Journal of Contaminant Hydrology 103 (2009) 145–156

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Journal of Contaminant Hydrology

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Effects of initial iron corrosion rate on long-term performance of ironpermeable reactive barriers: Column experiments and numerical simulation

Jin suk O 1, Sung-Wook Jeen⁎, Robert W. Gillham, Lai GuiDepartment of Earth and Environmental Sciences, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1

a r t i c l e i n f o

⁎ Corresponding author. Tel.: +1 519 888 4567x337484.

E-mail address: sjeen@uwaterloo.ca (S.-W. Jeen).1 Present Address: Golder Associates Ltd., 2390 A

sauga, Ontario, Canada L5N 5Z7.

0169-7722/$ – see front matter © 2008 Elsevier B.V.doi:10.1016/j.jconhyd.2008.09.013

a b s t r a c t

Article history:Received 10 January 2008Received in revised form 20 August 2008Accepted 29 September 2008Available online 15 October 2008

Column experiments and numerical simulationwere conducted to test the hypothesis that ironmaterial having a high corrosion rate is not beneficial for the long-term performance of ironpermeable reactive barriers (PRBs) because of faster passivation of iron and greater porosityloss close to the influent face of the PRBs. Four iron materials (Connelly, Gotthart-Maier,Peerless, and ISPAT) were used for the column experiments, and the changes in reactivitytoward cis-dichloroethene (cis-DCE) degradation in the presence of dissolved CaCO3 wereevaluated. The experimental results showed that the difference in distribution of theaccumulated precipitates, resulting from differences in iron corrosion rate, caused adifference in the migration rate of the cis-DCE profiles and a significant difference in thepattern of passivation, indicating a faster passivation in the region close to the influent end forthe material having a higher corrosion rate. For the numerical simulation, the accumulation ofsecondary minerals and reactivity loss of iron were coupled using an empirically-derivedrelationship that was incorporated into a multi-component reactive transport model. Thesimulation results provided a reasonable representation of the evolution of iron reactivitytoward cis-DCE treatment and the changes in geochemical conditions for each material,consistent with the observed data. The simulations for long-term performance were alsoconducted to further test the hypothesis and predict the differences in performance over aperiod of 40 years under typical groundwater conditions. The predictions showed that the casesof higher iron corrosion rates had earlier cis-DCE breakthrough and more reduction in porositystarting from near the influent face, due to more accumulation of carbonate minerals in thatregion. Therefore, both the experimental and simulation results appear to support thehypothesis and suggest that reactivity changes of iron materials resulting from evolution ofgeochemical conditions should be considered in the design of iron PRBs.

© 2008 Elsevier B.V. All rights reserved.

Keywords:Carbonate mineralcis-dichloroetheneCorrosion rateGranular ironPermeable reactive barrier

1. Introduction

Permeable reactive barriers (PRBs) containing granulariron have been shown to successfully treat a wide range ofcontaminants for substantial periods of time (e.g., O'Hannesinand Gillham, 1998; Blowes et al., 1999; Wilkin et al., 2003,2005; Warner et al., 2005). However, previous studies (e.g.,

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Mackenzie et al., 1999; Agrawal et al., 2002; Klausen et al.,2003) have suggested that iron PRBs, receiving high concen-trations of inorganic constituents in groundwater, mayexperience passivation and loss in permeability because ofthe accumulation of inorganic precipitates. In particular,Zhang and Gillham (2005) concluded that carbonate mineralscan passivate granular iron, and the passivation of iron canhave a major effect on the pattern and extent of precipitateformation. Jeen et al. (2006) conducted systematic columnexperiments using longer columns over longer periods oftime than the experiments reported in Zhang and Gillham(2005). The results indicated that migration of the mineralprecipitation front resulted in a more or less evenly

Table 1Column characteristics

Column Connelly Gotthart-Maier Peerless ISPAT

Source composition 10 mg L−1 cis-DCE+300 mg L−1 CaCO3

Grain size 40–18 mesh (0.42–1.00 mm)Surface area (m2/g) 1.38±0.25 0.51±0.12 0.66±0.12 0.62±0.25Column length (cm) 50Internal diameter (cm) 3.81Sampling port a (cm) 2.5, 5, 7.5, 10, 15, 20, 25, 30, 35, 40, 45Mass of iron (g) 1846.4 2045.3 1700.6 1364.2Pore volume (PV) (cm3) 260.4 284.1 334.4 382.3Porosity (–) 0.46 0.50 0.57 0.66Bulk density (g/cm3) 3.24 3.59 2.92 2.34Operation period b 588 PV 528 PV 396 PV 334 PV

(266 d) (260 d) (229 d) (221 d)

a Distance from the influent end.b The period after introduction of 10 mg L−1 cis-DCE+300 mg L−1 CaCO3.

146 Jin suk O et al. / Journal of Contaminant Hydrology 103 (2009) 145–156

distributed porosity loss throughout the columns. Thepatterns of various organic and inorganic profiles agreedqualitatively with those of Zhang and Gillham (2005).Furthermore, Jeen et al. (2007a) modeled the decliningreactivity of iron resulting from the accumulation of second-ary precipitates and the simulation results provided areasonable representation of the performance of iron treatingtrichloroethene (TCE) in the presence of dissolved CaCO3.

It has generally been assumed that materials of higherreactivity (toward degradation of contaminants) would bebeneficial because they degrade contaminants faster, redu-cing the thickness of a barrier and thus installation cost.However, aspects of accumulation of secondary precipitatesand reactivity loss may be counter to this expectation. One ofthe important implications from the results of Jeen et al.(2007a) is that iron having a high initial corrosion rate maynot be advantageous compared to iron having a lower initialcorrosion rate for the long-term performance of PRBs in thepresence of a high concentration of dissolved CaCO3. It washypothesized that in an iron PRB containing material of highinitial corrosion rate, a faster migration of the contaminantremoval front may occur due a faster accumulation ofsecondary precipitates. In contrast, an iron PRB containingmaterial of lower initial corrosion rate may show a sloweraccumulation of precipitates, and thus a slower migration ofthe contaminant removal front, leading to longer times ofeffective performance. Verifying this hypothesis will elucidatethe significance of initial iron corrosion rate and thus willprovide greater insight for selecting iron materials to be usedin construction of PRBs, particularly those that are likely toencounter high concentrations of inorganic constituents.

