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Eur. J. Mineral. 2010, 22, 639–649 Published online April 2010

Paper presented at the Mineralogy, Environment and Health symposium, Marne-la-Valle´e, September 2009

Health risk assessment for human exposure by direct ingestion of Pb, Cd, Zn bearing dust in the former miners’ village of Jebel Ressas (NE Tunisia) MANEL GHORBEL1,2, MARGUERITE MUNOZ1,*, PIERRE COURJAULT-RADE´1, CHRISTINE DESTRIGNEVILLE1, PHILIPPE DE PARSEVAL1, RADHIA SOUISSI3, FOUAD SOUISSI2, ABDALLAH BEN MAMMOU2 and SAˆADI ABDELJAOUAD2 1

Universite´ de Toulouse-UPS–CNRS–IRD, LMTG, 14 avenue E. Belin, 31400 Toulouse, France *Corresponding author, e-mail: [email protected] 2 Universite´ de Tunis El Manar, RME, Faculte´ des Sciences, 1060 Tunis, Tunisie 3 Institut National de Recherche et Analyses Physico-chimiques, Poˆle Technologique de Sidi Thabet, 2020 Sidi Thabet, Tunisie

Abstract: Mining activity in Jebel Ressas (1880–1956) generated important quantities of wastes. The former miners’ village is expanding very close to the waste dumps which are highly concentrated in Pb, Zn and Cd. Under the semi-arid Mediterranean climate, wind erosion triggers the transport of contaminated dust towards the village. A health risk may exist for inhabitants related to their exposure to contaminated dust via ingestion, inhalation and dermal contact. This study is dedicated to the evaluation of the health risk after direct ingestion of dusts. Seven samples of dusts were collected in living places over the village. Anomalous metal concentrations in dusts range respectively from 0.16 wt% to 1.14 wt% of Pb, 0.35 wt% to 2.49 wt% of Zn and 14 to 109 mg/kg of Cd. SEM-EDS analysis of the dust particles shows that calcite is dominant and that metalliferous minerals are mainly Pb and Zn carbonates and Zn silicates. Iron oxy-hydroxides exist in small proportions and Pb and Zn sulfides are scarce. Modeling the quantity of dissolved metals in a simulated gastric fluid was performed taking into account the dust mineralogy and the daily ingested quantities of dust, ranging from 100 mg for adults to 200 mg for children. The ratio of dissolved metals to initially ingested ones defines the bioaccessibility factor. It gives the fraction of metals able to reach the blood through the intestinal wall. Modeling the dissolution of two dust samples, the most and the less concentrated ones in metals, was performed considering a gastric fluid with two extreme pH values (0.93 and 5.0). All dust minerals totally dissolve except cerussite for the most concentrated sample in a gastric fluid of pH 5. Therefore, the bioaccessibility factor of Zn and Cd is equal to 1, that of Pb ranges between 0.27 and 1. Then, an estimation of the occurrence of risk was calculated from the ratio of the daily exposure dose by direct ingestion and the reference dose. The risk occurs with a ratio above 1. The global risk of ingestion of three metals is high for the children, especially for Pb with a ratio reaching 39. The risk for adults appears for Pb with a ratio of 4.6 in the case of ingestion of most concentrated dusts. However, the integration of the other routes of exposure in the calculation of the risk must be taken into account for a thorough estimation. Key-words: mining wastes, speciation, dust, metal-bearing carbonates, gastric fluid, bioaccessibility.

1. Introduction

digestive systems (Kabata-Pendias & Mukherjee, 2007). These heavy metals must be considered as hazardous substances which can induce a risk to human health (Xenidis et al., 2003). Among the various sources of metals, abandoned mining sites have to be considered. Particularly, former miners’ villages which lie immediately adjacent to former treatment plants have undergone historical accumulation of metals in soils and generate exposure of inhabitants via different pathways. Health risk assessment linked to mining sites will depend upon complex interactions of several parameters such as waste mineralogy, climatic conditions and contamination transfer, time elapsed since mine closure, and type of remediation if undertaken to

Heavy metals can migrate from the source of contamination to air, water and soil, via several physical-chemical transfer mechanisms. Contamination can reach the biosphere towards humans and heavy metals may accumulate and, eventually, reach thresholds of toxicity. Cadmium (Cd) and lead (Pb) are common pollutants which may have, in various degrees, a relationship with many pathological states such as renal and bones damage, growth and neurobehavioral problems, high blood pressure and even, potentially, cancer (Kabata-Pendias & Pendias, 2001; US EPA, 2005a). Although Zn is an essential oligoelement, it acts at very high doses especially on immunity and eschweizerbart_xxx

