Environ Monit Assess (2014) 186:8541–8553 DOI 10.1007/s10661-014-4023-z
Predicting bioavailability of metals from sludge-amended soils Debasis Golui & S. P. Datta & R. K. Rattan & B. S. Dwivedi & M. C. Meena
Received: 15 March 2014 / Accepted: 21 August 2014 / Published online: 3 September 2014 # Springer International Publishing Switzerland 2014
Abstract We attempted to develop a protocol for fixing the maximum permissible limit of sludge in agricultural lands based on transfer of metals from sludge-amended soils to human food chain. For this purpose, spinach was grown as a test crop on acid and alkaline soils with graded doses of sludge (0, 1.12, 2.24, 4.48, 8.96, 17.9, 35.8, 71.6, 142 and 285 g kg−1 of soil) in a pot experiment. Biomass yield of spinach was increased due to sludge application in both acid and alkaline soils. Among the chemical extractants, EDTA extracted the highest amount of metals from sludge-amended soil followed by diethylenetriaminepentaacetic acid (DTPA) and CaCl2. Elevated levels of Zn, Cu, Fe, Mn, Ni, Cd and Pb in spinach were observed due to sludge application over control. Application of sludge was more effective in increasing metal content in spinach grown on acid soil than alkaline soil. Solubility-free ion activity model as a function of pH, organic carbon and extractable metal was far more effective in predicting metal uptake by spinach grown on sludge-amended soils as compared to that of chemical extractants. Risk in terms of hazard quotient (HQ) for intake of metals through consumption of spinach by humans grown on sludge-treated soils was computed for different metals separately. In a 90-day pot experiment, safe rates of sludge application were worked out as 4.48 and 71.6 g kg−1 for acid and alkaline soils, respectively.
D. Golui : S. P. Datta (*) : R. K. Rattan : B. S. Dwivedi : M. C. Meena Division of Soil Science and Agricultural Chemistry, Indian Agricultural Research Institute, New Delhi 110012, India e-mail: [email protected]
Keywords Sludge . Agricultural lands . Permissible limit . Solubility-free ion activity model . Acid and alkaline soils
Introduction About 15,644 million litres per day (MLD) of sewage water has been generated from 35 metropolitan cities (more than 10 Lac populations) in India (CPCB, 2013). Land application of sewage sludge is becoming more popular due to the possibility of recycling valuable plant nutrients like N, P, K, etc. (Martinez et al. 2002; Samaras et al. 2008; Roy et al. 2013). Besides, sludge has a large amount of organic matter that can improve soil physical and chemical properties. Application of sludge has also been capable of changing soil pH, which opens up the possibility of its use in reclamation of acid and sodic soils (Samaras et al. 2008). Positive response of various crops, such as lentil (Yamur et al. 2005), wheat (Khan et al. 2007), maize (Zoubi et al. 2008) and spinach (Ngole 2010), to sludge application has widely been reported. Long-term use of sludge may lead to accumulation of heavy metals in agricultural soils and plants (Rattan et al. 2002; Sigua et al. 2005; Nabulo et al. 2011). Although some of the heavy metals such as Zn, Cu, Fe, Mn and Ni act as micronutrients at lower concentrations, they become toxic at higher concentrations. There is a growing body of evidence that food grown on urban and peri-urban sites may exceed statutory or advisory limits whether measured as metal concentrations in
Environ Monit Assess (2014) 186:8541–8553
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produce or expressed as projected daily intakes (Adekunle et al. 2009; Zhuang et al. 2009; Singh et al. 2010; Nabulo et al. 2011). This underlines the need for precise assessment of bioavailability of metals in sludge-amended soils. Arable land to which sewage sludge is applied must be managed with metal concentrations below toxic levels. Several researchers attempted to assess the phyto-availability of metals in soils using chemical extractants such as strong chelating agents, mild neutral salts and dilute acids (Paulose et al. 2007; Ray et al. 2013). Such tests, however, tend to be metal, soil or crop species specific, which have even not been adequately evaluated for sludge-amended soils (Paulose et al. 2007). It is evident from the literature that prediction of metal uptake by plants can also be made using solubility-free ion activity model (Datta and Young 2005; Hough et al. 2005; Rang Zan et al. 2013). However, the applicability of such models has not been studied in soils receiving a large amount of sludge. Intake of food materials grown on metalcontaminated soils is an important path of metal toxicity to human beings. Usually, risk to human health for intake of metals through consumption of food crops grown on contaminated soils is expressed in terms of hazard quotient (HQ) (Datta and Young 2005; Rattan et al. 2005; Singh et al. 2010; Giri et al. 2012; Chang et al. 2014). It seems to be rational and feasible that the maximum permissible limit of sludge application can be fixed based on the values of HQ. Specific objectives of this investigation are to (i) assess the impact of sludge addition on extractable metal content in acid and alkaline soils, (ii) predict the metal uptake by Indian spinach (Beta vulgaris) grown on sludge-amended soils and (iii) assess the maximum permissible limit of sludge addition to soils in respect to transfer of metal to human food chain using spinach as a test crop.
