Environ. Sci. Technol. 1996, 30, 3016-3024
Reactive Solute Transport in an Acidic Stream: Experimental pH Increase and Simulation of Controls on pH, Aluminum, and Iron ROBERT E. BROSHEARS,* ROBERT L. RUNKEL, BRIANT A. KIMBALL, DIANE M. MCKNIGHT, AND KENNETH E. BENCALA U.S. Geological Survey, MS 415, Denver Federal Center, Denver, Colorado 80225
Solute transport simulations quantitatively constrained hydrologic and geochemical hypotheses about field observations of a pH modification in an acid mine drainage stream. Carbonate chemistry, the formation of solid phases, and buffering interactions with the stream bed were important factors in explaining the behavior of pH, aluminum, and iron. The precipitation of microcrystalline gibbsite accounted for the behavior of aluminum; precipitation of Fe(OH)3 explained the general pattern of iron solubility. The dynamic experiment revealed limitations on assumptions that reactions were controlled only by equilibrium chemistry. Temporal variation in relative rates of photoreduction and oxidation influenced iron behavior. Kinetic limitations on ferrous iron oxidation and hydrous oxide precipitation and the effects of these limitations on field filtration were evident. Kinetic restraints also characterized interaction between the water column and the stream bed, including sorption and desorption of protons from iron oxides at the sediment-water interface and post-injection dissolution of the precipitated aluminum solid phase.
Introduction In their review of hydrochemical modeling of metals, Dzombak and Ali (1) emphasized the limitations of advancing detailed mechanistic models without interpretation of similarly detailed field data. They also called attention to the relative lack of geochemical sophistication in most simulation tools. In this paper, we interpret field data from a pH modification experiment with a model simulating the transient behavior of pH, aluminum, iron, and the carbonate system. The simulations accounted for physical transport and geochemical processes in the water column and at the sediment-water interface. Our objective * Corresponding author e-mail address:
[email protected].
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was to increase understanding of these processes and to develop simulation tools that will be effective in guiding remediation activities in watersheds affected by acid mine drainage. Field studies of the transport and fate of metals in acid mine waters have been conducted by several workers. Amacher et al. (2) concluded that dilution by inflows, precipitation of iron and aluminum hydroxides, and sorption of copper to iron precipitates controlled metal concentration in two mountain streams affected by acid mine drainage. Brown and Hosseinnipour (3) linked several watershed, geochemical, and solute transport codes to simulate the observed behavior of copper mobilized from mine wastes. Vezina and Cornett (4) spiked limnocorrals with radiolabeled iron to determine the partitioning of iron among dissolved, non-settling colloidal, and settleable particulate phases. Fuller and Davis (5) showed that photosynthetically induced changes in pH caused diel variation in arsenic concentration in stream water. The importance of uptake by periphyton and sorption to sediments on the mobility of copper in a stream was demonstrated in field experiments by Kuwabara et al. (6). Studies of natural or experimentally induced perturbations of pH have been particularly valuable in furthering the understanding of metal dynamics in streams. Chapman (7) used a geochemical speciation code coupled with a physical transport model to simulate the responses of aluminum, copper, iron, and zinc to an experimental manipulation of pH in a stream. Elevation of instream pH from 3 to 10 was accompanied by formation of precipitates and base-neutralizing surface reactions. McKnight and Bencala (8) and Bencala et al. (9) described the injection of sulfuric acid into a stream and attributed the resultant increase in iron concentration to dissolution enhanced by photoreduction. In analyzing their experiment, Runkel et al. (10) explained the dynamic iron response with a transport model using equilibrium-based precipitation and dissolution. The results in this paper were based on an experiment conducted in a mountain stream receiving acid mine drainage. A base injection raised pH from a background value of 3.5 to a maximum value of 5.8. To analyze the instream response, we developed a reactive solute transport model. The model simulated the physical processes of advection and dispersion, mixing and transient storage, and settling of particulate phases. Simulated chemical processes included gas exchange, precipitation-dissolution, sorption-desorption, and photoreduction-oxidation under equilibrium or kinetically restrained conditions. We used the model to evaluate concepts for major controls on pH, iron, and aluminum chemistry. For pH, these controls included the carbonate system, the formation of solid phases, and interactions with the stream bed. For aluminum and iron, pH-dependent formation and subsequent settling of metal hydroxide solids were the major controlling factors. For iron, photoreduction and oxidation also played key roles. The importance of kinetic limitations on the attainment of equilibrium between dissolved and solid phases and between the water column and the stream bed also was explored. S0013-936X(96)00055-7 This article not subject to U.S. copyright. Published 1996 by the American Chemical Society.
