Influence of hydrology on heavy metal speciation and by Hanna Kuzyo

Environmental Pollution 141 (2006) 310e320 www.elsevier.com/locate/envpol

Influence of hydrology on heavy metal speciation and mobility in a PbeZn mine tailing Elza Kova´cs a,*, William E. Dubbin b, Ja´nos Tama´s a a

Department of Water and Environmental Management, Center of Agricultural Sciences, University of Debrecen, H-4015 Debrecen, P.O. Box 10, Hungary b Department of Mineralogy, The Natural History Museum, Cromwell Road, London SW7 5BD, UK Received 15 December 2004; accepted 8 August 2005

Variable hydrology influences heavy metal speciation and mobility, and the formation of neutralization zones, in a PbeZn mine tailing. Abstract Among the inorganic toxicants of greatest concern in mine tailings, Pb, Zn, Cu, Cd and As figure prominently due to their abundance and potential toxicity. Here we report on their biolability and solid-phase speciation in two sediment cores subject to variable hydrological regimes at an abandoned pyritic mine tailing. The oxic conditions of well-drained sediments induced pyrite oxidation and the subsequent liberation of HC, SO2ÿ 4 and considerable quantities of Fe(III), which precipitated as goethite. Solubility of Pb, Zn, Cu and Cd was closely coupled to pH and goethite presence. Metal lability was particularly low in zones of neutralization, formed by the accumulation of calcite, first carried then deposited by percolating waters in both saturated and unsaturated cores. We conclude that differential hydrology induces variable heavy metal speciation and biolability in PbeZn mine tailings, and suggest that site-specific risk assessments must account for past and present hydrological regimes. Ó 2005 Elsevier Ltd. All rights reserved. Keywords: Mine tailing; Heavy metal; Speciation; Hydrology; Oxidation

1. Introduction The oxidative weathering of pyrite (FeS2) in pyritic mine wastes contributes to the formation of acid mine drainage waters and is therefore the dominant process controlling heavy metal mobility and speciation (Garcı´a et al., 1996; Hayes and Traina, 1998; Lacal et al., 2003). Pyrite oxidation is frequently mediated by O2 dissolved in the waters bathing the mineral surface. The process is complex, as it involves numerous biogeochemical pathways which vary both temporally and spatially. Factors such as pH, pO2, pyrite morphology and specific surface area, presence or absence of sulfide- and ironoxidizing bacteria (e.g. Leptospirillum ferrooxidans, Thiobacillus ferrooxidans, Thiobacillus thiooxidans) and clay minerals, as * Corresponding author. Tel.: C36 52 508 456; fax: C36 52 508 455. E-mail address: ekovacs@gisserver1.date.hu (E. Kova´cs). 0269-7491/$ - see front matter Ó 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.envpol.2005.08.043

well as various hydrological factors, determine the rate and extent of pyrite oxidation (Sengupta, 1993; Evangelou and Zhang, 1995; Jenkins et al., 2000; Johnson, 2003). Oxidative weathering of pyritic ore ultimately releases HC, which, in the absence of buffering agents, increases the solubility of heavy metalcontaining minerals, and also increases aqueous Fe3C, which can facilitate the oxidative dissolution of many heavy metal sulfides (Salomons, 1995; Fowler and Crundwell, 1998, 1999; Puura and Neretnieks, 2000). As pyrite oxidation is a surfacecontrolled reaction, cubic pyrite, with its smooth and minimal surface, is less reactive than the higher surface area conglomeritic and framboid forms (Moses et al., 1987; Stro¨mberg and Banwart, 1999). The acid-buffering capacity of a pyritic mine tailing is largely controlled by its constituent aluminosilicates (e.g. muscovite, illite), carbonates (e.g. calcite, dolomite, Sr-, Feand Mn-carbonates), and Al-, Fe- and Mn-hydroxides, which

