metal removal mechanisms 2008

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Effectiveness of sulfate-reducing passive bioreactors for treatinghighly contaminated acid mine drainage: II. Metal removal mechanismsand potential mobility

Carmen-Mihaela Neculita a,c, Grald J. Zagury a,c,*, Bruno Bussire b,c

a Department of Civil, Geological, and Mining Engineering, cole Polytechnique de Montral, Montreal, QC, Canada H3C 3A7b Department of Applied Sciences, UQAT, Rouyn-Noranda, QC, Canada J9X 5E4c Industrial NSERC-Polytechnique-UQAT Chair, Environment and Mine Waste Management, Canada

a r t i c l e i n f o

Article history:Received 6 March 2008Accepted 18 August 2008Available online 12 September 2008

Editorial handling by D. Fortin

a b s t r a c t

Column bioreactors were used for studying mechanisms of metal removal, assessment oflong-term stability of spent reactive mixtures, as well as potential metal mobility aftertreatinghighly contaminatedacidmine drainage (AMD; pH 2.95.7). Several physicochem-ical, microbiological, and mineralogical analyses were performed on spent reactive mix-tures collected from 4 bioreactors, which were tested in duplicate for two hydraulicretention times (7.3d and 10d), with downward flow over an 11-month period. Consistentwith the high metal concentrations in the AMD feed, and with low metal concentrationsmeasured in the treated effluent, the physicochemical analyses indicated very high concen-trations of metals (Fe, Mn, Cd, Ni, and Zn) in the top and bottom layers of the reactive mix-tures from all columns. Moreover, the concentrations of Fe (50.857.8 g/kg) and Mn (0.530.70 g/kg) were up to twice as high in the bottom layers, whereas the concentrations of Cd(6.7713.3 g/kg), Ni (1.805.19g/kg) and Zn (2.5313.2 g/kg) were up to 50-times higher inthe top layers. Chemical extractions and elemental analysis gave consistent results, which

indicated a low fraction of metals removed as sulfides (up to 15% of total metals recoveredin spent reactive mixtures). Moreover, Fe and Mn were found in a more stable chemicalform (residual fraction was 4274% for Mn and 3077% for Fe) relative to Cd, Ni or Zn,which seemed more weakly bound (oxidisable/reducible fractions) and showed higherpotential mobility. Besides identifying (oxy)hydroxide and carbonate minerals, the miner-alogical analyses identified metal sulfides containing Fe, Cd, Ni and Zn. Metal removalmechanisms were, therefore, mainly adsorption and other binding mechanisms withorganic matter (for Cd, Ni and Zn), and the precipitation as (oxy)hydroxide minerals (forFe and Mn). After 15 months, however, the column bioreactors did not lose their capacityfor removing metals from the AMD. Although the metals were immobile during the biore-actor treatment, their mobility could increase from spent reactive mixtures, if stored inap-propriately. Metal recovery by acidic leaching of spent substrates at the end of bioreactoroperation could be an alternative.

2008 Elsevier Ltd. All rights reserved.

1. Introduction

Mining and metallurgical industries deal with contami-nated acidic waters (often called acid mine drainage AMDor acid rock drainage ARD), which are generated by sulfide

0883-2927/$ - see front matter 2008 Elsevier Ltd. All rights reserved.doi:10.1016/j.apgeochem.2008.08.014

* Corresponding author. Address: Department of Civil, Geological, andMining Engineering, cole Polytechnique de Montral, Montreal, QC,Canada H3C 3A7. Tel.: +1 514 340 4711/4980; fax: +1 514 340 4477.

E-mail address: [email protected] (G.J. Zagury).

Applied Geochemistry 23 (2008) 35453560

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Applied Geochemistry

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oxidation during exposure of tailings to O2 and water, inthe absence of sufficient neutralizing minerals. Acid minedrainage is characterized by low pH and high SO24 and me-tal concentrations (e.g. Blowes, 2003). To avoid significantenvironmental impacts, AMD contaminated waters requireeffective technologies for their long-term treatment(Neculita et al., 2007). Lately, there has been an increasing

interest in SO4-reducing passive bioreactors as an alterna-tive technology to traditional water treatment plants forAMD treatment at closed sites, without electricity, and un-der extreme winter conditions (Kuyucak et al., 2006). Pas-sive bioreactors use SO4-reducing bacteria (SRB) which arecapable through their metabolism, of increasing the pHand alkalinity of contaminated water and of immobilizingdissolved metals by precipitating them as metal sulfides.The main mechanism of metal removal in bioreactors isprecipitation in the form of (oxy)hydroxide, carbonateand sulfide minerals (Neculita et al., 2007). Sorption mech-anisms (e.g. adsorption, surface precipitation) and co-pre-cipitation with (or adsorption onto) Fe and Mn oxidescan also occur.

Metal removal mechanisms change during the life of apassive bioreactor (Neculita et al., 2007). Upon start-up,the adsorption of dissolved metals onto organic sites inthe substrate material, as well as (oxy)hydroxide and car-bonate mineral precipitation are important processes ofmetal removal (Machemer and Wildeman, 1992; Gibertet al., 2005; Zagury et al., 2006). Over time, the adsorptionsites become saturated and, once SO4-reducing conditionsare established, sulfide precipitation becomes the predom-inant mechanism of metal removal (Machemer and Wild-eman, 1992). In the case of Fe, the sulfides (H2S and HS

)generated through SRB metabolism react with dissolvedFe and precipitate amorphous sulfides (Psfai et al.,2001). The more reducing the environment, the more re-duced are the forms of sulfides (Herbert et al., 1998).

Amorphous Fe sulfides such as greigite, and mackinawiteare very common metastable Fe sulfides generated by bio-logically induced mineralization. They act as precursors inthe formation of pyrite (FeS2) in highly reducing environ-ments through a series of solid-state transformations(Machemer et al., 1993; Psfai et al., 2001). The SRB favorthe creation of an optimal chemical environment for sul-fide precipitation; however, SRB do not control the growthof sulfide particles which can have a broad size and irreg-ular spatial distribution (Psfai et al., 2001). Pyrite forma-tion can, however, be limited by the rate of SO24reduction, and by Fe availability (Machemer et al., 1993).Although passive bioreactor systems are designed to per-form for several decades, they eventually fail after about10a of continuous operation. Little information is, how-ever, available on the possible fates of spent reactive mix-tures, except for the fact they are sometimes replaced/recharged because they become inefficient (Doshi, 2006).

