Suitability of environmental indices in assessment of soil remediation with conventional and next generation washing agents

Remediation of soils contaminated with metal must ensure high efficiency of metals removal, reduce bioavailability of residual metals and decrease ecological risk. Thus, for comprehensive environmental soil quality assessment, different indices must be used. In this study, suitability of 8 indices was used for soil highly contaminated with Cu (7874.5 mg kg−1), moderately with Pb (1414.3 mg kg−1) and low with Zn (566.1 mg kg−1), washed in batch and dynamic conditions with both conventional and next-generation washing agents. The following indices were used: modified contamination factor (mCf), modified contamination factor degree (mCdeg), mobility factor (MF), reduced partition index (IR), potential ecological risk factor (Er,Z), modified potential ecological risk factor (Er,m), potential ecological risk index (RIZ) and modified ecological risk index (RIm). For mCf, mCdeg and IR own classification scale was proposed. It was proven that most useful indices for assessment of soil pollution with metals were mCf and mCdeg. The mCf together with the IR allow to simultaneous assessment of soil pollution and stability for individual metals. These indices were appropriate for soil contaminated with different concentrations of metals, washed under both hydrodynamic conditions using various washing agents and different effectiveness of metals removal. Thus, they may be considered as most useful for evaluation of remediation method, feasibility of washing agent and assessing soil quality after washing.


Materials and methods
Soil. Soil taken from the top layer of agriculture area was used for the study. After air drying, the samples were ground and sieved through a 2 mm sieve. To obtain metals contamination similar to soils from the metallurgical area, the soil was spiked with a mixture of Cu(NO 3 ) 2 , Pb(NO 3 ) 2 and Zn(NO 3 ) 2 , according to the procedure of Chaiyaraksa and Sriwiriyanuphap 29 and incubated for three months at room temperature. Metals values were assumed according to concentrations in soils around the Legnica smelter in Poland 18 . Because the aim of this study was to check the suitability of different indices to assess degree of soil contamination (and subsequently soil remediation), it was assumed that soil must be contaminated with metals of different concentration: from very high (several times above permissible concentration) to low (below permissible concentration). Such concentration range is necessary to select universal indices and to propose own classification scale for these indices. So, in this study soil was very highly contaminated with Cu, moderately with Pb and weakly with Zn.
Before soil treatment, soil properties were determined (Table 1). Based on the granulometric composition, soil was characterized as sandy loam with a low content of organic matter (3.4%) and slightly acidic pH (6.4). Total concentration of metals and their distribution were also shown in Table 1.
Washing agents (WAs). Two groups of WAs were used in this study: (1) waste-derived in form of soluble organics from municipal sewage sludge (SS_WAs) and (2) commercially available Na 2 EDTA.
As SS_WAs, three different washing solutions were used: DOM, HLS and SHS. The previous study presented a detailed extraction procedure and characteristics of the used washing solutions 18,30 . Briefly, WAs were extracted (1:10 ratio (w/v)) with water (DOM) and 0.1 M NaOH (HLS and SHS) from the dried sewage sludge (105 °C). In addition, before the extraction of SHS, dissolved substances (i.e. sugars and proteins), waxes, and bitumen were removed from the sludge, as described in paper by Klik et al. 30 .
The methods of soil remediation and WAs were selected in such way to indicate various efficiency of metals removal from soil, e.g. Na 2 EDTA and HLS was extremely effective in removal of all metals, DOM was extremely Dynamic washing experiments. The experiments were carried out in a column reactor equipped with a set of two sieves (supporting and closing) and two layers of rinsed gravel (2-4 mm and 1-2 mm) (Fig. 1b). The column reactor with length of 30 cm and radius of 1.5 cm was packed with 200 g gravel and 50 g of contaminated soil.