E. KovaÂ´cs et al. / Environmental Pollution 141 (2006) 310e320

have variable effects on the acidebase behavior and metal content of the leachate (Benvenuti et al., 1997; Evangelou et al., 1998; Jambor, 2000). According to Salomons (1995) and Carrillo-ChaÂ´vez et al. (2003), the buffering effect of carbonates predominates in the short-term, whereas silicates confer long-term buffering capacity. Conversely, Puura and Neretnieks (2000) suggest that aluminosilicates provide buffering capacity over the short-term, while the remaining acidity is neutralized during subsequent carbonate dissolution. Underwater disposal of potentially reactive pyritic mine wastes is considered the most environmentally sound longterm storage solution because the exclusion of atmospheric O2 restricts oxidative weathering (Elberling and Damgaard, 2001). Transport of dissolved O2 through the aqueous solution is sufficiently slow to be of little concern with regard to oxidation dissolution of sulfides and subsequent HC liberation. However, it is often inadvisable to submerge existing, wellaerated deposits as this may mobilize acidity generated during previous weathering of the wastes (Sengupta, 1993). Despite the evident importance of hydrology on mine waste storage, there are currently insufficient data to assess the impact of varying hydrological regimes on mining wastes and environmental quality (HaÂ´mor, 2002; Jordan and Dâ&#x20AC;&#x2122;Alessandro, 2004). The objective of this study was therefore to examine the geochemical behavior of heavy metals in a pyritic mining waste subject to varying hydrological regimes. Specifically, total and bioavailable metal concentrations, and solid-phase speciation were determined for two sediment cores, unsaturated and saturated, of a pyritic mine tailing deposit. 2. Materials and methods 2.1. Site description and sampling In GyoÂ¨ngyoÂ¨soroszi, North Hungary, nearly 2.1 Mm3 (w3 Mt) of heavy metal rich mining waste was generated as a consequence of Pb and Zn extractive operations initiated in 1952. The tailing dump was continuously charged with mining waste, reaching a final depth of 20e30 m, before abandonment in 1986. Qualitative impact assessments of the mine tailing, including geological and geochemical investigations, were subsequently conducted by HorvaÂ´th and Â´ dor et al. (1998). However, the influence of hydrology on Gruiz (1996) and O heavy metal speciation has not yet been studied. Aerial photos taken in 1987

(A)

and 2000 (Fig. 1) infer submergence of certain areas of the mine tailing, presumably with short occasional drying periods, while other areas are continuously well-aerated. Vegetation remains sparse or absent on all areas of the tailings. The climate of North Hungary is wet continental, with an average annual precipitation of w650 mm (Hungarian Meteorological Service). Two sampling sites, one from an unsaturated area (a), and another from a saturated area (b), were selected to represent the two extreme moisture regimes. At each site, 12 bulk samples were collected at random depths from sampling cores, which extended from 0 to 300 cm below the surface of the tailings. Each sample of waste material was air-dried, ground with ceramic mortar and pestle, then sieved to !2 mm before analysis.

2.2. Characterization of the solid phase Particle size distribution was determined using both dry-sieving (O75 mm) and sedimentation (!75 mm) (Gee and Bauder, 1986). Mineral phases were identified by powder X-ray diffraction (XRD) using an Enraf-Nonius PDS 120 diffractometer with a curved position-sensitive detector configured in vertical geometry with a 2q detection range of 120 . A Ge-111 monochromator was used to select Cu Ka1 radiation. Tube operating conditions were 45 kV and 45 mA. Measurements were made in reflection geometry with the sample surface at a fixed angle of 12 to the incident beam. Samples were powdered, suspended in acetone then loaded into a circular well mount (15 mm diameter ! 1 mm deep), ensuring a smooth and flat surface. Data acquisition time was 10 min for the external silicon standard and 30 min for the multiphase samples. The 2q linearization was performed with ENRAF-GUFI software (Cressey and Schofield, 1996). Mineral identification was aided by comparing diffraction patterns with those in the JCPDS database. Particle morphology and elemental composition of the solid phases were determined by analysis with a JEOL 5900 LV scanning electron microscope (SEM) incorporating an Oxford Instruments INCA Energy analytical system. The energy-dispersive detector had an ultra-thin window (SATW), with a resolution of 130 eV measured at Mn Ka, and a take-off angle of 35 . Operating conditions were typically 20 kV accelerating voltage and w1.0 nA specimen current. The SEM working distance was set to 10 mm. For all analyses, w100 mg of sample was mounted on aluminum stubs with carbon-coated sticky tape then further vacuum-coated with carbon. Spot analyses and element mapping were undertaken at a processing time constant of five to optimize the detector to resolve potential overlapping of peaks. Individual spectra were acquired for 50 s live time. Element mapping was undertaken for a period of up to 200 frames at 100 ms per pixel.

2.3. Total element analysis A total elemental analysis (Mo, Zr, Sr, Rb, Pb, Se, As, Hg, Zn, Ni, Co, Cu, Fe, Mn and Cr) was conducted for each sample non-destructively using a field portable X-ray fluorescence (FPXRF) spectrometer (NITON XL-700)

(B)

~ 100 m

311

~ 100 m

Fig. 1. Aerial photos of the mine tailing in GyoÂ¨ngyoÂ¨soroszi, 1987 (A) and 2000 (B) (sampling points indicated, a: unsaturated, b: saturated; source: Institute of Geodesy, Cartography and Remote Sensing, Hungary).

