Journal of Contaminant Hydrology 161 (2014) 35–48

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Journal of Contaminant Hydrology

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Leaching potential of pervious concrete and immobilization ofCu, Pb and Zn using pervious concrete

U. Solpuker a,⁎, J. Sheets a, Y. Kim b, F.W. Schwartz a,1

a School of Earth Sciences, The Ohio State University, 125 S. Oval Mall, Columbus, OH 43210, USAb Korea Institute of Geoscience and Mineral Resources (KIGAM), 92 Gwahang-no, Yuseong-gu, Daejeon 305-350, Republic of Korea

a r t i c l e i n f o

⁎ Corresponding author. Tel.: +1 614 2926193; faxE-mail addresses: solpuker.1@osu.edu (U. Solpuke

(J. Sheets), yjkim@kigam.re.kr (Y. Kim), schwartz.11@(F.W. Schwartz).

1 Tel.: +1 614 2926196; fax: +1 614 2927688.

http://dx.doi.org/10.1016/j.jconhyd.2014.03.0020169-7722/© 2014 Elsevier B.V. All rights reserved.

a b s t r a c t

Article history:Received 10 October 2013Received in revised form 19 March 2014Accepted 21 March 2014Available online 30 March 2014

This paper investigates the leaching potential of pervious concrete and its capacity forimmobilizing Cu, Pb and Zn, which are common contaminants in urban runoff. Batchexperiments showed that the leachability of Cu, Pb and Zn increased when pH b 8. Accordingto PHREEQC equilibrium modeling, the leaching of major ions and trace metals was mainlycontrolled by the dissolution/precipitation and surface complexation reactions, respectively. A1-D reactive transport experiment was undertaken to better understand how perviousconcrete might function to attenuate contaminant migration. A porous concrete block wassprayed with low pH water (pH = 4.3 ± 0.1) for 190 h. The effluent was highly alkaline(pH ~ 10 to 12). In the first 50 h, specific conductance and trace-metal were high but declinedtowards steady state values. PHREEQC modeling showed that mixing of interstitial alkalinematrix waters with capillary pore water was required in order to produce the observed waterchemistry. The interstitial pore solutions seem responsible for the high pH values andrelatively high concentrations of trace metals and major cations in the early stages of theexperiment. Finally, pervious concrete was sprayed with a synthetic contaminated urbanrunoff (10 ppb Cu, Pb and Zn) with a pH of 4.3 ± 0.1 for 135 h. It was found that Pbimmobilization was greater than either Cu or Zn. Zn is the most mobile among three and alsohas the highest variation in the observed degree of immobilization.

© 2014 Elsevier B.V. All rights reserved.

Keywords:Pervious concreteUrban runoffPHREEQCTrace metalLeachingImmobilization

1. Introduction

Urbanization around the world has greatly expanded theimpermeable surface cover of cities (e.g. parking lots, road-ways, roof tops etc.) and the urban infrastructure (e.g., stormsewers), which are particularly efficient in transportingcontaminated stormwater to urban rivers and streams, andeventually to coastal environments. The types of pollutants(e.g. trace metals, nutrients and hydrocarbons) in urbanstormwater runoff are extremely varied and the pollutantloadings are significantly dependent on land use and rainfall

: +1 614 2927688.r), sheets.2@osu.eduosu.edu

(Davis et al., 2001; Herngren et al., 2005; Pitt et al., 2004).Among the sources of tracemetals (e.g., lead, copper, cadmium,and zinc) in urban runoff are sidings on buildings, automobileframes and bodies, particulates from vehicle brake and tirewear, and atmospheric pollution (Boving et al., 2008; Davis etal., 2001; Herngren et al., 2005; Pitt et al., 2004; Sansalone andBuchberger, 1997). Furthermore, polycyclic aromatic hydro-carbons (PAHs) are ubiquitous from sources that includeautomobile exhaust, lubricating oils, gasoline, tire particles,erosion of street asphalt, atmospheric deposition and coal-tarbased seal coats for asphalt parking lots (Mahler et al., 2005).

Problems of flooding and contamination associated withurban runoff are now widely known and understood. Citymanagers are now taking steps to reduce these problemsthrough engineered systems that are now part of the urbanlandscape. For example, pervious pavements are one of the

36 U. Solpuker et al. / Journal of Contaminant Hydrology 161 (2014) 35–48

popular Best Management Practices (BMPs) to reduce flashflooding due fast runoff from impervious surfaces and arecommonly used in parking lots, sidewalks and pathways,low traffic areas etc. (Boving et al., 2008). They minimizestormwater-related flooding by allowing the infiltration ofsurface runoff through the pavement (asphalt or concrete)(Tennis et al., 2004).

Pervious pavements can be constructed from the samematerials as conventional concrete except that the finefraction of the aggregate is eliminated, the size distributionof coarse fraction is narrowed, and just enough cementitiouspaste is used to coat the coarse aggregates while keeping theinterconnectivity of the voids (Tennis et al., 2004). Perviouspavements are placed over a 15 to 30 cm thick layer ofpermeable subbase made up of either a 2.5 cm maximumsize aggregate that is separated from the underlying soil witha non-woven geotextile that prevents the soil particles frommigrating into the subbase but allows water to drain into thesoil.

Providing a capability for infiltration of storm waterthrough permeable pavements to the subsurface reducesthe peak flows along stream and drainage channels andreduces the risk of floods (Boving et al., 2008; Pratt, 1999;Tennis et al., 2004). Furthermore, these pavements areeffective in reducing the pollutant loads in stormwater runoff(Boving et al., 2008; Kwiatkowski et al., 2007; Legret andColandini, 1999; Legret et al., 1996, 1999). Legret et al. (1996)concluded that runoff waters passing through porous pave-ments contain markedly lower pollutant loads than thosefrom a reference catchment due to the accumulation ofmetallic micro-pollutants from runoff waters on the surfaceof the pervious pavement. Nevertheless, there is still aquestion as to whether pervious pavements actually improvethe quality of urban streams or simply shift the contamina-tion problem to groundwater (Kwiatkowski et al., 2007).

