Introduction

Increasing urbanization, industrialization, and population pressures have resulted in growing challenges in wastewater management on a global scale (Allaoui et al. 2015). The disposal of residual sewage sludge issued from wastewater treatment plants (WWTP) in dedicated landfills or, by incineration, are options adopted in many parts of the world, but both strategies are expensive and can lead to environmental problems (Fijalkowski et al 2017). Spreading dewatered sewage sludge (DSS) on agricultural land is another disposal option used in several countries because of its potential for improving soil physical properties and for containing significant nutrients for plant growth (Melo et al. 2018; Delibacak et al. 2020). In Algeria for example, the quantity of sewage sludge produced annually by around 200 WWTP (Bouchaala et al. 2017) is not known with certainty but certainly higher than 2 105 t of which only 25% are spread on agricultural lands. As the DSS have been shown to have agricultural value, it would be economically profitable to increase this percentage in order to provide a sustainable solution while allowing a reduction in the use of fertilizers, but on the condition of respecting two important constraints: the conservation of the agronomic properties of the soil (Tarchouna et al. 2010; Cherfouh et al. 2018) and the absence of accumulation of contaminants such as heavy metals or organics (Alvarenga et al. 2015; Lamastra et al. 2018).

When DSS is used as organic amendments for agricultural purposes, its large amount of organic matter can indeed improve the biological activity and the physical properties of the soil (Börjesson and Kätterer 2018; Cherfouh et al. 2018, Skowrońska et al. 2020), but the presence of heavy metals is probably the main critical impediment to overcome (Su et al. 2014). Thus, it was noted that applying sewage sludge to soil might provide potentially toxic metals under labile forms (Fijalkowski et al. 2017). Many studies have proven that urban sewage sludge contains significant concentrations of heavy metals because municipal sewage treatment plants are likely to receive industrial and other wastewater (Feng et al. 2018; Tytla 2019). Heavy metals in sludge constitute a relevant constraint limiting their valorization on agricultural soils, in particular, because of their bioavailability to the soil–plant system (Fijalkowski et al. 2017), consequently several studies point out the total heavy metal content and their potential mobility in DSS (Karwowska and Dąbrowska, 2017; Tytla, 2019; Latosińska et al. 2021).

The total heavy metal content of a DSS is easily obtained by chemical analysis, usually after sample acid digestion and subsequent inductively coupled plasma measurement. Total metal contents are useful to assess a potential contamination of a DSS and are usually the only parameters considered by public regulation. They are, however, insufficient to deliver indication about the bioavailability of the metals, which depends on their chemical species (Karwowska and Dąbrowska, 2017; Uchimiya et al. 2020). These can be determined by sequential extraction, a functional technique which can be applied to soil, sludge or sediment samples for determining the distribution of metals in various fractions (Tessier et al 1979), some of which correspond to potentially bioavailable metals (Fijalkowski et al. 2017). Sequential extraction consists of the sequential use of specific reagents under different pH conditions. One of the most widely used protocols (Tessier et al. 1979) defines five geochemical fractions: easily exchangeable, bound to carbonates (acid-soluble), bound to Fe and Mn oxides (reducible), bound to organic matter or sulphides (oxidizable) and contained in primary and secondary minerals (residual).

Depending on the physicochemical conditions of the soil, the metals found in the first four fractions can be mobilized and made bioavailable: the hazard associated with a given element depends on its speciation but also on soil parameters such as pH, Eh, organic matter, clay or oxide content, characteristics of the type of soil. The assessment of heavy metal hazard must therefore consider both the metal contents by fraction, the variability of these contents between WWTPs, and the nature of the soils on which the spreading will be carried out. However, there are surprisingly few studies that deal, within a given economic and climatic zone, with the variability between treatment plants in the speciation of metals within DSS, whereas this essential information must be taken into account in public policies that guide the use of sludges (Ting et al 2017; Östman et al. 2017; Duan et al. 2017).