Solid phase analysis is therefore an important step forelucidating metal removal mechanisms. Moreover, animportant objective of passive bioreactors is to ensurethe stability of the spent reactive mixtures which containmetal precipitates. The stability of spent reactive mixturesdepends on the metals potential mobility, which is relatedto the quality of AMD treated, as well as to metal removal

mechanisms. Results from geochemical modeling confirmthat adsorption and precipitation of metal carbonates and(oxy)hydroxides can occur in batch organic-based bioreac-tors (Waybrant et al., 1998; Zagury et al., 2006; Neculitaand Zagury, 2008). Post-treatment analysis of reactive mix-tures can provide information on how efficient the systemis in removing metals, how long it will last, how available

the metals are to remobilization, and on stability of theenvironment over time (Machemer et al., 1993). Twogroups of approaches are mainly used for the post-treat-ment evaluation of reactive mixtures: mineralogical analy-sis and chemical extractions.

Mineralogical analyses may help to identify the chemi-cal form of metals retained in the solid phase. Few tech-niques are appropriate for the mineralogical analysis ofspent reactive mixtures due to the poor crystallinity ofthe precipitates and/or the relatively low concentrationsof metal sulfides (Song, 2003; Gibert et al., 2005). Amongthese methods, scanning electron microscopy equippedfor backscattered electron imaging (SEM-BSE) has beenthe most successful technique, whereas X-ray diffraction

or iron Mossbauer analyses have been less effective indetecting amorphous metal sulfides (Machemer et al.,1993). The SEM approach coupled with X-ray microanaly-sis has been proven successful for identifying sulfides inreactive mixtures from constructed wetlands (Machemeret al., 1993; Song, 2003), in reactive permeable walls(Herbert et al., 1998) and in passive bioreactors (Gibertet al., 2005; Neculita et al., 2006). Also, amorphous Feand Pb sulfides were reported by Song (2003) using SEM,while makinawite and greigite were found in the studyof Herbert et al. (1998). However, sulfides were not de-tected in spent reactive mixtures after 158 days of bioreac-tor operation (Gibert et al., 2005) whereas in a more recentstudy, SEM analysis indicated the presence of amorphouspyrite in the solid phase from a 350-day batch bioreactor

(Neculita et al., 2006). These results can be partially ex-plained by the fact that the first study used a reactive mix-ture having a single, simpler organic carbon source(municipal compost) for the treatment of an acidic AMD(pH 3.0), whereas the reactive mixture from the last studyhad a more complex organic carbon source (coming frommaple wood chips, leaf compost, and poultry manure)and treated a slightly less acidic AMD (pH 3.94.2).

Chemical analyses such as sequential extraction proce-dures (SEPs) combined with simultaneous determinationof acid volatile sulfides and extracted metals (AVS-EM)are also efficient tools for assessing metal fractionationand potential mobility (Song, 2003; Jong and Parry,2004). The SEP represents an important, widely used, anduseful tool for gaining information on the potential mobil-ity, potential bioavailability and toxicity of metals in theenvironment (Bacon and Davidson, 2008). The ranking ofmetal mobility in SEPs is based on metal concentrationsin the water-soluble and exchangeable fraction, as wellas fractions that are reducible, bound to carbonate, andbound to organic matter or sulfides. The results from SEPstherefore provide additional information on metal removalmechanisms. However, due to their operational nature andthe difficulty of data interpretation, sequential extractionsare not particularly suited for absolute studies, without

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reference to other analyses (Bacon and Davidson, 2008).The interpretation of results from AVS-EM is based onthe theory that metals are stable or potentially mobile ifthe EM/AVS molar ratio is less than one or greater thanone, respectively (Yu et al., 2001). Metal stability or poten-tial mobility is related to the chemical form; at an EM/AVSmolar ratio less than or equal to one, metals are mainly in

the form of sulfide minerals, whereas at an EM/AVS molarratio greater than one the (oxy)hydroxide and carbonateminerals are predominant. In addition, some authors havereported that the AVS-ES theory allows predicting theacute toxicity of Cd and Ni in sediments (Di Toro et al.,1992). Finally, thermal decomposition using differentialscanning calorimetry and thermogravimetric analysis(DSC-TGA) has already been reported as an appropriatemineralogical technique for studying chemical composi-tion of metal precipitates from acid mine drainage (Kimand Kim, 2003).

This being said, there are limited data on metal removalmechanisms and potential mobility in complex reactivemixtures from bioreactors which treat highly contami-

nated AMD, with metal concentrations (e.g. Mn, Cd, Ni,Zn) of 1015 mg/L and up to 500 mg/L Fe. Analysis of reac-tive mixtures collected from a bioreactor filled with acid-washed sand (very simple matrix) and fed with lactate(the best organic C source for SRB) for the treatment ofmildly contaminated AMD for 14 days, indicated that theorganic matter/sulfides bound fraction was the mostimportant scavenging phase of all metals (Jong and Parry,2004). In contrast, sulfides were not detected in a spentreactive mixture from a bioreactor filled with a mixtureof municipal compost, calcite, and river sediment, andwhich treated a comparable AMD over 158 days (Gibertet al., 2005). Additional work is therefore required to prop-erly evaluate metal removal mechanisms and potentialmobility in bioreactors filled with complex reactive mix-

tures and that are used for highly contaminated AMDtreatment.

The first part of the present study (Neculita et al., 2008)provides details on the set-up and operation of 6 SO4-redu-cing column bioreactors over an 1115 month period forthe treatment of a highly contaminated AMD at two differ-ent hydraulic retention times (HRTs). In this second part ofthe study, 4 of the bioreactors (in duplicate for each HRT)were then dismantled, and several physicochemical, mi-crobiological, and mineralogical analyses were performedon reactive mixtures collected from the first 10 cm in thetop and bottom layers. The main objective of this part ofthe study was to gain insight into the mechanisms of metalremoval, as well as to assess long-term stability of reactivemixtures and the potential mobility of metals after thetreatment of a highly contaminated AMD.