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312

containing a 109Cd target, following air-drying for 48 h at room temperature (20 G 2 C) and gentle grinding to minimize the effects of variable water content and grain size. Measurements were carried out following the US EPA 6200 Method (US EPA, 1998), optimized for the FPXRF technique.

the top 40 cm consists of 14e17% silt, whereas depths O50 cm silt comprises less than 4% of total particle mass. In core b, silt comprises less than 18% of each sample at depths !210 cm, while at 220e230 cm, silt is considerably more abundant, at 65%. These size distributions are important because they reflect, in a gross way, the mineralogy of the constituent particles. The XRD analyses reveal that there are no obvious qualitative mineralogical differences among the samples taken from sites of different hydrology (Fig. 3). Moreover, samples from each of these two environments were broadly similar in color and texture. The dominant mineral phases in all samples are quartz, pyrite and K-feldspar (orthoclase). In addition, trace quantities of calcite, gypsum, and aluminosilicates (chlorite, illite, montmorillonite, sanidine, albite and augite) were identified in certain samples, both unsaturated and saturated. Further, SEM/EDX investigations supported the findings of the XRD analysis, with the identification of quartz, pyrite and K-feldspar as the dominant minerals. However, SEM/EDX revealed differences in the distribution of the minor phases between the two cores. Sphalerite (ZnS), for example, is more abundant in the unsaturated core (a) than in the saturated core (b), where this mineral could be identified only in the sample from 220 cm depth. Galena (PbS) was identified at the surface of core a, while

2.4. Wet chemical analyses The pH, Eh and electrical conductivity (EC) of each sample were measured potentiometrically by first preparing suspensions of each mine waste sample in deionized water (1:2.5 w/w), allowing each to equilibrate for 24 h at room temperature (20 G 2 C) before measurement. Heavy metals (Pb, Zn, Cu, Cd, As and Fe) were extracted with both deionized water and DTPA (diethylenetriamineepentaacetic acid; Sigma), the latter giving a measure of the potentially bioavailable metal pool. For each extraction, 100 g air-dry mine waste was combined with either 200 mL deionized water or 200 mL 0.005 M DTPA extractant prepared previously (Quevauviller, 1998). The water and DTPA suspensions were agitated at 20 G 2 C in a mechanical shaker for 4 and 2 h, respectively. Following the reaction period each suspension was filtered to obtain the supernatant solution, which was then analyzed for total Pb, Zn, Cu, Cd, As and Fe by ICP-AES.

3. Results 3.1. Solid-phase characterization Particle size distributions for cores a and b are shown inFig. 2. In core a, silt is relatively abundant at depths !40 cm, as compared to the deeper sediments. Specifically, S%

GRAVEL

SAND

SILT

FINE SAND

CLAY

100 75-80 cm

120-130 cm

5-15 cm

50-60 cm

70 30-40 cm

60 50 40 30 20 10 0 5 4

10 8 7 6 5 4

1.0 8 7 6 5 4

0.1 8 7 6 5 4

0.01 8 7 6 5 4

(a)

3 0.002

0.001

lg "d" particle size, mm

GRAVEL

FINE SAND

SAND

SILT

CLAY

100 220-230 cm

90 180-190 cm

80 70

200-210 cm

110-120 cm

150-160 cm

40 30 20 10 0

5 4

10 8 7 6 5 4

1.0 8 7 6 5 4

0.1 8 7 6 5 4

0.01 8 7 6 5 4

(b)

3 0.002

0.001

lg "d" particle size, mm Fig. 2. Particle size distributions at selected depths in unsaturated (a) and saturated (b) cores.

E. Kova´cs et al. / Environmental Pollution 141 (2006) 310e320

313

STOE Powder Diffraction System qz 3600

3200

2800 qz

Absolute Intensity

2400

2000

au,ca al

1600

sa cl,or

ill

sp gy

1200

cl gy

py mont

qz ja py,ca,sp

il,py

mont

800

(b) 400

(a) 0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

2Theta

Fig. 3. XRD diffraction patterns of samples from unsaturated (a) and saturated (b) environments at depths 270e290 cm and 230e240 cm, respectively (al: albite, au: augite, ca: calcite, cl: chlorite, gy: gypsum, ill: illite, ja: jarosite, mont: montmorillonite, or: orthoclase, py: pyrite, qz: quartz, sa: sanidine, sp: sphalerite).

in core b it was found only at 220 cm. Calcite occurred throughout all but the top 30 cm of core a, while it was present only at 230 cm in core b. Gypsum abundance was negatively correlated with calcite in core a, while in core b, gypsum was found only at 170 cm. Iron(III) oxides were identified only in the upper 80 cm of core a, but were present throughout core b. SEM/EDX additionally revealed the presence of large, well-crystallized cubic pyrite grains present in all samples (Fig. 4), which, owing to their high degree of crystallinity, presumably minimizes the rate of FeS2 weathering in both cores a and b.