In this context, the objective of this work was to evaluate the characteristics and variability of five urban residual sludges coming from urban WWTP located in the same Mediterranean area through the determination of the relevant agronomic parameters, the concentration of heavy metals (Ag, Cd, Co, Cr, Cu, Pb, Ti, Zn) and their speciation by sequential extraction. Cd, Cr, Cu, Pb, and Zn were chosen because these are metals that can be observed in contents higher than the standards in the DSSs (Yang et al 2020); Ag and Ti were chosen because of their increasing use in the form of nanoparticles in manufactured products for household use (Pradas del Real et al 2016; Shi et al 2016); Co was chosen because of its potential effect on plant growth (Perez-Espinosa et al. 2002), while very few content values in DSSs are available in the literature.

In doing so, the indirect question was raised as to whether the origin of potential contaminations in the sewer network can be determined.

Material and methods

The DSS samples studied were taken from drying beds from five activated sludge of WWTP whose capacity ranges from 5 103 to 120 103 inhabitant equivalent, located in Algeria (Fig. 1). The technical characteristics of the WWTP are given in Table 1. All the sludges were of urban origin and resulted from an activated sludge process with sludge drying beds. The wastewater entering the WWTPs was theoretically domestic. However, there are small industries or craft activities in the collection areas which for the most part had no specific treatment of their effluents and were not, or incompletely, listed and controlled. The activities whose presence was known or probable are metal working, metal plating, painting, tanning, dairy, furniture manufacturing and oil milling. About 25% of the sludge was spread on agricultural lands; the rest was deposited in disposal sites. The crops benefiting from the spreading are mainly vines; spreading takes place once a year at an estimated dose of between 10 and 30 t ha−1 (Cherfouh et al. 2018).

Fig. 1
figure 1

Geographic localization of treated wastewater plants

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Table 1 Technical characteristics of the wastewater treatment plants (WWTP) (IE: inhabitant equivalent)
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For each WWTP, 5 samples taken on the same day were mixed to form an average sample. Three repetitions of this procedure at 3-month intervals allowed obtaining three average samples for each station. The sludge sampled corresponded to an integrated deposit over a period of time varying between 20 and 60 days, which makes it very unlikely to have a random result. Samples were air-dried, then dried in oven at 55 °C, grinded in an agate mortar, sieved through a 160-μm mesh sieve and stored in polyethylene bottles at 4 °C. For each sample, an aliquot was weighed for determining water content after drying at 105 °C.

For each analysis, three analysis replicates for each sample were performed in order to meet statistical acceptance requirements. All the extraction solutions were prepared using ultrapure water (conductivity = 18 μS cm−1) and trace metal grade chemical reagents (Merck).

Electrical conductivity and pH were determined using a 1:10 [w:w] sludge-to-water ratio. Cation exchange capacity (CEC) was determined using the cobalthexamine method (Tarchouna et al. 2010). Total organic carbon (TOC) and total N (tN) were measured on solid samples using a CHNS (Shimadzu, Flash2000). The organic matter content was calculated using the formula MO (%) = CO (%) × 1.72, based on the assumption that average soil organic matter is composed by 58% of carbon (Prybil, 2010). Aqueous extracts were realized using a 1:10 [w:w] sludge-to-water ratio, agitation for 16-h and 0.45-µm filtration. On aqueous extracts, the water-extractible organic carbon (WEOC) was measured using a TOC-meter (TOC-V CSH, Shimadzu) by difference between total carbon and inorganic carbon. Ion concentrations in solution (nutrients and other major species) were measured by ionic chromatography (Dionex-DX-120).