Over the past several years, we have been working todevelop a series of passive and semi-passive technologiesthat are capable of reducing the loading of metals and organiccontaminants from parking lots. The work reported in thispaper elucidates the trace metal geochemistry of perviouspavements. Our hypothesis is that pervious concrete pave-ments can serve as an important element of a systemdesigned to reduce contaminant loading. More specifically,we set out to describe both the trace metal retentionpotential of pervious pavements but also their potential toleach from concrete. The investigative approach involvesbatch and 1-D column experiments and model studies withPHREEQC (batch and 1-D reactive transport) to evaluate theefficacy of using permeable and reactive pavements tocontrol trace metal contamination associated with urbanrunoff.

2. Materials and methods

A pervious concrete block was prepared from Portlandcement type 1 and limestone aggregate No .8 (9.5 mm to2.36 mm) (ASTM Standard C 33, 2013), a common limestoneaggregate manufactured in Columbus, Ohio. An aggregate tocement ratio of 4.5 and water to cement ratio of 0.38 (byweight) was used in the concrete batch. About 10% (byweight) of Portland cement was mixed with limestone

aggregate for about 1 min to coat the surface of aggregateswith cement. The rest of the Portland cement and water wereadded to the concrete batch, and mixed manually for about3 min. After pausing for 2 min, the concrete batch was mixedfor an additional 3 min.

The batch was placed into a cylindrical low-densitypolyethylene (LDPE) mold in three layers. After placing thefirst layer, the surface of the mixture was struck 25 timeswith a rod to squeeze the mixture. The mold was then placedon a vibration table and shaken at high speed for 10 s. Thesame procedure was applied for the last two layers and apiece of wet cloth was laid over the top of the mold. The clothwas kept wet but not allowed to drip water. The sample wasstored at room temperature in a closed humid environmentfor 28 days. The final length and the diameter of the concretesamplewere 9.5 cmand 8.6 cm, respectively. The sample had aporosity of 10% measured using the Archimedes Principle(Montes et al., 2005).

2.1. Chemical analysis and phase characterizations

A qualitative assessment of the mineralogical assemblageof pervious concrete and hardened Portland cement wascarried out at 28 days using X-ray powder diffraction (XRD)of ground-up samples. The analysis was performed with aScintag XDS-2000 X-ray diffractometer (CuKα radiation) atthe Institute for Materials Research of the Ohio StateUniversity. This sample of pervious concrete was mainlycomposed of calcite and dolomite as suggested by their sharppeaks. Portlandite and quartz are among the minor phases(Fig. 1a). In addition, the XRD spectrum of the hardenedPortland cement indicates the presence of ettringite, hydro-talcite, monocarboaluminate and calcium silicate hydrate(CSH) (Fig. 1b). The CSH peak overlapped with the calcitepeak. The total elemental analysis of Portland cement andpervious concrete was determined by Elemental Analysis,Inc. (Lexington, KY) using proton induced X-ray emission(PIXE) analysis where proton beams are used as excitation ofthe atoms in the samples to produce characteristic X-rays(Table 1). Statistical error associated with each elemental isalso given in Table 1. Crushed pervious concrete washomogenized, providing a subsample of about 20 g. Thatsubsample was further pulverized to b200 mesh in size. Afterthe final homogenization, an aliquot of approximately 1 gwas taken from the sieved portion and used for PIXE analysis.

Scanning electronmicroscope (SEM) images of the perviousconcrete surfaceswere prepared for samples collected from theend of the 1-D column, after a solution spiked with Cu, Pb andZn was sprayed on the pervious concrete block for 135 h.Energy dispersive spectroscopy (EDS) analysis at 25 keV used aBruker QUANTAX SEM at the School of Earth Sciences of theOhio State University.

2.2. Experiments

Ultra-pure water (Millipore, 18.2 MΩ·cm at 25 °C) andtracemetal grade nitric acid (Fisher Scientific) were used in theexperiments. LDPE bottles and FEP tubing were used in theexperiments. Eluates were filtered through 0.45 μm mem-branes and acidified. New pipette tips were for each samplepreparation. Conductivity standards and pH buffers were used

Fig. 1. XRD pattern for pervious concrete (a) and hardened Portland cement at 28 days (b) (c: calcite, d: dolomite, q: quartz, p: portlandite, e: ettringite,m: monocarboaluminate, ht: hydrotalcite, csh: CSH).

Table 1PIXE analysis of Portland cement and pervious concrete.

37U. Solpuker et al. / Journal of Contaminant Hydrology 161 (2014) 35–48

to calibrate the conductivity meter (Oakton RS-232) and thepH meter (IQ Scientific Instruments), respectively before eachuse. Calibration standards and spiked solutions of Pb, Zn and Cuwere prepared by using certified solutions (Inorganic Ven-tures) of known concentrations. A certified reference material(NIST 1643e) was analyzed and compared to reference valuesfor accuracy. The percent errors for Ca, Al, Mg, Na, K, Fe, Cu, Zn,and Pb were 7%, 1%, 5%, 1%, 2%, 5%, 7%, 6%, and 2%, respectively.Internal standards, check standards and blank samples wererun periodically to check for the drift in the analysis. Percentrelative standard deviation (% RSD)was 3% or lower formost ofthe elements except K and Nawhich had an RSD of 14% and 4%,respectively.

Element Portland cement (mg/kg) Pervious concrete (mg/kg)

Ca 319,580 ± 3200 250,160 ± 2500Mg 14,840 ± 610 50,650 ± 580Al 21,740 ± 450 6350 ± 160Si 77,110 ± 770 23,890 ± 240S 16,480 ± 280 2990 ± 80Fe 16,270 ± 160 5520 ± 60Cl 2300 ± 120 410.7 ± 42.8K 6930 ± 220 1420 ± 80Ti 1,880 ± 110 384 ± 38.5Cr 106.5 ± 11.3 18.98 ± 5.4Mn 167.6 ± 8.3 140.8 ± 4.9Ni 21.0 ± 2.6 5.0 ± 1.5Cu 58.4 ± 2.7 10.8 ± 1.3Zn 170.9 ± 3.8 25.7 ± 1.5Br 65.3 ± 3.7 10.1 ± 1.4Rb 47.6 ± 4.7 12.4 ± 2.1Sr 384.0 ± 11.6 134.7 ± 5.3Zr 810.011.8 BDLa

Pb 33.2 ± 6.4 BDLa

a Below Detection Limit (BDL).