0935-1221/10/0022-2037 $ 4.95 DOI: 10.1127/0935-1221/2010/0022-2037

# 2010 E. Schweizerbart’sche Verlagsbuchhandlung, D-70176 Stuttgart

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reduce impacts of metal contamination. Under semi-arid Mediterranean climate, aeolian transport may carry contaminated dust to living places, representing a major exposure pathway. In this paper, we consider the former Pb-Zn mining site of Jebel Ressas and its miners’ village located in northeastern Tunisia under Mediterranean semi-arid climatic conditions. We focus on health risk assessment related to human exposure via direct ingestion of contaminated dust which is one of the most important exposure pathways, especially for children due to their hand-mouth habit (Al-Rajhi et al., 1996; Cohen Hubal et al., 2000; Bastos Paoliello et al., 2002; Malcoe et al., 2002; Xenidis et al., 2003; Glorennec, 2006) which leads to an estimation of children ingestion rate twice the adult one (US EPA, 1997). In order to assess health risk, mineralogical and geochemical characterization of dust has been carried out. The daily exposure dose, by oral direct ingestion of dust, was calculated for each contaminant (Pb, Cd and Zn) after analysis of the metal concentrations in dust samples and taking into account the bioaccessibilty factor, sensu Carrizales et al. (2006). The bioaccessible amount of a metal is the fraction of total ingested metal that can be released during digestion and then be available for intestinal absorption (Peijnenburg & Jager, 2003). This amount depends on solubility of minerals in gastric fluid. From the mineralogical characterization and on the basis of identified metal-bearing phases, geochemical modeling allowed

calculation of the amounts of metals released from ingested dust in a simulated gastric fluid leading to the determination of the bioaccessibility factor. The risk assessment is given by the ratio of daily exposure dose to the reference dose for each contaminant (US EPA, 2005a).

2. Materials and methods 2.1. Site description The village of Jebel Ressas, 30 km south-east of Tunis, stands at the foot of the Jebel Ressas mountain where the abandoned Pb-Zn extraction sites are located. Only the main road which crosses the village is available for cars, the other roads being just small trails. It is bordered southwards by the ore processing plant and westwards by the treatment dumps (Fig. 1a). Pb and Zn ores are hosted in the Jurassic calcareous layers and are composed of Pb and Zn sulfides and carbonates, and Zn silicates. The associated minerals are calcite, quartz and pyrite (Sainfeld, 1952). Seventy years of extraction and milling activities between 1880 and 1956 resulted in almost two millions of tons of gravimetry and flotation wastes generated by the ore treatment and dumped in three distinct flat top dumps, DI, DII and DIII (Fig. 1b). The waste materials have a weak cohesion and fine grain size dominated by silts and clay.

Fig. 1. (a) Site location. (b) Sampling points of dust in the Jebel Ressas village. (c) Wind speed and frequencies from National Institute of Meteorology of Tunisia. eschweizerbart_xxx

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processed simultaneously with the samples and validated the analytical procedure. Samples were analysed for total Zn, Pb and Cd using an Agilent 7500 ICP-MS with collision cell. Isobaric interferences were corrected by automatic calculations and polyatomic interferences were corrected by the operator. Dust grains were investigated by SEM-EDS (JEOL JSM 6360 LV) under vacuum and with a carbon coating. Particle chemical analyses were performed by a PGT energy dispersive X-ray microanalyses system (EDS). Backscattered imaging and microanalyses were carried out under an acceleration voltage of 20 kV. Microprobe analyses were carried out with a CAMECA SX50 instrument with SAM’ x automation equipped with three spectrometers (LiF, PET and TAP crystals). Three different programs were used. For sulfide minerals, the acceleration voltage was 25 kV and the current intensity was 20 nA. The time of acquisition was fixed to15 s for all the elements. For oxide minerals, the voltage and the beam current were respectively 15 kV and 10 nA. The time of acquisition was 15 s. The third program was conceived to decrease the detection limits for Cd in oxide minerals using higher beam current (20 nA) and acquisition time (40 s). The Cd detection limit of 0.10 wt% in standard conditions was decreased in optimized conditions to 0.07 wt%. Calibration standards were pure metals for As and Sb, synthetic or natural minerals for Mg (periclase), Ca and Si (wollastonite), Mn and Ti (pyrophanite), Al (corundum), Fe (hematite), Ba (barite), Na (albite), K (sanidine), P (graftonite), Sr (Sr–Ti oxide), Pb (galena and Pb-phosphate), Zn (sphalerite), Cu and S (chalcopyrite), Cd (greenockite). Geochemical modeling was performed with PHREEQC geochemical package (Parkhurst & Appelo, 1999) and we used the ‘‘llnl.dat’’ database which is the most complete mineral database delivered with the code.