Sequential extraction was performed using a five-step procedure modified from Tessier et al. (1979). Centrifugation was performed after each step at 4500 rpm for 15 mn; the supernatant was filtered at 0.45 µm on pre-washed nitrocellulose membrane before to be placed in polypropylene bottles where pH was adjusted at pH 2 with concentrated HNO3 (72%) in order to prevent hydrolysis of metals before analysis. The centrifugation pellet was recovered, washed by stirring 2 h at room temperature with 40 mL of ultrapure water then centrifuged for 15 min. The obtained pellet was then submitted to the next step. All the bottles and flasks were previously cleaned with HNO3 10% and rinsed.

  • Step 1 — Fraction F-ex. 2 g of soil or sludge was shaken in 20 mL of KNO3 1 M for 16 h at RT. The supernatant obtained after centrifugation corresponds to an easily exchangeable fraction.

  • Step 2 — Fraction F-ac. The pellet obtained after step 1 was stirred for 3 h at RT with sodium acetate 1 M adjusted at pH = 5. The supernatant obtained after centrifugation corresponds to a strongly adsorbed fraction, bound mainly to carbonates or to part of the Fe-sulphides (Flyhammar 1998).

  • Step 3 — Fraction F-red. The pellet obtained after step 2 was stirred for 2 h at 65 °C in 80 mL of 0.25 mol L−1 hydroxylammonium chloride at pH 1.5. The supernatant obtained after centrifugation corresponds to a fraction bound mainly to Fe and Mn (hydr)oxides.

  • Step 4 — Fraction F-ox. The pellet obtained after step 3 was suspended in hydrogen peroxide 30% (30 mL, pH = 2), stirred 5 h at 85 °C and centrifuged. The obtained pellet was stirred for 0.5 h in 20 mL of 3.2 mol L−1 ammonium acetate acidified at pH = 2 with HNO3 20% v/v. The supernatant obtained after centrifugation corresponds to a fraction bound mainly to organic matter or sulphides.

  • Step 5 — Fraction F-res. The residual fraction was obtained after aqua-regia extraction assisted by micro-wave (120 °C, 900 W, 1 h) of the pellet obtained after step 4.

The concentration of metals in the extraction solutions of the different fractions was measured using the inductively coupled plasma atomic emission spectrometry (ICP-AES) method (Agilent 5110). The validation of the ICP measurements was made following usual analytical laboratory practice, using multielement commercial standard (Agilent 6,610,030,600), working standard prepared with trace metal–grade stock solution and interlaboratory testing. Statistical analysis was conducted using the XLSTAT software (Addinsoft).

Results and discussion

Agronomic quality of sludges

The main agronomic parameters are given in Table 2. All the studied DSS had OM and tN contents which offer good prospects for agricultural use. The OM content is not too high (< 50%), which limits the risk of excessive nitrate burst after spreading (Kacprzak et al. 2017). The cation exchange capacity (CEC) was in the range expected from the high OM content. The pH values were standing between slightly acid 6.4 and alkaline 8.1. Such values were not expected to cause problems, particularly with regard to the mobility of trace metals (Yong and Phadungchewit 1993). The tN content ranged between 3.0 and 4.4%, a result similar to that of other studies (Stark and Clapp 1980). The C/N ratio ranged between 5.2 and 7.6. Some authors consider that such low values may promote nitrogen leaching. C/N ratio should ideally be raised to around 20 by adding bulking agents having a high C/N ratio (Tisdale and Nelson 1993). Others, however, using the same type of sludge, showed that, in the Mediterranean areas, biomass production was better improved by using sludge-alone amendment rather than sludge added to bulk agent amendment (Bousselhadj et al. 2004).

Table 2 Agronomic parameters of the studied urban dewatered sewage sludges depending on the WWTP location
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Regarding available P and K values, significant variability was observed between DSS samples (Table 2). PO43− varied from 4.6 to 0.2 and K+ from 3.7 to 0.6 g kg−1. These values are in the range of total P and K values found in other studies (Wen et al. 1997; Samaras et al. 2008; Tavazzi et al. 2012), which confirms their useful practical use as fertilizer. The measured electrical conductivity (EC) is only indicative, because there is no standard value for this type of measurement, which, in addition, is quite rare in the literature. It gives an indication of the salinization hazard for soils sensitive to this problem. In our case, the values for a 1:10 water extract varied from 409 to 1844 µS cm−1, which would correspond to 762 to 3432 µS cm−1 for a 1:5 water extract (Perez-Espinosa et al. 2000). These values are lower or in the range of values observed elsewhere (Perez-Espinosa et al. 2000), therefore without specific salinization hazard.