2.2.1. Batch experimentsThe leaching behavior of the pervious concrete was tested

following the European Standard CEN/TS 14429 (2004). Thistest is used to determine the influence of pH on the leachabilityof inorganic constituents from a material, inferred from theleachant composition at different pH values and the acidneutralizing capacity of the material. Crushed pervious con-crete sampleswere sieved to a grain size of less than 1 mmandplaced into LDPE bottles. Ultra-pure water was added toprovide a liquid to solid ratio of 10 ± 0.2 (L/kg). Testing wasperformed at eight different pH values across a range from 4 to12 at room temperature. Predetermined quantities of tracemetal grade nitric acid solutions were added to the homoge-nized samples to provide the desired pH values. After theaddition of acid, samples were agitated on a shaking table.Equilibrium of the suspension was considered to have beenreached when the difference between each pH measurement

of the suspension at 44 and 48 h of agitation differed by lessthan 0.3 pH units. The eluates were filtered through a 0.45 μmmembrane, acidified with nitric acid and analyzed for cationswith a Thermo Finnigan Element 2 ICP-Sector Field-MS.

2.2.2. 1-D column experimentThe pervious concrete block was placed in a LDPE column

with a spray nozzle at the top and a sampling port at thebottom. Ultrapure water was acidified to a pH of 4.3 ± 0.1

Table 2Thermodynamic data and the initial quantities of phases for calculations with PHREEQC.

Phase Reaction Log K Initial quantity(mol/kg dry matter)

Calcitea CaCO3 = Ca+2 + CO3−2 −8.48 3.49

Dolomitea CaMg(CO3)2 = Ca+2 + Mg+2 + 2CO3−2 −17.09 2.08

CSHb Ca1.7SiO3.7:1.7H2O = 1.7Ca+2 + H2SiO4−2 + 1.4OH− −11.28 0.53

Quartza SiO2 + 2H2O = H4SiO4 −4.00 0.33Portlanditea Ca(OH)2 + 2H+ = Ca+2 + 2H2O 22.804 0.17Monocarboaluminatec Ca4Al2(CO3)(OH)12:5H2O = 4Ca+2 + 2Al(OH)4− + CO3

−2 + 4OH− + 5H2O −31.47 0.08Ettringited Ca6(Al(OH)6)2(SO4)3:26H2O = 6Ca+2 + 2Al(OH)4− + 3SO4

−2 + 26H2O −44.90 0.015Hydrotalcitee Mg2Al(CO3)0.5(OH)6:H2O + 6H+ = 2 Mg+2 + Al+3 + 0.5CO3

−2 + 7H2O 25.43 0.026Fe-monosulfatef Ca4Fe2(SO4)(OH)12:6H2O + 12H+ = 4Ca+2 + 2Fe+3 + SO4

− + 18H2O 66.05 0.05CZSHg Ca4Si4ZnO12(OH)2:4H2O = 4Ca+2 + Zn(OH)2 + 4H2SiO4

−2 −40.00 3.3 × 10−5

Cr-monosulfateh Ca4Al2O6(CrO4):15H2O = 4Ca+2 + 2Al(OH)4− + CrO4−2 + 4OH− + 9H2O −30.33 3.5 × 10−4

Pb(OH)2a Pb(OH)2 + 2H+ = Pb+2 + 2H2O 8.15 6.6 × 10−6

Cu(OH)2a Cu(OH)2 + 2H+ = Cu+2 + 2H2O 8.674 1.7 × 10−5

Brucitea Mg(OH)2 + 2H+ = Mg+2 + 2H2O 17.10 –

Fe(OH)3(am)a Fe(OH)3 + 3 H+ = Fe+3 + 3H2O 4.89 –

Boehmitea AlOOH + 3H+ = Al+3 + 2H2O 8.578 –

a MINTEQ.V4 database (Allison et al., 1990).b Rothstein et al. (2002).c Lothenbach and Winnefeld (2006).d Perkins and Palmer (1999).e Johnson and Glasser (2003).f Blanc et al. (2010).g Tommaseo and Kersten (2002).h Perkins and Palmer (2001).

Table 3Parameters used in the surface complexation model.

Surface parameters

Adsorbent Hydrous ferric oxideBinding site (weak) 2.31 sites/nm2

Binding site (strong) 0.05775 sites/nm2

Specific surface area 600 m2/gMass 0.1 g

38 U. Solpuker et al. / Journal of Contaminant Hydrology 161 (2014) 35–48

using trace metal grade nitric acid and sprayed over theconcrete sample homogeneously with an intensity of2.7 cm3/min for approximately 190 h. The experiment wascontinued for an additional 135 h using a solution with10 ppb Zn, Cu and Pb and a pH of 4.3 ± 0.1. Spiked solutionwas prepared daily from concentrated standards and pH wasadjusted by adding diluted trace metal grade nitric acid.

A peristaltic pump maintained the flow of solutions intoand out of the pervious concrete block. Specific conductanceand pH were measured immediately after sampling. Eluateswere sampled periodically and stored in LDPE bottles, filteredthrough a 0.45 μm membrane and acidified with trace metalgrade nitric acid for cation analysis using Thermo FinniganElement 2 ICP-Sector Field-MS.

2.3. Modeling

The geochemical code PHREEQC (version 2.18.3) (Parkhurstand Appelo, 1999) was used to model the leaching behavior ofpervious concrete in batch and 1-D column experiments. TheMINTEQ.V4 thermodynamic database was used in simulationsbut equilibrium constants of some of the particular mineralphases associated with concrete were compiled from differentsources.

2.3.1. Batch modelingGeochemical modeling including surface complexation

was used to simulate the leaching behavior of perviousconcrete at different pH values. The Davies equation wasused for calculating activity coefficients of ion complexes. Itwas assumed that equilibrium would be attained betweenthe minerals and the solutions. The dissolution of CSH,quartz, dolomite and portlandite is assumed to be kineticallycontrolled. The kinetic reaction for the CSH is assumed to be a

function of the activity of hydrogen and the departure fromequilibrium. The rate equation used for CSH is

RCSH ¼ kCSH : aHþ� �0:2

: 1−SRCSHð Þ: mCSH=moCSHð Þ ð1Þ

where a is the activity of hydrogen ion, k is the rate constant(10−8 mol/L·s), mo is the initial moles of CSH, m is the molesof CSH at a given time and SR is the saturation ratio:

SR ¼ IAP=K ð2Þ

where IAP is the ion activity product and K is the equilibriumconstant. The rate equations for quartz, dolomite and portlanditeare given in Table 4.