Metal-bearing phases from DI and DIII waste dumps are dominated by carbonates and silicates while DII wastes are enriched in Pb and Zn sulfide minerals (Ghorbel et al., 2008). No vegetation has grown on these dumps and no specific management was conceived to prevent their erosion and chemical alteration. The northern dump DIII is under the westerly and north-westerly prevailing winds which favor contaminated dust transfer towards the village (Fig. 1c). Wind-speed frequencies were calculated on basis of 214,704 h observations in Tunis-Carthage station between 1981 and 2005. These data were personally given by the National Institute of Meteorology (NIM) of Tunisia. The annual precipitations average slightly less than 500 mm (NIM, 2009). This situation leads to health risk for inhabitants of the village which has expanded in relation with the development of agricultural activities. Indeed, the Jebel Ressas village involves an area of 0.07 km2 with a few hundreds of inhabitants and it naturally expands on the contaminated treatment area where the ore was ground and concentrated. By example, the football playground was set on the top of dump DIII.

2.2. Sampling and analytical methods Direct ingestion of contaminated particles occurs either outdoors or indoors. Under Mediterranean climatic conditions where people likely live outside, especially children, sampling of outdoor dust was chosen as a representative component for direct ingestion particles. In order to investigate the spreading of dust contamination over the village, seven samples have been collected in the village during Spring 2009 (Fig. 1b). Dust samples of 0.1 to 1.5 g were taken from various dust-laden outdoor surfaces such as window sills, terrace benches, gates and roof tiles. The samples were collected by sweeping with brushes previously cleaned using bi-distilled water as described by Akhter & Madany (1993) and Shinggu et al. (2007). The collected material was placed into cleaned polyethylene pillboxes. In the three treatment dumps, three drill cores of 4 m of depth were performed. The material was mixed, homogenized and quartered to obtain one representative sample of each dump. Grain-size distribution was determined using a Coulter LS 200 laser granulometer with a small volume module and a measurement range of 0.393 to 905.1 mm. From five of the biggest dust samples, 0.5 to 1 g were resuspended in water and ultrasonically dispersed. A mean grain-size distribution was obtained on two repetitions for each sample and two measurements for each repetition. Chemical analysis of dust was performed with ICP-MS after total digestion. First, 75 mg of sample were totally digested using successively 1.5 bi-distilled HNO3 and 1 mL of suprapure HF on a hot plate at 80  C. After partial evaporation, 1 mL of bi-distilled HNO3 was added and we proceeded to a total evaporation. The residue was dissolved in 2 % bi-distilled HNO3 solution. A blank and a certified reference material of zinc ore (RM30) were

3. Results and discussion 3.1. Dust characterization All the samples have almost a similar aspect with a brownish color and a fine grain size. Binocular observation showed that the collected dust is mostly composed of mineral phases with scarce debris of plants. Dust grain-size distribution is almost similar for all the samples, which indicates a homogeneous aeolian sorting all over the village. Grain size is comprised between 0.393 and 80.07 mm with a mono-modal distribution. Cumulative volume curves show that median granulometry is comprised between 19.26 and 32.24 mm (Fig. 2). This granulometry corresponds to dust which might be ingested and 15 to 33 % of the samples are composed of inhalable particles with a grain size below 10 mm (Sloss & Smith, 2000). Heavy-metal concentrations of the seven dust samples range from 0.35 to 2.49 wt% for Zn, from 0.16 to 1.14 wt% for Pb and from 14 to 109 mg/kg for Cd (Table 1). These eschweizerbart_xxx

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Fig. 2. Grain-size cumulative curves of dust samples.

Fig. 3. Pb and Zn concentrations in dust and treatment dump samples; correlation factor calculated for dust samples and DIII treatment dump sample.

