Extractability and leachability of heavy metals in Technosols prepared from mixtures of unconsolidated wastes

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Waste Management 28 (2008) 2653–2666 www.elsevier.com/locate/wasman

Extractability and leachability of heavy metals in Technosols prepared from mixtures of unconsolidated wastes M. Camps Arbestain a,*, Z. Madinabeitia b, M. Anza Hortala` a, F. Macı´as-Garcı´a b, S. Virgel a, F. Macı´as b b

a NEIKER, Agroecosistemas y Recursos Naturales, Berreaga 1, 48160 Derio, Bizkaia, Spain Departamento de Edafologı´a y Quı´mica Agrı´cola, Facultad de Biologı´a, Universidad de Santiago de Compostela, 15782 Santiago de Compostela, Spain

Accepted 14 January 2008 Available online 7 March 2008

Abstract Mixtures of wastes were prepared to improve on the characteristics of the individual ingredients as Technosols, with special attention given to heavy metal extractability. An anaerobic digested sewage sludge and a CaO-treated aerobic sludge were used. A mixture of the two sludges (50:50 DW basis) was also prepared to provide a third type of sludge. The residues were mixed with other types of waste, such as fly ash, Linz-Donowitz slag, foundry sand, shot blasting machine scrap, fettling and barley straw. Extractability of Cu, Cr, Ni, and Zn by 0.01 M CaCl2 extraction (MeCaCl2 ) was carried out, and leachability of these elements was estimated by acidification of an aqueous suspension of the mixtures with 0.5 N acetic acid (Meacetic). The total concentrations of the metals were also determined (MeT). The MeCaCl2 /MeT ratios for Cu and Ni (means: 4.0% and 3.1%) were higher than those for Cr and Zn (means: 0.07% each). The mean Meacetic/MeT ratios followed the order Ni, Zn, Cu, and Cr (19.5%, 4.1%, 3.7%, and 0.09%, respectively). The results highlight the existence of complex interactions among organic matter solubility, pH and heavy metal extractability. Ó 2008 Elsevier Ltd. All rights reserved.

1. Introduction Technosols are a new Reference Soil Group from the World Reference Base for Soil Resources (IUSS Working Group WRB, 2006) that ‘‘combine soils whose properties and pedogenesis are dominated by their technical origin” and include, among others, soils derived from wastes originated from human activities. The preparation of Technosols from mixtures of unconsolidated wastes, e.g., sludges, fly ash, may be an important and feasible method of re-using waste products and restoring degraded areas (Punshon et al., 2002), while at the same time recycling essential nutrients and stabilising the organic matter (OM) present in such materials. Environmental problems resulting from the use of these mixtures can be avoided if the characteristics of the materials employed are well *

Corresponding author. Tel.: +34 94 40 34 320; fax: +34 94 40 34 310. E-mail addresses: [email protected] (M. Camps Arbestain), [email protected] (F. Macı´as). 0956-053X/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.wasman.2008.01.008

known and adequate for such purposes. Moreover, the characteristics of the final products obtained should be suited to the pedoclimatic conditions and to the types of soil use in the area to be restored. Wastes can thus be effectively managed through the preparation of more or less complex mixtures, in which the proportions of each ingredient should be adjusted to provide an adequate environment for the formation of a new soil. The new artificial soils (Technosols) should represent (i) an environmentally sound mixture (e.g., low pollutant availability, low ecotoxicity), and display (ii) adequate mineralogical and biogeochemical conditions (e.g., reactive surfaces, acid–base and redox characteristics), (iii) a balanced content of essential nutrients, (iv) adequate physical characteristics (e.g., porosity, particle size distribution, water retention capacity, aggregate stability), (v) adequate biological environment in which biodiversity and activity of non-pathogenic microorganisms is promoted, and finally (vi) contain a large fraction of the organic C in a stabilized form. In other words, the newly formed soil produced from the mixture

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of wastes should fulfil the main soil functions, as defined by the EC-COM 231/2006 (EU, 2006). There are numerous studies in which mixtures of organic and inorganic by-products have been prepared with the purpose of improving on the characteristics of the individual ingredients, to produce amendments for agricultural soils. Sewage sludges – which are generally used as organic fertilizers through which OM and nutrients are recycled – have frequently been blended with alkaline combustion fly ashes to reduce the availability of heavy metals and to eliminate pathogens (Wong and Su, 1997a, b; Reynolds et al., 1999; Schumann and Sumner, 1999; Su and Wong, 2002). Others studies have described the use of mixtures of manures and Al and Fe-rich by-products (such as alum and Fe-rich by-products of TiO2 production) to reduce the availability of P in manures (Peters and Basta, 1996; Dao, 1999; Codling et al., 2000; Dao et al., 2001). Moreover, amendments derived from a wide variety of wastes (e.g., fly ash, red-mud gypsum, sugar foam, dolomite residues, etc.) have been used for purposes other than crop production, such as a soil remediation technology, in which the wastes are added as chemical stabilising agents to reduce heavy metal mobility (Kumpiene et al., 2007). Nonetheless, the re-use of industrial and municipal by-products presents on-going environmental challenges, especially as regards the preparation of Technosols, and many other by-products need to be tested to ensure that the main soil functions (EU, 2006) are fulfilled. As indicated above, one of the aspects that needs to be considered in the assessment of soil functions is pollutant bioavailability, which is defined as ‘‘the degree to which chemicals present in the soil may be absorbed or metabolised by human or ecological receptors or are available for interaction with biological systems” (IOS, 2006), and which can be assessed in two complementary ways: (i) chemical methods (e.g., extraction methods), and (ii) biological methods (e.g., growth inhibition) (IOS, 2006). Here, we studied the efficiency of different types of waste mixtures to immobilize Cu, Cr, Ni, and Zn, by using two extractants: 0.01 M CaCl2 and 0.5 N acetic acid. The former provides an estimate of exchangeable heavy metals, and has been reported to correlate with biosensors such as BIOMET (Tibazarwa et al., 2001; Geebelen et al., 2003) and plant uptake (Basta et al., 2005; IOS, 2006), whereas the latter has been reported to correlate with biological tests in which acidification takes place (e.g., the physiological based extraction test; Geebelen et al., 2003), and it is generally being used in heavy metal leachability tests (e.g., Spanish RO1989/26488 for Toxic and Dangerous Wastes). Nonetheless, the efficiency of a chemical extractant in predicting a biological response can vary greatly depending upon (i) the characteristics of the system (soil) in question, (ii) the type of pollutant source, and (iii) the organism under study (Geebelen et al., 2003). Therefore, the results should always be interpreted with caution. The final objective of this experiment was thus to evaluate the feasibility of recycling combustion fly ash (FA), different metallurgi-