2. Materials and methods

2.1. Sampling

Samples of reactive mixtures were collected from four3.5 L SO4-reducing column bioreactors after 44 weeks oftreating highly contaminated artificial AMD. The reactorswere filled with a reactive mixture (sandwiched between

two layers of gravel at the top and bottom of the col-umns) consisting of 60% (w/w, dry) organic materialsand 40% inorganic materials (sand, creek sediment, ureaand calcium carbonate). Organic materials were consti-tuted from equal proportions (30%, w/w) of cellulosicwastes (maple wood chips and sawdust) and organicwastes (leaf compost and poultry manure). The reactive

mixture was selected after being tested in long-term(120 day) batch bioreactors (Neculita and Zagury, 2008).The AMD was prepared on a weekly basis using distilledwater and metal sulfates and had the following composi-tion (Neculita et al., 2008): 372 mg/L Ca, 9.8 mg/L Cd,504 mg/L Fe, 66.3 mg/L K, 85.8 mg/L Mg, 10.1 mg/L Mn,625 mg/L Na, 13.7 mg/L Ni, 14.5 mg/L Zn and 4022 mg/LSO24 at pH 2.95.7.

The sampling of solids was carried out from the first10 cm layer of the top and bottom of 4 reactors, whichtested (in duplicate) two hydraulic retention times (HRTs)of 7.3d and 10d, in a downward flow configuration. It wasimportant to examine these two layers because, due to dif-ferences in the forms of the metals, they can control metal

mobility.

2.2. Physicochemical and microbiological analyses

Physicochemical analyses of the spent reactive mix-tures included pH, moisture content, total volatile solids,total C (TC), total organic C (TOC), total S, soluble SO4,and metals. The pH was determined in deionized waterusing a solid to liquid ratio of 1:10 according to the stan-dard D4972-95 (ASTM, 1995a) using a portable pH/mV/temperature meter (HACH, model sensION1) with a gel-filled pH electrode and a combination Ag/AgCl redox po-tential electrode (HACH, Hampton, NH). The water contentwas determined at 105C according to the standardD2216-92 (ASTM, 1995b). Volatile solids were determined

at 550 C according to Karam (1993). Total C and total Swere measured by combustion with an induction furnace(LECO Corporation, 1975). A HCl treatment followed bythe same combustion as in the case of the total C analysiswas performed to determine total organic C (Tiessen andMoir, 1993). Inorganic C was calculated by the differencebetween total C and total organic C. Soluble SO4 was ana-lyzed as S extracted in HCl (40%, v/v) and using ICP-AES,as per Sobek et al. (1978). Based on the fact that the totalmetal concentrations are related to the extraction condi-tions, the metals in the spent reactive mixtures (Fe, Mn,Cd, Ni and Zn) were determined using 4 digestion methods(A, B, C and D). These metal analyses were performedeither by atomic absorption spectrometry (AAS, Perkin El-mer, model A Analyst 200), where method detection limitsfor Fe, Mn, Cd, Ni and Zn were, respectively, 0.05, 0.02,0.03, 0.02 and 0.02 mg/L or by atomic emission spectros-copy (ICP-AES, Perkin Elmer Optima 3100), where themethod detection limit was


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B 1 g of solid and 71 mL of 30 HNO3 to 20 HClO4 to 20HCl to 1 HF.

C 0.5 g ofsolid and 3336 mL of10 HNO3 to1Br2 to20HCl to 25 HF (Potts, 1987).

D 1.25 g of solid and 25 mL of 6 M HCl (Brouwer andMurphy, 1994).

In digestion method B, samples of spent reactive mix-tures were weighed in Teflon vessels with 20 mL concen-trated HCl. After 24 h of reaction at room temperatureand under a fume hood, other acids were added and themixture was then treated as in digestion method A (Zaguryet al., 1997).

Microbiological analyses included counts of total anaer-obic heterotrophic bacteria (TAHB) and SO4-reducing bac-teria (SRB). The counts of TAHB and of SRB used the MostProbable Number technique as per Standard Methods(APHA, 1998) or/and ASTM (1990), respectively. All labora-tory glassware used during the analytical procedures wassequentially cleaned with a phosphate-free detergent,soaked in 10% (v/v) HNO3 for 24 h, then in distilled water,

and finally rinsed 3 times with deionized water(18.2 M ohms). Unless otherwise stated, all reagents wereof analytical grade (ACS) or better. All analyses were car-ried out in duplicate, for both top and bottom layers ofeach reactor. The reported concentrations were correctedfor moisture content.

2.3. Stability of metal precipitates and potential mobility

Stability of metal precipitates and potential mobility inthe reactive mixtures were assessed with a sequentialextraction procedure (SEP) and a simultaneous determina-tion of acid volatile sulfides and extracted metals (AVS-EM).

The SEP (Zaguryet al., 1997) used in the present study is

based on the classical Tessier et al. (1979) scheme, withsome modifications, especially on the extraction of theresidual fraction. The five operationally defined fractionsand the reagents employed were as follows: soluble andexchangeable metals (extracted with 0.5 M MgCl2, pH 7),carbonate bound (leached by 1 M NaOAc buffered withHOAc, pH 5), reducible or bound to FeMn oxides (ex-tracted with 0.04 M NH2OH HCl in 25% (v/v) HOAc), oxi-disable or bound to organic matter (released by HNO3,H2O2, and NH4OAc), and residual metal fraction (dissolvedby acid attack with HNO3, HF, and HClO4). The procedurewas conducted with 1 g of solid accurately weighed in50 mL polypropylene centrifuge tubes, to which 8 mL ofextracting solution was added. Between each of the succes-sive extractions, separation was carried out by centrifuging(BeckmanJ2-21) at 12,000gfor 30 min. Thesupernatant ex-tract was removedandcollectedin 50 mL vials. The residuewas rinsed twice with 8 mL deionized water, centrifugedfor 30 min, and the supernatant mixed with the initial ex-tract and analyzed for metal concentrations by AAS.