The objective of this study was to test this hypothesis byconducting 1) column experiments and 2) numerical simula-tion. Column experiments were conducted to evaluate thechanges in reactivity of different iron materials for cis-dichloroethene (cis-DCE) treatment in the presence ofdissolved CaCO3. Four sources of iron materials, differing ininitial corrosion rate, were used for the experiments. The cis-DCE removal rates and the geochemical profiles for eachmaterial were monitored over a period of 8 months. One ofthe challenges for iron PRBs is to ensure efficient reductivedechlorination not only for tetrachloroethene (PCE) and TCE,but also for the intermediates, in particular cis-DCE and vinylchloride (VC) (VanStone et al., 2004; Ebert et al., 2006).Generally cis-DCE and VC degrade more slowly than PCE andTCE. Thus, if cis-DCE and VC were already present in theplume as intermediates, PRB design should take these intoconsideration.

To simulate the changes in various chemical profilesobserved in column experiments, it is necessary for thenumerical simulation to include declining reactivity of iron,resulting from precipitation of secondary minerals. Jeen et al.(2007a) coupled the accumulation of secondary minerals andreactivity loss of iron using an empirically-derived relation-ship, by modifying the kinetic expressions of the reactivetransport model MIN3P (Mayer et al., 2002). This studyapplied the same model (Jeen et al., 2007a) to the results ofthe column experiments to test the hypothesis. The modelwas also used to predict the longevities of iron PRBscontaining materials of differing corrosion rates under typicalgroundwater conditions.

2. Column experiments

2.1. Methods

2.1.1. Iron materialsFour commercial iron materials were obtained from

Connelly-GPM, Inc. (Chicago, IL), Gotthart-Maier Metallpulver(Rheinfelden, Germany), Peerless Metal Powders and Abra-sive (Detroit, MI), and ISPAT Sidbec-Dosco (Quebec, Canada).Connelly, Gotthart-Maier, and Peerless consist of scrap metal,mostly cast irons and low alloy steels, have columnar andplaty shapes, and are covered with a variable thickness ofpassive iron oxides formed during themanufacturing process.ISPAT is a steelmaking byproduct and is also referred to as‘iron sponge’. The direct reduction of ore pellets yields aspheroidal shape with a porous inner structure, and up to 10%of lump ore is included (Ebert et al., 2006). ISPAT iron comesin larger (~1 cm) granules made by binding iron powder witha cementitious binder. The material was crushed to anequivalent size distribution as the other granular ironmaterials. All materials were sieved to a grain size withinthe range of 40–18 mesh (0.42–1.00 mm). The specific surfaceareas were measured by the Brunauer–Emmett–Teller (BET)method (Brunauer et al., 1938) (Table 1).

2.1.2. ColumnsThe columndesignwas similar to that described in Jeen et al.

(2006), except larger in diameter. Each column consisted of a50 cm long clear Plexiglas™ tube with an internal diameter of3.81 cm. Nine sampling ports were located at 5 cm intervalsalong the column with two additional ports at 2.5 and 7.5 cmfrom the influent end. All columns were packed dry with thesieved granular ironmaterials. The initial porosity (Table 1)wasdetermined from the volume of each column, the total mass ofiron added, and the columnweightmeasuredafter saturation ofthe columnwithwater. Afterfillingwith iron, the columnswerepurged with CO2 gas for about 2 h, followed by several porevolumes (PVs) of deoxygenated deionized water to ensurecomplete saturation prior to addition of the test solution.

2.1.3. Test solutionEach column received 10 mg L−1 cis-DCE in deoxygenated

deionized water for over 30 PV to remove surface oxide films

Fig. 1. Iron corrosion rates for each column following introduction ofdissolved CaCO3, calculated from the rates of hydrogen generation over time.

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through autoreduction (Ritter et al., 2002) and to determinethe initial kinetics of cis-DCE degradation in the absence ofdissolved CaCO3. This was followed by a solution containing10 mg L−1 cis-DCE+300 mg L−1 CaCO3. To prepare the CaCO3

solution, a pre-calculated amount of analytical grade CaCO3(s)was added to deionized water. The solution was purged withCO2 gas to dissolve the CaCO3(s), followed by adjustment ofpH to 6.7±0.2 by purging with oxygen-free N2 gas. Afterpurging, the dissolved oxygen concentrations were below0.2 mg L−1, as measured by CHEMets Kit (K-7501). Aconcentrated stock solution of cis-DCE in methanol wasspiked to the test solution to achieve a nominal concentrationof 10 mg L−1.

2.1.4. Column operationTo minimize oxygen invasion, except for short lengths

(15 cm) of Ismatec 2-stop Viton® tubing (Cole-Parmer) thatpassed through the pump, stainless steel tubing was used toconnect the glass bottles containing the test solutions to thecolumns. As a further precaution for preventing oxygenintrusion of the test solutions in the bottles, a Mylar™ balloonfilled with oxygen-free N2 gas was connected to a “guardbottle”. The “guard bottle” contained the same solution andthus the nitrogen gas was equilibrated with the cis-DCE in thesolution prior to entering the headspace in the feed bottle.The concentrations of cis-DCE and dissolved oxygen, both inthe feed and guard bottles, were checked periodically. In theevent of a significant decrease in cis-DCE concentration or anincrease in dissolved oxygen, the solution was replacedimmediately.

The test solutionwas pumped to the bottom (influent) endof the column at a flow rate of approximately 0.4 mL min−1

using an Ismatec multi-channel peristaltic pump (Model7619-30). The flow velocity varied among the columns as aconsequence of differences in porosity, but the initial valueswere all close to 1.0 m d−1. The time to displace one PV ofsolution was approximately 10, 12, 14, and 16 h for Connelly,Gotthart-Maier, Peerless, and ISPAT irons, respectively. Theeffluent volume was recorded weekly by weighing the massof water collected, allowing the average flow rate during thecollection period to be calculated. Columns were operated forapproximately 8 months, but the total treated PVs for theindividual columns differed as a consequence of differences inporosity (Table 1).

Teflon® tubing connected to “T” valves near the inlet andoutlet of each column were used as manometers to measurethe hydraulic head difference across the column. From thehydraulic gradient and solution flux, hydraulic conductivitywas calculated using the Darcy equation. The gases emittedfrom the effluent end were trapped in a sealed glass tubeconnected in the effluent line. The volume difference in thesealed glass tube over a specific time interval was recorded toestimate the rate of gas generation. The rate of gas productionwas used to calculate the corrosion rate of the iron in eachcolumn. Column weights were measured on a regular basisfor each column. Measured column weight at a particulartime was subtracted from the initial weight, to determine thenet cumulative gain or loss due to mineral precipitation andgas accumulation.

Samples were collected periodically for analyses of organicand inorganic parameters. Initially sampleswere collected each

week, then every 1 to 2 months later in the experiment, for atotal of 13 sampling events for Connelly and Gotthart-Maieriron materials and a total of 7 sampling events for the Peerlessand ISPATmaterials. Concentrationsof cis-DCE, VC andchloride,Eh, pH, and alkalinity were analyzed. Solid samples wereanalyzed at the end of the experiments to determine theamounts of carbonate precipitates accumulated ineach column.Analytical methods were identical to those described in Jeenet al. (2006). All experiments were conducted in the samelaboratory at ambient temperature (24±2 °C).