Table 1. Pb, Zn and Cd concentrations in treatment dumps (DI, DII, DII) and dust samples (Dust 1 to 7).

and Zn. Pb and Zn sulfide grains are rare and do not exceed a tenth of micrometer. No Cd peak appears in the SEMSample Pb (wt%) Zn (wt%) Cd (mg/kg) EDS spectra. All these minerals were already identified in the treatDI 1.27 5.20 170 ment wastes located next to the village (Ghorbel et al., DII 0.09 2.02 110 2008) and analysed with the electron microprobe. As there DIII 2.30 7.11 290 Dust 1 0.34 0.84 32 is no limitation of quantity of sample with the treatment Dust 2 0.38 0.75 26 wastes compared to dust, additional microprobe analyses Dust 3 0.56 1.40 49 were carried out with samples collected on the three Dust 4 0.40 0.83 36 dumps, especially to detect Cd in oxide minerals. Table 2 Dust 5 1.14 2.49 109 gives microprobe results obtained with both standard and Dust 6 0.16 0.35 14 Cd-specific programs on oxide minerals. Dust 7 0.23 0.61 26 Microprobe analyses showed that Pb-bearing phases are cerussite, Pb-bearing strontianite (up to 46.1 wt% of Pb), values largely exceed the global average soil values given iron oxy-hydroxides (up to 16.7 wt% of Pb). Zinc-bearing phases are smithsonite, hydrozincite, willemite, hemimorby Kabata-Pendias & Mukherjee (2007). The variability of metal concentrations is high and most phite and iron oxy-hydroxides (up to 9.6 wt% Zn). probably due to dilution of contaminated dust by not con- Identified sulfide minerals are galena, sphalerite and pyrite taminated surrounding material upon the site of sampling. In (Table 3). Fig. 3, Zn concentrations in dust samples as well as in treatment dump samples have been plotted as a function of Pb concentrations. The points representing dust concentrations line up on a mixing trend with the northern dump composition (DIII) as end-member. A same trend would appear when plotting Cd instead of Zn or Pb. This is consistent with a major contribution of this dump to the dust emission towards the village due to its localisation under the prevailing westerly and north-westerly winds (Fig. 1b, c). The SEM-EDS investigations on dust showed that calcite is the major mineral component (Fig. 4). Aluminosilicates were also noted in smaller proportions. Fig. 5 presents the metals-bearing phases recognized in sample dusts (105 particles analysed). The metalliferous phases are mainly oxides. Although SEM-EDS investigations cannot allow a definite mineral diagnosis, the context and the origin of dust suggest that the most frequent Pb and Zn Fig. 4. Backscattered electron image giving a general view of dust, phases are carbonates. Zn-silicates particles are also pre- and EDS spectrum of dominating grey calcite particles. The metalsent and iron oxy-hydroxides display minor contents of Pb bearing particles are the brighter ones. eschweizerbart_xxx

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Fig. 5. Backscattered electron images and individual EDS spectra of metal-bearing particles from dust sample.

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Min Max nd nd na na 25 27.6 na na nd nd nd nd nd 3.43 69.9 74.7 na na nd nd nd nd nd 0.44

Median – – 1.00 – 0.00 – 0.00 1.99 – – – –

Min – – 0.95 – 0.00 – 0.00 1.96 – – – –

Max – – 1.04 – 0.02 – 0.05 2.04 – – – –

cations ¼ 3

Median nd na 27 na nd nd nd 72.5 na nd nd nd

Willemite [31] Zn2 SiO4

Median 0.00 – 2.04 – 0.00 – – 3.96 – – – –

Min 0.00 – 1.81 – 0.00 – – 3.88 – – – –

Max 0.02 – 2.12 – 0.01 – – 4.17 – – – –

Median 0.01 – – – 0.02 0.00 0.00 0.96 – – 0.00 0.00

Min 0.00 – – – 0.00 0.00 0.00 0.95 – – 0.00 0.00

wt%

Hydrozincite [8] Zn5 (OH)6 (CO3)2

Max 0.04 – – – 0.04 0.00 0.00 0.99 – – 0.01 0.01

Median 0.01 – – – 0.01 0.00 0.00 4.95 – – 0.00 0.02

Min 0.00 – – – 0.00 0.00 0.00 4.91 – – 0.00 0.01

cations ¼ 5 Max 0.03 – – – 0.05 0.00 0.02 4.96 – – 0.02 0.03

Formula calculated on the basis of

Min – – – – 0.00 0.00 – 0.00 – 0.00 0.00 0.51

Max – – – – 0.06 0.00 – 0.11 – 0.45 0.01 1.00

cations ¼ 1 Median – – – – 0.01 0.00 – 0.01 – 0.00 0.00 0.97

Pb strontianite [10] Sr1–x Pbx (CO3)