(a)

3.2. Total Pb, Cu, Zn and Fe Total Pb, Cu and Zn concentrations in cores a and b are shown in Fig. 5. In core a, Pb, Cu and Zn concentrations vary from 40 to 516 mg kgÿ1, 70 to 452 mg kgÿ1, and 75 to 1890 mg kgÿ1, respectively. Lead concentration is highest at the surface, and is remarkably uniform throughout the remainder of the core, with the exception of a minimum at 90e 100 cm. Copper and Zn also show concentration minima at 90e100 cm. In core b, Pb, Cu and Zn concentrations vary from 25 to 1540 mg kgÿ1, 70 to 921 mg kgÿ1, and 63 to

(b)

100 µm

70 µm

Fig. 4. SEM images of cubic pyrite on K-feldspar from sites (a) and (b).

E. Kova´cs et al. / Environmental Pollution 141 (2006) 310e320

314 0

0 20 40 60

depth, cm

20 40 60 80 100 120 140 160 180 200 220 240 260 280

Pb Zn Cu

80 100 120 140 160 180 200 220 240 260 280 300

300 0

400

(a)

800

1200

1600

2000

concentration, mg kg-1

1000

(b)

2000

3000

4000

5000

concentration, mg kg-1

Fig. 5. Total Pb, Cu and Zn concentration profiles in the unsaturated (a) and saturated (b) sediments (FPXRF detection limits for Pb, Cu and Zn are 25, 70 and 60 mg kgÿ1, respectively).

4547 mg kgÿ1, respectively. However, metal concentrations greater than 300 mg kgÿ1 occur only below 200 cm. Total Fe in core a decreases from 51 890 mg kgÿ1 at the surface to 13 196 mg kgÿ1 at 50e60 cm, then peaks at 72 550 mg kgÿ1 between 70 and 90 cm (Fig. 6A). Below 100 cm, Fe concentration in core a increases gradually from 12 800 to 29 187 mg kgÿ1. In the top 190 cm of core b, Fe concentration varies between 20 889 and 41 984 mg kgÿ1. Between 190 and 230 cm, total Fe increases, with a maximum of 55 090 mg kgÿ1 at 230 cm.

280 cm. Within core b, pH values range from 4.0 at the surface to 3.2 at 180 cm depth. At depths O180 cm, pH values increase markedly, ranging from 6.6 at 200 cm to 7.2 at 240 cm. The redox potentials mirror the pH values. Where pH is acidic, the redox potential ranges from 200 to 250 mV, while a redox of 25 to ÿ10 mV is measured when pH is 6.6e7.0. At pH O 7, redox potentials are between ÿ20 and ÿ30 mV. The electrical conductivity profiles are shown in Fig. 8. EC values for core a are highest at the surface (10.5 mS cmÿ1) then decrease to w1 mS cmÿ1 at 20 cm. Below 40 cm, EC values vary between 5.3 and 7 mS cmÿ1. Within core b, EC generally increases with depth: 1.2 mS cmÿ1 at the surface and 9.8 mS cmÿ1 at 240 cm. The solubility of the highly toxic Pb and Cd, and less toxic Zn and Cu, is of considerable environmental importance. Iron, on the other hand, though abundant, is rarely toxic, but warrants attention for two principal reasons: (i) aqueous Fe concentrations reflect the thermodynamic equilibria between

3.3. pH, Eh, electric conductivity and soluble Fe The pH and redox potentials of tailing material from each of the two sampling cores are shown in Fig. 7. Within core a, pH values of the near-surface material are similar to those from the saturated core, with pH values ranging from 3.6 to 4.0. At depths O40 cm, pH values of the unsaturated material are considerably higher, ranging from 7.0 at 50 cm to 7.4 at 0

20 40

20 40 60 80 100 120 140

120 140

depth, cm

80 100

160 180 200 220

saturated

160 180 200 220 240 260 280

240 260 280 300

300 0

(A)

unsaturated

20000

40000

60000

concentration, mg kg-1

80000

(B)

concentration, mg kg-1

Fig. 6. Total (A) and water-soluble (B) Fe concentration profiles in the unsaturated (a) and saturated (b) sediments.