2.2. Results and discussion for the column experiments

2.2.1. Iron corrosion rateAnaerobic iron corrosion results in the formation of

hydrogen which, in columns containing granular iron, canpartition into three phases: gas phase, aqueous phase andsolid phase (entrapment of hydrogen in the iron) (Reardon,1995, 2005). In this study, the H2 in the gas phase wasmeasured directly by collection in the sealed glass tubes,assuming that the gas exiting at the effluent end was H2 only.The H2 in the aqueous phase was estimated assumingsaturation and using a solubility of 7.515×10−4 mol kg−1 (forpure water at 100 kPa H2 at 25 °C; Dean, 1992). H2 in the solidphase was estimated using Sievert's law (Reardon, 1995,2005). The sum of the three phases was used to calculate thecorrosion rate, as in Reardon (1995, 2005). Reaction betweenFe0 and cis-DCE was neglected because the magnitude ofcorrosion by cis-DCE was not significant compared to thatcalculated from corrosion by water. The H2 in the gas phasewas the major component, the dissolved H2 was relativelyminor for all columns (about 5−10%), and H2 uptake by theiron contributed up to approximately 30% of the totalcorrosion rates at early times. However, the contribution ofH2 uptake by the iron for all columns declined over time.

The average iron corrosion rates calculated before introduc-tion of dissolvedCaCO3were 0.76, 0.94,1.60, and 4.98mmol kg−1

Fe0 d−1 for Connelly, Gotthart-Maier, Peerless, and ISPAT irons,respectively, indicating that ISPAT iron had a significantly highercorrosion rate than the other three irons. The results arereasonably consistent with the corrosion cell tests of Reardon(2005), inwhich ISPAT had the highest corrosion rate (3.0 mmol

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kg−1 Fe0 d−1), while the other three were lower but similar toeach other (0.2 to 1.2 mmol kg−1 Fe0 d−1).

After dissolved CaCO3 was introduced, the iron corrosionrates for all four columns increased, reaching maximumvalues at about 50 PV (Fig. 1). In particular, ISPAT, which hadthe highest values in the absence of dissolved CaCO3, nearlydoubled after introduction of dissolved CaCO3, at 2−4 timeshigher than the maximum values of the other irons. Themaximum values for the iron corrosion rates after dissolvedCaCO3 was introduced were 3.53, 4.19, 5.29, and 12.62 mmolkg−1 Fe0 d−1 for Connelly, Gotthart-Maier, Peerless, and ISPATirons, respectively. The differences could be caused bydifferences in composition of the iron surfaces and geometricfactors such as packing and geometry of the particles. Itshould also be noted that ISPAT iron is derived from orematerial, whereas the others are grey cast irons. Thedifferences in corrosion rates provide evidence that the fouriron materials are suitable to test the hypothesis. Over time,the corrosion rates decreased gradually, with the greatestdecline in ISPAT iron (Fig. 1).

The magnitudes of corrosion rates and trends (initialenhancement and decrease over time) are consistent withother column studies (Köber et al., 2002; Kamolpornwijit et al.,2004; Parbs et al., 2007). As reported in the literature (e.g.,Parbs et al., 2007), there may be two conflicting processes inthe columns that either enhance or inhibit the corrosionprocess. The (temporary) enhancement of corrosion appearsto be due to a buffering effect of the aqueous CO2 species andthe subsequent inhibition is caused by the formation ofcarbonateminerals, which act as a barrier to further corrosion.In relatively early time periods, the formation of carbonateminerals is concentrated near the influent end of the column,and the region of relatively fresh iron still contributes

Fig. 2. The measured and simulated cis-DCE profiles for (a) Connelly, (b) Gotthart-periods in days, following introduction of dissolved CaCO3, and L and S represent th

significantly to the measured corrosion rate. At later times,the iron in the greater portion of the column is covered bycarbonate minerals, resulting in a substantial decrease in themeasured corrosion rate. The formation of carbonate mineralcoatings passivates the iron, which in turn limits furtheraccumulation of carbonate minerals.

2.2.2. Degradation of cis-DCEThe cis-DCE profiles for all columns, following introduction

of dissolved CaCO3 (Fig. 2), showed a shift toward the influentend of the columns compared to those in the absence ofdissolved CaCO3 (data not shown). The shift was substantial forConnelly, Gotthart-Maier, andPeerless, butminor for ISPAT. Thissuggests enhanced reactivity of iron toward cis-DCE degrada-tion caused by aqueous CO2 species. The (temporarily)increased reactivity of iron toward chlorinated organic com-pounds, in the presence of aqueous CO2 species, is consistentwith results reported by others (Dahmke et al., 2000; Agrawalet al., 2002; Klausen et al., 2003; Parbs et al., 2007).

Degradation of chlorinated organic compounds on gran-ular iron has been observed to follow pseudo-first-orderkinetics with respect to the concentrations of the targetorganic compounds (e.g., Gillham and O'Hannesin, 1994;Johnson et al., 1996; Su and Puls, 1999). However, the first-order kinetic model gave a reasonable match only to theearlier profiles for each column after introduction of dissolvedCaCO3. The highest reaction rates were establishedwithin lessthan 35 PV (20 d) for each column after introduction ofdissolved CaCO3. Those profiles were considered to havereached steady-state before experiencing passivation result-ing from mineral precipitation, and were thus used tocalculate the initial reactivities of iron toward cis-DCEdegradation in the presence of dissolved CaCO3. The

Maier, (c) Peerless, and (d) ISPAT iron. Figures in legend represent the timee laboratory and simulated results, respectively.

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calculated initial pseudo-first-order rate constants were2.14×10−3, 8.82×10−4, 7.82×10−4, and 5.77×10−5 s−1 forConnelly, Gotthart-Maier, Peerless, and ISPAT irons, respec-tively. The Connelly, Gotthart-Maier, and Peerless irons thushad similar initial reactivities, while that of ISPAT wassignificantly lower.

It was expected that the measured maximum corrosionrates would correlate with the initial degradation rateconstants for cis-DCE. However, the iron corrosion rates(Fig. 1) were not clearly related to the extent of thedegradation of cis-DCE for each column (Fig. 2). The extremecase was ISPAT iron, which showed the highest iron corrosionrate but the lowest degradation rate for cis-DCE afterintroduction of dissolved CaCO3. This may reflect the intrinsicproperties for a specific iron material toward degradation of aspecific organic compound, or possibly the high rate ofhydrogen gas generation in ISPAT iron hinders contact oforganic contaminant (cis-DCE) with the iron surfaces. Toelucidate this observation and clarify the terminology, in thefollowing text, reactivity of iron refers to the potential of ironto react with cis-DCE and iron corrosion rate refers to thepotential to react with water.