Total content of heavy metals

The total content of the studied heavy metals did not vary significantly between DSSs (Table 3). The maximum legal DSSs values (ceiling content) for France, the USA and China are given in Table 3; note that the European standards do not give a ceiling content, but only an interval of limit values, a fixed limit value to be defined later. For metals for which there are legal maximum values, all SSs values were below the permitted thresholds, except for Ni. TDM and BDM samples had Ni content higher than the French and Chinese legal ceiling value and sample AZF had Ni content higher than Chinese ceiling value. TDM and BDM sample had a Cr content lower, but rather close to the Chinese limit value. High Ni and Cr contents in DSSs were frequently observed in other studies (Juarez et al. 1987; Zufiaurre et al. 1998; Lasheen and Ammar, 2009). High content of heavy metals in WWTP sludges usually do not originate from domestic effluents, but from industries that discharge effluents in the sewer system or from entry of runoff stormwater into the sewer system (Sörme and Lagerkvist 2002; Westerhoff et al., 2015).

Table 3 Total content of heavy metals (mg kg−1 of dry matter ± std) in sludge and ceiling value application to the land, for each station n = 3
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Cr and Ni compounds may come from metal surface treatment or damascening industries. Ni compounds may also come from ceramic manufacturing industries and Cr compounds from textiles and tanning industries (Islam et al. 2017a). In our study, the high Ni and Cr contents in DSSs must be related to the fact that in the studied area there is no strict quality control of effluents from small industries which discharge directly in the sewer network.

No legal maximum value was found for Ag, Co and Ti. Ag content in the studied DSSs ranged from 1.1 to 7.4 mg kg−1. These values can be considered to be low in comparison with the few data available in the literature. A study from USEPA (2009) considered 74 sludge samples representative of U.S. WWTPs and found that Ag content was ranging from 2 to 195 mg kg−1 (20 on average), 50% of the samples having a value higher than 13. Pradas del Real et al. (2016) reported a value equal to 14 mg kg−1 for a sludge from Switzerland.

Cobalt is of special interest because it can act on biogeochemical cycles, in particular with regard to the availability of nitrogen for plants (Perez-Espinosa et al. 2002). Here, the Co content in sludges ranged from 9.5 to 27 mg kg−1, which can be considered as high and even outstanding values compared to the scarce data available in the literature, that range from 1 to 13 mg kg−1 (Grummitt 1976; Perez-Espinosa et al. 2002; Pradas del Real et al. 2016; Malinowska and Jankowski 2020; Östman et al. 2017). The higher value observed here (27 mg kg−1, AZF sample) is, however, unlikely to have an effect on plant growth (Perez-Espinosa et al. 2002). A cumulative effect of DSS application over several years, however, is not to be ruled out, depending on the mobility of Co in the soil.

Titanium in sludges was more studied due to the increasing use in recent decades of TiO2 nanoparticles, especially in personal care products, and because it is used as a catalyst for photocatalytic degradation of organic pollutant in wastewater (Wielinski et al., 2021). Data on bulk TiO2 content in DSSs, however, are also scarce. Values ranging from 305 to 1800 mg kg−1 were measured in DSS issued from European WWTPs (Johnson et al. 2011; Pradas del Real et al. 2018; Wielinski et al., 2021). Lazareva and Keller (2014) calculated, considering market studies, that the Ti content in sludges from New York, London and Shanghai would range from 40 to 208 mg kg−1. Here, the Ti content in DSS ranged between 946 and 1092 mg kg−1, values relatively high with regard to the literature. Titanium, mainly as TiO2, is a widely used product from paints to personal care products (Loosli et al., 2019). Poorly controlled house painting activity may be the cause of the high concentrations observed here.