Materials and methods Characterization of soil and sludge Two bulk surface (0–15 cm) soil samples were collected from Cooch Behar district, West Bengal, and experimental farm of Indian Agricultural Research Institute (IARI), New Delhi. Soil sample collected from Cooch Behar district belongs to Typic Fluvaquent located in the humid (precipitation >3,500 mm annually) tropical Tarai agro-climatic zone (26° 19′ N, 89° 23′ E; 43 m
above mean sea level). Soil of IARI farm belongs to Typic Haplustept in sub-tropical semi-arid agro-climatic zone (annual rainfall 651 mm) of the Upper Gangetic Plain (28° 30′ N, 77° 10′ E; 250 m above mean sea level). Soil samples were air dried, ground and sieved with a 2-mm nylon sieve. Soil samples were analysed for pH (soil/water, 1:2) and electrical conductivity, organic carbon and cation exchange capacity following standard procedures (Jackson 1973). Soil texture was determined by the hydrometer method (Bouyoucos 1962). Soil samples were digested using Aqua-regia (75 % concentration HCl and 25 % concentration HNO3) and analysed using flame atomic absorption spectrophotometer (FAAS). Soil samples were also extracted with diethylenetriaminepentaacetic acid (DTPA) for available metals (Lindsay and Norvell 1978). Sludge samples were collected from Okhla sewage treatment plant, New Delhi. After processing, it was digested in diacid mixture (HNO3/HClO4, 9:3) (Jackson 1973) and metal content in the extract was determined using FAAS or graphite furnace atomic absorption spectrometry (GFAAS). Initial characteristics of experimental soils and sludge were given in Table 1. Pot experiment A pot experiment was conducted to study the effect of sludge application on metal uptake by spinach grown on acid and alkaline soils. For this purpose, plastic pots were filled with 4 kg of soil. The sludge was added at the rates of 0, 1.12, 2.24, 4.48, 8.96, 17.9, 35.8, 71.6, 142 and 285 g kg−1 of soil, which are equivalent to field application of 0, 2.5, 5, 10, 20, 40, 80, 160, 320, 640 t ha−1. All 20 treatment combinations (2 soils × 10 levels of sludge) were replicated thrice and experiments were laid out in a completely randomized design. The sludge-amended soil was then irrigated with tap water to maintain field capacity. After 1 month, a uniform basal dose of 11.2 mg N, 11.2 mg P2O5 and 22.3 mg K2O kg−1 soil were added through urea, diammonium phosphate and muriate of potash, respectively. About 15 seeds of spinach were sown in each pot, and after 10 days of germination, a uniform population of 10 plants in each pot was maintained. Pots were irrigated daily to return the moisture close to field capacity. Plants were harvested at 65 days after sowing. After harvesting, fresh weight of the plant samples was recorded and plant samples were dried in a hot air oven at 60±5 °C for 72 h. Dried plant samples were ground and digested in a
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Table 1 Initial characteristic of experimental soils and sludge Parameter
Acid soil
Alkaline soil
Sludge
pH
4.52
8.44
6.71
EC (dS m−1)
0.81
0.29
3.32
Mechanical composition Clay (%)
22.8
12.3
Silt (%)
16.5
22.5
Sand (%)
62.7
63.2
Texture
Sandy clay loam 0.78
Sandy loam 0.57
43.3 –
Organic carbon (%)
Modelling solubility and plant uptake of metals
Cation exchange capacity [cmol(p+)kg−1] Available N (kg ha−1)
15.5
12.6
337
227
1.03*
Olsen P (kg ha−1)
19.5
26.8
0.45* 0.47*
Available K (kg ha−1)
185
371
E-Zn (mg kg−1)
2.01
1.52
–
E-Cu (mg kg−1)
4.21
2.29
–
E-Fe (mg kg−1)
52.2
4.80
–
E-Mn (mg kg )
30.7
9.60
–
E-Ni (μg kg−1)
371
220
–
E-Cd (μg kg−1)
18.1
10.5
–
E-Pb (mg kg−1)
1.56
0.92
–
−1
−1
and Norvell 1978), 0.05 M EDTA (Quevauviller 1998), 0.01 M CaCl2 (Houba et al. 2000) and metal concentrations in the extract were determined with FAAS or GFAAS. The pH of soil samples was determined in 1:2 (soil/water) suspensions with a glass electrode (Datta et al. 1997). Organic carbon content in soil was determined following the procedure of Walkley and Black (1934).