Median – – – – 0.06 – – 0.02 – 0.74 0.00 0.19

Min – – – – 0.01 – – 0.00 – 0.53 0.00 0.05

cations ¼ 1 Max – – – – 0.13 – – 0.03 – 0.83 0.00 0.45

Median – – – – – – – – – – – –

– – – – – – – – – – –

– – – – – – – – – – –

Min Max

Max 0.18 3.30 7.17 0.54 0.52 0.19 85.9 11.9 3.40 nd nd 18.7

Iron oxy-hydroxide [41]

Min Max Median Min Max Median Min nd nd nd nd nd nd nd nd nd nd nd nd 0.14 nd nd 0.14 nd nd nd 3.19 0.41 nd 0.68 nd nd nd 0.16 0.01 nd 1.36 1.95 0.40 4.84 0.18 nd nd 0.10 nd nd nd nd nd nd 0.56 nd nd 0.06 67.3 56.7 nd 3.76 0.75 nd 1.17 6.58 1.21 nd nd nd nd nd 1.37 0.10 nd 22.4 45.8 27 59.1 nd nd nd 0.50 nd nd 0.13 nd nd 54.4 84.3 25.3 7.2 49.7 5.5 2.2

Cerussite [36] PbCO3

Max Median Min Max Median 1.13 0.05 nd 0.21 nd nd nd nd nd nd 0.12 0.18 nd 0.31 nd 0.08 0.17 0.16 0.17 nd 1.70 0.12 nd 0.52 0.26 0.11 0.01 nd 0.05 nd 0.28 0.11 nd 0.65 nd 64.8 72.7 70.2 74.8 0.32 nd nd nd nd nd nd nd nd nd nd 0.57 nd nd 0.46 nd 1.07 0.95 0.54 1.23 81.7

cations ¼ 1

Min 0.00 nd nd 0.01 0.11 nd nd 61.5 nd nd nd nd

Smithsonite ZnCO3 [20] ZnCO3

Max Median 0.14 0.29 nd nd 26.7 nd nd 0.04 0.09 1.01 nd nd 0.33 nd 69.1 62.7 nd nd nd nd nd 0.21 nd 0.43

cations ¼ 6

Median Min nd nd nd nd 25.7 22.1 nd nd nd nd nd nd 0.24 nd 67.6 66.5 nd nd nd nd nd nd nd nd

Hemimorphite [5] Zn4 Si2O7 2H2O

Results are obtained with both standard and Cd specific programs for oxide minerals. nd ¼ not detected. na ¼ not analyzed. – ¼ not calculated. [n] ¼ analyses number for each mineral. (*) ¼ theoretical formula of the mineral.

Mg Al Si S Ca Mn Fe Zn As Sr Cd Pb

MgO Al2O SiO2 SO3 CaO MnO Fe2O3 ZnO As2O3 SrO CdO PbO

(*)

Table 2. Microprobe analyses and calculated structural formula of oxide-based minerals.

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Table 3. Microprobe analyses and structural formula of sulfide minerals. Pyrite [16]

Sphalerite [20]

Galena [8]

FeS2

ZnS

PbS

(*) S Fe Cu Zn As Cd Sb Pb

wt% Median 53.60 46.22 nd 0.58 0.40 nd nd nd

Min 52.41 44.85 nd 0.11 0.18 nd nd nd

Max 54.28 47.15 nd 0.91 0.79 nd nd 1.53

Median 33.40 0.12 nd 66.28 nd 0.52 nd nd

Min 32.84 0.04 nd 64.34 nd 0.16 nd nd

Max 33.89 1.69 nd 67.13 nd 0.98 nd nd

Median 14.02 nd nd 0.26 nd nd nd 86.51

Min 13.79 nd nd nd nd nd nd 85.46

Max 14.10 nd nd 1.08 0.29 nd nd 87.13

Formula calculated on the basis of cations ¼ 1 S As Fe Zn Cd Pb

Max 1.99 0.01 0.99 0.01 – 0.00

Max 1.98 0.00 0.96 0.00 – 0.00

cations ¼ 1 Max 2.00 0.01 1.00 0.03 – 0.01

Median 1.01 – 0.00 0.98 0.00 –

Min 1.00 – 0.00 0.95 0.00 –

cations ¼ 1 Max 1.02 – 0.03 1.00 0.01 –

Median 1.02 0.00 – 0.01 – 0.97

Min 1.00 0.00 – 0.00 – 0.96

Max 1.02 0.01 – 0.04 – 0.98

nd ¼ not detected. na ¼ not analyzed. – ¼ not calculated. [n] ¼ analyses number for each mineral. (*) ¼ theoretical formula of the mineral.