The AVS-EM procedure was conducted as per Brouwerand Murphy (1994), except for the fact that 6 M HCl wasused, instead of 2 M HCl, as specified in the protocol. Beforestarting the extraction, a sulfide antioxidant buffer solution(SAOB) (which selectively retains gaseous sulfides) was

prepared which contained 2 M NaOH (to convert H2S intoS2), 0.1 M ascorbic acid (to prevent S2 oxidation), and0.1 M EDTA (to complex metals that may catalyze the S2

oxidation) (Arowolo and Cresser, 1991). Samples of 1.25 gwet reactive mixture were placed in 50 mL scintillationvials (outer vial). Smaller open-vials (5 mL) (inner vial)with 2.5 mLof SAOB were then placed inside the outer vial,

and 25 mL of 6 M HCl was added to the reactive mixturefrom the outer vial, to dissolve metals and volatilize gas-eous H2S. The outer vial was then immediately closed toprevent the loss of H2S. The assembled vials were placedon a rotary shaker and agitated at 150 rpm for 1 h. Afteragitation, the outer vials were opened and the inner vialwas removed, its content mixed and analyzed for sulfidesusing methylene blue Standard Method (APHA, 1998).The supernatant from the 50 mL scintillation vial was thenfiltered using 0.45 lm membranes and analyzed for metalsby flame AAS (Perkin Elmer, model AAnalyst 200).

2.4. Solid mineralogy

A differential scanning calorimetry and thermogravi-metric analysis (DSC-TGA), in addition to X-ray diffraction(XRD), and scanning electron microscopy equipped with X-ray energy dispersion (SEM-EDS) microanalysis were usedfor evaluation of spent mixture mineralogy.

The DSC-TGA was carried out using a TA-SDT-Q600apparatus (TA Instruments), which allows recording ofweight loss and heat flow during thermal treatment of thesample. Thermal behavior of wet samples (2734 mg) wasstudied under a N2 atmosphere (100 mL/min), at a rate of10 C/min (up to 600 C) then 20 C/min (6001200 C).Morphological featuresof metal precipitates were observedwith a SEM (Hitachi S-3500N), equipped with an EDS X-raymicroanalysisdetector(OxfordLink-Isis300). TheX-ray dif-fraction analysis used a D8 Advance diffractometer (Bruker

AXS), equipped with a Cu source anda scintillation counter.Theanalyses were step-scannedfrom 5 to 60 C (2h)usingastep of 0.005 C (2h)at1 C divergence slit and1 s/stepinte-gration time. Due to the poor crystalline state of the miner-als, samples were passed several times which allowed thesoftwareto optimize the signal to noise ratio by adding sig-nals from each pass. Prior to the SEM and XRD analyses, thesamples were dried (at 40 C for 48 h), desegregated with aroller and manually homogenized. The SEM analyses wereperformed on polished surfaces, which were prepared un-der vacuum and used 24 g of dried samples embedded inan epoxy resin (Epoxycure resin, Buehler, Canada) andmounted on plastic stubs. The surface was then polishedwith diamond paper, diamond suspension and Al powderwith decreasing grit size down to 0.02 lm toproduce a highgloss surface. The observations were performed at an accel-erating potential of 20 kV, a probe current of 80 lA, and avacuum pressure of 25 kPa.

3. Results and discussion

Results from sampling and analysis of treated effluenton a weekly basis over an 11-month period showed theeffectiveness of column bioreactors for increasing the pHand alkalinity, and for removing SO24 and metals from a



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highly contaminated AMD at both 7.3d and 10d HRTs. Afinal analysis of treated effluent, carried out at week 60,also indicated that the columns were still effective forAMD treatment at both HRTs tested. Moreover, solidanalysis was necessary to gain insight into the mechanismsof metal removal, as well as to assess long-term stability ofthe reactive mixtures and the potential mobility of metals

after the AMD treatment. Chemical extractions andmineralogical analyses therefore especially focused onmetal stable forms (e.g. residual fraction of SEP or/andsulfide minerals).

3.1. Physicochemical and microbiological analyses

Physicochemical and microbiological parameters indi-cated similar trends between the top layers, as well as be-tween the bottom layers of all reactors (Table 1). The pHwas slightly higher (7.27.8) in the 10d HRT columns com-pared to the 7.3d HRT columns (6.87.3), with low (0.20.5units) or no differences between the pH in the top and bot-tom layers of the bioreactors. The bottom layers, however,

had up to 3% higher humidity, due to the vertical down-ward flow. Volatile solids (VS), determined at 550 C,which are generally used as an indication of organic mattercontent, showed higher values in the top layers comparedto the bottom layers. Among the reactors, the lowest VSvalues (32.034.5%) were found in reactor 1 and the high-est (42.450.8%) in reactor 2, which were both operated ata 10d HRT (Table 1). There is no clear explanation for thisdiscrepancy. Results also show that volatile solid valuesare not well correlated with total C, which was lowest inthe top layers of the reactors. The release of water fromthe (oxy)hydroxide minerals at temperatures as high asthose used during the volatile solids analysis (550 C)could account for this difference. Moreover, in the bottomlayers, both organic and inorganic C concentrations were

higher than in the top layers. The organic C in the bottomlayers could originate from leaching of the top layers, whilethe source of inorganic C could be either the initial TICfrom the reactive mixture composition or TIC generatedby SRB activity. It is noteworthy that the reactive mixturecontained calcium carbonate (2%) and leaf compost (20%,w/w, dry weight), with a very high content of TIC (14.3%)

(Neculita and Zagury, 2008). Overall, in the top and bottomlayers, TOC ranged from 17% to 24%. These values are sim-ilar to previously reported results on reactive mixturesafter 3 a of AMD treatment (Zaluski et al., 2003). Elementalanalyses also showed low concentrations of Stotal (0.31.2%) and Ssulfates (0.21%) in the top and bottom layers ofall columns. Moreover, Ssulfides (calculated as the difference

between Stotal and Ssulfates) was up to 0.8% which suggeststhat metals in sulfide minerals accounted for up to 0.8%(w/w) (or 15% of total metals recovered in spent reactivemixtures). Microbiological analyses indicated that TAHBin the top layers was around 106 cells/100 mL and 10-foldlower in the bottom layer (Table 1). The SRB (103 cells/100 mL) in the top layers also give twice the counts inthe bottom layers, except in reactor 4. However, MNPcounts are known to be variable up to an order of magni-tude; therefore, bacterial counts in the top and bottom lay-ers are comparable.

