Enhanced Copper Release from Pipes by Alternating Stagnation and

Traditional studies of copper release in plumbing systems assume that the water extracted from a pipe follows a plug-type flow and that the pipe surfa...
0 downloads 0 Views 342KB Size
Download PDF
Environ. Sci. Technol. 2007, 41, 7430-7436

Enhanced Copper Release from Pipes by Alternating Stagnation and Flow Events GUSTAVO R. CALLE, IGNACIO T. VARGAS, MARCO A. ALSINA, PABLO A. PASTE ´ N, AND GONZALO E. PIZARRO* Departamento de Ingenierı´a Hidra´ulica y Ambiental, Pontificia Universidad Cato´lica de Chile, Av. Vicun ˜a Mackenna 4860, Santiago 6904411, Chile

Traditional studies of copper release in plumbing systems assume that the water extracted from a pipe follows a plugtype flow and that the pipe surface does not interact with the bulk water under flow conditions. We characterized actual stagnation-flushing cycles in a household pipe undergoing corrosion in the presence of a microbial biofilm. The mass of copper released in 10 experiments was on average 8 times the value estimated by using the plugflow assumption. The experimental copper release pattern was explained by an advection-diffusion model only if a high copper concentration occurs near the pipe surface after stagnation. Microscopic examination of the pipe surface showed a complex assemblage of biotic and abiotic features. X-ray diffraction analyses identified only malachite, while X-ray absorption spectroscopy also revealed cupric hydroxide and cuprite. These results indicate that the surface serves as a storage compartment of labile copper that may be released under flow conditions. Thus, the diffusive transport from the pipe surface to the bulk during stagnation is not the only control of the flux of copper to the tap water when porous reactive microstructures cover the pipe. Our results highlight the need for models that consider the interaction between the hydrodynamics, chemistry, and structure at the solid-water interface to predict the release of corrosion byproducts into drinking water.

1. Introduction For decades, copper has been the material of choice for piping in household water distribution systems worldwide. Reported cases of structural failures (1) and population exposure to consumption of unsafe copper concentrations (2, 3) have encouraged several scientific studies to further understand the mechanisms that trigger and control copper corrosion in piping systems (3-9). Such studies have highlighted the influence of water-quality parameters (pH, temperature, oxygen, alkalinity, chloride, sulfate, phosphate, and organic matter)(4-6, 8), and operating conditions (i.e., stagnation time, pipe age) (7, 10, 11) on copper release into drinking water from copper pipes. Effort has been made to gain insight into the formation of solid byproducts during the corrosion of copper pipes, as solid-solution interactions are a key factor controlling the * Corresponding author. Fax: [email protected]. 7430

9

+ 56-2 354 5876. E-mail:

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 41, NO. 21, 2007

fate of soluble metals and metalloids in water (3, 5, 12). Stagnation experiments under abiotic conditions show that the nature and amount of the corrosion solid byproducts depend on the water composition, stagnation time, and aging of the pipe and suggest that in long-term stagnation (i.e., more than 30 h) the dissolved copper concentration in the bulk water follows the solubility of either cupric hydroxide (Cu(OH)2(S)), malachite (CuCO3‚Cu(OH)2(S)), or tenorite (CuO(S)) (5, 7, 10, 11). Thus, the thermodynamic equilibrium of the predominant solid in the corrosion scales at the solid-water interface is thought to be a major chemical control of the dissolved copper concentration in the bulk water in longterm stagnation. Although most copper problems in drinking water piping have been related to soluble copper, the release of particulate corrosion byproducts can also occur during a corrosion event. Such episodesscalled “blue water”sare commonly brought about by microbial activity (3, 12-15). Microbiologically influenced corrosion (MIC) usually occurs when coppertolerant bacteria develop biofilm colonies at the inner surface of the copper pipes (16), preventing the formation of passivating scales and thus establishing anodic sites underneath the biofilm (16, 17). MIC in domestic copper pipes has been reported in different countries like Australia, Germany, Sweden, and the United Kingdom (12-14, 16, 18, 19). Under MIC conditions, the exopolysaccharide matrix in biofilms has a high affinity for copper ions (17, 20, 21), constituting an additional potential site of copper storage and release if favorable hydrodynamic and chemical conditions occur. Copper corrosion in drinking water pipes may be envisioned as the result of concurrent processes that may be classified into three mechanistic groups as follows: redox processes, chemical reactions without electron transfer, and transport processes (22). These processes include solid and dissolved phases and take place in different temporal and spatial scales inside the pipe. Experiments on actual copper pipes have helped to elucidate how these processes and different water-quality parameters determine the bulk water concentration after a stagnation period (3, 5, 10, 12, 23) and to assess copper release kinetics (11). However, two important assumptions are usually made in order to estimate the copper release in an actual system based on the bulk water copper concentration measured after stagnation: The pipe surface does not interact with the bulk water when the tap is opened, and the water follows a plug-type flow (23). These assumptions may be accurate enough for pipes coated with abiotic, compact, and low-porosity corrosion byproducts, but they may be inadequate for pipes coated with thick, soft, and reactive porous microstructures, such as in the case of copper corrosion in the presence of biofilms. When flow conditions are established after opening the tap, the water velocity distribution imposes chemical and mechanical effects, such as changing water composition due to advective transport and shear stress due to viscosity. Consequently, a combination of processes such as desorption of labile copper and sloughing of nanoparticles from the pipe surface may enhance the flux of copper from the pipe to the tap water. The literature reporting a connection between hydrodynamics and metal release from metal surfaces focuses mostly on mechanical abrasion under flow conditions (24). Abundant evidence exists about the effects of hydrodynamics on the mass transfer at solid-water interfaces like the sediment-water interface (25-27), but this issue has been neglected in the literature studying copper release from copper pipes. Although the sediment-water and the pipe-water interfaces have different geometrical 10.1021/es071079b CCC: $37.00