The tests were carried out at concentration and pH of WAs the same as in batch washing. Washings solutions were added to the reactor from the top and the eluate was collected from the bottom of the reactor by the automatic sampling device over time. Samples were taken every hour. Before proper soil washing procedure, distilled water was applied for 1 h to saturate the soil. Pore volume for the column reactor was 56.8 ml. The research was conducted at 2 different flow rates (0.5 ml min −1 and 1 ml min −1 ), for each washing solution for 24 h. All column experiments were conducted at room temperature, under laboratory conditions. www.nature.com/scientificreports/ The environmental indices for soil remediation assessment. In the present study, different environmental indices were used to assess the efficiency of batch and dynamic soil washing with SS_WAs agents and Na 2 EDTA. These indices, including total metals concentrations in soil and metals distribution in chemical fractions, were divided into three groups: Indices based on soil pollution with metals.
Modified contamination factor (mC f ). The contamination factor (C f ), originally proposed by Hakanson 21 for sediments, now is commonly used to assess soil contamination with metals 23,[32][33][34][35] . For C f calculation, mostly preindustrial or geochemical background concentrations of metals are used. The use of such reference values can be not reliable for assessment of metal pollution in highly contaminated before and after remediation. This is because in remediated soil achieving metal concentration on the level of geochemical background is impossible and it is not legally required. According to Polish Environmental Protection Law 36 , remediation is based on the removal or reduction the amount of substances causing the risk from soil and groundwater to the level of limit values, their control and limitation of migration, so that the contaminated area ceases to pose a threat to human health or the state of the environment, taking into account the current and the planned land use. Therefore, in this study for the assessment of metal pollution in contaminated and post-remediated soil, original C f factor was modified to mC f , taking as reference of metal concentration, not preindustrial/geochemical background, but the limit values for metals in industrial soil given in a national regulation (here the Ordinance of the Minister of Environment 37 ). The mC f was calculated according to the following formula: where: C s is the concentration of metals in soil sample, C r is the limit value for a given metal in soil according to OME 37 : 600 mg kg −1 for Cu and Pb and 2000 mg kg −1 for Zn. The mC f was categorized into five levels: mC f ≤ 1 means that soil meets the national quality standard for industrial sites, 1 < mC f ≤ 2 means weakly to moderately contaminated soil, 2 m < C f ≤ 3 means moderately to strongly contaminated soil, 3 < mC f ≤ 4 means strongly to extremely contaminated soil and mC f > 4 means extremely contaminated soil.
Modified contamination degree (mC deg ). The overall assessment of sediment contamination with metals was introduced by Hakanson 21 as a contamination degree (C deg ). The C deg is a sum of the C f for individual metals.
Like the C f , the C deg was also used to assess soil contamination with metals 23,[32][33][34][35] . Because in the present study, the C f was changed for mC f , consequently the C deg was changed for mC deg and the mC deg equation was modified as follows: where: mC f is the modified contamination factor calculated in Eq. (1), n is the number of metals in soil, w is factor weight resulting from the value of mC f , i.e. when mC f ≤ 1 then w = 1 or when mC f > 1 then w = n. The classification of mC deg was simplified and two categories of soil quality were proposed: mC deg ≤ n means that soil meets the national quality standards for industrial sites and mC deg > n means that soil does not meet the national quality standards.
Indices based on the strength of metal binding in soil. Mobility factor (MF). The MF is used to assess changes in metal mobility, and is defined as the ratio of metal concentration in the mobile fraction to the sum of metal concentrations in all analyzed fractions 25 . The MF (based on the BCR fractionation procedure) is expressed by the following equation: where: C F1, C F2, C F3, and C F4 are the concentrations of metal in exchangeable/acid soluble, reducible, oxidizable and residual fractions, respectively. With the MF, metal can be immobile (< 1%), weakly mobile (1-10%), moderately mobile (11-30%), highly mobile (31-50%) and very highly mobile (> 50%).
Reduced partition index (IR). The IR informs about the strength of metals binding with mineral-organic soil components. When IR is close to 0, metal occurs in an easily soluble and exchangeable form, while IR close to 1 means that a given metal dominates in stable forms, mainly in the residual form 24,25 .