TABLE 1
Dissolved Constituents in St. Kevin Gulch, 10 m Upstream from Injection Site, August 25, 1988, prior to pH modification Experimenta calcium magnesium sodium chloride sulfate
386 248 112 83 1330
aluminum cadmium copper lead zinc
114 0.6 3 0.2 160
silica ferrous iron ferric iron manganese pH
300 9 11 106 3.5
a All concentrations are in micromoles per liter; pH is in standard units.
Methods Site Description. The study area was a 498-m reach of St. Kevin Gulch, a small tributary of Tennessee Creek in the headwaters of the Upper Arkansas River near Leadville, CO. The stream arises on Galena Mountain at an elevation of about 3600 m and descends about 600 m in 5 km through a forested watershed of about 10 km2. In 1988, there was little active mining in the basin, but abandoned mines and mine dumps remained from excavations begun in the last century. A major source of metal loading was seepage from a mine dump located about 850 m upstream from the study reach. Ground water discharge accounted for most stream flow under the low-flow conditions of the experiment. For 3 days prior to the pH modification experiment, a solution of lithium chloride was injected at a constant rate into St. Kevin Gulch approximately 400 m upstream from the mine dump. Plateau concentrations of lithium had developed throughout the study reach, and the dilution of this conservative salt was used to calculate the flow at each sampling location. Water samples were collected throughout the experiment immediately upstream from the experimental reach. A representative analysis from these samples is shown in Table 1. pH Modification Experiment. On August 25, 1988, instream pH in St. Kevin Gulch was increased in step wise fashion from 3.5 to 5.8 by injecting a concentrated solution of sodium carbonate. A sodium chloride solution was injected simultaneously to enhance the sodium pulse, which was used as a second conservative tracer for definition of subreach travel times and transient storage parameters. The injection began at 9.3 h (about 9:20 a.m.) and continued at a constant rate until 11.9 h. An increased rate of injection was sustained until 14.9 h, when the injection was stopped. As the pulse of increased pH moved downstream, the response of major ions and trace metals was documented by analyzing water samples collected at sites located 24, 70, 251, and 498 m from the injection site. We refer to these sites by their downstream distance from the injection. The injection point was 1306 m downstream from the common reference location established by Broshears et al. (11) and cited in other studies of St. Kevin Gulch (12-14). In describing the transport and fate of aluminum and iron, we distinguish two phases. The “dissolved” phase remains in water passing through a 0.1-µm filter; the “particulate” phase is the concentration difference between an unfiltered sample and a filtered sample. The particulate phase may include aggregates of particles individually smaller than the pore size. The particulate phase may also include constituents that have sorbed to these aggregates. The “total” concentration is the concentration in the unfiltered sample. Samples were filtered and preserved immediately upon collection. Metal concentrations were
determined by inductively coupled argon plasma atomic emission spectroscopy on samples acidified to less than pH 2.0 with ultrapure nitric acid. Concentrations of sulfate and other anions were determined by ion chromatography. Reactive Solute Transport Model. The primary interpretive tool was a reactive solute transport model consisting of an advection-dispersion-transient storage module coupled with a geochemical speciation module. The solute transport module was developed by Runkel and Broshears (15) from earlier work by Bencala and Walters (16). This code was based on two coupled equations. A onedimensional advection-dispersion equation for the stream channel included terms to account for lateral inflow and transient storage; a second equation accounted for the storage zone:
qL ∂C ∂C Q ∂C 1 ∂ DA + (CL - C) + R(CS - C) )+ ∂t A ∂x A∂x ∂x A
(
)
(1) dCS A ) -R (CS - C) dt AS
(2)
where C is the solute concentration in the stream (ML-3); t is the time (T); Q is the volumetric flow rate (L3 T-1); A is the cross-sectional area of the stream (L2); x is the distance (L); D is the dispersion coefficient (L2 T-1); qL is the volumetric inflow rate per unit stream length (L3 T-1 L-1); CL is the solute concentration in lateral inflow (ML-3); R is the stream-storage exchange coefficient (T-1); CS is the solute concentration in the storage zone (ML-3); AS is the cross-sectional area of the storage zone (L2). Transient storage is a useful empirical representation of a “dead zone” storage phenomenon that can be important in small streams. Additional details of the transient storage approach have been described by Bencala and Walters (16). The importance of biogeochemical processes in zones of transient storage has been demonstrated for nitrate by Kim et al. (17). The geochemical speciation module was based on MINTEQA2 (18). Given