cal by-products – such as Linz-Donowitz slag (LD), green foundry sand (FS), shot blasting machine scrap (SB), and fettling (FE) – and also barley straw (BS), by mixing the products with different types of sewage sludge, and determining the changes in their heavy metal extractability and leachability compared to the original ingredients. The balance of essential nutrient elements and the degree of stability of organic C forms of the mixtures were also evaluated, although they are not discussed here. 2. Materials and methods 2.1. Materials Two municipal sewage sludges were used in the study: a dewatered anaerobic digested sludge (AN) obtained from the wastewater treatment plant in Ourense (Galicia, NW Spain), and a previously CaO-treated aerobic sludge (AE), obtained from the water treatment plant in Santiago de Compostela (Galicia, NW Spain). A mixture of the two sludges (50:50, dry weight basis) was also prepared to provide a third type of sewage sludge (AN+AE). The fly ash (FA) was obtained from a paper production plant (Iurreta Corporation SA; Basque Country, N Spain) where it is produced during the cogeneration of energy by bark combustion. The green FS, SB, and FE produced from steel foundries were provided by INASMET (Basque Country, N Spain). The Linz-Donowitz slag was obtained from a steel production plant (ACERALIA, ARCELOR group) in Avile´s (Asturias, N Spain). Barley straw (BS) was also used as another ingredient for the mixtures. The sandiest wastes were the SB scraps (98% sand), the LD slag (81% sand), and the green FS (71% sand). The former and the latter residues mainly comprised quartz particles of sand size. The green FS contained a large clay fraction (20%) – mostly smectite – which is generally added to the sand as a binder to form the moulds for metal castings. The sand contained in the green FS was uniformly sized, high-quality silica sand, although it also contained residues of the metals being cast. The LD slag, in contrast, contained no quartz but rather FeO, Ca(OH)2, CaCO3, and Ca2SiO4. The LD slag thus contained a large fraction of liming material, which is always added during the production of steel to neutralise acidity. The FE residue, on the other hand, contained 53% sand, 43% silt, and 4% clay, and was mostly made up of Al and Fe oxides originating from the removal of burrs from veins and from other surface irregularities in the metal pieces. Finally, the FA contained 46% sand, 49% silt, and 5% clay, and included quartz, calcite, halloysite, and dolomite. The combustion FA also contained glassy material, which is consistent with previously published results (Adriano et al., 1980; Mattigod et al., 1990), and charcoal. The total concentrations of heavy metals in the sludges used in the study were below the limits established in EU Directive 86/278/CEE and in subsequent modifications of this Directive for sludges to be applied to agricultural soils,

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Table 1 pH, total organic C, and total heavy metal concentrations (in mg kg 1) of the sludges and conditioners used in the preparation of the mixtures Type of sludge

pH TOC (g kg 1) CdT (mg kg 1) CuT (mg kg 1) CrT (mg kg 1) NiT (mg kg 1) ZnT (mg kg 1) PbT (mg kg 1) HgT (mg kg 1)

Type of conditioner

AN + AE

AN

AE

SB

FE

LD

FS

FA

BS

10.5 156.0 3 273 61 43 330 115 0.50

6.8 234.2 3 522 78 59 627 182 1.31

11.4 119.3 2 108 61 30 136 49 0.30

8.2
9.6
12.1 42.3 3 14 468 20 33 47 0.06

9.6
8.6 188.0 5 111 56 27 873 454 0.39

– 375.0
AN = Anaerobic sludge, AE = Aerobic sludge, AN+AE = Anaerobic and aerobic mixture sludge, FA = Fly ashes, LD = Linz-Donowitz slag, FS = Green foundry sand, SB = Shot blasting machine scrap, FE = Fettling, BS = Barley straw. a Below detection limit.

as shown in Table 1. The concentrations of Ni and Cr in the SB and FE wastes (1513 and 3880 mg kg 1 of Ni and 5567 and 67500 mg kg 1 of Cr, for SB and FE, respectively) were well above the limits indicated in the Directive and subsequent modifications. The heavy metal contents of the remaining wastes were all below those indicated in EU Directive 86/278/CEE. Notwithstanding, the concentration of Cr in the LD slag was high (468 mg kg 1), and the concentrations of Zn and Cr in the green FS were also noteworthy (122 and 233 mg kg 1, respectively). Chromium was therefore present in substantial amounts in all wastes originating from the metallurgical industry. The contents of the most volatile heavy elements, such as Cd, Pb, Zn, and Hg (5, 454, 873, and 0.4 mg kg 1, respectively), were high in FA as these elements tend to concentrate during the process by which FA is generated. After diluting the inorganic ingredients by mixing them with the sludges (85:15 and 65:35 DW basis), as described in the methodology, all mixtures in which FE was added still surpassed the limits of Ni and Cr for the waste application to agricultural soils, according to EU Directive 86/278/CEE and subsequent modifications. The 65:35 mixtures of SB also surpassed the limits of Ni and Cr for the application of wastes to agricultural soils. The heavy metal contents of the remaining mixtures were all below the limits outlined in the above-mentioned Directive. 2.2. Methods The sewage sludges were air-dried and passed through a 4 mm sieve before use. The sludges were mixed with the other wastes tested, referred to here as ‘‘conditioners”, at two proportions: 85:15 and 65:35 (DW basis), except for those mixtures containing BS, in which the two ratios of sludge:conditioner mixtures studied were 99:1 and 97:3 (DW basis)1. Three replicates of the different mixtures were 1

To make the text easier to read we will refer to two ratios, 85:15 and the 65:35, including the 99:1 ratio of one BS type of mixture in the former, and including the 97:3 of the other BS type of mixture in the latter.

