u t i o n Computed Gas P a r t i a l P r e s s u r e s etc. ) (P. CH H 0,' C02 ' 2

:

AQUEOUS MODEL AND ANCILLARY CALCULATIONS Solvent Parameters ( a ^ , p , D, ) Solute F i t t i n g Parameters (b, B, e t c . ) Conversion to molal u n i t s Log K I n t e r p o l a t i o n Cation/Anion Balance Redox ( E h , p e ) A c t i v i t y C o e f f i c i e n t (7 ) Alkalinity vs. Total C

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OPTIONS AND EVOLUTIONARY CHANGES -

M i x i n g o f Waters T i t r a t i o n o f S o l i d s and Gases Outgassing Samples a t M u l t i p l e Temperatures Organic Ligands A d s o r p t i o n Models Reaction Path Simulation Adherence t o Phase B o u n d a r i e s I s o t o p e Mass B a l a n c e Pressure C o r r e c t i o n f o r Log K Pseudo-Kinetic Expressions Pitzer Ion-Interaction Expression M i x e d Redox C o u p l e s

Figure 2. Fundamental components of most aqueous chemical models and the options which are available with many of the more commonly used codes.


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parameters themselves. Machesky examined the magnitude of the effect of changing temperature on sorption and provides a generalized method for correcting the effects of temperature. NEW CONCEPTS IN M O D E L I N G New concepts in modeling which provide innovative advancements in the modeling of geochemical systems are also presented in this volume. Ideas were also discussed which reveal the deficiencies that must be addressed in the future to make the models more realistic. In the future, advancements in modeling will most likely be realized in four broad areas: the application of error analysis to the modeling, speciation of organic ligands and macromolecules with the adjustment for cosolvents, options to the aqueous theory currently used, and the more efficient coupling of flow models with chemical codes.


Model Sensitivities A serious pitfall to many modeling efforts is the lack of a rigorous evaluation of model sensitivities to the errors in sampling, chemical analysis, and system condition; and the propagation of this error throughout the modeling process. In the future, geochemical codes used for environmental issues, industrial applications, low and high level nuclear waste disposal, etc., will require verification for accuracy, and the capability of estimating error. These key components to geochemical modeling are subject to error, which is usually ignored in model computations. Sampling and Analytical Error. The methods used to collect samples has been shown to dramatically influence analytical results. In addition, chemical data that serve as input to modeling natural systems also have some degree of analytical error. The methods used in collecting groundwater samples have received greater scrutiny recently as geochemists take a closer look at how contaminants move in an aquifer. Barcelona, in this volume, points out that sample quality is a direct reflection of the drilling and sampling methods used, well materials, sampling equipment, and the well design. The results presented in this paper and the references to other related issues, set the framework for minimizing the variability of sample quality. Procedures which reduce error should be practiced by all geochemists and hydrologists before a field program begins and samples are obtained for laboratory analyses. The usual gauge of the quality of analytical data is the ionic charge balance, which is only a gross indicator of error. To rigorously define the magnitude of inherent analytical error, the precision for the analysis of each analyzed species must be known from repeated measurements, spiked samples, historical evidence of laboratory precision and accuracy, etc., which then could be incorporated into the computational scheme. As discussed by Wildeman in this volume, these errors can be large, even in government regulated programs. The error attributable to sampling alone has been shown to be significant, and can also be evaluated with blanks and spikes, this is especially important for organic compounds as pointed out by Barcelona. Most of the commonly used models compute a cation/anion equivalent balance, but even this information is seldom translated into error for any subsequent calculation. No codes currently incorporate known analytical precision into evaluation of the error and uncertainty of speciation, saturation index, or mass transfer calculations. Future codes such as INTERP (Appendix) or the expert system of Pearson and others described in this volume, should include an optimization routine which would calculate the propagation of these reported errors, and compute bounding values that clearly define the magnitude of uncertainty. Computational Errors. Errors in computation can be attributed to two specific circumstances: convergence criteria and improper selection of parametric equations. Most geochemical codes require that mass balance and mass action equations be solved to obtain an acceptable mathematical model of the aqueous solution. Minimal error can be attributed to the mathematical formulation of the equation solvers, because such narrow convergence criteria are used in the matrix inversion or iterative solution algorithms. Numerical dispersion or out of bounds computations generally do not occur unless phase boundaries are exceeded. The more significant error is associated with the specific mathematical model chosen to describe the system. Each computer code is based on assumptions concerning the equations, algorithms and constants used to compute basic quantities such as the activity coefficients, solvent parameters, (activity of water, dielectric constant, density, etc.), and how these quantities vary with temperature and pressure. None of the commonly used models report the likely range of error which is a