 2007 American Chemical Society Published on Web 10/05/2007

FIGURE 1. (a) Domestic plumbing system used in this work. (b) Hydrodynamic mathematical model. Velocity distribution profile is parabolic in laminar flow. The advection equation is used to calculate the mean total copper concentration at the sampling point. (c) Observed data for dissolved copper during flushing. During each experiment, 15 sequential water samples were extracted. This procedure was repeated 10 times. (d) Average characteristic curve of copper concentration as a function of volume of water extracted from the pipe. During flushing, water samples were taken to measure total copper (dashed line) and dissolved copper (empty squares). Error bars indicate 1 standard deviation of observed data. For a 1 m length of pipe, the mass of copper extracted during the flushing experiment (area under total copper curve) is 11 times the mass extracted if the plug flow were assumed. The thermodynamic model for equilibrium with malachite (black cross) predicts only the initial point of the characteristic curve. scales, the underlying processes are the same: diffusion, advection, scouring, and reaction with a porous solid phase. Thus, it is reasonable to expect that the hydrodynamic conditions also play a role in the mass transfer from the solid-water interface to the bulk water in copper pipes. In this work, we report the results of a field study that characterized the enhanced copper release during alternating stagnation-flow events in an actual household pipe undergoing corrosion in the presence of a microbial biofilm. Our study is based on the systematic quantification of the copper release pattern after the tap is opened and the microscopic and molecular analysis of the inner surface of the copper pipe. This study prompts the integration of hydrodynamic factors in the conceptual and quantitative models of copper exposure derived from stagnation experiments, especially when corrosion in the presence of a heterogeneous biofilm is present.

2. Methodology Our study was developed in a household system, which consisted of a copper pipe placed outdoors and supplied by well water. The house is located in the suburbs of the city of Talca (257 km south from Santiago, Chile). The methodology consisted of three principal tasks as follows: (1) sampling and in situ wet chemistry analyses, (2) character-

ization of surface corrosion byproducts, and (3) mathematical modeling of hydrodynamics and transport. The details of these three tasks are presented below. 2.1. Experimental Setup for Flushing Experiments. The system consists of a well connected to a PVC pipe followed by 1 m of copper pipe with an internal diameter of 1.95 cm and 300 mL of volume (Figure 1a). Water from the well is disinfected by a UV-radiation system located prior to the PVC connection. Chemical analysis of the water from the well is presented in Table 1. Prior to the study, the system operated for 2 years connected to the house plumbing system. For the flushing experiments, the well water was held stagnant within the system for 10 h before opening the tap. The pipe was flushed at a constant laminar flow rate of 0.48 L/min (Re ) 587). During flushing, 15 sequential water samples of 100 mL were taken from the tap to determine copper concentration until approximately 11 L were extracted from the pipe. Flushing experiments were repeated once a day during 10 consecutive days to achieve a reliable curve of copper concentration as a function of the volume of water extracted from the pipe (Figure 1c). The average water temperature during the flushing experiments was 19 °C. Although the flow conditions are not typical for a household operation, they were chosen because they allowed a careful and reliable sampling. Moreover, the employed methodology VOL. 41, NO. 21, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

9

7431

TABLE 1. Water-Quality Data of Well Water Used for Wet Chemistry Analysesa parameter

unit

value

total copper dissolved copper iron chloride total alkalinity total hardness sulfate nitrate phosphate pH dissolved oxygen conductivity DOC magnesium

mg Cu/L mg Cu/L mg Fe/L mg Cl/L mg CaCO3/L mg CaCO3/L mg SO4-2/L mg NO3--N/L mg PO4-3/L