Considering the total metal content, sludge from BKH and EST sewage treatment plants can be recommended as a fertilizer or as an organic soil amendment. For Ni, AZF sludge exceeds the Chinese standard, TDM and BDM sludges exceed both French and Chinese standards and therefore cannot be applied without costly prior treatment (Veeken and Hamelers 1999; Wong and Fang 2000), especially since this metal could easily be transferred to plants (Islam et al. 2015). It would be, however, more relevant to trace the origin of nickel in the corresponding localities to avoid its transfer to the sewer network. Anyway, these data underline the importance of quality control of sludges with regard to heavy metals.

Statistical analysis (PCA, principal component analysis) (Fig. 2) was able to identify two groups of metals with differentiated behaviours. Thus, PCA shows good correlations between metals in the (Cu, Ni, Cr, Cd, Ti) group, as well as in the (Pb, Zn) group, these two groups not being correlated with each other. Co was anticorrelated with Pb and Zn. The two first components explained 83.6% of the variance. The position of the BKH and TDM points is explained by lower and higher values, respectively, for metals from the (Cu, Ni, Cr, Cd, Ti) group. The position of the EST point is explained by higher values for Pb and Zn and low value for Co; the opposite being observed for the AZF point. The higher Co content in the AZF sludge is probably not related to the geological context of the area, which is the same for all the treatment plants; it is more likely related to effluents from the small metallurgical or ceramic industry (Kosiorek and Wyszkowski 2019). The high values of Pb and Zn could also be due to the entry into the sewer system of runoff waters in which these two elements have generally high values compared to other heavy metals (Nicolau et al. 2012).

Fig. 2
figure 2

PCA biplot on the first two factorial axes for total metal content. Stars correspond to the observed different WWTPs. Percent on each factorial axis gives the explained variance

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Speciation of heavy metals

In Mediterranean soils where the sludges are spread, the fractions most likely to release bioavailable metals are the F-ex, F-ac fractions, as well as the F-oxi fraction. The latter corresponds to metals bound to sulphides and organic matter, which are rapidly oxidized in a dry environment and, in the case of organic matter, at pH higher than 6.5 (Cherfouh et al. 2018).

The metals studied showed differentiated behaviours with high consistency between WWTPs, with the exception of Ag (Fig. 3, numerical values are given as Supplementary Material). For all metals, the exchangeable fraction (F-ex) was lower than 3.5%. As already observed for industrial sludges (Islam et al. 2017b), there was no correlation between the total content and the mobile fractions.

  • Ti, Cr and Ni were found mostly in the residual fraction (F-res) i.e. contained in minerals (more than 90% for Ti and Cr and more than 80% for Ni), therefore poorly bioavailable (Sims and Kline 1991). Small amounts of these metals (< 10%) were in the oxidable fraction (F-oxi) i.e. mainly bound to organic matter or sulphides and, for Ni, 8–12% were in the reducible fraction (F-red) i.e. mainly bound to Fe or Mn oxides, in agreement with other studies (Ahumada et al. 2004; Islam et al. 2017b; Yang et al. 2017).

  • The distribution of Co among the fractions looks like that of Ni, with a greater proportion in the F-oxi and F-red fractions. High values of the latter were observed for samples BDM and AZF. Cumulative contents in the F-ex, F-ac, F-oxi fraction (max. 3.3 mg kg−1 in the AZF sludge) were low enough, however, to rule out long-term risk with regard to plant growth.

  • Zn an Pb were mostly in the F-red fraction, as observed elsewhere (Silveira et al. 2006; Chen et al. 2008; Zufiaurre et al. 1998), with, for Zn, a non-negligible proportion (4.2 to 15.9%) in the acid-soluble fraction (F-ac).