T-Zn (mg kg )
125
130
1,600
T-Cu (mg kg−1)
62.0
53.0
203
T-Fe (%)
3.08
2.97
1.20
T-Mn (mg kg−1)
750
660
214
T-Ni (mg kg−1)
7.17
8.21
40.0
T-Cd (mg kg−1)
0.41
0.37
5.38
T-Pb (mg kg−1)
13.5
11.2
64.5
*Expressed in percentage E DTPA-extractable metal, T total metal
diacid mixture of HNO3:HClO4 (9:4) (Jackson 1973) and analysed for Zn, Cu, Fe, Mn, Ni, Cd and Pb using FAAS or GFAAS. Standard metal solution of Merck KGaA, 64271 Darmstadt, Germany, was used to calibrate the AAS. Soil analysis After harvest of crop, soil was taken out from each of the pot and mixed thoroughly. Soil samples were dried, ground and sieved through a 2-mm nylon sieve. Soil samples were extracted with 0.005 M DTPA (Lindsay
Metal uptake by Indian spinach was predicted by integrated solubility-free ion activity model without actually measuring free ion activity in soil pore water. Metal solubility was predicted by following a simple pH-dependent Frundlich equation (Jopony and Young 1994; Datta and Young 2005; Rang Zan et al. 2013): p½M C þ k 1 þ k 2 pH p M 2þ ¼ nF
ð1Þ
where (M2+) is the free metal ion activity in soil pore water; MC is the labile pool of metal in soil assumed to be exclusively adsorbed on humus (mol kg−1 carbon); k1 and k2 are the empirical, metal-specific constants; and nF is the power term from the Freundlich equation. This model predicts the free ion activity of trace metal in soil pore water from labile soil metal content and pH with the simplifying assumption that the whole amount of metal is adsorbed on humus. In the present study, 0.005 M DTPA, 0.05 M EDTA and 0.01 M CaCl2 extractable metals were used as estimates of labile pool of metals. Metal uptake is often characterized by a soil to plant transfer factor (TF) (Datta and Young 2005; Hough et al. 2005). However, the free ion activity model suggests that uptake of metals may be controlled by metal ion activity in the soil pore water (Parker and Pedler 1997). Therefore, transfer factor was expressed as the quotient of metal concentration in the plant [MPlant] to metal ion activity in soil pore water (M2+) derived from Eq. 1. TF ¼ log
½M Plant M 2þ
TF ¼ log½M Plant −log M 2þ
8544
Environ Monit Assess (2014) 186:8541–8553
‐log½M Plant ¼ −log M 2þ −TF p½M Plant ¼ p M 2þ −TF
By substituting the value of p M 2þ in Eq. 1, we can write p½M Plant ¼
p½M C þ k 1 þ k 2 pH −TF nF
p½M Plant ¼
p½M c k 1 k 2 pH þ −TF þ nF nF nF
p½M Plant ¼ C þ β1 p½M C þ β2 pH
ð2Þ
where C ¼ nk 1F −TF; β1 ¼ n1F ; β2 ¼ nk 2F where C, β1 and β2 are the empirical metal- and plant-specific coefficients. Equation 2 was parameterized by non-linear error minimization using the “SOLVER” facilities in Microsoft Excel 2007. Risk assessment Risk to human health for dietary intake of metals through consumption of spinach grown on sludgetreated soils was computed in terms of hazard quotient (HQ) following US Environmental Protection Agency (USEPA) protocol (IRIS 2014). Hazard quotient is the ratio of the average daily dose (ADD; mg kg−1 day−1) of metals to their reference dose (RfD; mg kg−1 day−1). RfD is defined as the maximum tolerable daily intake of the specific metal that does not result in any deleterious health effects: HQ ¼
ADD RfD
The values of RfD used for Zn, Mn, Ni and Cd were 0.3, 0.14, 0.02 and 0.001 mg kg−1 day−1, respectively (IRIS 2014). For Cu, provisional maximum tolerance daily intake (PMTDI) of 0.5 mg kg−1 day−1 was used in place of RfD (WHO 1982; Alam et al. 2003). The RfD value for Fe was used as 0.3 mg kg−1 day−1, which is the EPA provisional reference dose. Reference dose for Pb was used as 0.00035 mg kg−1 day−1, which is the recommended value for UK risk assessment (Hough et al. 2005). Daily intake of green vegetable was
assumed to be 0.2 kg day−1 which is the recommended amount from a nutritional point of view. A factor of 0.082 was used to convert the fresh to dry weight of spinach. Average body weight for an adult was assumed to be 70 kg. Thus, the HQ for an adult was calculated as HQ ¼
M Plant W F RfD 70
where MPlant is the metal content (mg kg−1) of Indian spinach, W is the daily intake of green vegetable and F is the factor of conversion of fresh to dry weight. Assessment of risk as computed here is not complete. Since metal accumulation to soil organisms, ground water and surface water are direct uptake by humans from soil and animals, some of the other risks have not been considered here. Moreover, intake of metals through food materials other than leafy green vegetables, drinking water and inhalation of dust was not considered here. Statistical analysis Analysis of variance method was followed to assess the effect of sludge on extractable metals, plant metal content and dry matter yield of spinach using the SPSS statistical package (IBM SPSS statistics). Simple correlation and regression analyses were carried out to evaluate the suitability of chemical extractants to predict phyto-availability of heavy metals.