Trace metal bearing phases such as Fe-monosulfate,Cr-monosulfate, zinc-bearing calcium silicate hydrate (CZSH),Cu(OH)2 and Pb(OH)2 were included in the model in additionto phases identified with the XRD analyses. CSH has a variablecomposition and exhibits increasingly incongruent solubility asits Ca/Si ratio increases (Kersten, 1996; Kulik and Kersten,2001; Stronach and Glasser, 1997; Walker et al., 2007). Toovercome this complication, Rothstein et al. (2002) used asimple approach to formulate an IAP from the mostabundant ions, fixing the ratios to maintain charge balance.

Fig. 2. The conceptual model for pervious concrete used in 1-D reactive-transport modeling.

39U. Solpuker et al. / Journal of Contaminant Hydrology 161 (2014) 35–48

Assuming the CSH to have a Ca/Si ration of 1.7 and using themost abundant calcium and silicon ions in the pore solutionresult in IAP = [Ca2+]1.7[H2SiO4

−2][OH−]1.4.Table 2 lists the phases and their initial quantities used in

the modeling. The initial quantities of each phase werecalculated based on establishing a mass balance between theavailable quantities of all elements determined by the chemicalanalysis of the pervious concrete (Table 1) and the totalquantities of elements used in the reconstructedmineralogy ofthe pervious concrete. The error was ≤2% for all the elementsconsidered except calcium which has 16% error.

Surface complexation is modeled based on the diffuse-double layer (DDL) theory of Dzombak and Morel (1990) forcomplexation of trace metal ions on hydrous ferric oxides.PHREEQC calculated the diffuse-double layer compositionaccording to the method of Borkovec and Westall (1983).Table 3 shows the parameters used in the surface modeling.Although, there are other phases that can be used as adsorbentssuch as CSH, only hydrous ferric oxides were considered as theadsorbent due to database restrictions.

2.3.2. 1-D reactive-transport modelingTwo types of porosity, namely capillary and matrix

porosities, were assumed present in the pervious concrete.Capillary and matrix porosities are connected to each otherbut the former has significantly greater influence on

Table 4Rate laws used in simulations.

Phase Dissolution rate laws (20 °C)

Calcitea (1.0 × 10−4.32 (aH+) + 1.0 × 10−7.59 (aCO2) + 1.0 × 10−

Dolomiteb (1.0 × 10−4.92 (aH+)0.5 + 1.0 × 10−6.47 (aCO2)0.5 + 1.0 × 1Quartzc 1.0 × 10−13.7 (1-SRQuartz) · (mQuartz/moQuartz)CSH 1.0 × 10−8 (aH+0.2) · (1-SRCSH) · (mCSH/moCSH)Portlandite 1.0 × 10−7.25 (1-SRPortlandite) · (mPortlandite/moPortlandite)Ettringite 1.0 × 10−8.75 (1-SREttringite) · (mEttringite/moEttringite)Monocarboaluminate 1.0 × 10−8.75 (1-SRMonocarboaluminate) · (mMonocarboaluminate/mHydrotalcite 1.0 × 10−9.25 (1-SRHydrotalcite) · (mHydrotalcite/moHydrotalcite)Monosulfate-Cr 1.0 × 10−11.25 (1-SRMonosulfate-Cr) · (mMonosulfate-Cr/moMonosu

Monosulfate-Fe 1.0 × 10−10.5 (1-SRMonosulfate-Fe) · (mMonosulfate-Fe/moMonosul

CZSH 1.0 × 10−10.5 (1-SRCZSH) · (mCZSH/moCZSH)Cu(OH)2 1.0 × 10−12.0 (1-SRCu(OH)2) · (mCu(OH)2/moCu(OH)2)Pb(OH)2 1.0 × 10−12.7 (1-SRPb(OH)2) · (mPb(OH)2/moPb(OH)2)NaOH 1.0 × 10−6.75 (1-SRNaOH) · (mNaOH/moNaOH)KOH 1.0 × 10-6.75 (1-SRKOH) · (mKOH/moKOH)

Rate constants: aPlummer et al. (1978), bBusenberg and Plummer (1982) (rate const

transport processes (Galindez et al., 2006). The acidicinfluent (pH ≈ 4.3) flows predominantly through capillarypores and reacts kinetically with concrete phases presentalong the interconnected pore system. The alkaline porewater found in the matrix is assumed at or near equilibriumwith concrete phases. PHREEQC was configured to representmobile and immobile “stagnant” zones, which correspondedto the capillary and matrix porosities, respectively. Thepervious concrete block was discretized as ten cells of0.95 cm each. The time step for each advective shift is101 s. Dispersion is ignored in this model. One stagnant cell isassociated with each mobile cell.

During 1-D transport, mixing of the mobile and immobilepore waters is simulated explicitly with MIX function inPHREEQC. During mixing, it is assumed that only portlanditeand CSH dissolve kinetically in the alkaline immobile porewater whereas all other concrete phases react kinetically inthe mobile pore water (Fig. 2).

The general rate law for the kinetic reactions is defined inTable 4 as:

Rp ¼ kp� mp=mop

� �: 1−SRp

� �ð3Þ

where kp is the reaction constant (mol/L/s),mp is the quantityof the phase at a given time (mol), mop is the phase quantity

9.94 (aH2O)) · (1–100.67xSICalcite) · (mCalcite/moCalcite)0.67

0−10.76 − 1.0 × 10−4.85 (aHCO3−)) · (1-SRDolomite) · (mDolomite/moDolomite)0.67

oMonocarboaluminate)

lfate-Cr)fate-Fe)

ant from dolomite sample B at 20 °C), cVan Lier et al. (1960); SIp = log (SRp).

Table 5Initial conditions and concentrations of elements assumed forthe pore waters.