Over time, all columns showed migration of the cis-DCEprofiles toward the effluent ends (Fig. 2), indicating gradualpassivation of the iron materials. While Connelly, Gotthart-Maier, and Peerless irons showed similar patterns of profilemigration, ISPAT showed the most pronounced passivationtoward the influent end, and had the lowest degradation ratesover the course of the experiments. Comparing Connelly andGotthart-Maier irons (Fig. 2a and b), which were operated forsimilar periods of time, the leading edges of the profiles forGotthart-Maier were further advanced than in the case of

Fig. 3. The measured and simulated alkalinity profiles for (a) Connelly, (b) Gotthart-Peerless and ISPAT iron, respectively, were notmeasured. Figures in legend representS represent the laboratory and simulated results, respectively.

Connelly at similar time periods. The data for Peerless(Fig. 2c), which was operated for a shorter period of timethan Connelly and Gotthart-Maier, suggested a migrationpattern similar to Gotthart-Maier iron. In the ISPAT iron, therewas an expanding zone adjacent to the influent end wherethere appeared to be little or no degradation, followed by azone where the rate of degradation is constant over distance(Fig. 2d). This suggests the greatest and fastest accumulationof carbonate precipitates in the region close to the influentend for ISPAT iron.

It should be noted that the degree of passivation towardcis-DCE degradation (Fig. 2) is consistent with the ironcorrosion rate for each iron (Fig. 1). That is, the materialwith the highest corrosion rate (ISPAT iron) shows thegreatest passivation near the influent end, Gotthart-Maierand Peerless irons, with similar corrosion rates, showmoderate passivation, and Connelly iron, having the lowestcorrosion rate, shows the least passivation. Although themaximum cis-DCE degradation rates do not correspond tothe iron corrosion rates, the rates of passivation and thus themigration rates of the cis-DCE profiles are dependent onthe iron corrosion rates, suggesting that iron corrosion rate isthe governing factor for passivation of the iron materials.

2.2.3. VC and chlorideThe only chlorinated product of cis-DCE degradation was

VC, and the maximum VC concentration was b4% of theinfluent cis-DCE concentration for all columns. The profilesfor VC migrated further into the column over time (data notshown), and the trends were consistent with those of cis-DCEfor each column. The results for the chloride concentrations(data not shown) were also consistent with the trends for the

Maier, (c) Peerless, and (d) ISPAT iron. Note that the data at day 81 and 73 forthe time periods in days, following introduction of dissolved CaCO3, and L and

150 Jin suk O et al. / Journal of Contaminant Hydrology 103 (2009) 145–156

cis-DCE and VC profiles. As the experiment proceeded, thelocation of the maximum chloride concentration for the fourcolumns migrated further into the columns, consistent withthe progression of the passivation front. Chloride massbalances at various times were calculated and rangedbetween 85 and 115%, with no apparent trend with distancealong the columns or between the various columns.

2.2.4. Alkalinity, pH, and EhAt early times, alkalinity was removed primarily in the

region near the influent end of each column, and as theexperiment proceeded, the decline in alkalinity occurredfurther into the columns (Fig. 3). All columns, except ISPATiron at early times, had similar alkalinity values at the effluentend of the column throughout the experiments, suggestingthat similar amounts of carbonate precipitates had accumu-lated within the columns at similar periods of time. TheConnelly, Gotthart-Maier, and Peerless irons showed similarrates of migration of the alkalinity front, whereas ISPAT ironhad a much slower migration rate. This indicates thatalthough the total amount of carbonate precipitates shouldbe similar for all columns at similar periods of time, thedistribution of precipitates could be significantly different.That is, the precipitates in the ISPAT column are concentratednear the influent end, relative to the other columns. It isproposed that the high rates of removal near the influent endin the ISPAT iron is a consequence of the high corrosion rate(Fig. 1). When corrosion rate is high, the increase in pH andpotential for mineral precipitation are high, resulting inmineral precipitation concentrated near the influent end. Incontrast, when corrosion rate is low, the process of precipita-tion occurs more uniformly along the length of the column.

Fig. 4. The measured and simulated pH profiles for (a) Connelly, (b) Gotthart-Maier, (and ISPAT iron, respectively, were not measured. Figures in legend represent the trepresent the laboratory and simulated results, respectively.

At early time the ISPAT iron showed a gradual increase inalkalinity from 15 cm from the influent end toward theeffluent end of the column (Fig. 3d). Of the four materials,ISPAT showed the highest pH values toward the effluent endat early times (NpH 11, Fig. 4d). Thus, in addition to carbonatealkalinity, hydroxide alkalinity was considered to contributeto the measured total alkalinity. When hydroxide alkalinitywas measured at 11 PV (7 d), for example, it accounted forabout 68 mg L−1 of the total alkalinity of 105 mg L−1 at theeffluent end. The contribution of hydroxide alkalinity to thetotal alkalinity decreased over time, as the pH valuesdecreased, due to passivation of the iron. For the other threecolumns, hydroxide alkalinity did not contribute significantlyto the total alkalinity.

The pH values increased to approximately 9−10 forConnelly, Gotthart-Maier and Peerless irons, and over 11 forISPAT iron, with pH buffering due to carbonate precipitationclose to the influent end for all columns (Fig. 4). As passivationof the ironproceeded, the locationwhere pH began to increasemigrated further toward the effluent ends of the columns. ThepH trends over time for Connelly, Gotthart-Maier and Peerlessironswere similar. However, ISPAT iron showed thehighest pHvalues among all columns throughout the experiments, andpH over 9 was still observed in the effluent half of the columnat the endof the experiment (Fig. 4d), correspondingwellwiththe highest corrosion rate (Fig. 1).

After addition of dissolved CaCO3, the measured Eh valueswere approximately −300 to −340 mV for Connelly andGotthart-Maier irons, −330 mV to −390 mV for Peerless iron,and −360 mV to −440 mV for ISPAT iron along the length ofthe columns. The passivation due to the accumulation ofcarbonate precipitates caused the Eh values to increase to

c) Peerless, and (d) ISPAT iron. Note that the data at day 81 and 73 for Peerlessime periods in days, following introduction of dissolved CaCO3, and L and S

Fig. 5. Distribution of carbonates along the length of each column, calculatedfrom the acid digestion of solid samples at the end of the experiments. Themass of carbonates are expressed as mass of equivalent CaCO3, and the errorbars represent the standard deviations of the triplicate samples for eachsampling location (most of error bars are less than symbol sizes).