0.07 0.07 0.045 15.6 80 160 30.2 3.2 1.66 6.0 8.11 235 1.5 6.44

mg O2/L µS/cm mg/L mg Mg/L

a All parameters were measured in situ, except DOC and magnesium concentrations that were measured in the laboratory

lays the groundwork for a first step in considering the hydrodynamic effects on copper release from drinking water pipes. .Stagnation time in domestic plumbing system varies according to local characteristics and is difficult to generalize. There is no comprehensive information about it. However, according to a water consumption survey in Santiago (Chile), stagnation time has a mean of 7.5 h (23). Only European and U.S. standards establish a regulatory level, usually within 6 to 12 h (23). The plumbing system in this field study has a consumption pattern with a mean stagnation time of 10 h. Dissolved and total copper concentrations were measured in situ by the bicinchoninate method (HACH no. 8506) with a portable spectrophotometer HACH DR/2010 (28). Dissolved copper was measured after membrane filtration (0.45 µm pore size, cellulose acetate). The filter apparatus used consisted of a 20 mL plastic syringe, a 25 mm diameter filter, and a polycarbonate support. For each point, 20 mL of sample was filtered. The filtration method used was tested and compared in previous corrosion studies (5, 29). Total copper was quantified in unfiltered samples after acidification with nitric acid. These methods were compared by measuring dissolved and total copper in a set of field samples in a Varian SpectrAA 800 flame atomic absorption spectrophotometer with an excellent agreement for concentrations over 0.1 mg/ L. Total copper measurements were performed after digestion with aqua regia (method 3030F) (30). The HACH no. 8506 method has an analytical window of 0.04-5.00 mg/L, and it has been used in previous corrosion studies to determine total and dissolved copper concentration (5, 6, 31). The well water was characterized through the determination of pH, electric conductivity, dissolved oxygen, dissolved organic carbon (DOC), iron, chloride, alkalinity, hardness, sulfate, nitrate, phosphate, and magnesium concentration (Table 1). Determination of conductivity was made with a Thermo Orion 125A+ meter, pH with a pH meter Thermo Orion 420A, and dissolved oxygen by a fluorescence optic oxygen sensor (FOXY, Oceans Optics, Inc.). 2.2. Characterization of Surface Corrosion Byproducts. After the 10 days of stagnation-flushing experiments, the copper pipe was removed from the household system and several coupons of 0.5 × 0.5 cm were cut for microscopic analysis. Tap water from the house in study was used to keep the coupons hydrated before the surface analyses. The coupons were treated with critical point drying and coated with a gold thin film. A LEO 1420VP scanning electron microscope coupled to an Oxford 7424 solid-state detector was used to obtain the micrographs and the energy dispersive X-ray spectra of the corrosion byproducts. X-ray absorption 7432

9

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 41, NO. 21, 2007

spectroscopy (XAS) and X-ray diffraction (XRD) analyses were carried out on scales extracted from the inner surface of the removed pipe. For XAS analyses, the surface of the pipe was previously rinsed with MilliQ water to remove the excess of salts and then gently removed with a Teflon-coated spatula to recover and place the detached material into Kapton tape. Reagent-grade chemicals (Sigma-Aldrich) of basic copper(II) carbonate (CuCO3Cu(OH)2), copper(II) hydroxide (Cu(OH)2), and copper(I) oxide (Cu2O), along with numerous copper minerals (provided by the CODELCO mining company collection) were also measured by XAS for use as copper reference compounds. XAS data were acquired at the bending magnet beam line of DND-CAT, sector 5 of the Advanced Photon Source, Argonne National Laboratory (IL). The samples were measured in transmission mode, and a copper foil was used to calibrate the monochromator using the Cu K edge (8979 eV). ATHENA software (32) was used for data processing . 2.3. Hydrodynamic Mathematical Model. To gain insight on the interaction between the hydrodynamic condition and the initial copper distribution in the bulk liquid after stagnation, a hydrodynamic mathematical model for flushing in laminar flow was developed using the Navier-Stokes and advection-diffusion equations in cylindrical coordinates. This model considers (i) an initial concentration profile of total copper at any section of the pipe at the end of the stagnation period and (ii) a transport model of copper by advection during flushing. Two initial copper concentration profiles were tested, an initial “diffusive profile” and a “surface-enriched” profile. The diffusive initial condition profile was determined by solving the diffusion equation in cylindrical coordinates (Figure 2b), assuming a boundary condition of constant concentration (CSD) at the surface of the pipe. CSD is a parameter for the model and is fitted using the data from the field experiments.

∂ 2C ∂C D ∂C -D 2 )0 ∂t r ∂r ∂r where C represents the copper concentration and D is the diffusion coefficient. The diffusion coefficient for all aqueous copper species was assumed the same as that for Cu2+ (D ) 0.72 × 10-5 cm2/s (33)). The diffusion equation was solved numerically using a finite volume scheme. The surface-enriched profile assumes a concentration of copper at the surface (CST) and zero concentration at a distance hT from the inner surface (Figure 2b). The concentration of copper changes linearly from CST at the surface of the pipe to zero at a distance hT. Both CST and hT are parameters for the model and are fitted using the data from field experiments. Once the initial concentration profile is determined, the hydrodynamic model calculates the profile of copper concentration at 1 m from the water input, consistent with the location where the experimental samples were collected. The advection equation,