Indices based on ecological risk from metals. Potential ecological risk factor (E r ). The E r assesses the impact of individual metal including their various toxicological effects 21 . The E r is also used to evaluate the ecological risk for sediments and soils 38,39 . In the present study, the E r was calculated and compared according to the formula given by Hakanson 21 and used in the study by Zhu et al. 40 (in this study noted as E i r,Z ) and according to our modification (in this study noted as E i r,m ) using mC f instead of C f : where: T r is the toxic-response factor for a given metal (5 for Cu and Pb, 1 for Zn, Hakanson 21 ), mC i f is the modified contamination factor.
Because in this study, similarly as in study by Zhu et al. 40 , the metals with the highest T r (Hg, Cd, As) were not analyzed, we assumed the same classification of soil ecological risk as Zhu et al. 40 : low risk (E r ≤ 15), moderate risk (15 < E r ≤ 30), considerable risk (30 < E r ≤ 60), high risk (60 < E r ≤ 120), and very high risk (E r > 120).
Potential ecological risk index (RI). The RI is defined as the sum of E r (Hakanson 21 ). Because in the present study E i r,Z and E i r,m were established, therefore two RI were also calculated according to the Eqs. (7,8): According to the classification of the E r, the classification of RI was different than that originally given by Hakanson 21 : low risk (RI ≤ 50), moderate risk (50 < RI ≤ 100), considerable risk (100 < RI ≤ 200), and very high risk (RI > 200) 41 .
Analytical methods. The equilibrium pH of soil was measured with a pH meter (Hanna Instruments) in distilled water (1:2.5 ratio, m/V). The soil texture was determined using a Mastersizer 2000 particle size analyzer. The content of organic matter was determined by the Tiurin method and CEC was measured according to the Kappen's method 42 . The concentration of metals in soil was determined with Flame Atomic Absorption Spectrometry (FAAS) using a spectrometer equipped with an automatic sample introduction and dilution system (SIPS). The samples were mineralized in a mixture of concentrated HCl and HNO 3 before determination of total metals content. Mineralization was carried out in a microwave oven (MarsXpress, CEM). Metals distribution was determined according to a modified BCR procedure given by Pueyo et al. 43 , the following fractions were determined: exchangeable and acid-soluble fraction (F1); reducible fraction (F2); oxidizable fraction (F3); and a residual fraction (F4).
The obtained results are averages of three replicate measurements. The statistical analyses were performed with Statistica 13.1 (StatSoft, Inc.). One-way analysis of variance (ANOVA), followed by Tukey's HSD test was employed to indicate significant differences between means for metal removal efficiencies and environmental indices in soil treated with different WAs under batch and dynamic soil washing. Validation of the data was carried out through comparing total metal content obtained by total digestion with sequential extraction of metals. The metal recovery ratio (R) was calculated as follows: where: C F1, C F2, C F3, and C F4 is the concentration of metal in a given fraction, C total is the total metal concentration.

Results and discussion
The removal efficiency of metals. Comparing the metals removal under different soil washing conditions, the batch washing was more efficient compared to dynamic washing. This may be due to the way of contact between the soil and WAs, which is more vigorous under batch conditions and a higher ratio of soil weight to volume of washing solution in comparison to dynamic washing. Although higher metal removal under batch than dynamic soil washing is typical phenomenon [44][45][46] , our intention was to show the different efficiency of metals removal and their different fractional distribution in batch-and dynamic-washed soil in terms of the possibility of assessing the usefulness of modified environmental indices for soils with different remediation efficiency. www.nature.com/scientificreports/ In the present study, the soil was contaminated to the largest extent with Cu, which exceeded over 13 times permissible limit for industrial soils according to Polish legislative 37 . Therefore, Cu removal mostly affected the overall efficiency of soil remediation.