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approximately −100 mV to −200 mV for Connelly andGotthart-Maier irons, and −200 to −250 mV for Peerless andISPAT irons along the length of the columns at later times. Theregion close the influent end showed a more substantialincrease (to about 0 mV) and the region progressed furtherinto the column over time (data not shown).

2.2.5. Accumulation of precipitatesThe distribution and amounts of precipitates formed in

each column were evaluated in several ways. The qualitativeevidence of precipitate formation was from visual inspectionof the columns. It appeared that the iron materials having thehigher corrosion rates showed a more distinctive grayishwhite color, particularly near the influent ends of thecolumns, with ISPAT iron showing the most distinctive colorchange. The precipitation fronts migrated slowly but con-tinuously over time, with the advance of the precipitationfront in the ISPAT iron being much slower than in the othercolumns.

Fig. 5 shows the distribution of carbonates along the lengthof each column, calculated from the acid digestion of solidsamples collected at the end of the column test. The operationperiods for Peerless and ISPAT irons were shorter than thosefor Connelly and Gotthart-Maier irons (Table 1); thus, directcomparison of the amounts of precipitate between the

Table 2Total mass of carbonates accumulated within each column by the end of theexperiments, calculated from the methods of acid digestion, alkalinity, andcolumn weights

Column Connelly Gotthart-Maier Peerless ISPAT

Acid digestion a (g) 77.7 78.0 65.2 62.3Alkalinity a (g) 69.8 70.6 66.6 63.1Column weight (g) 75.9 78.3 71.9 66.5Average (g) 74.5 (±4.1) 75.6 (±4.4) 67.9 (±3.6) 64.0 (±2.2)Precipitate/treatedwater (g/L) b

0.49 (±0.03) 0.51 (±0.03) 0.52 (±0.03) 0.51 (±0.02)

Errors represent the standard deviation for the three methods.a Refer to Jeen et al. (2006) for the detailed methods.b Average over the total treated water.

columns is not meaningful. Nonetheless, the results clearlyshow the distribution of precipitates in ISPAT to differsubstantially from those of the other three columns. That is,ISPAT showed a much higher accumulation of precipitatesnear the influent end, and precipitates were restricted largelyto the first 10 to 20 cm of the column. The remaining threecolumns showed similar patterns of precipitate accumulation,with relatively steady values over the first 30 cm of thecolumns then declining toward the effluent ends.

The amounts of precipitates were also calculated from themeasured decline in alkalinity (Table 2). The previous mineralidentification in a Connelly iron column, operated undersimilar geochemical condition by Jeen et al. (2007b), showedthat the major carbonate precipitates were aragonite (CaCO3)and iron hydroxy carbonate (Fe2(OH)2CO3). Thus, it wasassumed that thesewere also themajor carbonate precipitatesformed in this study. Because calciumdatawas not available, itwas also assumed that the two precipitates were formed in anequal molar ratio, as observed by Jeen et al. (2006).

Precipitate formation was also calculated from changes incolumn weight. All columns showed initial decreases incolumn weight prior to dissolved CaCO3 addition. The initialweight loss was caused by the accumulation of hydrogen gaswithin the pore space. Bubbles of H2 would accumulate in thepore space until a network of continuous gas-filled pores wasformed, at which time the continuing production of H2 wouldresult in the appearance of gas bubbles in the effluent line.Dissolved CaCO3 was introduced to all columns after thecolumn weights reached the lowest levels. The weights of allfour columns began to increase after addition of dissolvedCaCO3, and the weight increase was attributed to theaccumulation of precipitates.

Table 2 summarizes the total mass of the precipitatesaccumulated within the column by the end of the experi-ments, as determined from the above methods. The differ-ences in the total mass among the columns are consistentamong the different methods, showing that the amounts forConnelly and Gotthart-Maier irons, which were operated forsimilar periods of time, are similar, while those for Peerlessand ISPAT, which operated for a shorter period of time, aresimilar but lower. When the total mass of precipitates for eachcolumn is normalized to the total volume of water treated, theamounts of precipitates per unit volume of treated water are

Fig. 6. Hydraulic conductivity measured over time following introduction ofdissolved CaCO3 for each column.

152 Jin suk O et al. / Journal of Contaminant Hydrology 103 (2009) 145–156

very similar among the columns, suggesting that thedifference in precipitation among the columns is reflectedmainly in the location of the precipitates (Fig. 5) rather thanthe total amounts of precipitates in the respective columns.

Hydraulic conductivity was measured over time using themanometers connected to the influent and effluent lines ofthe columns. The periodic escape of gases in the effluent linehindered accurate hydraulic head measurements, providingvariations and uncertainties in the calculations, and thus adegree of scatter is evident in Fig. 6. The decrease in hydraulicconductivity following addition of dissolved CaCO3 wasattributed to the accumulation of precipitates. The hydraulicconductivity of Connelly, Gotthart-Maier, and Peerless ironshad similar trends and declined by approximately one orderof magnitude by 400 to 600 PV (Fig. 6). ISPAT iron showed amuch faster decrease in hydraulic conductivity, as great astwo orders of magnitude, by 200 PV. After 200 PV, thehydraulic head difference for the ISPAT iron column exceededthe measurable limits of the manometers, suggesting an evengreater decrease in hydraulic conductivity after that period.Because the average hydraulic conductivity in the directiontransverse to layering is dominated by the layer of lowesthydraulic conductivity, the faster decrease in hydraulicconductivity for ISPAT iron is consistent with the greaterconcentration of precipitates close to the influent end.

2.3. Summary of experimental results

In summary, the cis-DCE profiles and geochemical trendsobserved for each column were consistent with the ironcorrosion rates, indicating that iron corrosion rate is adetermining factor for the amount of carbonate precipitatesthat accumulate at a specific location and thus the geochem-ical changes over time. Although there are relatively smalldifferences in corrosion rate and thus relatively smalldifferences in the behavior of the various profiles over timeamong Connelly, Gotthart-Maier, and Peerless irons, ISPATiron shows distinct features in terms of migration of cis-DCEand other geochemical profiles. Thus, the data appear tosupport the hypothesis that iron materials having higherinitial corrosion rates accumulate secondary precipitatesfaster and thus experience faster passivation, particularly inthe region close to the influent end. It should also be notedthat the differences in distribution of the precipitates alsosignificantly affect the permeability of PRBs, with thematerials of higher corrosion rates having greater declinesin permeability due to preferential precipitation near theinfluent face.