0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300

315

0 20 40 60 80 100

depth, cm

E. Kova´cs et al. / Environmental Pollution 141 (2006) 310e320

unsaturated saturated

120 140 160 180 200 220 240 260 280 300

(A)

-100

-50

(B)

100

150

200

250

300

redox potential, mV

Fig. 7. pH (A) and redox potentials (B) of sample-water suspensions (1:2.5 w/w) for the unsaturated (a) and saturated (b) sediments.

dissolved Fe(III) and solid-phase Fe(III), and (ii) dissolution of the Fe(III) oxides will influence release of Pb, Cd, Zn and Cu to solution. As indicated in Fig. 6B, water-soluble Fe is %1 mg kgÿ1 throughout all of core a, while in core b, soluble Fe is markedly higher, reaching a maximum of w10 mg kgÿ1 at 150 cm depth, then decreasing to less than 1 mg kgÿ1 at depths O200 cm. From these data we predict increased solubility of Pb, Cd, Zn and Cu where Fe is most soluble (i.e. core b, 50e190 cm).

3.4. Heavy metal solubility and potential bioavailability

0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300

20 40

60 80

unsaturated saturated

depth, cm

The maximum water-extractable Pb concentrations in cores a and b are 0.3 mg kgÿ1 at 50 cm, and 0.4 mg kgÿ1 at 130 cm, respectively (Fig. 9). Water-soluble Pb is below the detection limit at depths O100 cm for core a, and at depths O200 cm for core b. The maximum DTPA-extractable Pb concentration

in core a is 0.4 mg kgÿ1 at 20 cm, while in core b it is 0.82 mg kgÿ1 at 130 cm. At 300 cm, in both cores a and b, the DTPA-extractable Pb concentrations are less than 0.1 mg kgÿ1. The maximum water- and DTPA-extractable Zn concentrations are observed at 90e110 cm (Fig. 10). However, soluble Zn in core a is approximately 1.5e2 times less than that for core b. Specifically, the water-extractable Zn concentrations for cores a and b are 5 and 7 mg kgÿ1, while the DTPAextractable Zn concentrations are 4.8 and 9.5 mg kgÿ1, respectively. At depths O200 cm, both water- and DTPA-extractable Zn concentrations are below 1 mg kgÿ1. The maximum concentrations of both water- and DTPAextractable Cu occur at 20e50 cm in core a, and at 120 cm in core b (Fig. 11). The water-extractable Cu concentration maximum is 5.5 mg kgÿ1 in core a and 11 mg kgÿ1 in core b, similar to the DTPA-extractable concentrations: 9.8 mg kgÿ1 and 10.8 mg kgÿ1, respectively.

100 100 120 140 160 180

water extract, unsaturated DTPA extract, unsaturated water extract, saturated DTPA extract, saturated

200 220 240 260 280 300 0

9 10 11 12 13 14

electric conductivity, mS cm-1 Fig. 8. Electrical conductivity of sample-water suspensions (1:2.5 w/w) for unsaturated (a) and saturated (b) sediments.

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

concentration, mg l-1 Fig. 9. Concentration of Pb in water and DTPA extracts of samples from unsaturated (a) and saturated (b) sediments.

E. Kova´cs et al. / Environmental Pollution 141 (2006) 310e320

316

0 20 40 60 80

60 80 100 120 140 160 180 200 220 240 260 280

water extract, unsaturated DTPA extract, unsaturated water extract, saturated DTPA extract, saturated

depth, cm

0 20 40

300 0

100 120 140 160 180 200 220 240 260 280 300

water extract, unsaturated DTPA extract, unsaturated water extract, saturated DTPA extract, saturated

concentration, mg l-1

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

1.1

concentration, mg l-1 Fig. 12. Concentration of Cd in water and DTPA extracts of samples from unsaturated (a) and saturated (b) sediments.

The maximum water-extractable Cd concentration in core a is 0.4 mg kgÿ1 at 50 cm, while in core b it is 0.7 mg kgÿ1 at 120 cm (Fig. 12). At depths O200 cm, water-extractable Cd concentrations are less than 0.02 mg kgÿ1 in both cores. The maximum DTPA-extractable Cd in core a is 1.1 mg kgÿ1 at 20 cm, while in core b it is 1.05 mg kgÿ1 at 120 cm. At depths O200 cm, the DTPA-extractable Cd concentrations of both cores are less than 0.15 mg kgÿ1. The soluble Cd concentration profiles are similar to those of Zn. The maximum concentrations for both the water- and DTPA-extractable As occur at 50 cm in core a, and at 120 cm in core b (Fig. 13). Specifically, these concentrations for cores a and b are 6.2 and 8.5 mg kgÿ1 in the water extracts, and 4.8 and 3.8 mg kgÿ1 in the DTPA extracts, respectively. In cores a and b, the water-extractable As concentrations are less than the detection limit below 160 and 240 cm, respectively, while for both cores the DTPA-extractable As concentrations are less than 1 mg kgÿ1 at depths O200 cm.