Under batch conditions with all tested WAs, the average efficiency of Cu removal was 88% (ranging from 79% for SHS to 93% for Na 2 EDTA). Under dynamic conditions, the higher efficiency of Cu removal, and consequently lower residual Cu concentration in soil, was at 1 ml min −1 than at 0.5 ml min −1 flow rate (Fig. 2). DOM and Na 2 EDTA removed the highest amount of Cu from soil under batch conditions (> 92%), while under dynamic conditions, DOM and HLS were the most effective for Cu removal (the efficiency > 70%). Similarly, higher Pb removal was obtained in batch than dynamic conditions. However, in both hydrodynamic conditions, most effective in Pb removal were HLS and Na 2 EDTA. In contrast to Cu, DOM was able to remove only 24% of Pb under batch washing and only 3% (on average) under dynamic conditions. As in contaminated soil, Zn concentration was the lowest, compared to Cu and Pb, and its removal efficiency with DOM, HLS, SHS and Na 2 EDTA were high in both washing conditions. However, batch conditions were also more favourable than dynamic conditions. For example, the efficiency of Zn removal with HLS was 90% under batch conditions (in washed soil Zn remained mainly in F4 fraction) and 70-78% under dynamic condition at both flow rates.
The difference in metal removal with tested washing agents was related to their characteristics and affinity to individual metals. The washing agents extracted from sewage are composed of multiple organic compounds and functional groups. DOM contains mainly low-molecular-weight organics and fulvic acids. HLS contains both low-molecular-weight organics and macromolecular compounds (fulvic and humic acids), whereas SHS are mainly consist of fulvic and humic acids 3 Among different organic functional groups, carboxyl (carboxyl-C) and amino (N-alkyl-C) groups readily interact with metals 47 . In all washing agents derived from sewage sludge, carboxyl (dissociated and undissociated) and unprotonated amino groups were the most abundant and the intensities in the infrared spectra for these groups decreased in the order DOM > HLS > SHS 30 . This can explain higher DOM efficiency in metal removal, especially Cu and Zn. In contrast, higher Pb removal with HLS and SHS than DOM suggests that its removal depends more on the presence of functional groups in macromolecular organic compounds in washing agents, especially humic acids than on functional groups in low-molecularweight organics.
Because better removal of Cu, Pb and Zn under dynamic conditions was at higher flow rate, to compare the suitability of the many commonly used indices for assessment remediation efficiency and soil quality, the results from batch and dynamic washing at flow rate of 1.0 ml min −1 were selected.  The results clearly demonstrated that the distribution patterns for individual metals depended on the soil washing conditions and the type of WA. The results have shown that the most mobile F1 fraction was considerably removed with the most of tested WAs under batch and dynamic conditions ( Table 2).
The share of F1 fraction for Cu in soil washed under batch conditions was lower than under dynamic conditions, which is associated with lower process efficiency for these washing conditions ("The removal efficiency of metals" section). In batch conditions small share of Cu in F1 fraction was in soil washed with Na 2 EDTA (108.2 mg kg −1 ;16.6%) and DOM (134.7 mg kg −1 ; 25.3%), and the largest in soil washed with SHS (1048 mg kg −1 ; 66.5%). Under dynamic conditions, despite decreasing of total Cu, its distribution in all washed soils was similar to that in unwashed soil with the same order of fractions as F1 > F2 > F4 > F3 (Table 2). It must be emphasized that under dynamic conditions, the greatest decrease in the Cu concentration in the F1 fraction was recorded for DOM. It means that although in batch conditions effectiveness of DOM and Na 2 EDTA for Cu removal from F1 was similar, in dynamic conditions more favorable for Cu removal was DOM.