  • Cu was mainly distributed between F-red, F-oxi and F-res fractions, with a F-ac fraction ranging from 1.7 to 7.3%. Compared to other metals, Cu is well known to be mainly associated with the oxidizable fraction, which is confirmed by our results with best affinity of this fraction comparatively to Cr, Zn, Ni, Pb and Co. This behaviour is similar to that observed by other authors (Chen et al. 2008; Walter et al. 2006; Zufiaurre et al. 1998).

  • Cd was the only metal having a low or under detection limit residual fraction (F-res). Most Cd was distributed between the F-ac and the F-red fractions, with a significant part (10.3 to 15.8%) in the F-oxi fraction. Similar distribution has already been described in sludge from the middle-south region of China (Chen et al. 2008). The low Cd contents in the fractions were low enough to rule out a long-term risk.

  • Ag was the only metal whose distribution was quite different from one sludge to another.

Fig. 3
figure 3

Metal speciation in the studied sludges from various WWTPs, values in mg kg−1

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The distribution of each metal between fractions showed similarities between stations, as shown in Fig. 4. There were, however, significant differences between WWTPs, which are best highlighted by statistical analysis (Fig. 5). The BKH and EST sludges were characterized by lower values for most of the metal fractions F-red, F-oxi and F-res, and proportionally higher values for the exchangeable fractions F-ex and F-ac. In contrast, the AZF, BDM and TDM sludges were characterized by higher values for F-res, F-oxi and F-red fractions of metals. AZF and sludges were separated from the TDM sludge mainly due to a higher Co values in the F-oxi fraction.

Fig. 4
figure 4

Metal speciation in the studied sludges from various WWTPs. Percent for each fraction in a given sludge

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Fig. 5
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PCA biplot on the first two factorial axes for the whole set of data. Colour of points/letters indicate the metal fraction. Stars correspond to the observed WWTPs

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The potential risk highlighted above due to high Ni and, to a lesser extent, Cr, can be put into perspective by the speciation data. More than 80% of Ni and Cr were found in the F-res fraction, the least likely to be made bioavailable by a change in acidity or redox potential in the soil. The pH usually greater than 6 of the soils of the region where these sludges can be spread is not favourable to the solubilization of Ni- or Cr-bearing metallic particles or minerals (Smith 1994). Here, the sum of the F-wat, F-ac and F-oxi Ni fractions, all capable of rapid release of bioavailable Ni, ranged from 6 (BDM) to 13 (TDM) mg kg−1. Considering that sludge application is around 20 t ha−1, neglecting leaching and plant uptake, and using 1.5 kg dm3 as soil bulk density, it would take 230 (TDM) to 500 (BDM) years to accumulate in the topsoil 10 cm the bioavailable Ni content above which toxic effects can be observed (Kumari et al. 2018). The speciation of Ni can be very different in other places. In a Slovenian sludge studied by Scancar et al. (2000), more than 81% of the high Ni contents (621 mg kg−1) were contained in potentially labile fractions. In contrast to Ni, while the total Cu content was below the authorized limits, the sum of the F-wat, F-ac and F-oxi fractions, all capable of rapid release of bioavailable Cu, ranged from 26 (BKH) to 102 (TDM) mg kg−1. Considering the same hypothesis than for Ni, it would take 3 (TDM) to 11 (BKH) years to accumulate in the topsoil 10 cm the bioavailable Cu content above which inhibition of nitrification can be observed (3.8 mg kg−1 soil) (Cela and Sumner 2002). These considerations underline the insufficiency of the regulations which only consider the total metal contents and not the conditions of their bioavailability. A risk indicator such as the potential environmental risk indicator (PERI) must be calculated for each sludge according to the characteristics of the soils on which they will be spread (Latosińska et al 2021). The “environmental risk determinant” (ERD) indicator can, however, be calculated without taking into account the characteristics of the soil (Latosińska et al 2021). It is calculated as follows:

$$ERD={f}_{ex}+{f}_{ac}+{f}_{red}^{2}+{f}_{oxi}^{3}$$

where fex, fac, fred and foxi are the metal contents of the fraction divided by the total metal contents of the sample for the F-ex, F-ac, F-red and F-oxi fractions, respectively. This indicator aims to take into account the potential mobility of the metal in the different fractions. The calculated values of ERD for each metal in the studied sludges and the corresponding risk classification are given in Fig. 6.