T (°C) 20.0

pH 12.8

Elements Concentration (mM)

Al 6.80 × 10−2

C 1.30 × 10−2

Ca 0.34 × 101

Cr 5.50 × 10−3

Cu 2.60 × 10−5

Fe 3.60 × 10−3

K 3.00 × 101

Mg 2.50 × 10−4

Na 1.30 × 101

Pb 4.10 × 10−6

S 1.30 × 10−1

Si 3.50 × 10−1

Zn 2.00 × 10−5

40 U. Solpuker et al. / Journal of Contaminant Hydrology 161 (2014) 35–48

at time zero (mol) and SRp is the saturation ratio of the phase.The kinetic reaction constants for concrete phases wereestimated by fitting the simulated aqueous concentrations tothe experimental results (Table 4). The initial conditions andcomposition of the pore waters are given in Table 5.

3. Results

3.1. Batch experiments and modeling

3.1.1. Acid neutralizing capacity of pervious concreteThe acid neutralizing capacity (ANC) of the pervious

concrete was measured following the European StandardCEN/TS 14429 (2004). ANC is a measure of the quantity ofacid needed to maintain the pH of the solution at somedesired value. The pervious concrete in this study has anANC profile that is typical of concrete slabs (Schiopu et al.,2007). It also has a large acid neutralizing capacity due to thelarge quantities of calcite, dolomite and portlandite phases thatcan donate carbonate and hydroxide ions to the solution(Fig. 3). The pH of solution decreases sharply from pH 12 to

Fig. 3. Acid neutralizing capacity (

about pH 6 with a small addition of acid (b2 mol H+/kg).However, the amount of acid significantly increases to about9 mol H+/kg in order to reduce the pH from 6 to 5.

3.1.2. Major ion leaching from pervious concreteFig. 4 shows the experimentally measured concentration

of selected major ions in an aqueous solution in equilibriumwith the pervious concrete at a particular pH (black circles).The solid lines represent model results from PHREEQC wherethe chemical equilibrium between the concrete phases andthe solution was sought for all elements except Si, Ca and Mg.Dissolution and precipitation of CSH, quartz, portlandite anddolomite were modeled kinetically to describe the behavior ofthese elements. The gray lines represent the associated phasecontribution for a given element where positive and negativevalues indicate precipitation and dissolution, respectively.These lines also assist in showing how the presence or absenceof each phase can affect the overall concentration of anelement. For example, it is the equilibration of Al-richphases, hydrotalcite and boehmite, with the solution thatreduces the Al concentration at different pH values. Similarly,eliminating brucite causes Mg concentrations to increase athigh pH values.

Within the given pH range, Si concentrations in solutiondecrease as the pHs of the solutions decrease. Si concentra-tion measured at pH b 4 is about two orders of magnitudehigher than the one measured at pH N 12 (Fig. 4a). For Si, themodel fit shown assumes kinetically controlled dissolution ofCSH and quartz. Additionally, amorphous SiO2 and CZSH areallowed to precipitate from the solution. The modeling showsthat observed concentration profile is related mostly to thedissolution of calcium silicate hydrates (CSH) under moreacidic conditions (Fig. 4a). Only at low pH values is amorphoussilica in equilibrium with the solution and only a portion ofCZSH dissolved to reach equilibrium with the solution at highpH values.

Measured Ca concentrations are relatively constant in therange from pH 6 to pH 12. At low pH values, Ca concentrationsare an order of magnitude higher (Fig. 4b). Modeling resultssuggest that calcite, dolomite and portlandite are the mainphases that control the concentration of Ca. The model shows

ANC) of pervious concrete.

41U. Solpuker et al. / Journal of Contaminant Hydrology 161 (2014) 35–48

that calcite is no longer a stable phase at low pH values, whichcauses an increase in the Ca concentration. Dolomite andportlandite dissolve kinetically at all pH values but dolomitereaches equilibrium at pH 5 to 7.

Mg concentrations remain relatively constant betweenpH 7 and pH 10 but in general, Mg concentrations increase asthe pH of the solution decreases (Fig. 4c). At high pH values(pH N 10), the concentration of Mg is three to four ordersmagnitude lower. According to the model, this decrease isassociated with equilibrium constraints provided by bruciteand hydrotalcite with the solution. Dolomite dissolves at all pHvalues but hydrotalcite is not at equilibrium with the solutionsat pH ≤ 7.

Finally, as shown in Fig. 4d, Al concentrations are relativelylowover a pH range between6 and 10, but ismuch higher underacidic (pH b 6) and alkaline (pH N 10) conditions. Themodelingsuggests that Al concentrations in the solutions are controlled bythe combination of Al-bearing phases (e.g. ettringite, hydrotal-cite, monocarboaluminate and boehmite). Boehmite is the onlyphase that is in equilibrium with the solutions at relatively lowpH values (pH b 7), while ettringite and monocarboaluminatereach equilibrium only under highly alkaline conditions(pH N 11). Additionally, hydrotalcite reaches equilibrium across3 pH units between pH 9 and pH 11.

Fig. 4. Major ion concentrations of solutions equilibrated with pervious concrete. samdotted black lines: model without the specified phase, dashed black lines: backgrouphase, the positive and negative values indicate precipitation and dissolution, respe

3.1.3. Trace metal leaching from pervious concreteFig. 5 shows the concentrations of trace metals in solutions

at equilibriumwith respect to pervious concrete (black circles).In numerous PHREEQC modeling trials, we examined thepotential constraints exerted by a variety of possible solidphases that contain these trace metals, and the controls exertedby differing initial concentrations. The purpose of the modelingwas to find a stable phase that could explain the observedconcentration constraints at equilibrium. Thus, in addition to100% of initial phase quantities used in modeling (Table 1), 10%of the initial amount of the phase was also considered wherenecessary, assuming that the rest of the solid phases mightpotentially occur in the matrix and be unavailable for reaction.Model results show the outcomes of both precipitation/dissolution equilibrium reactions (labeled ppt./diss. in the figurelegends) and surface complexation reactions (labeled as DDL).

In the case ofmeasured Fe concentrations, there is a trend indeclining concentrations from pH 4 to pH 7. At higher pHvalues (N7), concentrations again increased (Fig. 5a). Thisbehavior wasmodeled in terms of the dissolution/precipitationreaction of 100% Fe-monosulfate and amorphous Fe(OH)3.Fe-monosulfate reaches equilibrium only at high pH values(pH N 11) and amorphous hydrous ferric oxide precipitatesacross the range pH 4 to pH 11.

ple (L/S = 10) at various pH values (black circles). Solid black lines: model,nd equivalent concentration (BEC), gray lines: phase contributions. For eachctively.