4. Discussion 4.1. Mineralogy and total element content In core a, sphalerite was detected in each sample with SEM/EDX, which correlates well with the elevated total Zn concentration. In core b, sphalerite grains were not detected in the upper 220 cm, which explains the lower total Zn concentration in this profile (Fig. 5). Galena presence, as confirmed by SEM/EDX, coincided with maximum total Pb concentration in both cores, indicating that Pb occurred largely in the form of this mineral. Copper was identified in trace quantities with FPXRF. Although its host mineral could not be identified, the Cu-containing solid phases were found at 80 cm in core a, and 230 cm in core b, where total Cu concentrations also showed maxima. The vertical profile of CaCO3 and CaSO4 yields important information on weathering, as CaCO3 neutralizes acidity,

0 20 40 60 80

100 120 140 160 180 200 220 240 260 280

water extract, unsaturated DTPA extract, unsaturated water extract, saturated DTPA extract, saturated

depth, cm

Fig. 10. Concentration of Zn in water and DTPA extracts of samples from unsaturated (a) and saturated (b) sediments.

water extract, unsaturated DTPA extract, unsaturated water extract, saturated DTPA extract, saturated

300

300 0

concentration, mg l-1 Fig. 11. Concentration of Cu in water and DTPA extracts of samples from unsaturated (a) and saturated (b) sediments.

concentration, mg kg-1 Fig. 13. Concentration of As in water and DTPA extracts of samples from unsaturated (a) and saturated (b) sediments.

E. Kova´cs et al. / Environmental Pollution 141 (2006) 310e320

while CaSO4, stable at low pH, is formed from the sulfate produced by oxidation of pyrite. SEM/EDX reveals an inverse relationship between the two minerals in core a, where in the upper 30 cm layer there is no CaCO3 but CaSO4 is present. In core b, however, no such trend can be seen, and CaCO3 and CaSO4 appear only at w170 cm. Total Fe consists of Fe in all solid phases, including pyrite and Fe-oxides, as well as all sorbed Fe. In core a maximum Fe concentrations occur at 70e90 cm, whereas in core b, the highest total Fe concentrations occur at depths O200 cm. Iron-oxide presence, confirmed by SEM/EDX analysis, indicates that in core a weathering has occurred mainly in the upper layers, while in core b weathering has occurred throughout the profile. This is the opposite of what would be expected under water-saturated conditions (Romano et al., 2003), and alludes to a previous, more intensive weathering regime for core b. Total Pb, Zn and Cu concentrations are generally higher in core b than core a (Fig. 5). However, the uppermost portions of core a contain total Pb, Zn and Cu in concentrations that exceed those in core b. These trends can be explained by either less intensive weathering in core a, or more intensive leaching of weathered products within core b. The latter scenario may arise from the greater mobility of Pb, Zn and Cu under acidic conditions (Grasselly, 1995), such as those which characterize core b. 4.2. pH, Eh, and soluble Fe As previously mentioned, core b is more oxic than core a between 40 and 200 cm. This is unexpected given the presumed continual submergence of core b. However, high redox potentials coupled with low pH were observed previously in the sediments of an acidic mining lake (Bachmann et al., 2001), and also in laboratory core experiments utilizing saturated, pre-oxidized tailing materials (Simms et al., 2000). The pHeEh profiles also suggest that core b has experienced occasional drying in the past, and a consequent increase in oxidative weathering. Core b generally contains higher concentrations of soluble Fe than core a. Under saturated, reducing conditions, one would expect reductive dissolution of Fe(III) (oxy)hydroxides, releasing Fe(II) to solution. However, as core b is generally more oxic than core a (Fig. 6), pH is evidently the variable controlling Fe(III) oxide dissolution and subsequent release of Fe(III) to solution in core b. Relationships among pH, Eh and water-soluble Fe were modeled using the speciation program Visual MINTEQ (Gustafsson, 2003). The redox couples Fe2C/Fe3C and HSÿ/ SO2ÿ were considered in the thermodynamic calculations, 4 with Eh and pH fixed at the measured values ÿ30 mV and 3.2, and 250 mV and 7.5. The species activities in aqueous solution and the saturation indices (log[IAP/K]) of possible solid phases are given in Tables 1 and 2. Goethite, hematite and ferrihydrite become more stable, indicated by less negative saturation indices, as pH increases and as the system becomes more oxidizing. Based on these model calculations, goethite