Cadmium has been mainly detected in sphalerite, ranging between 0.16 and 0.98 wt% (Table 3), and in smithsonite with a maximum concentration of 0.5 % (Table 4). A few analyses have revealed Cd within hydrozincite, strontianite and cerussite at low concentrations. The normative composition of dusts has been determined in order to provide a mineralogical distribution of

metallic elements for the geochemical modeling. In the lack of major-element analyses due to small size of dust samples, normative composition of dusts was derived from the normative composition of waste DIII. Indeed, chemical analysis showed a tight relationship between dusts and DIII Pb and Zn contents. Normative mineral composition of DIII waste dump (Table 5) was determined on the basis

Table 4. Microprobe analysis of Cd bearing phases with both standard and specific programs and Cd detection frequencies. Hydrozincite [1/8]

Pb strontianite [1/10]

Cerussite [1/36]

Smithsonite [13/20]

wt% MgO SiO2 CaO MnO Fe2O3 ZnO SrO CdO PbO Calculated CO2 % Calculated H2O % Total DL (Cd)

nd nd 0.52 0.04 nd 73.13 nd 0.46 0.54 16.10 9.87 100.67 0.08

nd nd 4.24 nd nd nd 56.73 0.13 8.20 29.08 – 98.38 0.08

nd nd 0.18 nd nd 0.57 nd 0.50 82.74 16.94 – 100.93 0.29

Median nd nd 2.38 0.04 nd 73.13 28.37 0.29 4.37 – – –

Min nd nd 0.52 0.04 nd 73.13 nd 0.13 0.54 – – – 0.07

Max nd nd 4.24 0.04 nd 73.13 56.73 0.57 8.20 – – –

[m/n] ¼ [number of analyses when Cd was detected/total analyses number]. Median, minimum and maximum concentrations given for smithsonite are calculated on the basis of 13 analyses where Cd was detected. nd ¼ not detected. – ¼ not calculated. CO2 and H2O are calculated by stoichiometry. DL ¼ detection limit of Cd. eschweizerbart_xxx

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Table 5. Normative mineral composition of DIII treatment dump and of the most and the less metal-rich dust samples.

Table 6. Chemical composition in mmol/L of gastric fluid used for the geochemical modeling.

Mineral [mole %]

Element [mmol/L]

Calcite Quartz Cerussite Willemite Smithsonite Dolomite Iron oxy-hydroxide Baryte Celestite

DIII 78.0 2.7 1.5 12.4 6.7 2.2 0.9 0.3 0.3

Dust 5 91.1 3.20 1.47 4.00 0.24 – – – –

Dust 6

þ

95.8 3.40 0.20 0.57 0.03 – – – –

K Naþ Cl Ca2þ Total C

pH ¼ 0.93

pH ¼ 5.0

10 10 160 0.6 0.02

10 90 102 0.6 0.02

Borel et al. (1997) taking into account only inorganic components. The Cl and Naþ concentrations were adjusted for electrical balance (Table 6). Gastric fluid pH ranges between 0.93 and 5.0 during the day depending on the activity of the stomach (Lindahl et al., 1997). The total volume of gastric fluid secreted per day is between 1 and 2 L (Borel et al., 1997) and for the modeling purpose we will consider 1 L for children and 2 L for adults. Geochemical modeling considers only pure mineral phases. All the minerals identified in the dust, except hemimorphite, exist in the mineral database llnl.dat. As Cd does not exist as a pure mineral phase but was observed included in some zinciferous minerals (mainly smithsonite), its dissolved fraction was deduced from the fraction of Zn dissolved. In order to address the range of exposure in the village, geochemical modeling was performed for dust samples 5 and 6, which are the most and the less enriched in metals, respectively. Firstly, in children case, we have considered dissolution of 200 mg of dust (US EPA, 1997) in 1 L of gastric fluid and we have considered both extreme values of gastric fluid pH for modeling. Table 7 gives saturation indices of gastric fluid with respect to the dust minerals and pH values after dust ingestion. Table 8 gives the total dissolved metals after dust ingestion by children and adults bodies per day. With a very acid initial gastric pH of 0.93, the complete dissolution of all minerals contained in dust is thermodynamically possible as their SI remain negative. The pH