Fig. 5. Trace metal concentrations for solutions equilibrated with pervious concrete sample (L/S = 10) at various pH values (black circles). Dashed black lines:background equivalent concentration (BEC), (a) Solid black line: model, gray lines: phase contributions. For each phase, the positive and negative values indicateprecipitation and dissolution, respectively.

42 U. Solpuker et al. / Journal of Contaminant Hydrology 161 (2014) 35–48

Unlike Fe, the geochemical behavior of the other tracemetals (Cu, Pb, Zn, Cr) as a function of pH cannot beexplained with dissolution/precipitation processes alone.The approach we followed was to consider surface complex-ation in addition to the dissolution/precipitation processes.The measured data show the concentration of Cu to berelatively low between pH 7 and pH 10 with a slight tendencyfor concentrations to increase with increasing pH. Below pH 6,

concentrations of Cu increase significantly. The dissolution/precipitation processes alone (dotted and dash/dotted linesFig. 5b) do not explain the observed Cu behavior becauseCu(OH)2 was not stable at pH b 9 and as a result the modeledCu concentrations fit poorly with the measured valuesassuming both 100% and 10% for the initial phase. Adding thepossibility for surface complexation of Cu provides a possibleexplanation of the concentration behavior below pH b 7

43U. Solpuker et al. / Journal of Contaminant Hydrology 161 (2014) 35–48

(dashed line, Fig. 5b). However, this process ended up with Cuconcentrations less than the observed values in the pH range 6to 10 (Fig. 5b).

Pb concentrations exhibited the typical saddle-shapedbehavior of the other metals with concentrations increasingas a function of pH at pH b 6 and pH N 11. Pb concentrationswere below detection (10−10 mol/L) between pH 6 andpH 11. Modeling showed that Pb(OH)2 was stable onlybetween pH 9 and pH 11 and that equilibrium dissolution/precipitation processes again could not explain the Pbbehavior (see dotted and dash/dotted lines Fig. 5c). Modelingsuggested that lower concentrations of Pb at pHs b 11 couldbe simulated only by assuming that 10% of the initial phasewas involved in the reactions (solid line, Fig. 5c).

Measured Zn concentrations are highest at low pH values(pH 4 to pH 5) and decline up to 3 orders of magnitude as pHincreases. In modeling, Zn-bearing CSH (CZSH) was used asthe zinc phase to constrain dissolution/precipitation pro-cesses because it tended to be stable at high pH values. Thisphase was unstable at lower pH values and leaving onlysurface complexation as the only possibility for lowering theconcentration of Zn. The solid line in Fig. 5d represents ourbest fit of measured data with the model with CZHS as themineral phase at 10% of the initial phase quantity andsurface complexation.

Unlike Zn, Cr concentrations were observed to decrease asthe pH of the solution decreased, except at the lowest pHvalue (b4). The PHREEQC modeling showed that theCr-bearing concrete phase, Cr-monosulfate, is not stable atpH values b12. Thus, concentrations modeled assuming onlythe equilibrium dissolution of this phase (assuming both100% and 10% initial phase quantity) were unacceptably highrelative to observed values. The surface complexation modelwith 10% initial phase quantity produced significantly lowerconcentrations of Cr especially at 5 b pH b 10 (solid line,Fig. 5e).

One of the reasons for the discrepancies between theobserved and the simulated concentrations is that ourconceptualization uses a rather simplistic conceptualizationof sorption. There could be different types of surfacesavailable for complexation, such as CSH, besides ferrichydrous oxides that we modeled (Moulin, 1999; Rose et al.,2000; Ziegler and Johnson, 2001). Furthermore, models showelevated trace metal concentrations at high pH valuescompared to the observed values. For example, althoughthe modeled Zn concentration is about an order of magnitudehigher than the observed values at high pH values, Zn bearingphases cannot reach equilibrium at high pH values or Zncannot be adsorbed to charges surfaces. This is due to thespeciation of the Zn at high pH values, where the formation ofhigh concentrations of Zn(OH)4−2 prevents Zn bearingmineral phases from precipitating or being adsorbed to thesurfaces. Nonetheless, surface adsorption help to explain theleaching behavior of trace metals better than the dissolution/precipitation models alone.

3.2. 1-D column experiments and modeling

Through the course of the 1-D column experiment, wemonitored indicator variables, pH and specific conductance,selected major ions and selected trace metals. During the first

190 h of the experiment, only acidic water, representingslightly acid rain, was passed through the column. During thelast 125 h, synthetic urban runoff containing trace metals aspassed through the column.

Changes in pH and specific conductance through time areshown in Fig. 6a. The pH of the leachate decreased frompH 12.5to pH 10.5 at the end of the experiment at 325 h. Smallfluctuations associated with the pH measurements are likelyrelated to the heterogeneity of the sample. Specific conductancedecreased significantly in the first 60 h from 3000 μS/cm to 286μS/cm which is approximately 28 times higher than the initialspecific conductance of the influent solution. Subsequently, therate of decline slowed with the specific conductance decreasingto 101 μS/cm at the end of the experiment. Modeling suggeststhat the observed trends in the pH and the specific conductancecould be explained by mixing of high pH and high specificconductance porewaters in the immobile zonewith lowpHandlow specific conductance pore waters in the mobile zone. Thedual porosity formulation in the 1-D transport model generatedthe observed pH profile through time reasonably well (Fig. 6a).

The concentration behavior ofmajor ions is shown in Fig. 6band c. In the case of Ca, and Al, there is an initial markeddecrease in concentrations (Fig. 6b) followed by a slow butsteady decline. Mg concentrations increase slightly and thenremain steady through the remainder of the experiment. Therate of decline in concentration of K and Na becomes less intime with an overall reduction of two to three orders ofmagnitude (Fig. 6c). Si concentrations decreased slowly to theend of the experiment (Fig. 6d).