∂C ∂C + v(r) ) 0 ∂t ∂z is applied along the z axis to simulate flushing (Figure 1b), where v is the velocity of the fluid along z axis. For a laminar flow of water (constant density, Newtonian fluid) at steady state, the velocity distribution profile is parabolic (34) (Figure 2a). This equation was solved using a finite volume scheme. The stability criterion for this scheme is given by ∆z/(v∆t) e 1. To compare the results of the model with the field measurements, the mean concentration of copper at the sampling point was calculated for the model, obtaining a curve of estimated mean copper concentration versus volume

FIGURE 2. (a) Velocity profile in laminar regime. This profile corresponds to a 0.48 L/min flow. (b) Best fit of hydrodynamic model: surface-enriched profile with initial concentrations CST ) 25 mg/L and hT ) 1.2 mm (continuous line). Diffusion-based profile model is also presented as CSD ) 3.5 mg/L (dashed line). (c) Observed (empty squares) and calculated data obtained for a triangular initial concentrations profile (solid line). Results obtained for diffusion-based profile (dashed line) did not fit the observed data. Error bars indicate 1 standard deviation of observed data. of water extracted from the pipe. With this scheme, the parameters for diffusion-based initial profile (CSD) and triangular model (CST and hT) were calibrated using absolute least-squares fitting (LSF).

3. Results and Discussion Results of the laminar flow flushing experiments show that the copper release decays as the volume of water circulated through the pipe increases (Figure 1c,d). However, the shape of the observed release curve does not agree with the copper release curve when mass transfer from the surface is neglected and an ideal plug-flow condition is assumed. Furthermore, this assumption underestimates the average total mass of copper released during flushing, since, according to our measurements, the average dissolved mass of copper released during flushing experiments was 8.1 mg, 9 times the mass of copper predicted with the traditional ideal plug-flow assumption (Figure 1d). The mass of dissolved copper released was estimated by integrating the curves of copper concentration vs volume of water extracted from the pipe obtained experimentally from the 10 flushing experiments. The mass of copper released had a maximum value of 12.6 mg, a minimum value of 6.1 mg, and a standard deviation of 2. Similarly, for each flushing experiment, the mass that would have been released if plug flow were assumed was computed as the mass of copper within the 1 m pipe, that is, its volume (300 mL) times the bulk copper concentration (assumed as the concentration of copper in the first volume extracted from the pipe for each experiment). With these data, the ratio between the measured copper released and copper released assuming plug flow varied between 11.6 and 6.2. For comparison purposes, the geochemical software PHREEQC (35) was used to predict the maximum average concentration of dissolved copper as a function of the scale constituents, considering the average pH and temperature measured during the flushing experiments (pH ) 6, T ) 19 °C). Thermodynamic data for cupric species were obtained from a Lawrence Livermore National Laboratory database (36). Temperature corrections of the thermodynamic parameters in PHREEQC were made using the van’t Hoff relationship or analytical expressions included in the database. The soluble copper concentration can be expressed as the sum of the soluble cupric species, assuming that a solid phase is formed (4, 5, 10). Assuming that malachite controls the solubility, thermodynamic calculations predict a dissolved copper concentration of 2.91 mg/L (Figure 1d). Although

this value is in agreement with the average initial concentration of copper observed during the flushing experiments, it must be kept in mind that thermodynamic predictions do not provide any information regarding the kinetics of copper release from the pipe and that thermodynamic equilibrium is not expected at 10 h of stagnation (11, 22). Consequently, at least for this case study, the ideal plug flow and thermodynamic approaches are neither adequate nor sufficient to assess the controls of copper release during stagnation/flow periods. Scanning electron microscopy (SEM) analysis of the inner surface of the pipe shows a heterogeneous morphology, presenting randomly distributed hemispherical pits, corrosion byproduct scales, and the development of a bacterial biofilm (Figure 3a-c). This morphology is the consequence of 2 years of system operation with well water of pH 6, alkalinity of 80 mg/L, hardness of 160 mg/L as CaCO3, and negligible copper concentration (0.07 mg/L) (Table 1). A closer analysis of the surface shows that most of the precipitates are closely related to the bacterial biofilm, forming macrostructures larger than 100 µm. There are smaller features of less than 1 µm that can potentially detach from the surface, a fact that has been reported for the blue water phenomenon (3). The heterogeneity of the morphology observed can be related to the heterogeneity of the biofilm. Biofilm heterogeneity has been related to the effect of hydrodynamics (37-41) and to low substrate concentration (42-44), which is the case in our system. To address the nature of the corrosion byproducts, the measured X-ray absorption near the edge structure (XANES) spectrum was adjusted through a least-squares linear combination fitting (LCF) with known reference compounds. The results of the XANES analyses were confirmed by fitting the extended X-ray absorption fine structure (EXAFS) spectrum (Figure 3d,e). The LCF in the XANES region yielded mostly malachite (84%), cupric hydroxide (13%), and cuprite (3%). The LCF in the EXAFS region showed differences in composition of less than 3% compared to the XANES fit, with malachite (81%), cupric hydroxide (14%), and cuprite (5%). The identification of cupric hydroxide in the corrosion scale requires discussion, since according to predominance diagrams this compound should appear, if ever, at pH values above 8. Despite the latter condition, cupric hydroxide is predicted as thermodynamically feasible at the water conditions of our case study, but not as the predominant species. This is further corroborated by the identification of malachite VOL. 41, NO. 21, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