Fig. 6
figure 6

Environmental risk determinant (ERD) of metals in the studied sludges

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The ERD indicator reflects the low bioavailability of Ni whose ERD values indicate a low risk. However, the ERD values of Cu also indicate a low risk, whereas we have shown above that the risk of rapidly reaching a potentially crop-damaging content in the soil is greater. Furthermore, the ERD values of Cd indicate a risk between medium and high, whereas the total contents of this element in the sludges were very low, excluding a long-term risk. These considerations show that the risk associated with a metal must be related to both its total content and its potential mobility, this latter depending on the speciation in the sludge and the properties of the soil on which it is spread.

Whatever the agronomic value of the sludges, the speciation of the metals in sludges makes it possible to identify the sites on which the search for sources of contamination would be necessary. Analysis of the treated wastewater gives information on the contamination at the moment of sampling, while the sludge gives information on the contamination integrated on the entire deposition time. Here, the sources must be searched within the sewage network of the AZF, TDM and BDM WWTPs. The analysis showed that the contaminations concerned several metals simultaneously, the higher values of total Ni being accompanied by higher values for most F-red, F-oxi and F-res fractions of Cd, Co, Cr, Cu and Ti. Possible sources can be industries or cottage industries related to painting (Lokhande et al. 2011; Tesfalem and Abdrie 2017), metalworking and metal plating (Quin et al. 2018), tannery and textile dyeing (Imtiazuddin and Mumtaz 2013; Uma et al. 2016). Here, we identified metal plating industry in the BDM area and metalworking activities in the TDM area. An exhaustive identification of the sources is, however, an activity in its own right which must be carried out in collaboration with the competent regulatory services.

Conclusion

The analysis of sludges from various WWTPs made it possible to assess their variability within an area characteristic of a developing Mediterranean country. All the analysed sludges had satisfactory properties from an agronomic quality point of view. Analysis of the total content of heavy metals showed that some sludges were not usable under French or Chinese regulations. The speciation of metals by sequential extraction underlined, however, that these regulations do not take into account the bioavailability of metals in the spreading environment, here Mediterranean soils. For three of the studied sludges, the total Ni content was higher than maximum legal values while Ni was contained at more than 80% in very poorly bioavailable fractions. In contrast, the total Cu content was below the maximum legal values, while this metal was contained in fractions capable of rapid release of bioavailable Cu. The risk of plant toxicity in the short and medium term by spreading these sludges was consequently more linked to Cu than to Ni. Considering that sludge application was around 20 t ha−1, without leaching and plant uptake considerations, and using 1.5 kg dm3 as soil bulk density, it was possible to decalculate the time that would be required to accumulate bioavailable metal in the topsoil before reaching the threshold above which toxic effects appear. It, therefore, appears necessary to develop standards which take into account their bioavailability in the soils on which they will be spread. The agricultural use of the this type of sludges on Algerian soils must, henceforth, be accompanied by a monitoring of the short-term evolution of the bioavailable quantities of Cu, especially if the crops, such as the vine, undergo a supply of Cu by phytosanitary products and monitoring of the long-term evolution of the bioavailable quantities of Ni.

The speciation of the metals in sludges also makes it possible to identify the sewage network area on which the sources of contamination must be sought. The sludge gives information on the contamination integrated on the entire deposition time, and the metal species indicate what type of source should be sought. Note that the same type of approach could be applied to organic contaminants.