317

Table 1 Predicted species distribution under representative pH and Eh conditions Species (pH Z 3.2; Eh Z ÿ30 mV)

Log activity

Species (pH Z 7.5; Eh Z 250 mV)

Log activity

Fe2C

ÿ15.735

Fe(OH)2C Fe(OH)3 (aq) Fe(OH)ÿ 4 Fe2C FeOHC

ÿ15.838 ÿ16.304 ÿ17.832 ÿ17.438 ÿ19.335

H2S(aq) HSÿ

ÿ15.699 ÿ19.519

SO2ÿ 4

ÿ15.7

is the most stable Fe(III) oxide under both oxidizing and reducing conditions. Consequently, goethite is the Feoxide most likely to control sorption of metals in our systems. Experimental data support these model calculations, with both water- and DTPA-extractable Pb, Zn, Cu and Cd concentration profiles (Figs. 9e12) following the Fe-oxide abundance profiles detected with SEM/EDX. 4.3. Metal mobility and bioavailability The solubility and mobility of toxicant metals in our system can be described in terms of: (i) adsorptionedesorption reactions at mineral surfaces, principally the Fe-oxides, (ii) pH and Eh controlled dissolutioneprecipitation processes, and (iii) migration of colloid-bound metal through leaching. The solubility of Pb, Zn, Cd and Cu generally increase with decreasing pH. However, water-soluble concentrations do not show significant correlation with pH, with the exception of Zn in core b (r Z ÿ0.810, P ! 0.05) (Tables 3 and 4). In core a, the maximum soluble metal concentrations occur in the upper sediment, which is acidic. At depths R200 cm, where the sediments are at circumneutral pH, heavy metal solubility is predictably low. Within these and other sediments Table 2 Possible solid phases under representative pH and Eh conditions Mineral

Sat. index (pH Z 3.2; Eh Z ÿ30 mV)

Sat. index (pH Z 7.5; Eh Z 250 mV)

Fe(OH)2 Fe2(SO4)3 Fe3(OH)8 Ferrihydrite FeS (ppt) Goethite Greigite Hematite H-jarosite Lepidocrocite Mackinawite Maghemite Magnetite Melanterite Pyrite Sulfur Wustite

ÿ22.899 ÿ140.122 ÿ68.905 ÿ22.865 ÿ29.104 ÿ20.165 ÿ94.524 ÿ37.930 ÿ116.594 ÿ21.045 ÿ28.454 ÿ45.734 ÿ52.085 ÿ41.962 ÿ30.879 ÿ15.188 ÿ20.189

ÿ16.002 ÿ95.854 ÿ30.149 ÿ6.935 ÿ90.337 ÿ4.235 ÿ328.287 ÿ6.071 ÿ60.532 ÿ5.115 ÿ89.687 ÿ13.875 ÿ13.330 ÿ30.929 ÿ142.176 ÿ65.252 ÿ13.202

E. Kova´cs et al. / Environmental Pollution 141 (2006) 310e320

318

Table 3 Correlation coefficients of water- and DTPA-soluble heavy metal concentrations with pH for core a DTPA extract

Zn in water extract r P n

0.164 0.651 10

0.182 0.593 11

Cu in water extract r P n

ÿ0.035 0.914 12

ÿ0.049 0.880 12

Cd in water extract r P n

0.317 0.406 9

0.217 0.576 9

r: Spearman coefficient, P: significance level.

a ‘neutralization zone’, rich in acid-buffering carbonate minerals, is responsible for the markedly reduced solubility and bioavailability of Pb, Zn, Cu and Cd. Such zonation of contaminant availability, reflecting mineralogical composition of the sediments, has been reported previously (Blowes et al., 1991; Brown and Hosseinipour, 1991; Ljungberg and ¨ hlander, 2001; Dold and Fontbote´, 2002). O In core a, the oxidation zone occurs at depths !40 cm, where weathering is intense. Proton release arising from oxidation of pyritic minerals facilitates the dissolution of metalcontaining solids and the subsequent leaching of these metals to greater depths. Where pH is poised at pH 3e4 by the HC-buffering capacity of Fe-(oxy)hydroxides, heavy metal

Table 4 Correlation coefficients of water- and DTPA-soluble heavy metal concentrations with pH for core b DTPA extract

Pb in water extract r P n

0.886** 0.019 6

ÿ0.029 0.957 6

Zn in water extract r P n

0.929* 0.001 8

ÿ0.810** 0.015 8

Cu in water extract r P n

0.804* 0.002 12

ÿ0.727 0.057 12

Cd in water extract r P n

0.864* 0.001 11

ÿ0.391 0.235 11

As in water extract r P n

ÿ0.393 0.383 7

*Significant correlation, P ! 0.01; **significant correlation, P ! 0.05. r: Spearman coefficient, P: significance level.