analytical concentrations of chemical components, the code computed the distribution of chemical species at thermodynamic equilibrium. These computations accounted for gas exchange with the atmosphere, formation and dissociation of complexes, precipitation and dissolution of solid phases, and sorptiondesorption reactions. Precipitated and sorbed solid phases occurred either in the water column or on the stream bed. Solid phases in the water column were subject to settling at a user-specified settling velocity; resuspension was not modeled for our low-flow conditions. Recent developments in the model allowed specification of kinetic restraints on the attainment of equilibrium. For a more complete description of the reactive solute transport code, the reader is referred to Runkel et al. (19). Simulations were limited to the following components: aluminum, ferrous iron, ferric iron, carbonate, sulfate, and excess hydrogen. Ionic strength was fixed at 0.005. Static simulations with MINTEQA2 using all solutes (Table 1) demonstrated that interactions between these components alone defined the solubility of aluminum and iron within a pH range of 3.5-6.0. Initial and Boundary Conditions. Upstream boundary concentrations for aluminum, iron, and sulfate were measured at a site 10 m upstream from the injection (Table
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TABLE 2
TABLE 4
Upstream Boundary and Lateral Inflow Concentrations for Simulated Components during pH Modification Experiment
Variable Upstream Boundary Concentration for Carbonate and Sodium during pH Modification Experiment
component
upstream boundary concn (µM)
lateral inflow concn (µM)
excess hydrogen aluminum ferrous iron ferric iron sulfate carbonate
352 114 16 4 1330 time variablea
156 3 7.2 1.8 875 12
a
See Table 4.
TABLE 3
Simulated Properties of Hydrous Iron Oxides on Stream Bed mass per volume of overlying water subreach 1 (0-24 m) subreach 2 (24-70 m) subreach 3 (70-251 m) subreach 4 (251-498 m) initial excess hydrogen on stream bed subreach 1 (0-24 m) subreach 2 (24-70 m) subreach 3 (70-251 m) subreach 4 (251-498 m) initial sulfate on stream bed subreach 1 (0-24 m) subreach 2 (24-70 m) subreach 3 (70-251 m) subreach 4 (251-498 m) density of high-affinity sites density of low-affinity sites specific surface area
0.2 g/L 0.2 g/L 4.0 g/L 8.0 g/L 459 µM 459 µM 9180 µM 18400 µM 219 µM 219 µM 4380 µM 8760 µM 5.62 × 10-5 mol/g 2.25 × 10-3 mol/g 600 m2/g
2). Lateral inflow concentrations were measured at two sites, and the average value was used for all subreaches. The model calculated pH from the excess hydrogen concentration, also known as the proton condition (20). Additional details of this approach for modeling pH were described by Morel (21) and Morel and Hering (22). For boundary and lateral inflow concentrations, the excess hydrogen concentration was established by executing MINTEQA2 in static mode with pH fixed at the fieldmeasured value. A static simulation using MINTEQA2 also established initial conditions for the stream bed (Table 3); prior to the pH perturbation, most of the excess hydrogen concentration was calculated to reside on the stream bed. Inclusion of these protons on the bed conferred a substantial buffering capacity to the system, which became evident during the interval of increased carbonate injection. The ambient carbonate concentration was established in the static MINTEQA2 simulation, which included the assumption of equilibrium with CO2 in the atmosphere. The carbonate upstream boundary concentration changed step wise during the injection period (Table 4). Molar changes in total carbonate values at each step were calculated as half the difference between the molar increase in sodium concentration over background (due to both NaCl and Na2CO3 injections) and the molar increase in chloride concentration (due to the NaCl injection alone). Sunlight-driven variation in relative rates of iron photoreduction and oxidation causes a diel pattern in iron speciation in St. Kevin Gulch (12, 14, 23) and other iron-
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beginning of time carbonate upstream sodium upstream interval (clock hours) boundary concn (µM) boundary concn (µM) 8.0 9.3 11.9 14.9
12 140 370 12
120 700 1250 120
rich mountain streams (8, 24). On the day before the experiment, iron speciation was measured in the experimental reach for an 18-h period. The percentage of dissolved iron that was ferrous iron varied from 70% to more than 90% during midday hours (14). In our simulations, ferrous iron was a constant 80% of the dissolved iron in the water column. Consequences of this assumption are explored below. Solid-Phase Controls on Aluminum and Iron Solubility. The formation constant for amorphous Al(OH)3 has been reported at 10-10.8 (25); the formation constants for more crystalline forms of Al(OH)3 (gibbsite) range from 10-9.35 to 10-8.11 (26). The formation constant of Al(OH)3 in these simulations was specified as
{H+}3