In the case of Pb, although batch washing was more effective than dynamic washing, distribution pattern of Pb in washed soil in both conditions was similar. However, this phenomenon was observed only with SS_WAs. A different pattern was noted in Na 2 EDTA-washed soil: in soil washed under batch conditions F4 fraction predominated, whereas in soil washed in dynamic conditions the F1 fraction of Pb predominated. The results indicate that batch soil washing was more favourable for Pb removal from individual fractions with all tested WAs. Table 2. Total metal concentrations and their individual fractions in soil before and after soil washing under batch and dynamic conditions. *Limit values for industrial soils in Poland: Cu 600 mg kg −1 , Pb 600 mg kg −1 , Zn 2000 mg kg −1 (OME 37 ), metal fractions: F1 is the exchangeable and acid soluble, F2 is the reducible, F3 is the oxidizable, F4 is the residual, R is the HM recovery ratio.  www.nature.com/scientificreports/ The highest changes in fractional distribution were observed for Zn. Its distribution patterns in batchwashed soil with DOM, HLS, SHS and Na 2 EDTA were similar, with the largest share of Zn in F4 fraction (22.4-47.5 mg kg −1 ). In contrast, distribution patterns of Zn in dynamic-washed soil were more differential. Fraction F4, representing the lowest potential environmental risk, constituted the largest share in HLS-washed soil and in SHS-washed soil. However, the most mobile F1 fraction of Zn prevailed in DOM-and Na 2 EDTA-washed soil, followed by SHS-and HLS-washed soil ( Table 2).

Suitability of different environmental indices for assessment the quality of washed soil.
Soil pollution with metals. The soil pollution with metals before and after remediation was assessed with mC f and mC deg indices. With the mC f , unwashed soil characterized with different pollution levels for individual metals, from extreme contamination for Cu (mC f = 13.1) (Fig. 3a) to moderate/strongly contaminated for Pb (mC f = 2.4) (Fig. 3b). The soil has shown lack of contamination with Zn (mC f = 0.28) (Fig. 3c).
Soil washing had a great effect on decreasing of mC f : higher decrease was observed in soil after batch than dynamic washing. In soil after batch washing with DOM and HLS, Cu showed weak to moderate contamination, however after washing with SHS soil was still highly contaminated with Cu (mC f = 2.8). In soil washed under dynamic conditions with all WAs, the mC f for Cu was above 3, reflecting strong to extreme contamination (Fig. 3a). For Pb, only soil washed with DOM under batch and dynamic conditions did not meet soil quality standards for industrial area (mC f = 1.8 for batch washing and mC f = 2.3 for dynamic washing) (Fig. 3c). After washing with other WAs, mC f was < 1, meaning that soil met the national quality standard for industrial sites.
Assessing the soil contamination in relation to all metals (as mC deg ), only soil washed with Na 2 EDTA under batch washing met the quality standards for industrial areas. In other soil samples, mC deg was greater than 3 (from 5.0 to 18) (Fig. 3d). The results confirmed that total metal concentration is important for the efficiency of soil remediation and decreasing soil pollution level. Metal occurring at the highest concentration in soil before remediation (in this case Cu), affects mostly the mC deg in remediated soil.