incubated for 4 weeks. The mixtures were moistened daily with distilled deionised water to maintain the water contents at field capacity. At the end of the incubation period, the mixtures were dried at 40 °C until constant weight and passed through a 2 mm sieve prior to analysis of duplicate subsamples. The pH of all samples was measured in H2O (ratio of soil:solution, 1:2.5). The contents of the major heavy metals in the mixtures at the end of the experiment were determined by X-ray fluorescence spectroscopy (Cheburkin and Shotyk, 1996, 1999). The extractability of heavy metals with 0.01 M CaCl2 was determined by a single extraction of air-dried soil samples at a proportion of 1:10 (waste mixture:solution ratio; w/v) (Houba et al., 2000), following a 2 h end-over-end shaking (66 rpm). The resulting supernatants were filtered (0.45 lm) and analysed by atomic absorption spectrophotometry (Perkin– Elmer 2380, Norkwalk, CT, USA) for the determination of Cu, Cr, Ni, and Zn concentrations. The same extracts were analysed by a Flowsys – Third generation continuous flow analyzer (Flowsys, Anagni, Italy) to determine dissolved organic C (DOC) concentrations. To determine heavy metal leachability, we followed the methodology for the characterization of toxic and dangerous wastes, as described in the Spanish RO 1989/ 26488 for Toxic and Dangerous Wastes. For this, deionized distilled water was added to 2 g of subsamples of the residue mixtures and 0.5 N acetic acid was added, to a final volume of 40 mL, to adjust the pH to 4.5 ± 0.2; the process was carried out with end-over-end shaking (66 rpm) during a period of 24 h and thereafter the suspensions were filtered through 0.45 lm filters. The amount of 0.5 N acetic acid added in the method is limited to 4 mL g 1 soil, and because of this we could not adjust the pH to 4.5 in those samples in which lime was present (mixtures with AE sludge and/or LD conditioners), as they had a high acid buffering capacity. In these cases, the pH ranged between 6 and 7. Total concentrations of Cu, Cr, Ni, and Zn in the acidified extracts were also determined by atomic absorption spectrophotometry, as indicated above.

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2.3. Statistical analysis Analysis of variance was computed with SPSS version 11.0 for PC-Windows (SPSS Inc., Chicago, IL, USA). The Bonferroni post-hoc test was applied to make multiple comparisons and establish statistical differences among treatments at P < 0.05.

the latter: 119 and 234 g kg 1, respectively; Table 1), was mainly attributed to the enhanced solubility of OM due to the high alkalinity of this sludge. As expected, a high fraction of the organic C in the BS was present in a dissolved form, as the fresh organic residue contains a large amount of labile organic C. In the FA conditioner, organic C was mainly present as charred material, and therefore only a small fraction of organic C was soluble in CaCl2.

3. Results and discussion 3.1. Description of the ingredients 3.1.1. pH of the ingredients The LD slag had the highest pH (12.1) of all of the ingredients (Table 1), which was attributed to a high content of alkaline material, especially Ca(OH)2. The pH of the AE sludge was also high (pH 11.4), which was related to the CaO added to the waste during its processing in the wastewater treatment plant. The pH of the mixture of the two sludges was 10.5, which indicates that, after dilution of the AE sludge by one half, the alkaline materials still determined the pH of the mixture, although, as will be shown later, the pH of the AN + AE mixtures decreased to values similar to those of the AN mixtures soon after incubation. The total Ca content of all three limed wastes was high (292, 251, and 204 mg kg 1, for LD, AE, and AN + AE, respectively), as expected. The remaining ingredients also had relatively high pH (9.6, 9.6, and 8.6, for FS, FE, and FA, respectively), except the AN sludge (pH 6.8). 3.1.2. CaCl2-extractable DOC of the ingredients The concentration of DOCCaCl2 of the ingredients expressed as a percentage of the total organic C (DOCCaCl2/TOC  100) were above 5% for BS and AE sludge, 2.6% for the AN + AE sludge, 0.2% for the AN sludge, and 0.1% for the FA conditioner (Table 2). The amount of DOCCaCl2 in the other ingredients was very low or undetectable. The higher DOCCaCl2/TOC ratio in the AE sludge than in the AN sludge (despite the higher TOC content of

3.1.3. CaCl2-extractable heavy metals in the ingredients 3.1.3.1. Copper. Copper extractable with CaCl2 was almost negligible in the conditioners used in the experiments, with concentrations 60.2 mg kg 1, except for BS (1.6 mg kg 1), whereas the concentration of CuCaCl2 in the sludges was considerable, with values ranging from 10 to 45 mg kg 1 (Table 2). These results contrast with the CuT concentrations in the ingredients, which were above 100 mg kg 1 in all, except LD, FS and the BS conditioners, which contained <31 mg Cu kg 1 (Table 1). The organic wastes displayed high Cu extractability with CaCl2, with values of CuCaCl2/CuT of 80% for the BS conditioner, and of 20% for the AE sludge, whereas the ratio was <0.7% in the inorganic wastes (Table 2). The high CaCl2 extractability of Cu in the organic wastes was attributed to the well-known ability of this metal to form stable complexes with organic compounds (Sauve´ and Parker, 2005), including those of high solubility (McLean and Bledsoe, 1992), which were those released into the CaCl2 solution (Table 2). Moreover, the higher CaCl2 extractability of Cu in the CaO amended sludges (AE and AN + AE sludges) (22 and 45 mg kg 1, respectively) than in the AN sludge (10 mg kg 1) was attributed (i) to the high concentration of organic ligands in solution due to the high pH induced by the liming material present in these wastes, and (ii) the possible blockage of Cu sorption sites by Ca, abundant in these wastes, thereby increasing the mobility of Cu, as suggested by Cavallaro and McBride (1978) and Harter (1979). These phenomena thus counteract the well-known negative effect of high pH on the solubility of metal cations. Moreover, the higher

Table 2 Dissolved organic C (DOC) and heavy metal concentrations (in mg kg 1) of the CaCl2 extracts, as well as the ratios with their total contents (in %) of the different mixtures at the end of 4-week incubation Type of sludge DOCCaCl2 (g kg 1) DOCCaCl2/TOC (%) CuCaCl2 (mg kg 1) CuCaCl2/CuT (%) CrCaCl2 (mg kg 1) CrCaCl2/CrT (%) NiCaCl2 (mg kg 1) NiCaCl2/NiT (%) ZnCaCl2 (mg kg 1) ZnCaCl2/ZnT (%)

Type of conditioner

AN + AE

AN

AE

SB

FE

LD

FS

FA

BS

4.0 2.6 45.4 16.6 0.3 0.4 1.9 4.4 0.3 0.1

0.4 0.2 9.9 1.9 0.2 0.2 0.7 1.2 2.4 0.4

6.0 5.0 22.0 20.4 0.2 0.3 3.1 10.2 0.2 0.2





0.3 0.1 0.2 0.1 0.3 0.4 0.4 1.3 0.7 <0.1

21.7 5.8 1.6 80.0 0.5 1.9 0.5 – 2.5 41.7

0.3 <0.1 0.1 <0.1

AN = Anaerobic sludge, AE = Aerobic sludge, AN + AE = Anaerobic and aerobic mixture sludge, FA = Fly ash, LD = Linz-Donowitz slag, FS = Green foundry sand, SB = Shot blasting machine scrap, FE = Fettling, BS = Barley straw. a Below detection limit.