solubility is relatively high (Figs. 9e12). Low concentrations of soluble heavy metal at 50e60 cm indicate that a neutralization zone, dominated by carbonates, may be present at this depth. Additionally, gypsum, whose presence was confirmed by SEM/EDX and abundant soluble S (68 mg kgÿ1) may, along with calcite, form a cemented layer that restricts O2 diffusion to deeper layers (Bain et al., 2000). In the top 200 cm of core b, pH is again poised near 3.5 by Fe-(oxy)hydroxides (Salomons, 1995; Shaw et al., 2000). The absence of carbonate minerals in this top 200 cm contributes to the low pH, with the consequent high levels of soluble metals (Figs. 9e12). The presence of a neutralization zone below 200 cm, comparable to that in core a, is indicated by a circumneutral pH, decreased levels of soluble metal, and maximum levels of soluble Ca. Particle size distributions of sediments in cores a and b can also reveal much about past metal migration, as the metals sorbed to silt- and clay-size fractions are carried downward by the percolating waters (Fig. 2). Accumulation of silts and clays, arising from flocculation and precipitation of colloidal particles at circumneutral pH, gives further evidence for the presence of neutralization zones. In both cores a and b, silt abundance increases significantly at depths of 40 cm and 200 cm, respectively, further supporting our contention that these regions are neutralization zones, as defined previously. The DTPA-soluble heavy metal concentration maximum values correspond broadly with the water-soluble metal concentration maxima. However, statistically significant correlations were found only for core b, where every element correlated strongly (Tables 3 and 4). In core b, therefore, DTPA-extractable heavy metal concentrations can be estimated reliably from the water-soluble concentrations, indicating that these two extraction methods are mobilizing broadly equivalent metal pools. Ratios of total element concentration to DTPA-extractable element concentration are given in Table 5. The values reported in this study are highly relative to those found for other PbeZn mine tailings. For comparison, Ye et al. (2002) calculated ratios of 9.1, 33.9, and 32.3 for Pb, Zn and Cu, respectively, while Vega et al. (2004) calculated 19.3, 55.5, and 6.5, respectively. The greater total/extractable ratios observed in our study reveal a relatively smaller labile metal pool and suggest that the sediments examined at Gyo¨ngyo¨soroszi are less weathered than those examined by Ye et al. (2002) and Vega et al. (2004). Consequently, a smaller proportion of total metal pool is bioavailable at our study site, in both cores a and b. 5. Conclusions Total element and SEM/EDX analyses reveal qualitative differences in the vertical distribution of minor mineral phases between well-aerated and predominantly submerged mine tailing sediments. Contrasting hydrology has induced differential weathering within the two sediment cores, with the well-aerated core showing the most intense near-surface weathering. Furthermore, total element and mineral abundance profiles, along with pH, Eh and particle size distribution profiles, reveal the

E. Kova´cs et al. / Environmental Pollution 141 (2006) 310e320 Table 5 Ratios of total element concentration to DTPA-extractable element concentrations for Pb, Zn and Cu in cores a and b Core a

Core b

Depth, cm (a)

Depth, cm (b)

5 20 30 50 70 90 100 120 150 200 260 290

15 856 2191 516 2662 4275 564 2096 7102 11 945 5369 2079 19 514

46 22 2 34 28 8642 13 72 311 277 78 893

16 nd 39 263 20 671 nd 272 nd 135 nd nd

10 30 50 70 90 110 130 150 180 200 220 240

nd 3260 nd 524 2151 3297 1056 3780 3913 nd 3369 28 224

15 110 14 94 237 318 25 641 249 5516 66 409

nd nd nd nd nd 189 nd nd nd 1188 88 4623

nd: non-detectable concentration for either total or DTPA-soluble element concentration.

presence of metal attenuation zones at different depths in each core, created by the downward transport and subsequent accumulation of water-borne silt-sized carbonate minerals. Goethite accumulations in the weathered sediments serve as effective sorbents, at circumneutral pH, of many of the toxicant metals. We conclude that differential hydrology induces variable heavy metal speciation and biolability in PbeZn mine tailings, with the consequence that site-specific risk assessments must account for past and present hydrological regimes to accurately assess the risk posed by metal toxicants.

Acknowledgement Analyses were conducted at The Natural History Museum, London, UK, with financial support from the European Union FPV SYS-RESOURCE Programme. The authors thank the staff of the Mineralogy Department, Natural History Museum, and the Department of Water and Environmental Management, University of Debrecen, Hungary, for assistance with many of the analyses.

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