9

7433

FIGURE 3. SEM images and XAS spectra of the inner surface copper pipe. (a) Heterogeneous distribution of pits and botryoidal corrosion byproducts. (b) Magnification of the previous image, showing a biofilm closely attached to the metallic surface. (c) Image of the close interactions between bacteria and nanosized mineralizations. (d) XANES spectrum of the corrosion byproducts (solid line) along with the best LSF with known copper reference compounds for both the XANES (dashed line, percentages given in the figure) and the EXAFS region (axis line). Inset in d shows the structure feature at ∼8978 eV, assigned to the 1s f 3d electronic transition of Cu(II) compounds, along with the rise in the absorption structure after 8980 eV. This can be attributed to the allowed electronic transitions for Cu(I) compound cuprite. (e) EXAFS spectrum of the corrosion byproducts (solid line), along with the best LCF with known copper reference compounds for both the EXAFS (axis line, percentages given in the figure) and the XANES regions (dashed line).

as the predominant corrosion scale. Cupric hydroxide formation has been speculated for corrosion events (5), but to our knowledge it has not been experimentally confirmed. The lack of direct confirmation of cupric hydroxide formation in the literature may be related to insufficient long-range ordering of the scales if identified by X-ray diffraction. However, long-range ordering is not required in XAS, and this advantage was fundamental to select XAS as the tool for solid-phase characterization of the corrosion scales. Despite the morphologic similarities in the layered copper octahedra (CuO610-) structures of both malachite and cupric hydroxide, XAS relies on spectroscopic differences to identify and quantify the relative presence of both compounds. The distorted geometry of the copper octahedra in cupric hydroxide produces absorption features in the Cu K edge XANES spectrum that are absent for malachite. For EXAFS, the distortion of the octahedra translates into different Cu-O interatomic distances for both compounds, being on average lower for malachite (2.15 Å) than for cupric hydroxide (2.19 Å). To quantify the theoretical accuracy of XAS when distinguishing between malachite and cupric hydroxide, XANES signals of both compounds were mathematically mixed in proportions ranging from 0 to 100% (10% intervals) for each compound, and the resulting signals were analyzed through the LCF procedure. The estimated percentages after LCF showed differences of less than 1% compared to the original mathematical mixture. Similar agreements were obtained when EXAFS signals were used. It is important to notice that the XANES spectral signature of cupric hydroxide shows linear dependency with the spectrum of Cu(II) bound to organic material, preventing cupric hydroxide and surface-bound Cu(II) from being discriminated using only the LCF in the XANES region. Further spectral differences between cupric hydroxide and surface-bound Cu(II) can be found in the EXAFS region. The average distance between copper and the apical oxygen atoms 7434

9

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 41, NO. 21, 2007

is higher in cupric hydroxide (∼2.18 Å) than in Cu(II) bound to organic material (∼1.97 Å), resulting in a lower frequency for the first-shell single scattering in the EXAFS spectrum of cupric hydroxide when compared with Cu(II) bound to organic material. The identification of cupric hydroxide in the sample in non-negligible amounts is supported by the good agreement between the LSF in the XANES and the EXAFS regions (differences within 3%) and the lower goodness of the fit when sorbed Cu(II) was considered. Adsorbed phases of copper are extremely hard to assess using XAS if solid phases of copper are also present in the sample. A rough estimation shows that a sample with 50% w/w composition of Cu(II) bound to organic material (assuming an adsorption of up to 50 mg Cu/g biomass) will only contribute ∼8% to the overall XAS signal if the other 50% w/w is either cupric hydroxide or malachite. However, the presence of surfacebound Cu(II) in the actual system cannot be ruled out due to a possible desorption of Cu(II) during sample preparation and the possibility of having mixtures of cupric hydroxide with small contributions of sorbed Cu(II). The pH value measured in the water extracted from the pipe was 6. This value could be considered as the average of the cross section where spatial variability of chemical parameters occurs due to transport and chemical processes. Independent of the tenet that the precipitation of cupric hydroxide at pH 6 may be thermodynamically feasible, the presence of heterogeneous biofilms on the pipe’s surface could establish microenvironments with favorable conditions for Cu(OH)2 formation,which is coherent with the identification of Cu(OH)2 in the scale. Therefore, the solid matrix at the inner surface of the pipe is a complex reactive surface (on the order of 100 µm thick) made up by biofilm material and abiotic precipitates. The biofilm matrix contains organic compounds (proteins, polysaccharides, and humic substances) that are capable of binding copper ions during stagnation periods (45-47) The