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CaCl2-extractability of Cu in the AN+AE sludge (45 mg kg 1) than in the AE sludge (22 mg kg 1) may be explained by the greater susceptibility of the OM present in the AN sludge to dissolution – after being in contact with the liming material present in the AE sludge – compared with the OM present in the AE sludge. This may have led to a greater mobilisation of organo-Cu complexes in the mixed sludge. 3.1.3.2. Chromium. The concentration of CrCaCl2 was low in both sludges and conditioners (60.7 mg kg 1: Table 2), and the CrCaCl2/CrT ratios were 60.4%, except for BS, for which the CrCaCl2/CrT ratio was 1.9% (Table 2). This again contrasts with the concentrations of CrT in the ingredients, which in the case of SB and FE were as high as 5567 and 67,500 mg kg 1, respectively, whereas that of BS was 24 mg kg 1 (Table 1). Therefore, despite the fact that Cr was present in substantial amounts in the wastes originating from the metallurgical industry, the CaCl2-extractability of this metal was very low.

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below 0.4%, except in BS, for which the ratio was 41.7% (Table 2). 3.2. Description of the mixtures 3.2.1. pH of the mixtures during and after incubation There were no significant differences (P < 0.05) in the mean pH values of the two mixture ratios studied (85:15 and 65:35) at the different sampling times (data not shown), and therefore only the pH values of the 65:35 mixtures are represented and discussed here (Fig. 1). The results indicate that there were significant differences (at P < 0.05) between the mean pH values of the mixtures when grouped according to the three types of sludges tested. At the three incubation times tested, mean pH values of the AE mixtures (week 1: 12.0; week 2: 11.0; week 4: 9.7) were significantly

3.1.3.3. Nickel. The concentration of NiCaCl2 ranged between 0.3 and 0.8 mg kg 1 in the conditioners, and between 0.7 and 3.1 mg kg 1 in the sludges (Table 2). The CaCl2 extractability of Ni was therefore slightly higher in the sludges than in the conditioners, which again contrasts with the high concentrations of NiT in some of the latter ingredients, such as SB and FE, in which the concentrations (1513 and 3880 mg kg 1, respectively) were three orders of magnitude greater than in the other residues (<86 mg kg 1) (Table 1). This is further reflected by the NiCaCl2/NiT values, which ranged between 1.2% and 10.2% in the sludges, whereas in the SB and FE conditioners they were <0.1% (Table 2). As observed for Cu, the concentration of NiT in the AN sludge was higher than in the AE sludge (59 compared with 30 mg kg 1), but the concentration of NiCaCl2 was lower in the former (0.7 compared with 3.1 mg kg 1); it is therefore possible that the same factors – high solubility of OM at high pH values and Ca blocking retention sites attributed to the lime added to this sludge – affected the observed pattern of Ni to some extent. In fact, the formation of complexes between Ni and organic ligands has been reported to enhance Ni mobility in soils (Amrhein et al., 1992). Finally, the NiCaCl2/NiT ratio in the LD conditioner, characterized by having been limed in the steel production process, was higher than in the other conditioners (2.5% compared with 61.3%) (Table 2). 3.1.3.4. Zinc. The concentration of ZnCaCl2 in the ingredients ranged from below detection limits to 2.5 mg kg 1 (Table 2). Of all the conditioners tested, BS contained the least amount of ZnT (6 mg kg 1), but the highest amount of ZnCaCl2 (2.5 mg kg 1). In contrast, the AN sludge contained the highest amount of ZnT (627 mg kg 1) of the sludges tested, and also the highest amount of ZnCaCl2 (2.4 mg kg 1). The ZnCaCl2/ZnT ratios were always

Fig. 1. Mean pH values and standard deviations of the 65:35 mixtures grouped by type of sludge and type of conditioner at the three sampling times. AN = Anaerobic sludge, AE = Aerobic sludge, AN + AE = Anaerobic and aerobic mixture sludge, FA = Fly ash, LD = Linz-Donowitz slag, FS = Green foundry sand, SB = Shot blasting machine scrap, FE = Fettling, BS = Barley straw. For BS the mixture ratio was 97:3.

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higher than those of the other two types of sludges, and those of the AN + AE sludge (week 1: 8.1; week 2: 8.0; week 4: 8.1) were significantly higher than those of the AN sludge (week 1: 7.1; week 2: 7.3; week 4: 7.0). The higher pH values of the AE and AN + AE mixtures compared with those of the AN mixtures were attributed to higher pH of the AE sludge than of the AN sludge, as indicated above (Table 1). The data obtained also indicated a decrease in pH of more than two units in the AE mixtures over the incubation time, which was mainly attributed to the formation of H2CO3 from microbial respiration, and its further deprotonation at the high pH of the system. In contrast, the mean pH values of the mixtures with the AN and AN + AE sludges remained relatively constant over time. The type of conditioner had a significant effect (at P < 0.05) on the pH of the mixtures at weeks 1 and 2 (Fig. 1), and the mean pH values of the LD mixtures (week 1: 9.6; week 2: 9.1) were always significantly higher (at P < 0.05) than those of the rest of mixtures (week 1: <9.1; week 2: <8.8). Differences tended to attenuate with time, and the effect of the conditioners on the pH of the mixtures was no longer significant (P < 0.05) at the end of the experiment, although mean pH values of the LD mixtures (means: AE 11.0, AN + AE 8.5, AN 7.7) remained higher than those of other mixtures (means: AE 9.5, AN + AE 8.0, AN 6.9), which is consistent with the presence of Ca(OH)2 as one of its main components. 3.2.2. CaCl2-extractable DOC of the mixtures after incubation The ratios of DOCCaCl2/TOC (%) in the mixtures after incubation were significantly affected (P < 0.05) by (i) the