3. Numerical simulation

3.1. Modeling approach

3.1.1. Reactive transport modelNumerical simulations were conducted as a further test of

the initial hypothesis and as a means of extrapolating theexperimental observations to longer times. As indicated byFig. 2, because of the changing degradation profiles over time,the entire data set for cis-DCE degradation in a particularcolumn cannot be represented by a single kinetic expression.Since degradation by iron is generally considered to be a first-

order kinetic process, it is proposed that the changing cis-DCEprofiles over time reflect a varying first-order rate constantalong the length of the column, caused by the accumulation ofcarbonate precipitates, rather than a varying kinetic expres-sion over time. Thus accurate simulation of the experimentalresults requires a model that allows the rate constant to varyin space and time, depending upon the quantity and identityof accumulated secondary minerals.

Although previous studies attempted to account forreactivity change of iron due to dissolution of iron andchanges in porosity (Mayer et al., 2001; Morrison, 2003; Liet al., 2005, 2006), the study of Jeen et al. (2007a) was the firstmodeling attempt to directly link the accumulation ofsecondary minerals to the reactivity of iron. Jeen et al.(2007a) incorporated the decreasing reactivity of iron due tomineral precipitation into a multi-component reactive trans-port model MIN3P (Mayer et al., 2002), by updating thesurface area of the iron in the kinetic formulations, based onan empirical relationship between secondary mineral volumefraction and the surface area of the iron:

S x; tð Þ = S0exp −∑iαiφi x; tð Þ

� �ð1Þ

where S(x,t) is the reactive surface area of iron at a specificlocation along the flow path and time (m2 iron L−1 bulk), S0is the initial reactive surface area of the iron (m2 iron L−1

bulk), αi is the proportionality constant for mineral phase i,which represents the extent to which mineral phase icontributes to the reactivity loss of the iron, and φi(x,t) isthe volume fraction of mineral phase i at a specific locationand time (–).

The essence of the modified MIN3P (Jeen et al., 2007a) isthat rate constants are changed by updating the reactivesurface area along the flow path at different times usingEq. (1). In Eq. (1), the surface area of iron is the mathematicalrepresentation of the reaction potential of iron at a certaintime, though it does not imply a particular mechanism ofpassivation. It is convenient to express the reaction potentialof iron as the reactive surface area rather than havingmultiplerelationships between mineral precipitation and particularreactions, because the reactive surface area can affectreactivity toward various reactions simultaneously.

In this study, the model of Jeen et al. (2007a) was appliedto the experimental data. To represent the observed geo-chemical changes in the column systems, cis-DCE degrada-tion, iron corrosion, and secondary mineral precipitation (seeTable S4 in Jeen et al., 2007a, for reaction stoichiometries andequilibrium constants) were considered to be the importantchemical reactions. Ten aqueous components (Ca2+, Cl−, CO3

2−,Fe2+, H+, H2(aq), cis-DCE, vinyl chloride (VC), ethene, and H2O)were included in the chemical reactions. A total of 12 aqueouscomplexes (see Table S1 in Jeen et al., 2007a) were alsoincluded for appropriate determination of mineral solubili-ties. The rate for cis-DCE degradation is expressed as:

d cis‐DCE½ �dt

= −kSA–cis�DCE–Fe0 � S cis‐DCE�½ ð2Þ

where kSA–cis-DCE–Fe0 is the first-order rate constant for cis-DCEdegradation normalized to the iron surface area (L H2O m−2

Table 3Reaction rate constants for cis-DCE degradation and iron corrosion reactions, the initial surface area of the irons, the effective rate constants for secondary mineralprecipitation, and the proportionality constants for aragonite and Fe2(OH)2CO3(s)

Parameter Connelly Gotthart-Maier Peerless ISPAT

Normalized cis-DCE degradation rate constant −6.65 −6.61 −6.63 −7.58log kSA–cis-DCE–Fe0 (L H2O m−2 iron s−1)Normalized iron corrosion rate constant a −9.83 −9.41 −9.43 −8.41log kSA–H2O–Fe0 (mol m−2 iron s−1) (−10.53) (−10.01) (−10.03) (−9.63)Initial reactive surface area b 4.48×103 1.80×103 1.92×103 1.45×103

S0 (m2 iron L−1 bulk)kobs

c (s−1) 2.14×10−3 8.82×10−4 7.82×10−4 5.77×10−5

k0–H2O–Fe0d (mol L−1 bulk s−1) 6.63×10−7 7.00×10−7 7.13×10−7 5.64×10−6

Rate constant for the mineral dissolution CaCO3(s) (aragonite) −7.44log keff (mol L−1 H2O s−1) Fe2(OH)2CO3(s) −10.89

Fe(OH)2(am) −8.68Proportionality constant for aragonite, α1 90.0Proportionality constant for Fe2(OH)2CO3(s), α2 2.0

a Initiated from the measured gas generation rates, and was further adjusted to reproduce the best simulation results. The values in parentheses represent themaximum corrosion rate calculated from the measured rates of gas generation.

b Measured using Brunauer–Emmett–Teller (BET) analyses.c Multiplication of kSA–cis-DCE–Fe0 and the initial reactive surface area.d Multiplication of kSA–H2O–Fe0 and the initial reactive surface area.

Table 4Input parameters used in the simulations

Parameter Connelly Gotthart-Maier

Peerless ISPAT

Column length (m) 0.50Fe0 volume fraction (–) 0.54 0.50 0.43 0.34Porosity (–) 0.46 0.50 0.57 0.66Hydraulic conductivity (m s−1) 6.57×10−5 7.10×10−5 7.27×10−5 6.96×10−5

Diffusion coefficient (m2 s−1) 1.5×10−9

Longitudinal dispersivity (m) 9.9×10−4

Running time (days) 265 260 226 217Flow rate (Darcy flux) (m s−1) 5.83×10−6

pH 7.35Ca2+ (mol L−1) 3.0×10−3

Total CO32− (mol L−1) 7.50×10−3

cis-DCE (mol L−1) 1.03×10−4

153Jin suk O et al. / Journal of Contaminant Hydrology 103 (2009) 145–156

iron s−1) and [cis-DCE] is the concentration of cis-DCE (mol L−1

H2O). The iron corrosion rate is expressed in the form:

RH2O–Fe0 = −max kSA–H2O–Fe

0 � S 1−IAPH2O–Fe

0

KH2O–Fe0

!" #;0

( )ð3Þ

where kSA–H2O–Fe0 is the rate constant of iron corrosionnormalized to iron surface area (mol m−2 iron s−1), IAPH2O–Fe0

is the ion activity product, and KH2O–Fe0 is the equilibriumconstant. The rate expression for secondarymineral precipita-tion is given by:

Rmi = −keff ;i 1−

IAPmiKmi

� �ð4Þ

where keff,i is the effective rate constant for the dissolution ofmineral phase i (mol L−1 H2O s−1), IAPim is the ion activityproduct, and Ki

m is the corresponding equilibrium constant. Inaddition, the model updates the changes in porosity andhydraulic conductivity, as secondary minerals precipitate andiron dissolves. Further details of themodeling approach can befound in Jeen et al. (2007a).