(3) ) 10-9.82 {Al3+} This formation constant was intermediate between reported values for amorphous Al(OH)3 and microcrystalline gibbsite (25-28) and represented a continuum of Al(OH)3 phases likely to control aluminum solubility in diluted acid mine drainage (29). Literature values for the formation constant of Fe(OH)3 have varied from 10-8 to 10-0 (30, 31), but most amorphous to microcrystalline values are in the range of 10-5 to 10-3 (25). For this simulation the formation constant for Fe(OH)3 was specified as KF )
{H+}3
(4) ) 10-3.65 {Fe3+} This formation constant was determined in an experiment addressing the solubility of similar iron hydroxide solids in the Snake River, another mountain stream in Colorado (32). Interactions between the Water Column and the Stream Bed. Buffering reactions involving the stream bed may affect instream profiles of pH. This hypothesis was tested by including hydrous iron oxides as a stream bed component within the simulation. Properties of these hydrous iron oxides (Table 3) were adopted from Dzombak and Morel (33), who recommended values for these properties in their critical review of published data for metal sorption on hydrous iron oxides. Interactions of metals and sulfate with the stream bed were characterized by surface-complexation reactions embodied in a double-layer submodel (18, 33). Smith et al. (34) and Smith (35) applied this submodel within MINTEQA2 in interpreting the behavior of copper and zinc during batch sorption experiments using water and sediments from St. Kevin Gulch. In our simulations, the mass of hydrous iron oxide on the stream bed in equilibrium with the water column was varied in each reach to obtain a visually optimum fit between observed and simulated values. Although the mass of sorbent on the stream bed was essentially a fitted parameter, KF )
TABLE 5
Subreach Variable Stream Geometry and Physical Transport Parameters for Simulation of Reactive Solute Transport during pH Modification Experiment subreach boundaries (m)
discharge at downstream end of reach (m3/s)
stream cross-sectional area (m2)
cumulative travel time from injection (min)
mean stream width (m)
storage zone cross-sectional area (m2)
stream-storage exchange coeff (s-1)
0-24 24-70 70-251 251-498
1.23 × 10-2 1.25 × 10-2 1.32 × 10-2 1.32 × 10-2
0.185 0.243 0.149 0.130
6 21 56 97
1.0 1.0 2.0 10.0
0.15 0.15 0.35 0.05
1.0 × 10-4 1.0 × 10-4 1.0 × 10-4 0.3 × 10-4
physically realistic values were used. The model required as input the mass of sorbent per liter of overlying water. Stream cross-sectional areas for each subreach (Table 5) provided values of water column volume per unit length of stream. Calculation of the sorbent mass per unit length of stream required an estimate of stream width and the dry density, porosity, and depth of interactive bed sorbent. The dry density of hydrous ferric oxide has been estimated at 3.5 g/cm3 (33). Porosity of bed material at the sedimentwater interface is variable, but ranges of 70-90% are typical (36). The depth of interactive sediments is difficult to quantify. For these simulations, we considered interactive bed depths of 0.1-0.5 mm. Using these values for stream geometry and the dry density of hydrous ferric oxide as well as these ranges for porosity and interactive bed depth, the mass of sorbent per volume of overlying water was constrained within the range of 0.1-40 g/L, with the higher end of the range applying only to the more downstream subreaches. Initial concentrations of sulfate and excess hydrogen on the stream bed were established by static executions of MINTEQA2 using the double-layer routine (Table 3). Kinetic Restraints on Sorption-Desorption and Dissolution. For ground water systems, the assumption commonly is made that transport is slow relative to rates of chemical reactions, and thus solutes remain in geochemical equilibrium with respect to controlling solid phases. Transport velocities in streams commonly are too fast to permit the immediate establishment of equilibrium between solutes in the water column and the stream bed (1). Kinetic restraints may be due to slow rates of reaction relative to stream velocities or to the necessity for solutes in the water column to achieve physical contact with reactive surfaces on the bed. The latter restraint would be affected by the degree of vertical mixing in the water column and by the development of a stagnant boundary layer at the sediment-water interface. Mass transfer across such a boundary layer might be diffusion-limited. Bencala et al. (37) and Bencala (38) described the behavior of strontium injected into a stream in terms of a kinetically limited incremental approach toward equilibrium between strontium dissolved in the water column and strontium sorbed on the stream bed. We used a similar approach in our simulations. At each time step, we calculated the sorbed concentration that would result if all sorption reactions were allowed to proceed to equilibrium between the water column and the stream bed. We then allowed only a fractional closure of the difference between the current concentration and the equilibrium concentration during each time step of the simulation.