of its mineralogical and total chemical composition (Ghorbel et al., 2008). Normative mineral composition of dusts was determined for the most and the less metal-enriched samples, dust sample 5 and dust sample 6 respectively (Table 5). All Pb content in dusts was attributed to cerussite. Zn content was distributed between a carbonate (smithsonite) and a silicate (willemite) with respect to their relative proportions in DIII waste dump. In the same way, the non-metalliferous fraction of dust was distributed between calcite and quartz. 3.2. Direct ingestion exposure estimation and risk assessment 3.2.1. Evaluation by geochemical modeling of the bioaccessibility in gastric fluids Geochemical modeling was performed in order to determine the fate of ingested dust in gastric fluid. Indeed, metal speciation in solid form in the dust particles may limit the bioaccessible fraction of metals. This fraction is considered to represent the maximum amount of contaminant available for intestinal absorption. Bioaccessible contaminants can subsequently be absorbed, in other words, transported across the intestinal wall and transferred into the blood or the lymph stream. The bioaccessibility factor is the fraction of the total quantity of ingested metal that can be dissolved in gastric fluids. Following the approach of Wood et al. (2006), geochemical modeling consisted on simulating the dissolution of the minerals contained in ingested dust in a simplified gastric fluid until it reaches saturation and minerals stop dissolving. This is a first approach on solubility control without any kinetics consideration. The saturation indices (SI) evaluate the minerals reactivity and correspond to log (IAP/K), where IAP is the ion activity product in the solution and K is the equilibrium constant of mineral dissolution. The mineral dissolves if SI , 0 (subsaturation), is in equilibrium with the fluid if SI ¼ 0, and does not dissolve if SI . 0 (supersaturation). The simplified gastric fluid composition used for geochemical modeling was given by Lindahl et al. (1997) and

Table 7. Saturation indices of gastric fluid with respect to the ingested minerals. Initial pH ¼ 0.93

Initial pH ¼ 5.0

Final pH ¼ 0.94

Final pH ¼ 5.6

Dust 5 Mineral Calcite Quartz Smithsonite Willemite Hydrozincite Cerussite eschweizerbart_xxx

Dust 6

Dust 5

Dust 6

Saturation indices 10.79 0.05 10.96 22.46 60.12 8.87

10.78 0.12 11.82 24.24 64.39 9.75

1.47 0.05 1.63 3.55 13.08 0.00

1.45 0.12 2.48 5.32 17.33 0.32

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Table 8. Dissolved quantities of Pb, Zn and Cd in gastric fluid from dust ingested and bioaccessibility factors for children case. Ingested quantities by children in 200 mg of dust (mg/day)

Pb Zn Cd

Dissolved quantities from 200 mg of dust ingested by children (mg/day)

Bioaccessibility factor for children

Dust 5

Dust 6

Dust 5

Dust 6

Dust 5

Dust 6

2.28 4.95 2.18  105

0.32 0.70 0.28  105

0.63(*) to 2.27(**) 4.95 2.18  105

0.32 0.70 0.28  105

0.27 to 1 1 1

1 1 1

(*) Maximum (**)

dissolved Pb in pH 5.0 gastric fluid. Maximum dissolved Pb in pH 0.93 gastric fluid.