The TAHB counts in post-treatment reactive mixturesshowed that they remained high relative to initial values,which varied from 104 cells/100 mL (maple sawdust) to

>10

7

cells/100 mL (composted poultry manure and leafcompost) (Neculita and Zagury, 2008). Although these highfinal counts could be an indication of a heterotrophicmicrobial population still capable of decomposing complexorganic C to simple molecules, which SRB will eventuallybe ableto use (Neculita et al., 2007), the MPN method doesnot provide information about the activity of the bacteriain the columns.

As expected, due to the very high contaminant load inthe AMD used to feed the columns, metal concentrationsdetermined with all 4 methods (A, B, C and D) were veryhigh (Table 2). In the top layers of the columns, lower con-centrations of Fe and Mn, as well as higher concentrationsof Cd, Ni and Zn were found relative to the bottom layers,regardless of the digestion method. Relative standard devi-

ations (RSD) were high and varied in the range 225% forFe and Mn, 161% Ni and Zn, and 1126% for Cd. The scat-tering of results was not unexpected, given the heteroge-neous state of the samples which were collected fromreactive mixtures containing several organic materials(e.g. chips and sawdust of maple wood, composted poultrymanure, leaf compost) and inorganic materials (e.g. sand,

Table 1

Physicochemical and microbiological characterization of spent reactive mixtures

Columnnumber

HRT Samplelocation

pH Moisture(%)

Volatilesolids (%)

TC (%) TOC (%) TIC (%) Stotal(%)

Ssulfates(%)

TAHB 106

(cells/100 mL)SRB 103

(cells/100 mL)

1 10d Top 7.60 0.12 52.6 1.2 34.5 13.8 17.9 0.2 17.0 0.4 0.9 0.3 1.0 1.0 3.0 3.0Bottom 7.80 0 .03 53.3 4.0 32.0 4 .1 20.9 0 .3 19.4 0 .2 1.5 0 .2 1.1 0.6 0.3 1.7

2 10d Top 7.24 0.02 52.6 0.9 50.8 3.7 22.1 0.2 21.5 0.5 0.6 0.7 1.0 0.8 2.8 5.0Bottom 7.52 0 .05 54.5 0 .4 42.4 0 .0 20.1 0 .2 18.8 0 .2 1.3 0 .0 0.9 0.7 0.8 2.3

3 7.3d Top 6.89 0.43 48.1 1.8 45.0 14.0 23.2 0.1 22.5 0.2 0.7 0.3 0.3 0.2 3.0 5.0Bottom 7.34 0 .06 5 1.8 1.3 41.9 7 .7 25.5 0 .2 23.7 0 .4 1.7 0 .3 1.2 0.6 0.5 3.0

4 7.3d Top 6.88 0.01 50.9 4.9 41.1 3.4 19.10.3 17.3 0.4 1.7 0.4 0.8 0.6 5.0 1.3Bottom 6.85 0 .05 53.9 2.6 42.4 3 .9 19.5 0 .1 18.0 0 .5 1.5 0 .5 1.1 0.3 0.5 1.7

Results are expressed as mean standard deviation from n = 4 (2 columns, in duplicate).Columns #1 and #2 were operated at a 10d HRT; columns #3 and #4 were operated at a 7.3d HRT.SRB sulfate-reducing bacteria.TAHB total anaerobic heterotrophic bacteria.

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creek sediment). Generally, the highest metal concentra-tions (except for Cd) were found using digestion methodB, which was performed with a mixture of 4 strong inor-ganic acids (HCl, HF, HNO3, and HClO4) and the lowest con-centrations were determined with digestion method D(6 M HCl), which was in fact the method used in theAVS-EM procedure. Metal concentrations determined withmethod B were up to 6- and 8-times higher for Fe and Mn,respectively. For Ni and Zn, the differences between resultswere more variable, whereas for Cd comparable concentra-tions with the two digestion methods were obtained,reflective of a less strong bond to solid matrix of this metal.Moreover, the Fe and Mn concentrations determined withmethod B were twice as high in the bottom layers, whereasCd, Ni and Zn concentrations were up to 50-times higher inthe top layers (Table 2). Among the metals, Fe concentra-tions were the highest (100-fold or more) and varied from19.9 g/kg to 35.7 g/kg in the top layers and from 50.8 g/kgto 57.8 g/kg in the bottom layers.

Overall, results from elemental analyses indicated thatCd, Ni and Zn were concentrated in the top layers andeventually removed from the AMD by adsorption or boundto organic matter, whereas Fe and Mn were concentrated

in the bottom layers and eventually removed as sulfideminerals, in addition to (oxy)hydroxides and carbonates.

3.2. Stability of metal precipitates and potential mobility

As previously specified, the spent reactive mixturesfrom both top and bottom layers of all reactors containedvery high concentrations of metals. Results from the AVS-EM procedure also indicated a high excess of metals rela-tive to volatile sulfides and a molar ratio of EM to AVS > 1,whichis based on AVS-EM theory (Yu et al., 2001) suggestsa high mobility of metals under acidic conditions (Table 3).These results are consistentwithelemental analyses, whichindicatedhigh total metalconcentrations(up to 5.8% for Fe)and low Ssulfides (up to 0.8%) in spent reactive mixtures. Themobile fraction of Fe (as determined using AVS-EM proce-dure) was 3539% in the bottom layers, and 1829% inthe top layers. For Mn, the mobile fraction was comparableto Fe (2632%) in the bottom layers, while in the top layersit was less than that for Fe (1317%). Thepotential for metalmobility was also confirmed by results from the SEPprocedure (Table 4), which are presented in terms of abso-lute concentrationsto allowthe direct comparison between

Table 2

Total concentrations of Fe, Mn, Cd, Ni, and Zn in spent reactive mixtures using four digestion methods

Method Column number Sample location Fe (g/kg) Mn (g/kg) Cd (g/kg) Ni (g/kg) Zn (g/kg)