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consequence of these assumptions. A rigorous comparison of simulated results to actual data is needed, however, to evaluate the present magnitude of error. Pearson and others (Chapter 26), have proposed a method for using an expert system approach for selecting an optimum method for solving a geochemical computational problem. The approach they have presented here is a first step toward completion of a system that can be used by both practicing geochemists and others for selecting the proper approach to solve a problem. The goal of their approach is to attempt to make all modeling efforts as rigorous and defensible as possible while maintaining a critical objectivity. The approach presented is a promising application of expert systems for addressing geochemical issues which will assist the user in identifying problems when modeling water/rock interactions in natural systems. System Condition: Redox and Metastabilitv. Two major sources of uncertainty in modeling aqueous systems are the redox potential and metastability; these are frequently acknowledged as conceptual problems, but discussion of the error which results from improper assumptions and calculations is generally avoided. The Eh or electrochemical potential which is computed from a potential measured with a platinum electrode, is used in almost all geochemical models as a system parameter. The issue of whether or not redox conditions for a system can be accurately reflected by an Eh value is no longer a question. Most geochemists recognize that many aqueous systems are not in redox equilibrium for all sensitive species. This realization has led many researchers to question the use of the standard platinum electrode measurement techniques. Unfortunately, most redox species do not actually distribute according to the potential indicated by the platinum electrode measurement. Kempton and Runnels, Macalady et al., and Scott and Morgan discuss this situation in this volume and indicate that only iron and possibly manganese are affecting this measured potential. Models which force a system Eh to be used in calculating the distribution of the redox species may generate large errors in the distribution of other redox couples which act independently. This uncertainty must be evaluated because of the likelihood of large error in critical speciation calculations especially involving transition metals. The non-equilibrium condition of most groundwater systems with respect to many primary minerals, or similarly the metastability which exists with respect to many semi-crystalline or amorphous phases are common problems, especially for silicates. Some clear identification is needed for system reaction time, or the rate at which equilibrium is approached, and similarly identification is needed for metastable plateaus of pseudo-equilibrium, especially for compounds such as amorphous silica, cristobalite, quartz, clay minerals, etc. The likely magnitude of saturation indices which could apply to a given mineral could be specified for a variety of conditions. In this volume, Glynn, and elsewhere others, have recently shown that some error occurs in the calculated saturation values for trace elements when pure end member minerals are assumed to be present, when actually the phases are solid solutions. The consensus among modelers appears to be that error is present and significant; the challenge is to develop procedures that quantify the error, so models become tools that provide realistic and interpretable results. Thermodynamic and Kinetic Data Advancements Early codes contained externally referenced thermodynamic databases which were compilations of constants selected by the code authors. These values could be replaced, updated or deleted by the user which led to the proliferation of codes for special applications containing their own customized files. Current model development is becoming more of a multidisciplinary team effort; recognizing that a large source of error may well be the thermodynamic database. The three most advanced efforts to standardize these data are SUPCRT (29), C O D A T A and the EQ3/6 data management system (50), and NEA TDB (51). Delaney (50) is building a database management system that will have the capability to reconfigure the EQ3/6 database into a format that can be read by other popular geochemical codes. INTERA (52) conducted a performance assessment comparison using the models P H R E E Q E and EQ3/6 by generating a single database that both models could access. This exercise underscored the value of a database management system which will not only aid in standardizing the databases but will assist in verifying code calculations with published algorithms. Reference files containing the thermodynamic database used by most computer models are constructed from both experimental data and from data which have been estimated. Many rely heavily on extrapolation techniques for determining the equilibrium constants or Gibbs Free Energy values at higher temperatures. These estimation techniques are essential, but the error in the estimated constants is generally not reported and is large for extreme conditions of T and P. The