The necessity of modification of original pollution indices (C f and C deg ) given by Hakanson 21 resulted from the fact that these indices were dedicated to sediments. Moreover, the classification of C f and C deg reflects the lower values of metal concentrations in contaminated sediments. Thus, the use of this classification for highly contaminated soils can be confused. For example, in this study Cu concentration in contaminated soil was 7874.5 mg kg −1 (13.1 times higher than OME 37 limit), while Zn concentration was 566.1 mg kg −1 (3.5 times lower than OME 37 limit). Calculated values of the original C f for Cu and Zn were 787.4 and 6.4, respectively and in both cases, they indicated very high contamination (C f ≥ 6). Another example is for soil washed in batch The strength of metal binding in soil. Mobility factor (MF). In the present study, all metals in contaminated soil were highly mobile (74% < MF < 86%) (Fig. 4). Such superior values of the MF for Cu, Pb and Zn were associated with high share of metals in the exchangeable and acid soluble (F1) fraction. Metals in this fraction are bound to soil constituents with weak bonds and thus they are highly mobile 51 . The values of MF have dropped significantly after washing, especially in batch-washed soil. The WAs had different ability to decrease the MF for individual metals. For Cu, the lowest MFs were in DOM-and Na 2 EDTA-washed soil (Fig. 4a). The low Cu mobility that has been observed for these agents corresponded to high metal stability in soil (as IR). In the case of HLS and SHS, the MFs were still high (45% and 66%, respectively). After soil washing under dynamic conditions, the MFs for Cu were higher for DOM, HLS and Na 2 EDTA than after washing under batch conditions, and they did not differ statistically (MF 67.7%, on average) (Fig. 4a). Comparable MFs for Cu were obtained in soil after washing with SHS under batch and dynamic conditions. The highest effect on the MF decrease for Pb had HLS, SHS and Na 2 EDTA. It worth noticing that in soil washed with Na 2 EDTA under batch conditions, the MF for Pb was very low (5.2%), however, in soil washed under dynamic conditions it was 10 times higher (MF = 55.4%). In the case of HLS, the difference in MFs for both washing conditions was 9.5%, and Pb. For DOM and SHS, the conditions of soil washing did not affect the MF values of Pb. In soil washed with DOM, the MF of Pb was comparable as in unwashed soil (Fig. 4b).
The effect of washing conditions on the changes in MF was the greatest for Zn. With all WAs, the MF decreased from very high to low (5.4%, on average; p > 0.05) under batch soil washing. Despite decreasing the MF of Zn under dynamic conditions, the Zn mobility was still high for DOM-washed soil (MF = 67.1%) and Na 2 EDTA-washed soil (MF = 52.2%). The use of HLS and SHS led to decrease Zn mobility to low and medium level, respectively (Fig. 4c).
High values of the MF are typical for highly metal-contaminated soils. Kulikowska et al. 18 demonstrated that in soil from metallurgical area in Poland, Cu and Zn showed very high mobility (MF), i.e. 73.1 and 70.6%, respectively. Cheng et al. 52 found high MFs for Cu, Ni and Zn, i.e. 68%, 64% and 53%, respectively in soil from the electroplating factory (Dongguan City, China). The values of the MF for Cu, Ni and Zn were significantly decreased after soil batch washing with mixture of EDTA and oxalic acid to 22%, 25% and 23% for Cu, Ni and Zn, respectively. Decrease in metal mobility in soil after remediation is typical phenomenon. Gusiatin and Klimiuk 25 demonstrated that significant decreasing of the MF values can be obtained through multiple batch soil washing. In soil spiked with Cu, Cd and Zn, the metals presented very high mobility (61% < MF < 84%), which was decreased below 10% for Cu and Cd and below 20% for Zn after triple soil washing with saponin www.nature.com/scientificreports/ biosurfactant. Also, Wang et al. 53 showed that batch washing was very effective in decreasing Pb mobility with N,N-bis (carboxymethyl)-l-glutamic acid in mine soil, from 80 to 17%.
Reduced partition index (IR). One of the tools to evaluate the stability of metals in soil is the IR index based on the metal distribution patterns 24,25 . Originally, the index was applied for assessment of metal stability in soil amended with different additives. Nowadays, it can be used also for soil remediated with soil washing 25 . An increase of the IR indicates metals redistribution in soil, from less to more stable fractions. In the case of BCR sequential scheme of metal fractionation, the F1 fraction is mobile, the F2 and F3 fractions are potentially mobile, and the F4 fraction is stable. Thus, the considerable increase of the IR is favoured by the increase of metal share in the most stable fraction.