type of sludge, and by (ii) the type of conditioner (Fig. 2a–b). Comparison of the different types of sludges revealed that the mean DOCCaCl2/TOC values for the AN + AE and AE mixtures (2.2% and 2.0%, respectively) were significantly higher (P < 0.05) than the value for the AN mixtures (0.7%), in accordance with the characteristics of the original ingredients. Again, this was mainly attributed to the enhanced solubility of OM due to the high alkalinity of the original AE and AN + AE sludges, although other factors may be involved. In fact, one week after incubation, the pH values of the AN + AE mixtures decreased to a mean value of pH 8, and remained fairly constant until the end of the experiment (Fig. 1). Thus the results may also be explained by greater susceptibility of the OM present in the AN sludge to dissolution – after being in contact with the liming material present in the AE sludge – in comparison with the OM present in the AE sludge. High pH has been reported to have a greater effect on the dissolution of humic acids than of fulvic acids (Impellitteri et al., 2002). Comparison of the type of conditioners (Fig. 2a–b) revealed that the FS mixtures had the highest mean DOCCaCl2/TOC values (2.6%) and that the FA had the lowest (0.8%), and that both were significantly different (<0.05) from the remaining treatments (means ranging from 1.2% to 1.9%). The high DOCCaCl2/TOC values of the FS mixtures were attributed to the practical inexistence of inorganic reactive surfaces able to stabilize organic C compounds. The FS residue mainly comprises silica sand (71%) and the smectite present in this material may not be very reactive after being exposed to high temperatures during the blasting process, therefore stabilisation of the more abundant labile organic compounds in the mixture

Fig. 2. Mean DOCCaCl2/TOC indexes and standard deviations of the 85:15 mixtures (a) and of the 65:35 mixtures (b) grouped by type of sludge and type of conditioner. Mean concentrations of DOCCaCl2 (mg kg 1) and standard deviations of the 85:15 mixtures (c) and of the 65:35 mixtures (d) grouped by type of sludge and type of conditioner. AN = Anaerobic sludge, AE = Aerobic sludge, AN+AE = Anaerobic and aerobic mixture sludge, FA = Fly ash, LD = Linz-Donowitz slag, FS = Green foundry sand, SB = Shot blasting machine scrap, FE = Fettling, BS = Barley straw. For BS the mixture ratios were 99:1 and 97:3.

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may be impeded. The low values of the DOCCaCl2/TOC ratios in the FA mixtures, on the other hand, were mainly attributed to the fact that part of organic C present in the FA residue was in the form of charred material, as already indicated above. Sorption of organic compounds to charcoal surfaces, as suggested by Liang et al. (2006), may also have contributed to the low DOCCaCl2/TOC ratio observed; however, more data is needed to confirm this hypothesis. Finally, the liming material present in the LD slag had no significant effect (P < 0.05) on the DOCCaCl2/TOC ratios of the mixtures containing this conditioner (mean: 1.7%), in comparison with other conditioners without lime, such as SB or FE (means: 1.9% and 1.5%, respectively). However, there were significant differences (P < 0.05) when the concentrations of DOCCaCl2 were considered (means: 1.7 g kg 1 compared with 1.2 and 1.0 g kg 1, respectively) (Fig. 2c–d) instead of the ratios of DOCCaCl2/TOC, although the differences were only evident in the AN + AE mixtures. The concentrations of DOCCaCl2 in the BS mixtures were the highest of all the mixtures studied (mean: 2.0 g kg 1), mainly because the high TOC content of the mixtures containing this organic residue (data not shown), and thus these differences were not apparent when the data was reported as DOCCaCl2/TOC. Finally, the TOC concentrations in the sludges were 119, 156, and 234 g kg 1 for the AE, AN + AE, and AN, respectively (Table 1), and the mean concentrations of TOC of the mixtures at the end of the experiment were 87, 103, and 161 g kg 1, respectively (data not shown); the concentrations of TOC in the AN sludge and mixtures were therefore always higher than in the AE sludge and mixtures, which contrasts with the corresponding concentrations of DOCCaCl2 (Fig. 2c–d), indicating the effect of pH on their solubility, as reflected by the DOCCaCl2/TOC ratios (Fig. 2a–b). 3.2.3. CaCl2-extractable heavy metals of the mixtures after incubation 3.2.3.1. Copper. The extractability of Cu with CaCl2 was significantly affected (P < 0.05) by the three variables studied: (i) the type of sludge, (ii) the type of conditioner, and (iii) the type of mixture ratio (Fig. 3a–b). Comparison of the different types of sludge revealed, in accordance with the results obtained with the ingredients, that (i) mixtures with AN sludge contained significantly lower (at P < 0.05) amounts of CuCaCl2 than the AE and AN+AE mixtures (means: 4.7, 9.8 and 9.8 mg kg 1, respectively) (Fig. 3a–b), and that (i) the mean CuCaCl2/CuT value of the AN mixtures (0.9%) was also significantly lower (at P < 0.05) than the corresponding mean ratios of the AE and AN + AE mixtures (8.0% and 3.0%, respectively) (Fig. 4a–b). The concentrations of CuCaCl2 in the mixtures were parallel to those of DOC (Fig. 2a–b), and there was a significant positive correlation (R = 0.77, P < 0.05) between the two variables. However, other factors may also have affected the systems, thereby explaining the sig-