extracellular polymeric substances (EPS) matrix and the bacteria within the biofilm can also retain copper by mineralization of corrosion byproducts (1, 10), as evidenced by our SEM analysis. The corrosion byproducts are crystalline (e.g., malachite, evidenced by XRD analysis) and amorphous (e.g., cupric hydroxide, evidenced by XAS analysis). Consequently, the reactive layer on the pipe’s surface acts as a potential reservoir of copper that can be released by desorption or by mechanical shear stress. The latter implies that particles of corrosion byproducts and pieces of biofilm may detach from the surface of the pipe during flow events and can increase the risk of human exposure to copper compared with the traditional models. The results of the hydrodynamic model after the calibration process are presented in Figure 2. The best fit of the model was achieved for an initial surface-enriched concentration profile, since the diffusive profile shows an inconsistency with the observed concentrations of released copper (Figure 2c). The values of surface-enriched profile thickness (hT) and border concentration (CST) obtained after calibration were 1.2 mm and 25 mg Cu/L, respectively, suggesting that after the stagnation period most of the labile copper is located close to the pipe surface, probably related to the solid/ aqueous interface and its reactivity. The results of stagnation/flow experiments and the analysis with the hydrodynamic model indicate that diffusion is not the principal mechanism that governs the release of copper from the copper pipe, since most of the copper mass remains near the pipe’s surface. Rather, these results suggest that physical and chemical processes at the solid-liquid interface coupled with hydrodynamic mechanisms control the release of copper corrosion byproducts into drinking water. These processes at the solid-liquid interface are not necessary related to any MIC episode; rather, they are related with the presence of reactive species like the EPS of microbial biofilms. Copper sorption within a reactive layer should be noted as a possible mechanism of enhanced copper release during flow conditions when diffusion during stagnation cannot explain the measured copper release pattern (Figure 2c). Even though our experiments were performed under laminar flow conditions, we can speculate about the factors that would control copper release for higher flow rates. For a flow rate of 8 L/min, the flow would be turbulent (Re ) 9700), the viscous sublayer thickness may be estimated in the range of 50-100 µm, and the shear stress would be approximately 50 times larger compared with that of laminar flow conditions. For the same volume of water extracted from the pipe, there would be a shorter time for copper to desorb from the reactive surface under turbulent conditions compared with those of laminar flow. Thus, it is more likely that the kinetics of copper desorption might constrain the mass transfer of copper to the bulk water under turbulent conditions. However, the higher shear stress on the pipe’s surface and the sharper concentration gradient would enhance copper release. Another factor that can produce copper desorption from the reactive layer is the presence of hydroxyl radicals formed by UV-radiation disinfection. These radicals are capable of rapidly oxidizing organic matter from water (48). However, in the experimental setup used in this research, the UVradiation source was located away (40 m) from the copper pipe under study. Given the high reactivity of these radicals with organic matter, it is unlikely that hydroxyl radicals formed by UV-radiation could interact with the biofilm on the copper pipe. Copper spatial distribution near the reactive layer, sorption and desorption mechanisms of copper on abiotic and biotic microscopic features, and detachment of nanoparticles

of corrosion byproducts or biofilm from the surface are still uncertain, and hence, further work in this line of research is required.

Acknowledgments This research was funded by FONDECYT projects 10707372007 and 1040607-2004. Portions of this work were performed at the DuPont-Northwestern-Dow Collaborative Access Team (DND-CAT) Synchrotron Research Center located at Sector 5 of the Advanced Photon Source. DND-CAT is supported by the E. I. DuPont de Nemours & Co., The Dow Chemical Company, the U.S. National Science Foundation through Grant DMR-9304725, and the State of Illinois through the Department of Commerce and the Board of Higher Education Grant IBHE HECA NWU 96. Use of the Advanced Photon Source was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Contract No. W-31-109-Eng-38.