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computed results derived from a specific model run may not always be affected by these poorly known parameters, but no indication of such uncertainty is reported. Numerous efforts are currently underway to provide internally consistent thermodynamic data, such as the one presented in this volume by Nordstrom and others. Once attained, even an internally consistent database is still heavily dependent upon extrapolation techniques to provide the needed constants where none exist. The problem remains that the user is not provided with an indication of the magnitude of the error expected from this collection of thermodynamic data. A fundamental question still exists, however; can a truly internally consistent data base ever be assembled that addresses a wide range of geochemical problems? It is more likely that a database will evolve that is less than consistent, but contains known and evaluated error. A central issue in the attempt to establish a reliable database is the requirement of critically evaluated thermodynamic data for several key species. One such pivotal element is aluminum, which has an extensive literature of solubility and thermochemical data from which to choose, for each of the aqueous species or complexes. The aluminum species are fundamental to the calculation of solubility and reaction state with respect to many silicates and aluminum oxides and hydroxides and are principal components in numerous surface chemical reactions in the environment. Two key chapters in this volume address this fundamental problem: Apps and Neil give a critical evaluation of the data for the aluminum system and Hem and Roberson present the kinetic mechanisms for hydrolysis of aluminum species. Organic Compounds Organic compounds in aqueous systems have taken on increased importance over the past decade both as a research topic and as a topic public concern. The issue of anthropogenic organic contamination of aquifers and hydrophilic ligand complexation are the focus of much current work. Early models (REDEQL, MINEQL, G E O C H E M , SOLMNEQ) recognized the need to incorporate hydrophilic organic ligands into the thermodynamic database; and conveniently, the speciation could be treated in a numerically identical fashion to that of inorganic ligands. Anticipated advancements are the modeling of three new classes of organic interactions in aqueous systems: macromolecules and their multiple binding sites, organic cosolvents, and partitioning of organic and inorganic species in a two phase system. Macromolecules. Humic substances are ubiquitous in natural systems and are generally recognized as a significant component of natural water compositions. The structure and chemistry of these macromolecules are complex such that it is almost impossible to characterize a complete molecule. As a result, thermochemical data on these molecules are unavailable for modeling. The currently available geochemical models do not have the capability to easily incorporate these substances into speciation calculations. Humic substances, are large macromolecules for which the existing expression for activity coefficients such as Debye-Huckel and the attendant extensions, do not apply, however, significant binding with metals is known to occur. Additionally, as pointed out in this volulme by Choppin and Clark, and Holm and Curtis, metals bind to specific sites on the molecule with binding energy dependent on site location and specific functional group; kinetic effects which impact this association are at present not well understood. Because of the importance of these large molecules in facilitating transport of many trace metals, and in partitioning organics between themselves and the aqueous phase, these substances must be part of the computational scheme of future models. Cosolvents. The effect of organic solvents on the physical properties of water is a historically useful phenomenon and well defined for countless industrial and scientific applications. This phenomenon has always been ignored in the chemical models available for general usage. Cosolvents affect the dielectric constant of the water, impacting activity coefficient calculations, hydration of species, and adsorption computations. Application of current chemical codes to environmental contamination investigations will require a capability for simulating the effect of a wide variety of miscible solvents on the aqueous system. As the currently available codes are refined, subroutines should be added that address this issue. Partitioning of Organic Molecules. Organic molecules in natural aqueous systems have a tendency to partition themselves depending on the structure, size, and functionality. This area of concern has taken on greater importance recently from two divergent interest groups. One group involved with the extraction of petroleum has focused on the partitioning of hydrophilic and hydrophobic petroleum components and the impact hydrophilic components have on mineral surfaces.