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nificantly higher CuCaCl2/CuT (P < 0.05) in the AE mixtures than in the AN + AE mixtures (Fig. 4a–b). The results also showed lower values of CuCaCl2 in the mixtures (means: AN + AE: 9.8 mg kg 1; AN: 4.7 mg kg 1; AE: 9.8 mg kg 1) (Fig. 3a–b) than those corresponding to the original sludges (AN + AE: 45.4 mg kg 1; AN: 9.9 mg kg 1; AE: 22.0 mg kg 1) (Table 2), and this decrease was greater than that expected from the ‘‘dilution effect” that the addition of inorganic conditioners to the sludges (85:15 and 65:35 dry weight basis) had on the mixtures. Other factors may have been involved, such as (i) a negative effect of the decrease in pH over time on OM solubility, and also (ii) sorption onto compounds present in the conditioners, such as Fe and Al oxy-hydroxides, which are able to fix not only organic compounds, but also Cu on their surfaces. The latter effect, however, varied among conditioners, as discussed below. As observed with the sludges, there was no relationship between CuT contents of the different conditioners used and CuCaCl2. Thus, although the FE conditioner contained the highest concentration of CuT (475 mg kg 1), mixtures prepared with this waste displayed the lowest mean concentrations of CuCaCl2 (6.5 mg kg 1 in the 85:15 mixture ratio and 4.7 mg kg 1 in the 65:35 mixture ratio). On the contrary, mixtures prepared with BS, which contained the lowest amount of CuT (2 mg kg 1) (Table 1), displayed the highest mean concentration of CuCaCl2 (10.7 mg kg 1 for the 85:15 mixture ratio), followed by the LD mixtures (10.6 mg kg 1 for the 85:15 mixture ratio). These different trends were again mainly attributed to the opposing effects of (i) concentrations of DOC, and (ii) amount of reactive surfaces in the mixtures on Cu solubility. The latter may also explain the significant decrease (P < 0.05) in CuCaCl2 when the ratio of inorganic conditioners increased from 85:15 to 65:35; the mean concentration of CuCaCl2 in the 65:35 mixtures (mean: 6.8 mg kg 1) was significantly lower (at P < 0.05) than in the 85:15 mixtures (means: 8.4 mg kg 1), with mean CuCaCl2/CuT values of 3.7% and 4.3%, respectively. 3.2.3.2. Chromium. The SB and FE conditioners had a significant effect (P < 0.05) on extractability of Cr with CaCl2 following incubation of the mixtures in which they were present (Fig. 3c–d), and the concentration of CrCaCl2 (mean values up to 0.7 mg kg 1) was higher than in the ingredients before mixing (<0.3 mg kg 1). No significant effect (P < 0.05) was observed on CrCaCl2 concentrations, in either the comparison between the different sludges used or between the two ratios of mixtures studied. However, the AE mixtures with FA and with BS conditioners displayed significantly higher (P < 0.05) CrCaCl2/CrT values than the mixtures with the other conditioners (>0.19% compared with 60.13%; Fig. 4c–d), although no clear explanation was found for this pattern. No relationship between the concentrations of CrCaCl2 and those of DOCCaCl2 was observed. Nonetheless, it should be noted that the differences in the concentrations of CrCaCl2 corresponding to the

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Fig. 3. Mean concentrations of MeCaCl2 (mg kg 1) and standard deviations of the 85:15 mixtures (a, c, e, g) and of the 65:35 mixtures (b, d, f, h) grouped by type of sludge and type of conditioner. (n.d. not determined). AN = Anaerobic sludge, AE = Aerobic sludge, AN + AE = Anaerobic and aerobic mixture sludge, FA = Fly ash, LD = Linz-Donowitz slag, FS = Green foundry sand, SB = Shot blasting machine scrap, FE = Fettling, BS = Barley straw. For BS the mixture ratios were 99:1 and 97:3.

different treatments (Fig. 3c–d) were much smaller than the differences in CrT concentrations in the different ingredients (Table 1), thereby indicating that only a very small fraction of the CrT present in the SB and FE residues was mobilized. This was reflected in the CrCaCl2/CrT values, with the mean value for the mixtures with FE conditioners being below 0.03% (Fig. 4c–d). In fact, the lowest mean CrCaCl2/CrT values corresponded to the mixtures in which wastes from the metallurgic industry were used (<0.04%; Fig. 4c–d) – all characterized by a high CrT content (Table 1) – whereas the mean ratio was >0.10% in FA and BS (Fig. 4c–d), both of which had a low CrT content (Table 1).

3.2.3.3. Nickel. CaCl2-extractable Ni in the mixtures was significantly affected (P < 0.05) by the type of sludge and type of conditioner, whereas the mixture ratio did not have any significant effect, at P < 0.05 (Fig. 3e–f). Comparison of the type of sludges again revealed that (i) mixtures with AN sludge contained significantly lower (P < 0.05) amounts of NiCaCl2 than the AE and AN + AE mixtures (means: 1.2 mg kg 1 compared with 1.7 and 1.6 mg kg 1, respectively), and that (ii) mean NiCaCl2/NiT values of the AN mixtures (1.4%) were significantly smaller (P < 0.05) than the corresponding mean ratios of the AE and AN + AE mixtures (4.8% and 3.2%, respectively) (Fig. 4e–f). In fact, the concentrations of CaCl2-extractable

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Fig. 4. Mean MeCaCl2/MeT indexes, expressed as percentages, and standard deviations, of the 85:15 mixtures (a, c, e, g) and of the 65:35 mixtures (b, d, f, h) grouped by type of sludge and type of conditioner. (n.d. not determined). AN = Anaerobic sludge, AE = Aerobic sludge, AN + AE = Anaerobic and aerobic mixture sludge, FA = Fly ash, LD = Linz-Donowitz slag, FS = Green foundry sand, SB = Shot blasting machine scrap, FE = Fettling, BS = Barley straw. For BS the mixture ratios were 99:1 and 97:3.

Ni (excluding those of FE) were significantly correlated with DOC (R = 0.53, P < 0.05), although the correlation coefficient was smaller than for Cu (R = 0.77). The addition to the sludges of compounds with highly reactive surfaces did not have any apparent effect on Ni extractability with CaCl2 (means: 1.2, 1.7, and 1.6 mg kg 1, for the AN, AE, and AN + AE mixtures), as indicated by comparison with that of the original sludges (0.7– 3.1 mg kg 1) (Table 2), which reflects the lower affinity of this metal for sorption sites than other metals such as Pb and Cu, and which is consistent with previously reported findings (Harter, 1983). Comparison of the different types of conditioners showed a significantly (P < 0.05) higher mean concentration of NiCaCl2 in the FE mixtures than in

the rest of the mixtures (2.9 mg kg 1 compared with 1.0– 1.5 mg kg 1 in the other conditioners), which is consistent with the high Ni content of this inorganic residue (3880 mg kg 1) (1). This, however, was not reflected by the NiCaCl2/NiT ratios, as the mean value in the mixtures amended with FE was the lowest (1.0%), whereas that of the sludges amended with BS, which had a negligible presence of Ni (Table 1), was the highest (4.5%) (Fig. 4e–f), a pattern already observed with Cu. 3.2.3.4. Zinc. The CaCl2-extractable Zn content was significantly affected by the type of sludge (P < 0.05), which was notably higher in the AN mixtures than in the AE and AN + AE mixtures (means 0.8 mg kg 1 in the AN