Results and Discussion Physical Transport. Sodium and lithium were assumed to behave conservatively in St. Kevin Gulch throughout the
FIGURE 1. Observed (diamonds) and simulated (solid lines) concentrations of sodium, a conservative tracer during the pH modification experiment.
range of pH in the experiment. Thus, these cations served as tracers in defining physical transport. The degree of dilution of the lithium tracer quantified flow at each sampling location. Injection of both sodium carbonate and sodium chloride sufficiently elevated instream concentration of sodium above background values such that a distinct concentration pulse delineated the injection period (Figure 1). The sequential arrival of the sodium pulse at each sampling site permitted definition of subreach travel times, while the asymmetry of the arriving shoulders and departing tails of the pulse allowed calibration of parameters of dispersion and transient storage (11, 16, 39). Physical transport parameters for the experiment are shown in Table 5. Instream flow ranged from 12.3 L/s at site 24 to 13.2 L/s at sites 251 and 498. Mean travel time between the injection site and site 24 was approximately 6 min. Mean travel time from the injection site to site 498 was about 97 min. Parameters of transient storage (Table 5) were within the ranges of those calibrated in earlier studies at St. Kevin Gulch and other mountain streams (11). Particle settling velocity was 2 × 10-5 m/s, which was consistent with a mean particle radius of about 2 µm. The dispersion coefficient was set at 0.05 m2/s for all subreaches. Observed Profiles of pH, Aluminum, and Iron. pH. Prior to the injection, background pH was 3.5. The time course of pH at the four sites during the experiment is shown in Figure 2a-d. The injection quickly resulted in a pH of 4.2 at site 24. An increased injection rate begun at 11.9 h eventually resulted in a pH of 5.8 at this site. At the three downstream sampling sites, the pH pulse was subdued relative to the upstream profile. At site 498, for example, pH never exceeded 4.5. Lateral inflow of low pH water could not account for the attenuation of the pH pulse. These observations suggested reactions that liberated protons as the perturbation was transported through the reach. Plausible reactions liberating protons included hydrolysis
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FIGURE 2. Observed profiles of pH and dissolved (open circles) and particulate (solid diamonds) concentrations of aluminum and iron during the pH modification experiment.
of aluminum and iron or desorption of protons from the stream bed. Aluminum. Background concentration of aluminum was spatially uniform at about 115 µM before the injection began. When pH increased to 4.2 at site 24, the aluminum concentration did not change (Figure 2e). As pH increased above 5.0, a decrease in dissolved aluminum was accompanied by an increase in particulate aluminum. These observations were consistent with the formation of a slowly settling precipitate during the injection. After the injection stopped, aluminum concentrations eventually returned to preinjection values (Figure 2e). However, for approximately 30 min after the injection ended, dissolved aluminum concentration at site 24 was higher than the background level. This post-injection spike in aluminum concentration indicated the recruitment of aluminum from a finite source. A flow-weighted integration of total aluminum concentration versus time at site 24 showed that 27 g of aluminum was removed from the water column along the first subreach during the injection interval (40). A similar integration during the post-injection aluminum spike showed that 28 g of aluminum was recruited back into the water column. The virtual mass balance indicated that the finite source of aluminum during the post-injection spike was the dissolution of freshly settled aluminum from the injection period. This observation was consistent with the summary by Norton et al. (41) of several instream acidification experiments in which dissolution of streambed Al(OH)3 was identified as the source of rapid increases in aluminum concentration in the water column. Similar to the situation for pH, the response of aluminum at the three downstream sampling sites was a subdued translation of the profile at site 24 (Figure 2f-h). The aluminum mass in the postinjection spike in dissolved aluminum increased at each successive downstream site. Iron. Before the injection, background concentration of dissolved iron declined gradually from 20 µM at site 24