A 1 Top 14.1 2.0 0.18 0.02 8.09 1.66 1.74 0.03 2.90 0.59Bottom 30.1 0.3 0.31 0.00 0.05 0.00 0.06 0.01 0.15 0.01

2 Top 11.0 1.6 0.15 0.01 10.4 1.2 0.54 0.29 1.771.03Bottom 30.3 1.5 0.30 0.01 0.06 0.01 0.09 0.03 0.15 0.04

3 Top 11.6 1.8 0.14 0.01 7.67 0.52 0.36 0.01 1.14 0.09Bottom 28.7 2.7 0.22 0.02 0.15 0.06 0.06 0.00 0.15 0.03

4 Top 31.6 1.0 0.32 0.02 0.00 0.00 4.07 0.62 3.05 0.21Bottom 30.7 1.0 0.37 0.01 0.03 0.04 0.06 0.02 0.12 0.01

B 1 Top 35.7 2.1 0.44 0.03 13.3 1.3 2.37 0.23 2.53 0.01Bottom 51.8 6.6 0.61 0.09 0.26 0.08 0.82 0.02 0.51 0.12

2 Top 30.9 1.7 0.47 0.01 10.2 5.9 5.19 1.97 13.2 3.9Bottom 57.8 2.3 0.67 0.05 0.33 0.18 0.89 0.00 0.45 0.01

3 Top 19.9 3.9 0.35 0.03 6.77 0.09 1.87 0.12 4.07 2.37Bottom 50.8 2.4 0.53 0.02 0.38 0.19 0.86 0.03 0.51 0.14

4 Top 31.8 5.9 0.49 0.06 8.33 0.46 1.80 0.11 5.79 1.34Bottom 52.7 4.0 0.70 0.05 0.26 0.10 0.85 0.06 0.45 0.06

C 1 Top 25.0 0.37 3.96 4.23 6.78Bottom 32.9 0.44


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studies (Bacon and Davidson, 2008). Based on partitioningdata (sum of metal concentrations from 5 extracted frac-tions), the ranking of metal mobility was similar betweenthe top layers, as well as between the bottom layers of allreactors for Fe, Mn, Ni and Zn, whereas Cd behaved differ-ently for the two HRTs of7.3d and 10d (Table 4). A ratio be-tweenthe total metal concentrations in the bottomand toplayers showed relatively low values for Fe (1.23.7) and Mn(1.32.6). For Cd, Ni and Zn, however, the concentration ra-tio between the top and bottom layers was significantlyhigher (4166), with the lowest variation for Zn (1026)and the highest variation for Cd (50166). Moreover, for

Cd this ratio was twice as high in the 10d HRT columns(100166) compared to the 7.3d HRT columns (5080).Based on the ranking of metals in the reactive mixturesfrom the top and bottom layers the results indicated that:

1. In the top and bottom layers, Fe had the lowest solu-ble and exchangeable fraction, as well as the lowestcarbonate bound fraction, with concentrations varyingfrom 0.5 to 30 mg/kg. The precipitation of insolubleFe(III) minerals at the top, and the generation ofinsoluble Fe(II) sulfides at the bottom of the columns,could explain these low mobile fractions. However,Mn, Cd, Ni and Zn concentrations were higher in thesoluble and exchangeable fraction compared to Fe(while at least 4-fold lower than the residualfraction), whereas the carbonate bound fraction waslow for all metals.

2. In the top layers, Fe and Mn were mainly recovered intheresidualfraction, Cd and Zn in theoxidisable/organicmatter bound fraction and Ni in the reducible fraction.

3. In the bottom layers, metals were mainly found in thereducible fraction (Fe and Zn in all columns, and Ni inthe 10d HRT columns), in the residual fraction (Mn, Niin the 7.3d HRT columns) and in the oxidisable/organicmatter bound fraction (Cd).

In summary, the lowest potential mobility was foundfor Mn, which was mainly recovered in the residual frac-tion from the top (4674%) and bottom (4244%) layersof all columns. A low potential mobility was also foundfor Fe in the top layers which had a higher residual fraction(4477%) than in the bottom layers which had a higherreducible fraction (3539%). Nickel and Zn were dividedbetween reducible, oxidisable/organic matter bound orresidual fractions, whereas Cd was recovered (7297%)only from the oxidisable/organic matter bound fraction.Organic matter acts as a strong, although temporaryreversible binder for Cd from which it can be easily be des-

orbed and/or extracted (Palgyi et al., 2006). The pHis veryimportant in Cd sorption, and the precipitation of hydro-lytic products of Cd usually takes place at basic values(pH > 7). However, although the AMD feed used in thepresent study was acidic (2.95.7), Cd was not releasedin the treated effluent at any time, indication of organicmatter still having the capacity to retain Cd by sorption.

The results from both chemical extractions (SEP andAVS-EM) and elemental analysis were therefore consistentand indicated a low fraction of metals removed as sulfides.Moreover, Fe and Mn were found in a more stable chemicalform (residual fraction) relative to Cd, Ni or Zn, whichseemed weakly bound (oxidisable/reducible fractions)and had higher potential mobility (Table 5).

3.3. Solid mineralogy: X-ray diffraction

Although elemental analysis and chemical extractionsprovided data on metal concentrations, as well as on theirstability and potential mobility from spent reactive mix-tures, they provided limited insight into metal removalmechanisms. Mineralogical analyses can be used to iden-tify the mineralogy of metal precipitates and to evaluatemechanisms of metal removal.