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mixtures compared with 0.1 and 0.3 mg kg 1 in the AE and AN + AE mixtures, respectively) (Fig. 3g–h). This is consistent with the higher ZnT contents in the original AN sludge than in the other two sludges (AN sludge: 627 mg kg 1 compared with AE sludge: 136 mg kg 1) (Table 1). The results also reflect the lack of apparent relationship between DOCCaCl2 and ZnCaCl2 (Fig. 2; Fig. 3g– h). The mean ZnCaCl2/ZnT ratios were 0.10%, 0.07%, and 0.06%, for the AN, AE and AN + AE mixtures, which indicated that mixtures with AN sludge contained a greater fraction of extractable Zn compared with the mixtures containing the other sludges, although CaCl2-extractability was lower than in the original AN sludge (ZnCaCl2/ ZnT = 0.4%). This was mainly attributed to the effect of the addition of reactive surfaces to the sludges with the blending conditioners able to fix Zn. The latter effect, however, varied among conditioners, as discussed below. The concentrations of ZnCaCl2 were significantly affected (P < 0.05) by the type of conditioner, with the mean values being above 0.5 mg kg 1 in the SB, FA, and BS mixtures, and below 0.4 mg kg 1 in the FE, LD, and FS mixtures (Fig. 3g–h). The mean ZnCaCl2/ZnT ratios were, however, very similar in the two groups of conditioners indicated (SB, FA, and BS, compared with FE, LD, and FS), and ranged between 0.06% and 0.09% (Fig. 4g–h). It should be noted that the waste with the highest concentration of ZnT of all the wastes used was FA (873 mg kg 1), in which the ZnT content was even higher than that of the AN sludge (627 mg kg 1) (Table 1), but that the lowest mean ZnCaCl2/ZnT ratios (0.06%) corresponded to the FA mixtures. This suggests that the form of Zn present in the FA conditioner was less mobile than that in the AN sludge, and highlights the need to discern which forms of Zn are present in the wastes, as well as that of the other heavy metals studied, to be able to predict their mobility once in the mixture and how they change over time. 3.3. Heavy metal leachability in the mixtures after incubation As indicated in the methodology, subsamples of the residue mixtures were suspended in water (1:20) and acidi-

fied with acetic acid – which is considered a non-sorbing organic acid (Jones and Brassington, 1998) – to achieve a pH of 4.5 ± 0.2. We could not adjust the pH down to 4.5 in those samples in which lime was present (AE sludge, AN + AE sludges, LD conditioner), as there is a limit to the volume of diluted acetic acid to be added in the method (4 mL g 1 soil). In these cases, pH ranged between 6 and 7 (Table 3), and the implications of these differences in pH adjustment for heavy metal leachability are discussed. 3.3.1. Copper Acidification of the suspensions down to pH 4.5 – which occurred in all AN mixtures except that with LD at 65:35 ratio (Table 3) – promoted the dissolution of Cu. This effect was attributed to a decrease in the negative surface charge of solid phases at low pH and to the occurrence of dissolution reactions (McLean and Bledsoe, 1992). The mean concentration of Cuacetic in the AN mixtures (mean = 9.9 mg kg 1) (Fig. 5a–b) was significantly greater (P < 0.05) than that of the CuCaCl2 for the same mixtures (mean = 4.7 mg kg 1) (Fig. 3a–b). Consequently, the mean Cu partitioning ratio also increased, from 0.9% (Fig. 4a–b) to 2.0% (Fig. 6a–b). In contrast, acidification of the AN + AE and AE mixtures from mean pH values of 8.1 and 9.7, respectively, to mean pH values of 6.4 and 6.9 (Table 3), respectively, produced a decrease in the concentration of Cu in the extracts; the mean concentrations of Cuacetic (7.0 and 8.0 mg kg 1, respectively: Fig. 5a–b) were significantly lower (P < 0.05) than the mean concentrations of CuCaCl2 (9.8 mg kg 1, both; Fig. 3a–b). The decrease was attributed to the negative effect that a shift in pH from alkalinity to neutrality has on OM solubility, and thus, on Cu leachability. Consequently, this led to a decrease in the mean Cu partitioning ratio, from 3.0% and 8.0% for the AN + AE and AE mixtures, respectively, (Fig. 4a–b) to 2.1% and 6.7% (Fig. 6a–b), respectively. 3.3.2. Chromium Acidification with acetic acid favoured dissolution of Cr in all the mixtures in comparison with the CaCl2 extraction, but the effect was more pronounced in the mixtures in which the pH decreased from alkalinity to between 6

Table 3 Mean pH values (and standard deviations in parentheses) of the residue suspensions acidified with diluted acetic acid Mean pH values of the acidified suspensions 85:15 (on weight basis)a

SB FE LD FS FA BS

(65:35 on weight basis)b

AN + AE

AN

6.3 6.3 6.6 6.3 6.3 6.3

4.4 4.4 4.8 4.5 4.5 4.5

(0.1) (0.1) (0.1) (0.1) (0.1) (0.1)

AE (0.0) (0.1) (0.1) (0.2) (0.2) (0.2)

6.9 7.1 7.6 6.9 6.9 7.2

(0.0) (0.2) (0.7) (0.1) (0.1) (0.1)

AN + AE

AN

6.4 6.4 6.9 6.3 6.4 6.4

4.4 4.6 6.0 4.4 4.5 4.4

(0.1) (0.1) (0.1) (0.0) (0.1) (0.1)

AE (0.0) (0.1) (0.4) (0.0) (0.1) (0.0)

6.7 7.0 7.0 6.5 6.6 6.8

(0.4) (0.3) (0.2) (0.1) (0.1) (0.2)

AN = Anaerobic sludge, AE = Aerobic sludge, AN + AE = Anaerobic and aerobic mixture sludge, FA = Fly ash, LD = Linz-Donowitz slag, FS = Green foundry sand, SB = Shot blasting machine scrap, FE = Fettling, BS = Barley straw. a For BS the ratio was 99:1. b For BS the ratio was 97:3.

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Fig. 5. Mean concentrations of Meacetic (mg kg 1) and standard deviations, in the acidified 85:15 mixtures (a, c, e, g) and the acidified 65:35 mixtures (b, d, f, h) grouped by type of sludge and type of conditioner. AN = Anaerobic sludge, AE = Aerobic sludge, AN + AE = Anaerobic and aerobic mixture sludge, FA = Fly ash, LD = Linz-Donowitz slag, FS = Green foundry sand, SB = Shot blasting machine scrap, FE = Fettling, BS = Barley straw. For BS the mixture ratios were 99:1 and 97:3.

and 7 (AN + AE and AE mixtures) (Table 3), than in the mixtures in which the pH decreased to 4.5 (AN mixtures). Thus, whereas the mean concentration of CrCaCl2 was 0.2 mg kg 1 for all three types of sludges (Fig. 4c–d), the mean concentrations of Cracetic were 1.8, 4.6 and 5.8 mg kg 1 for the AN, AN + AE, and AE, respectively (Fig. 6c–d). On the other hand, when the Cracetic concentrations were reported as ratios of CrT concentrations (Fig. 6c–d), the patterns observed were similar to those observed for CrCaCl2 (Fig. 4c–d), although on a different scale, in that the maxima corresponded to FA and BS mixtures, with mean values of 7.2% and 3.5%, respectively.