With the use of the IR index the changes in metal stability were captured. The values of the IR index for unwashed soil and soil washed with different WAs are shown in Fig. 5. The results indicate that IR values in unwashed soil were relatively low (IR = 0.12-0.22) indicating low stability of all metals. Soil washing increased the IR for all metals, except for Pb in DOM-washed soil (IR < 0.3). In general, metals in soil from batch washing showed higher bonding intensities compared to soil from dynamic washing. In additions, metals differed in bonding intensities in washed soil. The differences were strongly related to metal distribution patterns ("Patterns of metal distribution in soil washed under batch and dynamic conditions" section). Batch washing with DOM and Na 2 EDTA resulted in high stability of Cu (IR = 0.61 for both agents), whereas the stability of Cu in soil from dynamic washing was 2.6 times lower (IR = 0.26 for DOM and 0.22 for Na 2 EDTA). For Pb, the greatest differences in the metal stability between batch-and dynamic-washed soil (by IR = 0.47) was indicated for Na 2 EDTA. Table 3. Comparison of potential ecological risk factors (E r,Z , E r,m ) and potential ecological risk indices (RI Z , RI m ) in soil before and after washing. www.nature.com/scientificreports/ Medium Pb stability was in soil washed with SS_WAs under batch and dynamic conditions (IR = 0.5 and 0.4 for HLS and IR = 0.33 and 0.32 for SHS, respectively). Batch soil washing was especially effective for Zn removal from mobile and potentially mobile fractions by all WAs, which resulted in high stability (IR > 0.8). In contrast, the Zn stability in soil after dynamic washing ranged from low for DOM (IR = 0.28) to elevated for HLS (IR = 0.66).
Studies evaluating the metal stability (based on IR) in soils after washing were conducted by Gusiatin et al. 54 . The authors have found that application of different biosurfactants as WAs (saponin, tannic acid, rhamnolipids) significantly increased the stability of Cd, Cu, Ni, Pb and Zn (based on the IR) in spiked soil. Similar observations were made by Cheng et al. 52 , who noticed an increase in the IR index in soils after washing with a mixture of EDTA and organic acids. The increase was associated with the effective removal of Cu, Ni, and Zn, mainly from F1 fraction, and increasing the share of the most stable fractions, which were removed less efficiently.
Ecological risk assessment of metals. In this study, calculated values of E r , Z and E r , m for individual metals, and the values of RI Z and RI m for overall risk assessment are shown in Table 3. Based on the values of the indices calculated for contaminated soil and soil washed under different hydrodynamic conditions with conventional and next-generation WAs, differing in the efficiency of soil remediation, it turned out that neither of these two indices is universal. The most visible discrepancy of these indices for remediated soil was observed for Cu. Despite a 13-15 fold decrease in the total Cu concentration in soil after washing with DOM and Na 2 EDTA, and the decrease in E r , Z from 3937.3 to 300.3 and 264.6, respectively, the potential ecological risk was still very high (according to Zhu et al. 41 , E r , Z ≥ 120 means very high potential ecological risk). Similar discrepancy was demonstrated for Cu removed under dynamic soil washing. For E r , m , its discrepancy was noted for Pb in contaminated soil and in soil after washing. In both soils, Pb has shown the same potential ecological risk. This means that both E r , Z and E r , m cannot be considered as universal for ecological risk assessment in soil contaminated with metals and soil remediated in batch and dynamic soil washing with SS_WAs and Na 2 EDTA under specific operational conditions.

Conclusions
Considering legislative purposes of soil remediation, in this study, the use of current metal concentration in relation to permissible levels in soil instead of geochemical background/pre-industrial level was proposed for calculation the indices of soil pollution after remediation. In addition, own classification scale for soil pollution indices and metal stability in soil was proposed. The mC f and mC deg were useful to identify soil pollution with metals. The mC f together with the IR characterize individual metals in terms of their pollution and stability degree in soil. The indices clearly distinguished the environmental quality of soil after remediation under different hydrodynamic washing conditions with Na 2 EDTA and SS_WAs. Thus, they may be an useful tool for assessment of soil remediation with different WAs. Their usefulness requires further verification in case of treatment of other types of soils contaminated with different levels of metals and/or metalloids.