The model fits these observed patterns of decline well(Fig. 6b and c). It points to a slow consumption of portlanditeand CSH in the immobile zone, providing a continuous sourcefor Ca and Si. In effect, the mobile zone concentrations of Ca andSi are not high enough to explain the observed values alone(Fig. 6b, d). The model replicates the tendency for Mgconcentrations to increase slightly and decline back to aconstant concentration towards the end of the experiment(Fig. 6b). The concentration of Mg is controlled by dolomite andhydrotalcite dissolution in the mobile zone. Specifically, theconcentration of Mg decreases after the first 125 h in responseto the decrease in dolomite. The slow hydrotalcite dissolutionalso contributes Mg. Al and Fe decline slowly throughout theexperiment (Fig. 6b, d). This result is explained by the slowdissolution of Al and Fe bearing phases (e.g. ettringite,monocarboaluminate, hydrotalcite and monosulfate-Fe) in themobile zones. These elements eventually become depleted inthe immobile zones due to mixing. Thus, the immobile zonecontribution of these elements is most evident for a short timeat the beginning of the experiment. Themodel suggests that thetemporal behavior of Na and K concentrations is caused by thedepletion of these elements in the immobile zones. The processessentially involves the linear mixing of mass in the immobilezone with a smaller constant mass in the mobile zone.

The behavior of the trace metals Cu, Pb and Zn is similar inthe first 190 h. The measured concentrations are low anddecrease slowly over the first 190 h (Fig. 6e). This is modeledreasonably well in terms of the slow dissolution of trace-metalbearing phases in the mobile zone and a decreasing contribu-tion from the immobile zone. After a marked decrease in thefirst 50 h, Cr concentrations continued to decline somewhatlinearly for an additional 140 h after which it remained nearly

Fig. 6. pH, specific conductance and ICP-MS analysis of effluent through time and results of the PHREEQC simulation.

44 U. Solpuker et al. / Journal of Contaminant Hydrology 161 (2014) 35–48

constant (Fig. 6d). The model suggests that the observedbehavior in Cr concentrations can be explained by the slow lossof Cr from the immobile zone through time. After 190 h, onlythe slow dissolution of Monosulfate-Cr in the mobile zonecontinues to contribute Cr.

The capacity of pervious concrete to immobilize certain tracemetals was tested by spraying a synthetic solution representingcontaminated urban runoff (10 ppb Cu, Pb and Zn) with a pH of

4.3 ± 0.1 over the concrete for 125 h. Spraying of the spikedinfluent solution began after 190 h which caused an increase inthe concentrations of Cu, Pb and Zn relative to the concentra-tions observed earlier during the first 190 h. The concentrationsof Cu and Pb are stable until the end of the experiment. Znconcentrations, however, decrease slowly. Fig. 7 shows thedegree of the trace metal immobilization as a ratio of theconcentration of leachate (C) to the initial concentration of Cu,

Fig. 7. The degree of the trace metal immobilization as a ratio of concentration of leachate (C) to initial Cu, Pb and Zn spiked acidic solution (Co).

45U. Solpuker et al. / Journal of Contaminant Hydrology 161 (2014) 35–48

Pb and Zn in the spiked acidic solution (Co). The lowest andhighest medians for the C/Co ratios are evident with Pb and Zn,respectively. Pb immobilization was greater than either Cu orZn. Zn is the most mobile of the three and it also exhibits thelargest variability in terms of this ratio. PHREEQC calculatespositive saturation indices for CuO, Cu(OH)2 and Pb(OH)2whichcan explain the immobilization of Cu and Pb. However, neitherzincite nor Zn(OH)2 has positive saturation indices under theconditions of the experiment. This result is due to highconcentrations of X(OH)4−2 species which inhibits saturation ofZn phases. Additionally, Zn immobilization could also be relatedto adsorption or surface precipitation, although the latter isassociated with slow kinetics.

Previously, Coleman et al. (2005) published an EDSspectrum of a fresh concrete surface, which indicated thatcalcium, aluminum, silicon, iron, magnesium, sulfur, sodium,potassium and trace quantities of titanium, manganese andchromium are the typical constituents of the Portland cement.SEM images of the pervious concrete block surfaces at the end ofthe 1-D column experiment after 132 h of spraying the spikedsolution onto the column show flaky bright irregular precipi-tates in the pore spaces between the dolomite grains (Fig. 8a).The corresponding EDS analysis indicates the presence of trace

Fig. 8. SEM images of the pervious concrete block surfaces at the end of the 1-D colcolumn. (a) Zn, Cu and Pb bearing flaky bright irregular precipitates, (b) the EDS an

quantities of Zn, Cu and Pb in addition to other elementstypically found in Portland cement (Fig. 8b).

4. Discussion

The main goal of this study is to test whether perviousconcrete could function as a passive reactive barrier toattenuate the spread of trace metals from parking lots inurban environments. First of all, the leaching behavior ofconcrete was studied by batch and column experiments andPHREEQC modeling to determine whether the concretematerial itself could serve as a source of pollution. Modelingefforts to explain the leaching behavior of concrete werecomplicated by the extremely complex nature of thismaterial geochemically, because of its varied mineralogy,reactive surfaces and different microenvironments createdby the interaction of capillary and matrix porosities.

Batch experiments show that there is an increasing trendtowards higher concentrations of major elements (Ca, Si, Al, Mg)and trace metals (Cu, Pb and Zn) associated with lower pHvalues. This observed leaching behavior is similar to thatdetermined from other studies (e.g. Karamalidis and Voudrias,2007; Li et al., 2001; Schiopu et al., 2007, 2009; Van Der Sloot,

umn experiment following 132 h with the spiked solution spraying onto thealysis of the precipitates.

46 U. Solpuker et al. / Journal of Contaminant Hydrology 161 (2014) 35–48

2002). The observedmajor element and trace element (Cr, Cu, Pband Zn) leaching behavior is best explained by the dissolution/precipitation of concrete phases and surface complexation,respectively. Generally higher pH values reduce loading buttrace metals do tend to increase to some extent at pH N 9.However, surface complexation did not explain the experimentaldata at high pH values (pH N 9). The predicted model concen-trations are especially high for Zn at high pH values. Karamalidisand Voudrias (2009) observed similar trends for Zn andsuggested that a combination of surface complexation andsurface precipitation was the dominant mechanism for loweringthemodel Zn values. Among the tracemetals, only the leaching ofFe could be explained by the dissolution/precipitation alonewithreactions of Fe-monosulfate and Fe(OH)3(a).