Literature Cited (1) Callot, P.; Jaegle, A.; Kalt, A.; Nanse, G. Pitting Corrosion of Copper Tubes and Carbon Deposits: ESCS Studies. Werkst. Korros. 1987, 29 (8), 519-522. (2) Dietrich, A. M.; Glindemann, D.; Pizarro, F.; Gidi, V.; Olivares, M.; Araya, M.; Camper, A.; Duncan, S.; Dwyer, S.; Whelton, A. J.; Younos, T.; Subramanian, S.; Burlingame, G. A.; Khiari, D.; Edwards, M. Health and aesthetic impacts of copper corrosion on drinking water. Water Sci. Technol. 2004, 49 (2), 55-62. (3) Edwards, M.; Jacobs, S.; Taylor, R. J. The blue water phenomenon. J.sAm. Water Works Assoc. 2000, 92 (7), 72-82. (4) Schock, M. R.; Lytle, D. A.; Clement, J. A. Effect of pH, DIC, Orthophosphate and Sulfate Drinking Water Cuprosolvency; EPA/600/R-95/085; U.S. Environmental Protection Agency: Washington, DC, 1995. (5) Edwards, M.; Schock, M. R.; Meyer, T. E. Alkalinity, pH, and copper corrosion by-product release. J.sAm. Water Works Assoc. 1996, 88 (3), 81-94. (6) Boulay, N.; Edwards, M. Role of temperature, chlorine, and organic matter in copper corrosion by-product release in soft water. Water Res. 2001, 35 (3), 683-690. (7) Edwards, M.; Powers, K.; Hidmi, L.; Schock, M. R. The role of pipe ageing in copper corrosion by-product release. Water Sci. Technol.: Water Supply 2001, 1 (3), 25-32. (8) Pehkonen, S. O.; Palit, A.; Zhang, X. Effect of specific water quality parameters on copper corrosion. Corrosion 2002, 58 (2), 156165. (9) Keevil, C. W. The physico-chemistry of biofilm-mediated pitting corrosion of copper pipe supplying potable water. Water Sci. Technol. 2004, 49 (2), 91-98. (10) Lagos, G. E.; Cuadrado, C. A.; Letelier, M. V. Aging of copper pipes by drinking water. J.sAm. Water Works. Assoc. 2001, 93 (11), 94-103. (11) Merkel, T. H.; Groβ, H.-J.; Wernera, W.; Dahlkeb, T.; Reichertera, S.; Beuchleb, G.; Eberle, S. H. Copper corrosion by-product release in long-term stagnation experiments. Water Res. 2002, 36 (6), 1547-1555. (12) Critchley, M. M.; Pasetto, R.; O’Halloran, R. J. Microbiological influences in ‘blue water’ copper corrosion. J. Appl. Microbiol. 2004, 97 (3), 590-597. (13) Geesey, G. G.; Bremer, P. J.; Fischer, W.; Wagner, D.; Keevil, C. W.; Walker, J. T.; Chamberlain, A. H. L.; Angell, P. Unusual types of pitting corrosion of copper tubes in potable water systems. In Biofouling and Biocorrosion in Industrial Water Systems; Geesey, G. G., Lewandowski, Z., Flemming, H. C., Eds.; Lewis Publishers: New York, 1994; pp 243-263. (14) Arens, P.; Tuschewitzki, G. J.; Wollmann, H.; Follner, H.; Jacobi, H. Indicators for microbiologically induced corrosion of copper pipes in a cold water plumbing system. Int. J. Hyg. Environ. Med. 1995, 196 (5), 444-454. (15) Arens, P.; Tuschewitzki, G. J.; Follner, M.; Jacobi, H.; Leuner, S. Experiments for stimulating microbiologically induced corrosion of copper pipes in a cold-water plumbing system. Mater. Corros. 1996, 47 (2), 96-102. (16) Wagner, D.; Chamberlain, A. H. L. Microbiologically influenced copper corrosion in potable water with emphasis on practical relevance. Biodegradation 1997, 8 (3), 177-187. VOL. 41, NO. 21, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

9

7435

(17) Geesey, G. G.; Mittelman, M. W.; Iwaoka, T.; Griffiths, P. R. Role of bacterial exopolymers in the deterioration of metallic copper surfaces. Mater. Perform. 1986, 25 (2), 37. (18) Critchley, M. M.; Cromar, N. J.; McClure, N. C.; Fallowfield, H. J. The influence of the chemical composition of drinking water on cuprosolvency by biofilm bacteria. J. Appl. Microbiol. 2003, 94 (3), 501-507. (19) Dutkiewicz, C.; Fallowfield, H. J. Assessment of microbial involvement in the elevation of copper levels in drinking water. J. Appl. Microbiol. 1998, 85 (3), 597-602. (20) Jolley, J. G.; Geesey, G. G.; Hankins, M. R.; Wright, R. B.; Wichlacz, P. L. Auger electron and X-ray photoelectron spectroscopic study of the biocorrosion of copper by alginic acid polysaccharide. Appl. Surf. Sci. (1985) 1989, 37 (4), 469. (21) Hu, Z. Q.; Jin, J.; Abruna, H. D.; Houston, P. L.; Hay, A. G.; Ghiorse, W. C.; Shuler, M. L.; Hidalgo, G.; Lion, L. W. Spatial distributions of copper in microbial biofilms by scanning electrochemical microscopy. Environ. Sci. Technol. 2007, 41 (3), 936-941. (22) Merkel, T. H.; Pehkonen, S. O. General corrosion of copper in domestic drinking water installations: Scientific background and mechanistic understanding. Corros. Eng. Sci. Technol. 2006, 41 (1), 21-37. (23) Lagos, G. E.; Maggi, L. C.; Peters, D.; Reveco, F. Model for estimation of human exposure to copper in drinking water. Sci. Total Environ. 1999, 239 (1-3), 49-70. (24) Poulson, B. Advances in understanding hydrodynamic effects on corrosion. Corros. Sci. 1993, 35 (1-4), 655-665. (25) Higashino, M.; Stefan, H. G. Diffusive boundary layer development above a sediment-water interface. Water Environ. Res. 2004, 76 (4), 292-300. (26) Steinberger, N.; Hondzo, M. Diffusional mass transfer at sediment-water interface. J. Environ. Eng. (Reston, VA, U.S.) 1999, 125 (2), 192-200. (27) Fries, J. S. Predicting interfacial diffusion coefficients for fluxes across the sediment-water interface. J. Hydraulic Eng. 2007, 133 (3), 267-272. (28) HACH Company. Water Analyst Handbook, 4th ed.; Loveland, CO,, 2003. (29) Hidmi, L.; Edwards, M. Role of temperature and pH in Cu(OH)2 solubility. Environ. Sci. Technol. 1999, 33 (15), 2607-2610. (30) American Public Health Association; American Water Works Association; Water Environmental Federation. Standard Methods for the Examination of Water and Wastewater, 21st ed.; American Public Health Association: Washington, DC, 2005. (31) Lehtola, M. J.; Miettinen, K. T.; Keinanen, M. M.; Kekki, T. K.; Laine, O.; Hirvonen, A.; Vartiainen, T.; Martikainen, P. J. Microbiology, chemistry and biofilm development in a pilot drinking water distribution system with copper and plastic pipes. Water Res. 2004, 38 (17), 3769-3779. (32) Ravel, B.; Newville, M. ATHENA, ARTEMIS, HEPHAESTUS: Data analysis for X-ray absorption spectroscopy using IFEFFIT. J. Synchrotron Radiat. 2005, 12, 537-541. (33) Newman, J. S. Electrochemical Systems. Prentice Hall International, Inc.: London, 1973. (34) Bird, R. B.; Stewart, W. E.; Lightfoot, E. N. Transport Phenomena; John Wiley & Sons, Inc.: New York, 2002.