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A variant of the above problem is the presence of immiscible liquids such as oil, dissolved hydrophilic organics, or hydrophobic organic matter on mineral surfaces. As discussed by MacGowan and Surdam in this volume, aluminum and other inorganic species important to our understanding of mineral systems, partition between immiscible liquids such as oil and water. Another group concerned with the partitioning of organic molecules is focusing on the environmental impact these compounds have on the biosphere. This area of research is in its infancy and requires great attention in the future. This issue of partitioning between immiscible water/organic solvent systems or between aqueous solutions and organic substrates as described in this volume by Bales and Szecsody, also is significant and cannot be easily simulated at present. Nirmalakhandan and Speece presented a model in this volume based on structural parameters for predicting aqueous solubility of organic compounds; whereas Groves and El-Zoobi used empirical relationships to predict solubility and subsequently used activity coefficient relationships to arrive at activity values. Much more activity will be seen in this area as aquifer contaminant problems are remediated and the focus of engineering efforts moves toward restoring groundwater quality. Clearly a theoretically based approach will have longer lasting use and help us understand the effects each hydrophobic compound has on the systems as a whole. Coupled Hydrology/Chemistry Coupling of geochemical and hydrologic codes to model the impact geochemical reactions have on aquifer composition is a prime research effort at present. Both geochemists and hydrologists have recognized that aquifer properties such as permeability and fracture geometry can change as a result of mineral dissolution or precipitation. Changes in the physical properties of the aquifer can consequently affect the fluid residence times and thus impact aquifer mineralogy and solution chemistry. This area of concern is particularly crucial grown in importance in petroleum extraction, nuclear waste disposal, and in the general understanding of mineral deposition. Carnahan, and Steefel and Lasaga (in this volume), have demonstrated that coupling of geochemical and hydrologic models is both conceptually and mathematically complex for just simple hydrologic systems. As the system components and hydrologic details increase, the demand for faster computer systems will be critical. Tripathi has discussed a highly sophisticated coupled model, H Y D R O G E O C H E M that is yet to be published. Numerous discussions (53) have been held on the convergence of the two modeling disciplines: flow/transport models and aqueous chemical codes. The literature is extensive on attempts to merge these two approaches, but major conceptual problems remain, such as the conflict between the enormous detail provided in chemical codes regarding species, temperature adjustments and partitioning between gas and solid phase, vs. the conflict of transporting each specie individually from point to point in the hydrologic system. Current research is advancing in several directions simultaneously, from suggestions to optimize the number of species to reduce the iteration time, execute the hydrologic and chemical models separately, or to completely integrate the models accepting the enormous computational times as a transient problem to be solved by faster machines. CONCLUSIONS Few new model codes are emerging at present and greater effort is underway to improve and qualify existing models. Model development is now more driven by application needs and the quality assurance and quality control constraints than by pure research needs, as in the past. The future should witness much progress in the evaluation of error, better understanding of the effect of organic material and solvents and perhaps, a strong parallel development in the area of coupling chemistry with transport. Certainly decoupled geochemical modeling alone will continue to have strong application and will without question become a tool more useful for many new scientific and engineering applications. LITERATURE CITED 1. Garrels, R.M.; Thompson, M.E. Am. J. Sci., 1962, 260, 57-66. 2. Jenne, E.D. ed.; Chemical Modeling in Aqueous Systems, ACS Symposium Series No. 93; American Chemical Society: Washington, DC, 1979. 3. Jenne, E.A.; Geochemical Modeling: A Review, Pacific Northwest Laboratory, PNL-3574, 1981.



