Eh - pH diagram for system As - S - O - H
Eh - pH diagram for system As - S - O - H  Activity As(OH)4- = 0.0001 Activity SO4-2 = 0.0001
Eh - pH diagram for system As - S - O - H Activity As(OH)4- = 0.0001 Activity SO4-2 = 0.0001


Dissolved Arsenic Species
Eh pH diagram for system As - S - O - H Activity of As(OH)4- = 0.0001
Activity of SO4-2 =  0.0001 prepared using The Geochemist's Workbench
Eh pH diagram for system As - S - O - H Activity of As(OH)4- = 0.0001 Activity of SO4-2 = 0.0001 prepared using The Geochemist's Workbench


Eh pH Diagram for Cu - C - S - O - H
Eh pH Diagram for Cu - C - S - O - H  Activity Cu+ = 0.0001, HCO3- = 0.005, SO4-2 = 0.005
Eh pH Diagram for Cu - C - S - O - H Activity Cu+ = 0.0001, HCO3- = 0.005, SO4-2 = 0.005

Our Philosophy

Our philosophy is that projects that require expertise in environmental geochemistry follow a series of similar steps.  Such similarities exist because all environmental geochemistry projects require an understanding of the relationships between a source of chemicals and an environment.  These steps involve characterization of the source terms, understanding the geochemical condition of the receiving environment, as well as understanding the chemical reactions between the source and the environment.

Understanding and predicting the behavior of releases to the environment requires that the geochemical reactions between the source and geochemical setting be thoroughly understood.  In most situations, a series of competing reactions are taking place within the geochemical environment and it is critical to identify the dominant reactions early in the characterization process.  More importantly, the dominant reactions can change over time or as a function of distance as reactants are consumed and new chemical species are produced.  

To enhance our understanding of geochemical conditions models are often employed.  Because of the diversity of reactions that can occur in these situations, geochemical models can be used in many stages of a project.  The nature of a “model” can range from a simple qualitative description that may describe why the pH changes along a groundwater plume, to an Eh-pH diagram showing the importance of different chemical species, to complicated numerical models that may utilize various types of geologic, hydrologic and chemical data.   Although many models have been applied for long term predictions of water composition, geochemical models are often best used as a management tool to select the best options without having to resort to full scale testing or committing to a specific treatment method. 

This process of characterization, understanding geochemical conditions and modeling applies to projects that involve:

  • Permitting of new facilities that may require predictive models, such as a pit lake model,

  • Optimization of ongoing operations, such as improving in-situ recovery of metals, and

  • Remediation of previous releases, which may have occurred at legacy operations.

In our role as “a consultant to the consultant”, we have acquired the experience in developing the types of data that are needed for these diverse projects, as well as the ability to understand and quantify the detailed chemical reactions that are critical to a successful project outcome.  

Mahoney Geochemical Consulting was founded in 2009.  At that time I expected to put on the occasional short course on geochemical modeling, but I did not expect that the demand for this service would be so great.  Since 2010 I have organized or been involved with 18 short courses on geochemical modeling.  These courses have been held in the United States, Canada, Australia, Sweden and South Africa.   Most have been open to anyone interested in geochemical modeling; a few have been private course sponsored by mining companies, consulting firms or other resource recovery corporations.  I estimate that over 160 people have participated in these training sessions.  Currently, I have two courses that are available.  The basic introduction to modeling course, which is the course I wish I had when I started modeling.  In that course we introduce most of the keywords using in PHREEQC, and include some hands on work with  PHAST and HYDRA/MEDUSA.  The course also covers some basic geochemistry, and presents some environmental consulting topics including separate presentations on uranium and arsenic geochemistry as well as discussions on mining related topics, including pit lakes.  The advanced course skips some of the introductory presentations and the consulting topics.  It covers some of the same areas related to PHREEQC modeling as in the introductory course  but it is currently set up to provide more time with PHAST and PhreePlot.  


I have included a description of PhreePlot on this page because its capabilities, particularly as applied to optimization of model parameters, have greatly reshaped my thoughts on this topic.  Optimization or fitting of model parameters,  with PhreePlot or PEST or UCODE, will become more and more common and will actually be expected for many applications.  PhreePlot is the simplest approach to fitting parameters in a PHREEQC model.  

The following link will get you to the PhreePlot Website where you can download PhreePlot, the USer's Guide and numerous examples.   Link to PhreePlot page

Over the last five years, I have been working with PhreePlot, a PHREEQC based geochemical modeling program, that allows the preparation of various activity - activity diagrams as well as providing various data fitting options, which can greatly improve PHREEQC based models.  PhreePlot has a lot of flexibility and options to prepare report quality images.  Images may be colored, black and white, or grayscale, and overlays are also possible.  As the name suggests, this program uses PHREEQC to perform all the chemical calculations and this setup provide another feature that is not generally available in the packages such as Geochemist's Workbench or HYDRA/MEDUSA.  One of the features that is shown below is the ability to include surface complexation reactions in Eh-pH space, In this figure the surface sites are linked to the concentration of hydrous ferric oxide that is present in the underlying model calculations..


Another feature is the ability to prepare concentration contour diagrams.  The figure below shows the log ppm concentrations of arsenic for the scorodite figure shown above.



But the real power in PhreePlot is the ability to fit model parameters to a data set. 

This example shows how to fit speciation reactions (log K values) from a titration curve. The example is an idealized case, as we use PHREEQC to generate an essentially perfect titration curve, which is then used by PhreePlot to optimize the log K values for the following reactions:

#CO2     could be used instead of H2CO3
CO3-2 + 2 H+ = CO2 + H2O
log_k <k2fit>

#HCO3-               27
H+ + CO3-2 = HCO3- 
log_k <k1fit>
This is a simple demonstration and was set up to show the capabilities in PhreePlot.  The fitted values are identical to the values used in the initial PHREEQC simulation.

A more realistic fitting effort is shown in  the following figure.  The adsorption of dimethylarsinic acid [DMAA(V)] onto goethite is used to calculate CD-MUSIC sorption constants.  Two different sources of data were used to fit these sorption reactions. One set was by Lafferty and Loepert  (2005), the other source was from a dissertation by Zhang (2005, University of Singapore).   Only a single reaction is needed to produce a reasonably good fit.

      Goe_uniOH-0.5 + H+ + Dmasv- = Goe_uniOH2Dmasv-0.5
         log_k     <fit_Dmasv> # SHR2008
        -cd_music  1 <z1> 0 0 0

The surface area for the goethite used by L and L was not included in their paper, therefore it was added as another fitting parameter.
I am still working of the charge distribution for these surface complexes, so some corrections are possible.  But at the present time, the fitted value appears to provide a reasonable fit.