7436

9

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 41, NO. 21, 2007

(35) Parkhurst, D. L.; Appelo, C. A. J. User’s Guide to PHREEQC (Version 2)sA Computer Program for Speciation, Batch-Reaction, One-Dimensional Transport, and Inverse Geochemical Calculations; Water Resources Investigation Report 99-4259; U.S. Geological Survey: Denver, CO, 1999. (36) Johnson, J.; Anderson, G.; Parkhurst, D. Database from “thermo.com.V8.R6.230”; prepared at Lawrence Livermore National Laboratory: Livermore, CA, 2005. (37) deBeer, D.; Stoodley, P.; Lewandowski, Z. Liquid flow and mass transport in heterogeneous biofilms. Water Res. 1996, 30 (11), 2761-2765. (38) Stoodley, P.; Dodds, I.; Boyle, J. D.; Lappin-Scott, H. M. Influence of hydrodynamics and nutrients on biofilm structure. J. Appl. Microbiol. 1999, 85, 19S-28S. (39) Stoodley, P.; Lewandowski, Z.; Boyle, J. D.; Lappin-Scott, H. M. Oscillation characteristics of biofilm streamers in turbulent flowing water as related to drag and pressure drop. Biotechnol. Bioeng. 1998, 57 (5), 536-544. (40) Stoodley, P.; Lewandowski, Z.; Boyle, J. D.; Lappin-Scott, H. M. The formation of migratory ripples in a mixed species bacterial biofilm growing in turbulent flow. Environ. Microbiol. 1999, 1 (5), 447-455. (41) Stoodley, P.; Lewandowski, Z.; Boyle, J. D.; Lappin-Scott, H. M. Structural deformation of bacterial biofilms caused by shortterm fluctuations in fluid shear: an in situ investigation of biofilm rheology. Biotechnol. Bioeng. 1999, 65 (1), 83-92. (42) Picioreanu, C.; van Loosdrecht, M. C. M.; Heijnen, J. J. Effect of diffusive and convective substrate transport on biofilm structure formation: a two-dimensional modeling study. Biotechnol. Bioeng. 2000, 69 (5), 504-515. (43) Pizarro, G. E.; Garcia, C.; Moreno, R.; Sepulveda, M. E. Twodimensional cellular automaton model for mixed-culture biofilm. Water Sci. Technol. 2004, 49 (11-12), 193-198. (44) Pizarro, G. E.; Teixeira, J.; Sepulveda, M.; Noguera, D. R. Bitwise implementation of a two-dimensional cellular automata biofilm model. J. Comput. Civil Eng. 2005, 19 (3), 258-268. (45) Edwards, M.; Sprague, N. Organic matter and copper corrosion by-product release: a mechanistic study. Corros. Sci. 2001, 43 (1), 1-18. (46) Beech, W. B.; Sunner, J. Biocorrosion: towards understanding interactions between biofilms and metals. Curr. Opin. Biotechnol. 2004, 15 (3), 181-186. (47) Guibaud, G.; Tixier, N.; Bouju, A.; Baudu, M. Relation between extracellular polymers’ composition and its ability to complex Cd, Cu and Pb. Chemosphere 2003, 52 (10), 1701-1710. (48) Thomson, J.; Roddick, F.; Drikas, M. Natural organic matter removal by enhanced photo-oxidation using low pressure mercury vapour lamps. Water Sci. Technol.: Water Supply 2002, 2 (5-6), 435.

Received for review May 8, 2007. Revised manuscript received August 20, 2007. Accepted August 30, 2007. ES071079B