increases to 0.94 due to carbonate buffering effect specially exposure frequency [day/year], ED the exposure duration exerted by calcite. As all minerals contained in 200 mg of [year], BW the body weight [kg], and AT is the averaging dust dissolve in 1 L of gastric fluid, Pb and Zn quantities time of exposure [day]. In the case of inhabitants staying in released correspond to the total quantities ingested by a the village and daily exposed to contamination, the averchild body per day. With an initial gastric pH of 5.0, all aging time of exposure (AT) corresponds to the product of minerals dissolve for the less contaminated dust sample 6 exposure frequency (EF) by exposure duration (ED). Then and all minerals dissolve except cerussite for dust sample 5. DID mathematical expression becomes as follows and In the case of dust sample 5, gastric fluid reaches equili- exposure is maximal: brium with cerussite after dissolution of 3.08  10 6 moles of mineral, so an equivalent molar amount of Pb is released DID ¼ C  IR in solution. Final pH is 5.6. However, during the day, gastric BW fluid pH is variable, so that additional quantities of cerussite may dissolve when the pH decreases. Consequently, the Following Carrizales et al. (2006) a bioaccessibility factor amount of Pb released would be between the values calcu- must be applied to the ingested dose to obtain the daily exposure dose (DED): lated with the two extreme pH conditions for this sample. In adult’s case, dust intake is 100 mg and we consider 2 L of gastric fluid per day leading to four times lower dust DED ¼ DID  bioaccessibility factor content by liter of gastric fluid compared to children. All minerals will dissolve and all their Pb, Zn and Cd contents DED calculations were performed for the most and the less will be released in gastric fluid. Being half the dust daily contaminated dust samples considering a maximum bioacintake of children, an adult daily intake of 100 mg of dust cessibility factor of 1 and body weights of 15 kg and 70 kg leads to half the metal quantities ingested by children. for children and adults, respectively (Table 9). DED values The totality of dust Cd contents is released in solution are compared to the recommendations of the World Health since all zinciferous carbonates can dissolve. Organization (WHO) which are applied to Tunisia. For Cd In this paper, we consider the bioaccessibility factor of and Zn the WHO reference dose (RfD) is the same than the an element to be the proportion of the total ingested quan- last US EPA recommendation (Table 9). However, contity which is released in gastric fluid (Table 8). For adults, cerning Pb, a revision of US EPA standards in 2005 finally all ingested Pb, Zn and Cd bearing-minerals are dissolved lead to consider that Pb is a non-threshold toxicant (any in the gastric fluid, so the metal bioaccessibility factor is concentration of lead would be with adverse effects and it equal to 1. For children, Zn and Cd bioaccessibility factor is not appropriate to develop RfDs) while WHO RfD for Pb is equal to 1, as well. However, Pb bioaccessibility factor is 3.5  103 mg/kg/day (WHO, 2006). ranges between 0.27 and 1. Finally, the risk value for human health is given by the quotient of DED and RfD. When the risk value is equal to 3.2.2. Exposure estimation and risk assessment or exceeds 1, the risk is ascertained. On the basis of investigations carried out in the northRisk values for children (Table 9) are greater than 1 for American context (Binder et al., 1986; Calabrese et al., the three metals and for the most contaminated dust, even if 1989; Davis et al., 1990; Stanek & Calabrese, 1995), US considering a bioaccessibility factor of 0.27 for Pb. They EPA (1997) has proposed calculation of daily intake dose are also above 1 for Pb in the less contaminated dust. (DID) of a contaminant by direct ingestion route with the Indeed, threshold Pb, Zn and Cd concentrations in dust to following equation, expressed in [mg/kg/day]: create a risk value of 1 are 0.026 %, 2.26 % and 75 mg/kg, respectively. Risk values for adults exceed 1 only for Pb IR  EF  ED and for the most contaminated dust (Table 9) but will DID ¼ C  BW  AT concern as well any dust with Pb concentration higher where C is the concentration in the point of exposure [mg/ than 0.25 %. Remark that among the seven dust samples kg or mg/m3], IR the ingestion rate [kg/day], EF the collected in the village, five are concerned (Table 1). eschweizerbart_xxx

648

M. Ghorbel et al.

Table 9. Direct ingestion DED values and risk values calculated for Pb, Cd and Zn. DED (mg/kg/day) Children (15 kg) Dust 5 Pb Zn Cd

Adults (70 kg)

Dust 6 3

Risk value

3

Dust 5 3

153  10 21  10 16  10 36  103 332  103 47  103 1.45  103 0.18  103 0.15  103

Children

Dust 6> 3

2.3  10 5  103 0.02  103

RfD 3

3.5  10 (WHO, 2006) 0.3 (US EPA, 2005b) 1.0  103 (US EPA, 2005b; WHO, 2006)

However, dust ingestion is only one contamination pathway and DED values for dermal contact, inhalation and food ingestion have to be added to obtain the global DED which might get close to the RfD or even exceed them.

Adults

Dust 5

Dust 6

Dust 5

Dust 6

43.7 1.10 1.45

6.0 0.15 0.18

4.6 0.12 0.15

0.65 0.01 0.02

Acknowledgments: We are grateful for the support provided by the IRD PhD grant and the CMCU program (N 09G 1003). We are indebted to Christiane Cavare´ for the quality of her graphics which enhance the manuscript.

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4. Conclusion

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