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4. Nordstrom, D.K.; Plummer, L.N.; Wigley, T.M.L.; Wolery, T.J.; Ball, J.W.; Jenne, E.A.; Bassett, R.L.; Crerar, D.A.; Florence, T.M.; Fritz, B.; Hoffman, M.; Holdren, G.R., Jr.; Lafon, G.M.; Mattigod, S.V.; McDuff, R.E.; Morel, F.M.M.; Reddy, M.M.; Sposito, G.; and Thrailkill, J. In Chemical Modeling in Aqueous Systems, Jenne, E . A . ed. Amer. Chem. Soc. Symp. Series 1979, vol. 79; pp. 857-892. 5. Barnes, I.; Clarke, F.E.; U.S. Geol. Survey Professional Paper 498-D, 1969. 6. Kharaka, Y.K.; Barnes, I. SOLMNEQ: Solution-Mineral Equilibrium Computations, NTIS Technical Report PB214-899, 1973. 7. Kharaka, Y.K.; Gunter, W.D.; Aggarwal, P.K.; Perkins, E.H.; DeBraal, J.D. U.S. Geol. Survey Water-Resources Invest. Report 88-4227, 1988. 8. Perkins, E.H.; Kharaka, Y.K.; Gunter W.D.; Debraal, J.D. 1989-, this volume. 9. Truesdell, D.H.; Jones, B.F. WATEQ: A computer Program for Calculating Chemical Equilibria of Natural Waters., NTIS Technical Report PB2-20464, 1973. 10. Ball, J.W.; Jenne, E.A.; Nordstrom, D.K. In chemical Modeling in Aqueous Systems; Jenne, E.A., Ed.; ACS Symposium Series No. 93; American Chemical Society: Washington, DC, 1979; pp 815-835. 11. Ball, J.W.; Jenne, E.A.; Cantrell, M.W. U.S. Geol. Survey Open-File Report 81--1183, 1981. 12. Ball, J.W.; Nordstrom, D.K.; Zachman, D.W. U.S. Geol. Survey Open File Report 87-50, 1987. 13. Wigley, T.M.L. Brit. Geomorph. Res. Group Tech. Bull. 20, 1977. 14. Morel, F.; Morgan, J.J. Env. Sci. Tech. 1972, 6, 58-67. 15. Westall, J.C.; Zachary, J.L.; Morel, F.M.M. MINEQL, A Computer Program for the Calculation of Chemical Equilibrium Composition of Aqueous Systems, MIT Technical Note 18, 1976. 16. Westall, J.C. MICROQL. A Chemical Equilibrium Program in BASIC. Report 86-02, Oregon State University: Corvallis, Oregon, 1986. 17. Ingri, N.; Kakolowlez, W.; Sillen, L.G.; Warnquist, B. Talenta, 1967, 114, 1261-1286. 18. Detar, D.F. Computer Programs for Chemistry; W.A. Benjamin: New York, 1969. 19. Perrin, D.D. Nature 1986, 206, 170-171. 20. Fritz, B., Ph.D. Thesis, Univ. Louis Pasteur, Strausbourg, France, 1975. 21. Lafon, G.M. Ph.D. Thesis, Northwestern University, Evanston, Illinois, 1969. 22. Holdren, G.R., Jr. Ph.D. thesis, Johns Hopkins University, Baltimore, Maryland, 1977. 23. Thrailkill, J. University of Kentucky Water Res. Inst. Res. Rep. 19, 1970. 24. Mattigod, S.V.; Sposito, G. In Chemical Modeling in Aqueous Systems; Jenne, E.A., Ed.; ACS Symposium Series, No. 93; American Chemical Society: Washington, DC, 1979; 837-856. 25. Van Breeman, N. Geochim. Cosmochim. Acta 1973, 37, 101-107. 26. MacCarthy, P.; Smith, G.C. In Chemical Modeling in Aqueous Systems; Jenne, E.A., Ed.; ACS Symposium Series No. 93-American Chemical Society: Washington, DC, 1979; 201-222. 27. Helgeson, H.C. Geochim. Cosmochim Acta, 1968, 32, 853-877. 28. Helgeson, H.C.; Brown, T.H.; Nigrini, A.; Jones, T.A. Geochim Cosmochim. Acta 1970,34, 569592. 29. Helgeson, H.C.; Delany, J.M.; Nesbitt, H.W.; Bird, D.K.Am. J. Sci. 1978, 278A, 1-229. 30. Reed, M.H. Geochim. Cosmochim. Acta 1982, 79, 422-425. 31. Spycher, N.F.; Reed, M.H. Geochim. Cosmochim. Acta 1988, 52, 739-749. 32. Wolery, T.J. Calculation of Chemical Equilibrium Between Aqueous Solutions and Minerals, Lawrence Livermore Laboratory, UCRL-52658, 1979. 33. Wolery, T.J. EQ3NR, A Computer Program for Geochemical Speciation-Solubility Calculations, User's Guide and Documentation, UCRL-5314, 1983. 34. Wolery, T.J. EQ6, A Computer Program for Reaction-Path Modeling of Aqueous Geochemical Systems, UCRL-51. 35. Wolery, T.J.; Jackson, K.J.; Bourcier, W.L.; Bruton, C.J.; Viani, B.E.; Knauss, K.G., Delaney, J.M. 1989; this volume 36. Parkhurst, D.L.; Thorstenson, D.C.; Plummer, L.N. U.S. Geol. Survey Water-Resources Invest. Report 80-60, 1980. 37. Plummer, L.N.; Parkhurst, D.L.; Fleming, G.W.; Dunkle, S.A. U.S. Geol. Survey Water-Resources Invest. Report 88-4153, 1988. 38. Plummer, L.N.; Parkhurst, D.L. 1989; this volume. 39. Felmy, A.R.; Girvin, D.; Jenne, E.A. MINTEQ: A Computer Program for Calculating Aqueous Geochemical Equilibria. U.S. Env. Protect. Agency, 1984. 40. Brown, D.S.; Allison, J.D. U.S. Env. Prot. Agency, EPA 60013-871012, 1987. 41. Shannon, D.W.; Morrey, J.R.; Smith, R.P. Proc. International Symp. Oilfield and Geothermal Chemistry. 1977, 21-36. 42. Pitzer, K.S. J. Phys. Chem. 1973, 77, 268-277.


