surface complexation modeling of arsenic in natural water and sediment systems

216 Pages·2001·0.98 MB·English

by  Gregory Miller

SURFACE COMPLEXATION MODELING OF
ARSENIC IN NATURALWATERAND SEDIMENT SYSTEMS
by
GregoryP. Miller
Submitted inPartialFulfillment
ofthe Requirements forthe
DoctorateofPhilosophyin Earthand EnvironmentalScience
withDissertation inGeochemistry
New Mexico InstituteofMining and Technology
Department ofEarthand EnvironmentalScience
Socorro,New Mexico
May, 2001
I have greatly profited from the love, faith, and
guidance of two women, my mother, Zena P. Miller,
and my wife, Theresa Apodaca. They saved my life.
Completion of my Ph.D. truly represents the melding
of our collective dreams. I thank you both for being
there whenI needed you the most.
GregoryP. Miller
December, 2000
Our discussion will be adequate if it has as much clearness as the
subject-matter admits of, for precision is not to be sought for alike in
all discussions, any more than in all the products ofthe crafts. Now
fine and just actions, which political science investigates, admit of
much varietyand fluctuationofopinion, so that theymay be thought
to exist only by convention, and not by nature. And goods also give
rise to a similar fluctuation because they bring harmto manypeople;
for before now men have been undone by reason oftheir wealth and
others by reason of their courage. We must be content, then, in
speaking of such subjects and with such premises to indicate the
truth roughly and in outline, and in speaking about things which are
only for the most part true and with premises of the same kind to
reach conclusions that are no better. In the same spirit, therefore,
should each type of statement be received; for it is the mark of an
educated man to look for precision in each class of things just so far
as the nature of the subject admits; it is evidently equally foolish to
accept probable reasoning from a mathematician and to demand
froma rhetoricianscientific proofs.
Aristotle, NicomacheanEthics
You can’t make the impossible possible by hallucinating new
numbers.
Dilbert, ina comic strip byScott Adams
ABSTRACT
Sorptionto solids controls arsenic mobility in most naturalwaters. Hydrous
metaloxides are the dominant sorbing solids in manynaturalsystems. Surface
complexationtheorywilldescribe water-rock partitioning ofarsenic inthe laboratory
withpure mineralphases; however, published applicationto arsenic in naturalsystems is
scant. Icompare the concentrations ofarsenic sorbed to sediments froma geothermally
influenced streaminMexico (100-1200µg/L, 6-20mg/kg As), and two contaminated
sites in Florida (10-450 µg/L, 10-44 mg/kg As), to the sediment concentrationpredicted
bya surface complexation model.
Definitionofwater chemistryand the properties and number ofsorptionsites is
required for surface complexation modeling. Generalwater quality, arsenic speciation,
and trace metalchemistrywas determined. Arsenic species separationwas conducted in
the field. The Mexico waters are 90% As5+withthe remainder present as organic arsenic
compounds and As3+. Smallamounts ofAs3+detected inMexico allowed determination
ofan in-streamAs3+t of0.13 h. The waterfromthe Florida sites was approximatelyan
1/2
equalmixture ofAs3+and As5+,withsmallamounts oforganic arsenic present.
Water-sediment ratios were determined fromgravimetricallydetermined porosity
and bulk density. The concentrationofhydrous metaloxides and sorbed arsenic onthe
sediments was determined using HNO , H PO ,citrate-bicarbonate-dithionate,
3 3 4
hydroxylamine hydrochloride + HCl, and the Tessier partialextractiontechniques. The
surface complexation literature provides ion-specific mass-actioncoefficients (K ) for
int
the pure mineralphases goethite, ferrihydrite, and gibbsite. Competitionsimulations
used K for calcium, strontium, barium, zinc, magnesium, manganese, silicic acid,
int
phosphate, carbonate, bicarbonate, sulfate, borate,and fluoride. Coefficients were fitted
orsubstitutedifnot inthe format ofthe generalizedtwo-layer surface complexation
modelofDzomback and Morel. The FITEQL4.0code was used for K fitting. Some
int
coefficients were derived fromlinear free energyrelationships.
The PHREEQC codeand the generalized two-layer modelwere used to model
arsenic sorptionusing a component additivityapproach. The component additivity
approach is conceptuallysuperior to bulk-characterizationofsolid-phase sorbing-
properties. Partitioncoefficients (K ) determined fromadsorption isotherms are also
d
inferiorto acomponent additivityapproach. Component additivityuses individual
surface complexationcoefficients measured onpure-mineralphases to represent the
sorbing surface. A localequilibriumassumption was made and new solid phases were
not allowed to precipitate ordissolve. Water-rockinteractionwas simulated and the
predicted equilibriumconcentrationofarsenic onsediments is compared to theobserved
concentrationas an indicatorofmodelfit.
The simulations were verysensitive tothe extractionmethod usedto define the
hydrous metaloxide phases and the ironhydroxide solid phase assumed to be present.