Table 3

Metal and sulfide concentrations in reactive mixtures using a simultaneous determination of acid volatile sulfides and extracted metals (AVS-EM)

Columnnumber

Samplelocation

Fe (mmol/kg)(%)

Mn (mmol/kg)(%)

Cd (mmol/kg)(%)

Ni (mmol/kg)(%)

Zn (mmol/kg)(%)

H2S + H S

(mmol/kg)

1 Top 123.1 4.7 1.2 0.1 57.0 11.6 26.5 4.6 59.2 11.9 0.03 0.02(19.6 3.8) (15.1 9.4) (48.2 20.4) (65.6 17.4) (67.1 13.5)

Bottom 328.6 2.1 3.1 0.2 0.5 0.6 0.7 0.4 1.6 0.5 0.03 0.01

(35.4 0.6) (27.9 6.2) (21 122) (5.2 56.3) (20.5 33.9)2 Top 105.7 4.8 1.1 0.0 92.9 22.0 29.5 3.5 146.2 33.5 0.05 0.02

(19.1 4.6) (12.8 2.0) (103 23.6) (33.4 12.0) (72.3 22.9)Bottom 364.0 8.4 3.8 0.6 0.9 0.9 0.8 0.4 2.8 1.7 0.07 0.00

(35.2 2.3) (30.6 15.7) (29.5 100) (5.1 56.6) (41.5 60.7)

3 Top 102.2 7.4 1.1 0.3 92.6 25.6 23.6 5.7 48.7 4.6 0.00 0.00(28.6 7.3) (17.0 25.2) (154 28) (74.3 24.1) (78.3 9.4)

Bottom 349.1 17.3 2.5 0.0 0.0 0.0 0.4 0.1 1.1 0.0 0.04 0.01(38.3 5.0) (26.0 1.5) (0.9 47.1) (2.9 25.7) (13.6 2.3)

4 Top 99.7 10.1 1.4 0.2 91.0 27.8 24.4 7.3 91.3 19.1 0.00 0.00(17.5 10.1) (16.1 14.7) (123 31) (79.5 30.0) (103 21)

Bottom 363.6 49.7 4.1 0.5 1.2 1.2 0.9 0.5 2.0 1.0 0.05 0.00(38.5 13.7) (32.1 11.9) (49.7 106) (6.0 56.8) (29.2 48.3)

Results (mmol/kg) are expressed as mean standard deviation from n = 4 (2 columns, in duplicate).Results presented in parenthesis (%) are expressed as mean (EM) to mean (total concentration as determined with method B) ratio RSD.RSD relative standard deviation (standard deviation to mean ratio, %) Columns #1 and #2 were operated at a 10dHRT; columns #3 and#4 were operated

at a 7.3d HRT.



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Due to a high organic content and sample heterogene-ity, the X-ray diffraction technique allowed only qualita-tive characterization of the spent reactive mixtures. Also,due to a high detection limit of the method (15%, depend-ing on mineral crystallinity) the XRD peaks in samplesfrom the top and bottom layers of all columns indicated lit-tle difference in mineral composition (Fig. 1). The identi-fied peaks correspond mainly to silicate (quartz, albite,and muscovite), (oxy)hydroxide (goethite: a-FeO(OH) andlepidocrocite: y-FeO(OH)), carbonate (calcite and oxamite:(NH2)2(CO2)2H2O), sulfate (gypsum), urea (from reactivemixture constitution), and monosulfide (makinawite andgreigite) minerals. These findings are not in agreement

with previously reported results, where an XRD analysisdid not detect any peak in solids recovered from the inletof a columnfilled with a mixture of calcite, municipal com-post, and river sediment, and which was used for the treat-ment of AMD over a 158-day period (Gibert et al., 2005).However, they are comparable with results from a studyperformed on substrates (mixtures of mushroom compost,animal manure, and barley mash wastes) collected fromthe inlet and outlet pipes of a field-scale wetland whichtreated AMD for over 2 a (Machemer et al., 1993).

Moreover, based on the XRD peaks heights/areas(Fig. 1), lower contents of calcite were present in the toplayers compared to the bottom layers, probably due to

Table 4

Metal (Fe, Mn, Cd, Ni, and Zn) fractionation in reactive mixtures using a sequential extraction procedure (SEP)

Column number Sample location Fraction Fe (g/kg) Mn (mg/kg) Cd (mg/kg) Ni (mg/kg) Zn (mg/kg)

1 Top F1


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the acidic pH of the AMD reactor feed (pH 2.95.7). Slightlylower concentrations of Fe (oxy)hydroxides (goethite andlepidocrocite) also seemed be present in the top layers rel-ative to the bottom layers in the 10d HRT column, while inthe 7.3d HRT column, no difference was observed for these

minerals in the top and bottom layers. Although the X-raydiffraction technique provided some information about thechemical form of the minerals present in the spent reactivemixtures, its high detection limit mainly allowed the iden-tification of Fe precipitates as (oxy)hydroxides (goethite

0

1000

2000

3000

4000

5000

5 10 20 30 5 10 20 30

5 10 20 30

U

U

UGtCa, Ox

U Gt

Gt Ca

GtGt

GrOx Gp GtGp Gr

Qz

Qz

Qz

Qz

Lin

(Counts)

2-Theta-Scale 2-Theta-Scale

2-Theta-Scale

5 10 20 30

2-Theta-Scale

0

1000

2000

3000

4000

5000

Lin(Counts)

0

1000

2000

3000

4000

5000

Lin(Counts)

0

1000

2000

3000

4000

5000

Lin

(Counts)

a

b

Fig. 1. Results from X-ray diffraction (XRD) analysis on reactive mixtures collected in top (left) and bottom (right) layers from columns operated at (a) 10dHRT and (b) 7.3d HRT. (Qz quartz, Gt goethite, U urea, Ca calcite, Ox oxamite, Gp gypsum, Gr greigite).

Table 5

Chemical form of metals determined with different techniques on spent reactive mixtures from top and bottom layers of bioreactors

Approach Technique Chemical form Metals/characteristics

Chemical analyses Digestion Metal total concentration Fe Mn Cd Ni Zn upto 2-timeshigherinthe bottom layers

up to 50-times higher in the toplayers relative to bottom layers

Elemental analyses Sulfates and sulfides 0.21.2% total sulfur with 0.21.0% in sulfates form and up to

0.8% in sulfides form Carbonates and bicarbonates 0.61.7% in the top layers and 1.31.7% in the bottom layers

Fe Mn Cd Ni ZnSEP Soluble and exchangeable 60.2% 1625% 110% 962% 218%

Carbonate bound >>1; low fraction of metals in sulfidesform Metals

Mineralogical analyses XRD (Oxy)hydroxides Goethite (a-FeO(OH) and lepidocrocite (y-FeO(OH)) Carbonates Calcite (CaCO3) Sulfides Makinawite (FeS) and greigite (Fe3S4) Sulfates Gypsum (CaSO4 2H2O) Silicates Quartz

DSC-TGA Sulfur compounds SO3 evolving at temperatures around 730 CSEM-EDS (Oxy)hydroxides Phases consisting mainly of Fe and O, along with S, Ni, and Zn

Carbonates Phases consisting mainly of Ca, O

Sulfides Pyrite, pyrrhotite (Fe1xS), chalcopyrite (CuFeS2), CdS, ZnS, aswell as other metals in the structure (Ni, Al, Na)

Silicates E.g. ZrSiO4

SEP sequential extraction procedure.AVS-EM acid volatile sulfides and extracted metals.XRD X-ray diffraction.DSC-TGA differential scanning calorimetry and thermogravimetric analysis.SEM-EDS scanning electron microscopy with X-ray dispersion microanalysis.