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43. Stokes, R.H.; Robinson, R.A. J. Amer. Chem. Soc. 1948, 70, 1870-1878. 44. Guggenhein, E.A. Phil. Mag. 1935, 19, 588. 45. Harvie, C.E.; Weare, J.H. Geochim. Cosmochim. Acta 1980, 44, 981-997. 46. Harvie, C.E.; Moller, N.; Weare, J.H. Geochim. Cosmochim. Acta. 1984, 48, 723-751. 47. Weare, J.H. Reviews in Mineralogy, 1987, 17, 143-174. 48. Davis, J.A.; Hayes, K.F., Eds. ACS Symposium Series No. 168; American Chemical Society: Washington, DC, 1981, p 683. 49. Honeyman, B.D. Ph.D. Thesis, Stanford Univ., Stanford, CA. 1984. 50. Delany, J.M. written communication, Appendix this paper. 51. Muller, A.B. Rad. Waste Mgmt. Nuclear Fuel Cycle 1985, 6, 131-141. 52. INTERA. PHREEQE: A Geochemical Speciation and Mass Transfer Code Suitable for Nuclear Waste Performance Assessment 1983; Office of Nuclear Waste Isolation, Tech. Report ONWI435, Columbus, Ohio. 53. Tripathi, V.S.; Yeh, G.T. Abstracts of Papers 1988; 196th ACS National Meeting, Los Angeles, California, GEOC 109.


1.

13

BASSETT & MELCHIOR Overview APPENDIX. Computer models and supporting software demonstrated at the Modeling Workshop convened with the Chemical Modeling in Aqueous Systems II Symposium, September 25-30, 1988 1

PROGRAM NAME

COMPUTER

2

SOURCE

PC

P.D. Glynn USGS-WRD 432 National Center Reston, V A 22092

H Y D R A Q L A version of MINEQL, a chemical speciation code, which has been expanded to simulate adsorption with the triple layer model.