3.1.2. Model parametersConstraints for model parameters are similar to those

described in Jeen et al. (2007a). The initial cis-DCE rateconstants were taken from the fit to the initial cis-DCE profilesfor each column. The initial first-order rate constant forConnelly iron was slightly higher than those for Gotthart-Maier and Peerless (kobs in Table 3), but the rate constantsnormalized to the initial reactive surface area were similar forall three irons (log kSA–cis-DCE–Fe0 in Table 3). The ISPAT ironhad the lowest cis-DCE degradation rate constant (Table 3).

The initial rates for iron corrosion by water for each column(log kSA–H2O–Fe0 in Table 3) were based on the maximumhydrogen gas generation rates, measured in the laboratory. Thevalues were then further adjusted to reproduce the bestsimulation fits. The initial corrosion rates used in the simula-tions were higher than the measured values; however, therelative differences between the columns remained similar.

The initial iron corrosion rate used in the simulations was thelowest for Connelly iron, Gotthart-Maier and Peerless ironswere similar and intermediate, and ISPAT iron had the highestvalue (Table 3).

The effective rate constants for the dissolution of eachmineral (Table 3) were taken from the values for one column(column C) of Jeen et al. (2007a), of which the average grainsize was similar to that of the materials used in this study. Theproportionality constants for aragonite and Fe2(OH)2CO3(s)(i.e., α1 and α2 in Table 3) were determined by a trial-and-error method until the best fits for the entire profiles overtime for all columns (i.e., the profiles of cis-DCE, alkalinity,and pH for all columns) were obtained.

The experimental data suggested that the differences inobserved geochemical trends in each column should berepresented by the differences in iron reactivities towardcis-DCE degradation and corrosion rates, keeping the passiva-tion mechanism (i.e., carbonate precipitation) for differentiron materials the same. This indicates that the modelparameters related to carbonate precipitation should be thesame for all columns, whereas the initial cis-DCE degradationand iron corrosion rate constants should represent thecharacteristics of each column. Thus, once a set of parameters

Fig. 7. The predicted cis-DCE breakthrough curves for each material at theeffluent surface of the PRB over a period of 40 years.

154 Jin suk O et al. / Journal of Contaminant Hydrology 103 (2009) 145–156

relative to carbonate mineral precipitation was determined,they were not calibrated further for each column (Table 3).Spatial discretization, physical parameters, and initial andboundary conditions are similar to those described in Jeenet al. (2007a), with the specific values used in this study listedin Table 4.

3.2. Results and discussion for the numerical simulation

3.2.1. Simulation of the column resultsFig. 2 includes the simulated cis-DCE profiles correspond-

ingwith themeasured data. Consistent with the experimentalresults, the trends in simulation results for Connelly,Gotthart-Maier, and Peerless irons are similar. ISPAT differsin that the initial degradation rate is significantly lower, andalmost complete reactivity loss is observed, initiating fromthe region close to the influent end, because of greateraccumulation of carbonates in that region. The initialdegradation rate for ISPAT is generally maintained wherethere is no significant accumulation of carbonates, i.e., theregion close to the effluent end.

The simulated cis-DCE profiles do not match themeasuredprofiles precisely, however, noting that there was no calibra-tion of the model parameters relative to carbonate mineralprecipitation, the simulation results gave a good representa-tion of the major trends in the data. More importantly, thesignificant difference in the pattern of passivation is success-fully represented. For example, consistent with the laboratoryobservations, for Connelly iron, there is no expanding (highlypassivating) zone where there appears to be little degrada-tion. On the other hand, the expanding zone adjacent to theinfluent end for ISPAT iron, resulting from the higher ironcorrosion rate (Table 3) and thus greater precipitate forma-tion, is reflected in the simulation results. Consistent with themeasured data, the simulations also show the leading edge ofthe degradation profiles to be somewhat advanced inGotthart-Maier relative to Connelly.

The matching of the alkalinity profiles between themeasured and simulated results was also reasonably good(Fig. 3). The differences in migration of the alkalinity profilesamong Connelly, Gotthart-Maier, and Peerless irons were lessobvious than for the cis-DCE profiles, because the alkalinityprofiles are governed only by the iron corrosion rate, whilethe cis-DCE profiles are affected by both the cis-DCEdegradation rate and iron corrosion rate. ISPAT iron has amuch higher corrosion rate compared to the other irons. As aresult, the simulated alkalinity profiles for ISPAT are muchsteeper than for the other iron materials (Fig. 3), indicating ahigher alkalinity removal rate (higher carbonate precipitationrate) at early time, consistent with the laboratory results.However, the gradual increase in alkalinity from 15 cm fromthe influent end toward the effluent end of the ISPAT columnon days 7 and 42 could not be reproduced by the simulation(Fig. 3d). The simulated pH values in that regionwere not highenough (highest pH values of 10.78 vs. 11.17 for the simulatedand measured values, respectively). A possible reason for thelower simulated pH is that pH is controlled by precipitation ofa small amount of Fe(OH)2(am), a representative of iron(hydr)oxide, in that region in the simulation. Over time, boththe measured and simulated alkalinity profiles for ISPAT irondo not advance as far toward the effluent end compared to the

other irons for similar time periods. The simulated pH profilesdo not match the measured profiles as well as those of cis-DCE and alkalinity, but the general trends are consistent withthose of the measured pH values (Fig. 4).

As expected from the simulated alkalinity profiles, thesimulated distribution of aragonite and Fe2(OH)2CO3(s) (datanot shown) were similar along the Connelly, Gotthart-Maier,and Peerless columns, while ISPAT iron had a greateraccumulation of aragonite and Fe2(OH)2CO3(s) near theinfluent end, causing greater passivation of the iron in thatregion, as indicated by the cis-DCE profiles (Fig. 2d).

It is important to note that except for the initial cis-DCErate constants and iron corrosion rates, all other modelparameters are the same for all columns (Table 3). Thus, thedifferences in the simulated performance of the columnswere due solely to the differences in the initial cis-DCE rateconstants, which are intrinsic characteristics of each materialtoward degradation of cis-DCE, and to the differences in ironcorrosion rates, which govern the carbonate precipitation andthus passivation of iron materials over time. That is, changingiron corrosion rate resulted in changes in simulated profilebehavior that were consistent with the data and consistentwith our original hypothesis.