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and lepidocrocite) and sulfides (greigite and makinawite)but not of the minerals containing Mn, Cd, Ni and Zn. Theseresults can be explained by the total Fe concentration,which was the highest of all metals (up to 5.8%, w/w). Ahigher inorganic C content in the bottom layers relativeto top layers is also supported by the chemical analyses.

3.4. Thermogravimetry and differential scanning calorimetry

Thermal behavior of wet reactive mixture samplesfrom the top layers of two reactors (one for each 7.3d

and 10d HRT) was characterized by 3 endotherms atapproximately 100 C, 360 C, and 730 C (Fig. 2). At thebeginning, with increasing temperatures up to 100 Cwhen the first endotherm was observed, the weight losswas 53% (7.3d HRT columns) and 35% (10d HRT columns)(Fig. 2). The evaporation of adsorbed water and structuralOH which were rapidly lost at a large rate of thermal

transformation could explain the weight loss. Withincreasing temperature, additional weight was lost (13%and 23% for 7.3d and 10d HRTs columns, respectively)at slower rates, to yield a second endotherm at around

Fig. 2. Differential scanning calorimetry and thermogravimetric analysis (DSC-TGA) on reactive mixtures from columns operated at (a) 10d HRT and (b)7.3d HRT.



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360 C. The degassing of CO2 and H2O derived from or-ganic matter oxidation (peptidic structures are lost at360 C) could explain this trend (Provenzano et al.,

2000). As the temperature further increased, less weight(1.7%) was lost (in the 7.3d HRT column only) to finallyreach a third endotherm around 730 C. This last

Fig. 3. SEM-BSE image and elemental mapping for C, S, Fe, Ni, Cu, and Zn on reactive mixture from the bottom of a column operated at 10d HRT. Sulfideprecipitation with a Fe:S ratio corresponding to pyrrhotite and the presence of other metals (Ni, Cu, Zn) in the structure was observed. The top image(50lm width) is a composite of the bottom six images (25 lm).



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transformation was attributed to SO3 volatilization (Kimand Kim, 2003).

The thermal behavior of spent reactive mixtures clearlyshowed that organic matter content was still high after 11months of operation, which is also supported by a contin-uously high TOC/DOC outflow during the final steady-statephase (Neculita et al., 2008). This is an indication that

depletion of organic C would not be a limiting factor formetal removal during long-term operation of bioreactors.The study also provides insight into oxidation andvolatilization of S compounds (Table 5).

3.5. Scanning electron microscopy and X-ray microanalysis

A lower limit of detection (0.2%) compared to XRD al-lows a closer study of the chemical form of metal precipi-tates, especially of those unidentified during the XRDanalysis. Indeed, the SEM images from samples of reactivemixtures showed abundant precipitates of a broad size (2

10lm) and irregular spatial distribution (Figs. 36).According to elemental mapping and EDS analysis, thegranular precipitates contained sulfides which were en-trenched both in organic fibers and around the edge of

Fig. 4. SEM-BSE image and elemental mapping for C, Ca, S, and Zn on reactive mixture from the top of a column operated at 10d HRT. Sulfide precipitationwas observed with a metal to sulfur ratio corresponding to ZnS and CdS, as well as the presence of other metals (Fe, Cu) in the structure. The top image(50lm width) is a composite of the bottom four images (25 lm).



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alveoli from the cellular texture of maple wood. Sulfidesdetected in the bottom layer of the 10d HRT column con-tained Fe associated with S in stoichiometric ratios similarto pyrrhotite (Fe1xS) with inclusion of Zn, Ni, and some-times Cu (Fig. 3), while in the top layer of the samecolumn,the presence of CdS and ZnS was confirmed (Fig. 4). In thebottom layer of the 7.3d HRT column, in addition to metal

sulfides such as chalcopyrite (CuFeS2), some carbonateswere also observed (Fig. 5), while in the top layer, the me-tal precipitates contained Fe (oxy)hydroxide minerals withS, Ni and Zn in the structure (Fig. 6). The morphology andsize-distribution of the metal sulfides is comparable to pre-

viously reported results (Machemer and Wildeman, 1992;Herbert et al., 1998).

Thus, in addition to (oxy)hydroxide and carbonate min-erals, and complementary to the XRD analyses, the SEM-EDS technique allowed observing what was interpretedas other metal sulfides (containing Cd, Ni and Zn) whichwere unidentified by XRD analyses. Moreover, although

the SEM-EDS technique did not provide quantitative dataon the chemical form of the metal minerals, it confirmedthe results from chemical extractions (AVS-EM) on thepresence of metal sulfides in spent reactive mixtures fromcolumn bioreactors (Table 5).

Fig. 5. SEM-BSE image andelemental mapping forC, O, Ca, andSi on reactive mixture from thebottom of a column operated at 7.3d HRT. Sulfur(as sulfate)was mainly associated with O2, Ca, and Al. The top image (50 lm width) is a composite of the bottom four images (25lm).



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Fig. 6. SEM-BSE image and elemental mapping for C, O, S, Zn, Fe, and Ni on reactive mixture from the top of a column operated at 7.3d HRT. Iron(oxy)hydroxide and the presence of S, Ni, and Zn in the structure were observed. The top image (50 lm width) is a composite of the bottom six images(25lm).



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