The 1-D column experiment showed that water (pH ~ 4.3)passing through pervious concrete experiences an increase inpH because of reactions with portlandite, calcite etc. in theporous cement. However, the high pH values associated withpervious concrete are transient in nature and pH will decreasewith time. High pH waters were also observed in long-term(≥100 days) dynamic leaching tests and field tests on concretepaving slabs (Schiopu et al., 2009). Schiopu et al. (2009) usedimpervious concrete slabs in their experiments and therefore,diffusion was important in their transport models. Neverthe-less, their dynamic leaching experiments and stagnation fieldtest showed high pHwaters in the range from pH 10 to pH 12.For most of the elements, after an initial marked decline inconcentrations, the decrease in the concentrations was gener-ally slow. Ca and Mg had the highest and the lowestconcentrations among the major elements, respectively. Pbdisplayed the least amount of leaching and Cu, Zn, Cr and Fetending to be somewhat larger. The concentrations of Ca, Si andAl were comparable to the results of dynamic leaching tests ofSchiopu et al. (2009).

A dual porosity conceptualization for concrete, i.e., bothcapillary and matrix porosity, was invoked in other studies(e.g. Galindez et al., 2006) where capillary porosity has sig-nificantly greater influence on transport processes. Schiopuet al. (2009) also used the mixing between matrix porewaters and a leachate compartment to explain the dynamicleaching where they defined the leaching compartment asthe immobile zone. Here, the capillary pores and matrix poreswere defined as mobile and immobile zones, respectively. Theobserved leaching behaviors could be well explained by aconceptual model encompassing two main processes, dissolu-tion of mineral phases in the pores and mixing of mobile andimmobile waters in themedium. In order to show the effects ofstagnant zone on the concentration behavior of the effluentsolution, the relative contribution of the stagnant zone wasboth increased and decreased. Increasing stagnant zone con-tribution increased the pH and the Ca concentrations of theeffluent solution (Fig. 6a, b). Decreasing the stagnant zonecontribution lowered the pH and Ca concentrations of theeffluent solutions (Fig. 6a, b).

Our study envisions that pervious concrete could functionas a passive reactive barrier to attenuate the spread of tracemetals from parking lots in urban environments until theANC is exhausted in future. Previous studies demonstratedthat when porous pavements are used in the field, there ispotential for improvements in the water quality of urbanrunoff such as reducing organic and metal contaminants,

suspended solids, and chemical oxygen demand (COD) loadscompared to conventional pavements (e.g., Boving et al.,2008; Legret and Colandini, 1999; Legret et al., 1999;Newton, 2005; Ranchet et al., 1993). For example, Dierkeset al. (1999) charged porous pavements with syntheticrainwater containing elevated concentrations of Cu, Pb andZn. They found that trace metal retention was very high(N95%) for gravel subbase and the most metals wereprecipitated in the upper 2 cm of the porous concrete. The1-D column experiment, in this study, tested the retentionpotential of pervious concrete for dissolved trace metals andconfirmed the previous studies in that the concentrations oftrace metals were reduced as trace metal spiked syntheticrain water passed through the column (Figs. 6 and 7). Thequantity of trace metal retention is high for Pb and Cu andrelatively small for Zn.

Johnson (2004) summarized basic types of binding mech-anism for tracemetals andmetalloid ions in the cementmatrix.A metal ion could be sorbed or precipitated onto surfaces ofcement minerals, incorporated into hydrated cement mineralsor precipitated in the alkaline cement matrix. Based on thesecondary electron images and back-scattered electron imagesof the crushed concrete surfaces, Coleman et al. (2005)concluded that the uptake of Zn by crushed concrete occurredvia the formation of three discretely precipitated layers on thesurface of the matrix and Cu was immobilized through theformation of foliated precipitate on the surface of the cementmatrix. Furthermore, the immobilization of Pb was controlledby diffusion where isomorphic substitution of Pb for Ca in CSHwas the suggested mechanism (Coleman et al., 2005). In ourmodel, we tested only the precipitation of metal hydroxidesand oxides on the concrete surface which can explain theobserved patterns of Cu, Pb and Zn immobilizationwhich couldbe related to other mechanisms like surface precipitation. Li etal. (2001) reported that the hydroxy-complexes Zn(OH)4−2 andZn(OH)5−3 can be present in a strong alkaline solution and theiranionic properties preclude their adsorption onto the negativesurface of the CSH, but theymay form the calciumzinc complexhydrated compound CaZn2(OH)6.H2O.

5. Conclusions

Batch experiments and PHREEQC modeling suggest thatthe leaching of major ions and trace metals from perviousconcrete is mainly controlled by dissolution/precipitationand surface complexation reactions, respectively. The leach-ability of trace metals increases under acidic conditionsexcept for Cr which has high leachability only when pH = 3.

1-D reactive column experiments show that the effluenthas high pH (pH ~ 10) even after 325 h of spraying with lowpH water (pH ~ 4.3). Specific conductance decreases rapidlyin the first 50 h and then decreases more slowly. Trace metalleaching is higher in the earlier stages of the experiment butbecomes lower after approximately 50 h and continues todecrease slowly with time. The water chemistry in thepervious concrete can be explained by the mixing of theinterstitial alkaline pore waters with the capillary waters. Theinterstitial pore solutions are responsible for the relativelyhigh concentrations of trace metals and major cations in theearly stages of the experiment. Subsequently, the dissolutionof concrete phases and trace metal bearing phases in the

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capillary pores controls the leachability of these elements asthe interstitial pore solutions become diluted by capillarypore solutions.

We conclude overall that prospects are good for perviousconcrete to provide a passive barrier for the control of tracemetals from urban surfaces.

Acknowledgements

Funding for this study was provided as part of the GlobalResearch Laboratory (GRL), Korea project “Novel Technologiesfor Best Management of Non-point Source Pollution”. Authorsthank Trace Element Research Laboratory (TERL) and SubsurfaceCharacterization and Analysis Laboratory (SEMCAL) personnelat the School of Earth Sciences of the Ohio State University fortheir help.

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