PC

J.O. Leckie Dept. Civil. Eng. Stanford Univ. Stanford, C A 94305

INTERP

A menu-driven geochemical utility that provides an interpretive environment for geochemical codes. One selects from several models, views, edits and graphi cally displays results. Output is examined as elemental percentage distri bution, saturation index, multi-window plots for Pitzer computations, and reaction path plots with overlays for error and uncertainty.

PC

R.L. Bassett Dept. Hydrology Univ. of Arizona Tucson, A Z 85721

LLE

A model for computing activity and activity coefficients for organicaqueous liquid liquid equilibrium (LLE) in multicomponent systems using the UNIQUAC equations.

GBSSAS


DESCRIPTION A code for the Guggenheim parameterization of equilibrium relations in binary solid-solution aqueous solution systems.

PC

F.R. Groves Dept. Chem. Eng. LSU Baton Rouge, L A 70803

P H R E E Q E A geochemical computer code based on (w/PHRQ- the ion-pairing model which calculates pH, redox potential and mass transfer. INPT and Balance)

PC

L.N. Plummer USGS-WRD 432 National Center Reston, V A 22092

PHRQPITZ A program adapted from the computer code P H R E E Q E which makes geo chemical calculations in brines and other electrolyte solutions at high concentrations, using the Pitzer virial coefficient approach (see paper, this volume).

M

SOLMNEQ.88

PC

Geochemical code which is the most recent version of SOLMNEQ which runs on a microcomputer via a PC-shell (see paper, this volume).

J

WATSTORE PROGRAM OFFICE; USGS 437 National Center Reston, V A 22092

Y.K. Kharaka USGS - WRD, MS 427 345 Middlefield Road Menlo Park, C A 94025 Continued on next page



14

APPENDIX. Continued


PROGRAM NAME

DESCRIPTION

COMPUTER

SOLVEQ SOLVEQ is a program for computing (with multicomponent homogeneous chemical CHILLER) equilibria in aqueous systems. For a given temperature and total composi tion of a homogeneous aqueous solution, it computes the activities of all aqueous species and the saturation indices of solids and the fugacities of gases. CHILLER is a program to compute multicomponent heterogeneous chemical equilibria among solids, gases, and an aqueous phase; suitable for modeling processes such as cooling, heating, mixing of solutions (aqueous, solid, or gaseous), mass transfer (titration of rock or of other reactants), boiling, condensation, and evaporation.

PC

2

SOURCE M . Reed Dept. Geol. Sci. Univ. of Oregon Eugene, OR 97403

WATEQ4F A F O R T R A N 77 version of the PL/1 computer program for the geochemical model WATEQ2 written for the personal computer. Limited data base revisions are included.

PC

J.W. Ball USGS - WRD, MS 420 345 Middlefield Road Menlo Park, C A 94025

PTX

A program that calculates complete pressure-temperature (P-T), temperaturecomposition (T-Xpj Q „ ), and pressurecomposition (P-X 2 ^^2) diagrams.

PC

E.H. Perkins Alberta Res. Council P.O. Box 8330 Postal Station F Edmonton, Alberta C A N A D A T6H5X2

LLNL DATA BASE

A thermochemical data base for use in geochemical modeling calculations to simulate interactions between the groundwater, rock and a waste form in a geologic repository environment. Data are included for radionuclides, canister materials, key rock forming minerals and associated aqueous species coordination with other data groups, such as CODATA and NBS is being maintained.

M

J.M. Delany LLNL L-219 P.O. Box 808 Livermore, C A 94550

Notes 1

A11 other models considered at the Symposium are either referenced in Figure 1 (this paper) or in the specific manuscript in which discussed (this volume). P C = personal computer, M = mini-computer. P C version available from R.L. Bassett, Dept. Hydrology, Univ. of Arizona, Tucson, A Z 85721. 2 3

RECEIVED August 23,1989


Chemical Modeling of Aqueous Systems - ACS Symposium Series

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