These conditioners were the only ones that did not originate from the metallurgic industry, and thus, the total concentrations of CrT were much lower than in the other conditioners (Table 1). 3.3.3. Nickel This element was the most strongly affected by acidification (Fig. 5e–f), even in the AN + AE and the AE mixtures, in which pH did not decrease beyond 6. The enhancement of Ni solubility was particularly evident in the mixtures containing FE, which was the conditioner with the highest concentration of NiT (3880 mg kg 1). Within the FE mixtures,

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Fig. 6. Mean Meacetic/MeT indexes, expressed as percentages, and standard deviations, for the acidified 85:15 mixtures (a, c, e, g) and the acidified 65:35 mixtures (b, d, f, h) grouped by type of sludge and type of conditioner. (n.d. not determined). AN = Anaerobic sludge, AE = Aerobic sludge, AN + AE = Anaerobic and aerobic mixture sludge, FA = Fly ash, LD = Linz-Donowitz slag, FS = Green foundry sand, SB = Shot blasting machine scrap, FE = Fettling, BS = Barley straw. For BS the mixture ratios were 99:1 and 97:3.

the one containing AN sludge had the highest concentrations of Niacetic, with a mean value of 157 mg kg 1, which was several times higher than of the concentrations in the AN + AE and AE mixtures (57 and 22 mg kg 1, respectively), and which highlights the important effect of low pH values on Ni solubility. These values contrast with those of the rest of the mixtures, in which mean values did not reach 12 mg kg 1. When the concentrations of Niacetic were expressed as a ratio (Niacetic/NiT), no general pattern could be discerned for the different treatments (Fig. 6e–f), although the ratios of Niacetic/NiT observed in the mixtures were high, with a mean value close to 20%.

3.3.4. Zinc Acidification of the suspensions down to pH 4.5 greatly promoted the dissolution of Zn (Fig. 5g–h). The mean concentration of ZnCaCl2 in the AN mixtures was 0.8 mg kg 1 (Fig. 3), whereas the mean concentration of Znacetic was 95 mg kg 1 (Fig. 5g–h). Concomitantly, the mean ratio of ZnCaCl2/ZnT was below 0.2% (Fig. 4g–h), whereas the mean ratio of Znacetic/ZnT was 11.4% (Fig. 6g–h). In contrast, the mean concentrations of Znacetic in acidified AN + AE and AE mixtures, all with pH higher than 6.3 (Table 4), were <1.9 mg kg 1 and the mean ratios of Znacetic/ZnT were <0.9%. There was therefore a clear

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relationship between low pH and Zn leachability, indicating a greater risk in those mixtures with low acid buffering capacity (the low acid buffering capacity was demonstrated by the decrease in pH to 4.5 after addition of acetic acid, in contrast with the mixtures comprising limed material, in which the pH was buffered at values above 6). Overall, the results indicate the existence of a positive effect of acidification on metal leachability, although this does not appear to be straightforward, as there were several counteracting factors involved, such as the presence of organic ligands and the high acid buffering capacity of some of the mixtures.

of total metal contents as thresholds for regulating the application of wastes to soils. However, the current study was carried out with only pure artefacts, so their behaviour once applied to soils and under outdoors conditions is unknown, and might differ greatly from present results. Future studies must thus focus on a better understanding of the geochemistry of each of the elements in the environments under consideration, and of how they change over time, to enable prediction of future changes in their availability.

4. Conclusions

The authors express their gratitude to Urko Santisteban for his collaboration in incubating the mixtures, and to Marı´a Santiso for laboratory assistance. This project was financed by funding provided by the Spanish Ministry of the Environment (Project 2.5-206/2005/2) and by the Diputacio´n Foral de Bizkaia (EKINBERRI). INASMET, ACERALIA, and Iurreta Corporation S.A. are gratefully acknowledged for supplying the waste samples studied.

The results obtained indicate that mixtures comprising limed materials (AE, AN + AE, LD) displayed higher concentrations of CuCaCl2 and NiCaCl2 than mixtures comprising unlimed ingredients, despite (i) the fact that in most cases CuT and NiT contents were lower in the former mixtures, and (ii) the higher pH of the mixtures consisting of limed materials. The higher extractability of these heavy metals by CaCl2 was attributed to (i) solubilization of OM at high pH values, with the concomitant complexation and mobilization of the heavy metals, and also (ii) the blockage of exchange sites by Ca. The results therefore indicate that, in the presence of a high OM content, the mixtures should not have high pH values as these conditions enhance mobilization of heavy metals, such as Cu and Ni. On the other hand, a scavenging effect of DOC, and also Cu, Ni, and Zn by the inorganic reactive surfaces present in the conditioners, such as Fe and Al oxy-hydroxides, may explain the lower availability of these metal cations in the mixtures in which the reactive compounds were present, compared with their availability in the original ingredients. The risk of leachability was especially high for Ni, followed by Zn, as the extractability of these metals was greatly enhanced after acidification with acetic acid, and the effect was especially evident in the mixtures with low acid buffering capacity, such as those with AN sludge. Thus, the presence of liming materials may be beneficial if mixtures are used to restore areas in a high leaching environment, because of the high pH-buffering capacity that these confer, making the mixtures less susceptible to acidification, and thus, to heavy metal mobilization. However, the amount of liming material should be adequate to prevent increased mobilization of organo-metal complexes. The results obtained do not reflect a relationship between total heavy metal contents and heavy metal extractability in the mixtures made from sewage sludges and conditioners, although the risk of leachability was generally higher in those mixtures with high contents of heavy metals, such as those containing the FE conditioner. The conservative approach of risk assessment generally assumes that the total concentration of a contaminant present in a system is available for uptake by organisms. This is possibly an extremely cautious approach, there being a need to reconsider the use

Acknowledgments

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