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to 13 µM at site 498 (Figure 2i-l). Background particulate iron concentration was essentially unchanged at about 1 µM along the reach. These observations suggested that iron had precipitated at pH 3.5, but that aggregation of precipitates to a size larger than 0.1 µm required time comparable to the travel time through the reach (several tens of minutes). Iron-stained rocks throughout the experimental reach testified to the continuing settlement of iron solids from the water column. When pH increased to 4.2 at site 24, there was a slight decline in dissolved iron (to 18 µM) and an increase in particulate iron (to 2 µM). As pH increased to 5.8, dissolved iron decreased to 7 µM and particulate iron increased to 13 µM (Figure 2i). These observations were consistent with the formation of a very slowly settling iron hydroxide at higher pH. At pH 5.8, enhanced abiotic oxidation of ferrous iron (42) could result in a faster net rate of oxidation and subsequent precipitation of iron hydroxide, but the rate would still be slow relative to hydrologic transport times to the upstream sites. Total concentration of iron continued to decrease in the downstream direction throughout the experiment (Figures 2j-l), consistent with continuing oxidation of ferrous iron. The pulse of particulate iron was diminished with downstream distance. These observations were consistent with an increased rate of pH-dependent oxidation of ferrous iron and production of particulate ferric iron immediately downstream from the injection and the continued oxidation of ferrous iron and production and settling of particulate ferric iron during the travel interval to the downstream sites. Simulations of pH, Aluminum, and Iron. Figure 3 displays observed pH and dissolved concentrations of aluminum and iron with the results of simulations conducted under the conditions described in Tables 2-5. These simulations included carbonate chemistry, precipitation of Al(OH)3, oxidation of ferrous iron and precipitation of Fe(OH)3, and sorptive interactions with the stream bed.
FIGURE 3. Observed (open diamonds) and simulated (solid lines) pH and concentrations of dissolved aluminum and iron during the pH modification experiment.
These reactions were simulated both in the stream channel and in the storage zones. The stream bed was conceptualized as a surface of hydrous iron oxides undergoing doublelayer complexation reactions. Kinetic restraints were applied to all interactions between the water column and the stream bed, including sorption-desorption and the dissolution of mass settled to the stream bed during the interval of higher pH. Because iron oxidation state was not determined during the experiment, kinetic restraints on the oxidation of ferrous iron were not applied in the simulations. Simulations reproduced the general features of the pulse of modified pH as it was transported downstream and the accompanying changes in aluminum and iron concentration. Lack of fit between simulations and field observations was apparent for some constituents. Simulated concentrations of iron were substantially lower than observed values at site 24 (Figure 3i) and site 70 (Figure 3j) during the injection interval. An improved fit was evident at the two downstream sites, and the fit was best at site 498 (Figure 3l). The lack of agreement for iron at the two upstream sites was a consequence of setting a fixed percentage of ferrous iron. Current formulation in the model allowed for an instantaneous transformation of ferrous iron to ferric iron to replenish ferric iron removed from solution by precipitation. Travel time to the two upstream sites, 6 and 21 min, respectively, apparently was shorter than the time required for oxidation. Simulated pH was less than observed pH at site 24 and site 70 (Figure 3a,b) during the injection interval, but the fit improved substantially at site 251 and site 498 (Figure 3c,d). This pattern was related to the pattern for iron. Iron removal from the dissolved phase requires oxidation of ferrous iron, hydrolysis of ferric iron, formation of solid nuclei, and aggregation of these nuclei into precipitates greater than the filter pore size. Ferric iron hydrolysis liberates protons, thus decreasing pH. The kinetics of ferric
iron hydrolysis are relatively fast, with reported half-lives less than 1 s (43). Ferrous iron oxidation is much slower (42). McKnight and Bencala (8) calculated a first-order ferrous iron oxidation rate coefficient of 0.28 h-1 in water from the Snake River, CO. McKnight et al. (12) calculated an oxidation rate coefficient of 0.26 h-1 in St. Kevin Gulch. Under similar kinetics, limitations on the rate of supply of ferric iron for hydrolysis could explain both the underprediction of pH and dissolved iron at the two upstream sites and the improved fits at the two downstream sites. If the lack of fit for pH can be explained by kinetic limitation on iron oxidation and subsequent precipitation, we would expect an improved simulation of pH at site 24 if iron precipitation was not simulated. When iron was not permitted to precipitate, the simulation agreed well with the observed pH during the first stage of the injection (Figure 4). This result was consistent with a minimal change in oxidation rate at a pH of 4.0-4.2. During the interval of highest pH, the simulations with and without iron precipitation bracketed the observed values, indicating that some oxidation and precipitation occurred but did not reach equilibrium at a pH of 5.0-5.8 during the 6-min transport time to site 24. In addition to the absence of kinetic restraints on oxidation and precipitation of iron, our operational definition of dissolved iron (i.e.,