The error levelin predictionofarsenic concentrationcanexceed three ordersof
magnitude ifa plausible, but inappropriate, solid sorbing phase is selected. Modelfits
using ironoxide surfaces defined as ferrihydrite are superiortothose using goethite.
When metaloxide surfaces are defined using the HNO extractiondatathe modelwill
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closelysimulate the observed arsenic concentration. The simulations using HNO
3
extractiondata predict approximately75% ofthe observed arsenic concentrationonthe
sediments and are superiorto simulations using other extractiondata.
Sensitivityanalysis ofthe simulations was conducted. The modelresponse to
perturbationofsilica concentration, pH,orarsenic K was nonlinear. The competitive
int
effect ofsilicate, phosphate, carbonate, bicarbonate, sulfate, and boronoxyanions caused
large errorsin modelpredictions (20 to 1000 fold) ifnottreated explicitly. Silica is the
most important competing species inthe Rio Salado simulations. Phosphate is the most
important competing species inthe Florida simulations. For Rio Salado,the silica
concentration is equalin importance to arsenic sorptionas dissolved arsenic
concentration, sorbing surface concentration,or pH. Dissolved silica at concentrations as
low as 1 mg/kg influenced arsenic surface complexation inthe Florida simulations.
Phosphate, at halfthe concentrationofsilica, out-competes arsenic and silica for sorption
sites inthe Florida simulations. Estimating porosityresulted in modelresponse differing
bya factorof1.4to 2.1 fromthe response to measured porosity. Unfiltered water
analysis provided simulations withthe greatest internalconsistency.
The component additivityapproachdepends onthe transferabilityoflaboratory-
derived K fromthe literatureto field application. Sensitivityanalysis ofarsenic K on
int int
ferrihydrite indicated thatthe simulations are 10-fold more sensitive tooverestimationof
arsenic K thanunderestimation. Sensitivityto arsenic K is greatest atthe lowest
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observed sediment arsenic level. Three published values for silica K on ferrihydrite
int
were used inthe simulations. The various K forsilica caused the simulated sorbed
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arsenic concentrationto varyover fourordersofmagnitude. The modelis sensitive to
arsenic and silica K variability. The variabilityin K fromthe literature should be
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evaluated using sensitivityanalysis as the simulationerrorfromK values mayequalor
int
exceed that frompoor definitionofsolid phases.
Successfulsimulationofarsenic component additivitysurface complexation in
naturalsystems requires detailed characterizationofthe aqueous and solid phases. The
success ofthe approachwas found to be more dependant the quantification method used
for solid phasesthanquantificationofaqueouschemistry. The dependencyondefinition
ofironoxide as amorphous (ferrihydrite) orcrystalline (goethite) is equaltothe
dependencyonsolid phase quantification method. The breadthofthe aqueous analysis
used to supportthe simulation is more importantthanthe accuracyofthe individual
analyses. Failure to include quantificationofcompeting species inthe analysis, and
subsequent failure to simulate competition inthe model, affects the simulations to afar
greaterdegreethanthe analyticalerror inherent tothe quantification.
Areasonable simulationofthe observed arsenic concentrations was obtained
using competitive complexation, sorptionconstants fromthe literature, and detailed
characterizationofthe aqueous chemistryand solid phases occurring at field sites. It was
apparent that smalldifferences inthe conceptualmodeland data collectiontechniques
have a large effect onthe errorofthe simulation. Withouttuning ofinput parameters,the
explicit component additivityapproachwas able to predict the sediment arsenic
concentrationto within ±50% oftheobserved concentrations.
ACKNOWLEDGEMENTS
Withoutthe interest andoversight ofDr. D.I.Norman, Dr. R.M.Prol-Ledesma of
Universidad Nacional Autonoma de Mexico, andDr.I.P.Murarka and Dr.M.E.
McLearnofEPRI (formerlythe Electric PowerResearchInstitute),this effort would
never have beenstarted. It requires scientists ofa breed apart to guide graduate students;
for their dedication, Ithank myadvisors Drs. D.I.Norman, C. J.Popp,R. S. Bowman,
and G. W. Gross. Iamgreatlyindebted to David Welchofthe New Mexico Instituteof
Mining and Technologyfor his help inthe field and laboratory. Similarly, Lynn A.
Brandvold provided laboratoryresources at the New Mexico Bureau ofMines and
MineralResources that would have beenunavailable otherwise. David Parkhurst ofthe
US GeologicalSurveyprovided assistance withthe PHREEQC modelas did Sabine
Goldberg and Bruce Manning withanearlyreview ofthe modeling. JohnVittimade for
plant identifications, JosephKelliher provided field assistance, and Shannon Krause
performed Tc/Tklcoding. Dr.Dante J.MoranZenteno ofUniversidad Nacional
Autónoma de Mexico, Alfredo Ramirez OrozcoofComisiónFederalde Electricidad, and
Oscar A. Escolaro Fuentes, bothofComisiónNacionaldelAgua were ofgreat aid in
providing logistics support inMexico, andobtaining historicaldata.
The field investigationand modeling were funded byEPRI under Agreement No.