3.2.2. Long-term predictionTo illustrate the effects of different initial corrosion rates

on the performance of a PRB under typical groundwaterconditions, further simulations were performed to predict thedifferences in performance over longer periods of time fordifferent iron materials. The longevities of each iron materialwere simulated under the following conditions. The ground-water velocity was assumed to be 0.1 m d−1, and the cis-DCEand CaCO3 concentrations were taken to be the same as in thecolumn experiments (10 mg L−1 cis-DCE+300 mg L−1 CaCO3).The pH of the inflowing water was assumed to be 7.0, and theporosity and hydraulic conductivity of the PRB were assumedto be 0.5 and 6.57×10−5 m s−1, respectively. The thickness ofthe PRB was 0.5 m and the period of operation was 40 years.For the four cases tested, the characteristics of the ironmaterials, such as the initial cis-DCE degradation rates andiron corrosion rates, were selected from the values represen-tative of Connelly, Gotthart-Maier, Peerless, and ISPAT irons,as used in the simulations of the column experiments. Allother parameters were taken to be the same for all cases, as inthe simulations for the column experiments.

155Jin suk O et al. / Journal of Contaminant Hydrology 103 (2009) 145–156

Fig. 7 shows the predicted breakthrough curves for cis-DCE at the effluent face of the PRB for each iron material.Under the imposed conditions, cis-DCE begins to break-through the PRB after about 10, 15, 16 and 23 years ofoperation, for ISPAT, Peerless, Gotthart-Maier, and Connellyirons, respectively. ISPAT iron, which has the highest corro-sion rate and the lowest cis-DCE degradation rate (kobs inTable 3), shows the earliest breakthrough and thus thepoorest performance. On the other hand, Connelly iron,which has the lowest corrosion rate and the highest cis-DCEdegradation rate (kobs in Table 3), shows the latest break-through. Gotthart-Maier and Peerless irons have similarcorrosion rates, but the slightly higher cis-DCE degradationrate for Gotthart-Maier iron (kobs in Table 3) results in slightlylater breakthrough than Peerless iron. The steepness of thebreakthrough curves is also dependent on the corrosion rate.That is, the materials with higher corrosion rates have steepercurves than those of lower rates (Fig. 7). Depending on theincoming cis-DCE concentration and the remediation goal(e.g., maximum contaminant level (MCL)), this could haveimportant consequences. For example, if theMCL correspondsto a C/C0 value of 0.1, the Connelly iron would performadequately for a period of more than 33 years, while ISPATiron would fail at about 13 years.

Predictions of porosity reduction are shown in Fig. 8 for a5-year (a) and 40-year (b) period of operation. The cases withhigher corrosion rates showgreater reduction in porosity nearthe influent face of the PRB at 5 years because of greateraccumulation of carbonate minerals in that region, while thecases of lower corrosion rates show a greater spread inporosity losses (Fig. 8a). Over time, the reduction in porosity isspread further into the barrier for all cases, and is simply

Fig. 8. The predicted porosity loss along the length of the PRB for fourdifferent irons after (a) 5 years and (b) 40 years.

dependent on the initial corrosion rates (Fig. 8b), indicatingthat lower corrosion rates lead to better performance in termsof permeability. It is also noted that no further porosity lossoccurs once the iron is passivated.

The predicted longevities for each material may not bedirectly applicable for field situations because of variability ofthe model parameters and other non-accounted factors. Thesimulations account for only the passivation of iron caused bycarbonate precipitation in the one-dimensional case. Thus thesimulations should be regarded as guidance rather thanaccurate prediction of longevity for each material. Also, itshould be noted that ISPAT iron presents an unusual material,having a high corrosion rate yet low cis-DCE degradation rate.Commonly, it is expected that an iron material having a highcorrosion rate may also have a high degradation rate for achlorinated organic compound. Thus, if an iron material had acorrosion rate similar to ISPAT but also a high cis-DCEdegradation rate, the breakthrough time might be longerthan indicated for ISPAT. For instance, for a hypotheticalmaterial having the same corrosion rate as ISPAT but the samecis-DCE degradation rate as Connelly, the predicted cis-DCEbreakthrough time is about 15 years (Fig. 7), while thepredicted porosity loss is similar to the result for ISPAT.Nonetheless, the predictions clearly show how iron materialshaving different corrosion rates affect the behavior of cis-DCEdegradation and the changes in porosity. The simulations thusprovide valuable insight for selecting ironmaterials to be usedin construction of PRBs. For this study, cis-DCEwas selected asa potential determining chlorinated compound for thelifetime of a barrier. Because the effect of iron passivationresulting from mineral precipitation can be simultaneouslyapplied to each dechlorination reaction in the current model,the modeling approach used in this study may be similarlyapplied to other situations, where cis-DCE is an intermediateproduct from TCE or PCE degradation, if the productdistributions and rate constants for each dechlorinationreaction are known.

4. Conclusions

The previous modeling study of Jeen et al. (2007a)suggested that iron material having a high corrosion ratemay not be more beneficial than material having a lowercorrosion rate in terms of long-term performance because ofgreater overall accumulation of secondary precipitates. Theresults of both the laboratory experiments and numericalsimulations generally support this hypothesis in that ironmaterial with a higher corrosion rate has greater accumula-tion of precipitates, particularly near the influent end,resulting in faster passivation of the iron.

The differences in the patterns of accumulation ofprecipitates resulted in a significant difference in the patternof passivation. Whereas the ISPAT iron shows a highlypassivated zone adjacent to the influent end, passivation ofthe Connelly iron is reflected in a gradual decline in slope ofthe degradation profile, starting from the influent end, withminor evidence of a highly passivated zone. In the long-termsimulations, these patterns resulted in differences in onset ofcis-DCE breakthrough and relative steepness of the break-through curves, which affected significantly the estimatedlongevities of the PRB.

156 Jin suk O et al. / Journal of Contaminant Hydrology 103 (2009) 145–156

The patterns of accumulation of precipitates also affectedthe pattern of permeability changes. The ISPAT iron, havingthe most intensive precipitation near the influent end,showed a much faster decrease in porosity in that regioncompared to the other irons. Thus, iron materials with highcorrosion rates may experience local clogging or bypass ofgroundwater flow at some future time.

Overall, iron corrosion rates in the presence of dissolvedinorganics should be considered as an important factor at thedesign stage when considering the long-term performance ofa PRB. It is suggested that iron material having a highcorrosion rate is not beneficial in the presence of a highconcentration of dissolved CaCO3 because of a faster migra-tion of organic profiles and greater porosity loss near theinfluent face.

Acknowledgments

Funding for this research was provided through theNSERC/DuPont/EnviroMetal Industrial Research Chair heldby R.W. Gillham. We thank Wayne Noble for the technicalassistance in the laboratory.

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