4CH6890. The refinement ofarsenic species field-separationwas funded bythe New
Mexico Waste-Management EnvironmentalResearchConsortium(WERC).
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TABLE OFCONTENTS
Page
TABLE OFCONTENTS...............................................................................................iii
LIST OFTABLES.........................................................................................................vi
LIST OFFIGURES........................................................................................................ix
LIST OFSYMBOLS AND ABBREVIATIONS............................................................xi
CHAPTER 1INTRODUCTION.....................................................................................1
1.1 Arsenic HealthEffects..........................................................................................3
1.2 Arsenic Geochemistry...........................................................................................4
1.3 GeochemicalModels and Modeling......................................................................6
1.4 Surface ComplexationTheory...............................................................................8
1.5 Related ResearchonSurface ComplexationModeling........................................13
CHAPTER 2 FIELD SITES..........................................................................................18
2.1 Methods..............................................................................................................18
2.2 Rio Salado, Mexico.............................................................................................18
2.2.1Filtered and Unfiltered Analysis...................................................................22
2.2.2Sediment Geochemistry...............................................................................30
2.2.3Rio Salado Flow and Chemical Flux............................................................31
2.2.4Arsenic Speciationand TransformationKinetics..........................................33
2.3 Florida Sites........................................................................................................36
2.3.1TyndallAir Force Base................................................................................39
2.3.2Fort Walton.................................................................................................40
2.3.3Water Sample Chemistry.............................................................................40
2.3.4Sediments....................................................................................................41
CHAPTER 3 METHODS..............................................................................................42
3.1 Modeling Approach............................................................................................42
3.2 SelectionofComputationalModel......................................................................49
3.3 Input Data Sets....................................................................................................50
3.3.1Rio Salado Surface Chemistry.....................................................................51
3.3.2Florida Surface Chemistry...........................................................................52
3.3.3Water-MineralRatio....................................................................................53
3.4 SensitivityAnalysis ............................................................................................54
3.5 Computationaland Data-Processing Environment...............................................55
3.6 ModelOutput and Post-Processing......................................................................56
CHAPTER 4 RESULTS................................................................................................58
4.1 Rio Salado..........................................................................................................58
4.1.1MedianR-values .........................................................................................58
4.1.2Trends inR as Compared to Select Input Data.............................................61
4.2 The Effect ofIonCompetition.............................................................................64
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4.3 Florida Sites........................................................................................................76
4.4 SensitivityAnalysis ............................................................................................79
4.4.1Variation inConceptualModel....................................................................79
4.4.2PerturbationofSelect Input Parameters.......................................................80
4.4.3PerturbationofArsenic K .........................................................................83
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CHAPTER 5 DISCUSSION..........................................................................................86
5.1 KnownLimitations to Approach.........................................................................86
5.1.1Surface Phase Limitations ...........................................................................86
5.1.2OperationallyDefined Extractions...............................................................86
5.1.3Equilibrium Assumption..............................................................................90
5.1.4Organic Substrates.......................................................................................92
5.1.5Organic Arsenic...........................................................................................93
5.2 ExtractionMethod for GeochemicalModeling....................................................93
5.2.1Rio Salado...................................................................................................93
5.2.2Florida Sites................................................................................................94
5.3 Findings Regarding the Sorbing MineralPhase...................................................95
5.3.1IronOxides..................................................................................................95
5.3.2Gibbsite.......................................................................................................96
5.4 Arsenic Speciationto Support Surface ComplexationModeling..........................96
5.5 Competition for SorptionSites byCommon Anions............................................98
5.6 Trends inR: The Ratio ofModeled to Observed Arsenic ..................................100
5.7 GeneralObservations........................................................................................102
5.8 Suggested Approach.........................................................................................105
CHAPTER 6 RECOMMENDATIONS FOR FUTURE WORK..................................107
CHAPTER 7 CONCLUSIONS...................................................................................109
REFERENCES CITED...............................................................................................111
APPENDIX ARIO SALADO FIELD INVESTIGATIONS........................................119
A.1. Site Selection..................................................................................................119
A.2. StreamFlow....................................................................................................126
A.2.1. Tracer Tests.............................................................................................126
A.2.1.1 Dye Tests..........................................................................................127
A.2.1.2 SodiumChloride Test .......................................................................127
A.2.2. Velocity-Area Method.............................................................................127
A.3. Surface Water Sampling..................................................................................130
A.3.1. Field Parameters......................................................................................130
A.3.2. Arsenic Source Variability.......................................................................133
A.3.3. Arsenic DiurnalVariation– Replicate Sampling......................................133
A.4. StreamSediment Sampling.............................................................................136
A.5. Plant and Algae Sampling...............................................................................137
A.6. AnalyticalMethods.........................................................................................137
A.6.1. AnalyticalTechniques and DetectionLimits............................................137
A.6.2. Sediment Extractions...............................................................................139
A.6.2.1 Selective Extraction..........................................................................139
A.6.2.2 HNO Digestions ..............................................................................140
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A.6.2.3 SpeciationofArsenic inSediments...................................................140
A.7. Sediment Mineralogy......................................................................................142
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