Results and discussion pH, organic carbon and extractable metal There was a concomitant increase in pH with the increasing rates of sludge addition on acid soil (Table 2). However, a reverse trend was observed in the case of alkaline soil, where a substantial decrease in pH was observed with increase in sludge addition. Organic carbon content in both the soils was enhanced as a result of sludge application (Table 2). This is related to addition of substantial amount of organic carbon through sludge. EDTA-extractable Zn, Cu, Fe, Mn, Ni, Cd and Pb were increased by 28.6, 6.07, 2.79, 2.68, 4.37, 20.5 and 1.23 times, respectively, at the highest level of sludge addition (285 g kg−1 of soil) over control in acid soil (Table 3). In alkaline soil, EDTA-extractable Zn, Cu, Fe, Mn, Ni and Cd increased by 31.2, 5.05, 5.28, 3.38, 3.15 and 53 times in sludge-amended soils (285 g kg−1
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8545
Table 2 Effect of sludge addition on dry matter yield of Indian spinach and change in pH and organic carbon (mg kg−1) of acid and alkaline soils Soil
Acid
Alkaline
Rates of sludge addition (g kg−1)
Dry matter yield (g pot−1)
pH
Organic carbon (%)
0
5.98a
4.36a
0.76a
1.12
5.69a
4.52b
0.85b
2.23
6.29a
4.64bc
0.89bc
4.46
6.90a
4.72c
0.93c
8.93
9.71b
5.10d
1.02d
17.8
9.46b
5.70e
1.11e
35.7
8.95b
5.93f
1.26f
71.4
11.1c
6.23g
1.76g
142
12.3c
6.52h
1.99h
285
11.3c
6.71i
2.61i
0
4.09a
8.30h
0.61a
1.12
4.40ab
7.94g
0.62a
2.23
4.64ab
7.72f
0.66ab
4.46
5.66bc
7.55e
0.73b
8.93
6.57cd
7.42de
0.85c
17.8
7.45d
7.38d
0.99d
35.7
7.82d
7.34cd
1.16e
71.4
9.67e
7.24c
1.45f
142
16.7f
7.09b
1.80g
285
19.5g
6.81a
1.88h
Values followed by common letters are not significantly different at P≤0.05
of soil), respectively, over control. The mean EDTAextractable Zn, Cu, Fe, Mn, Ni, Cd and Pb was 56.2, 98.6, 278, 15.7, 83.8, 79.8 and 87.6 %, respectively, higher in acid soil as compared to that of alkaline soil. Application of sludge was more effective in enhancing the EDTA-extractable Zn, Cu, Fe, Mn, Ni, Cd and Pb in acid soil than that of alkaline soil. More or less similar trend of DTPA and CaCl2 extractable metals was obtained (Tables 4 and 5). In spite of the fact that acid soil had higher values of clay, organic carbon and cation exchange capacity as compared to alkaline soil, both EDTA and DTPA could extract higher amount of metals from acid soil than that from alkaline soil. This suggests that pH is the most important factor controlling the solubility and extractability of metals in soil. EDTA extracted the highest amount of metals, followed by DTPA and CaCl2. In general, chelating agents such as EDTA and DTPA
extracted much higher amounts of metal from soil as compared to weaker extractants like Ca-salts (e.g. Brennan et al. 2008). Neutral salt solution is able to extract weakly sorbed metal species, particularly those retained on soil surface by relatively weak electrostatic force and those that can be released through exchangeable process (Gleyzes et al. 2002). Recently, Ray et al. (2013) reported similar extractability of chelating agents and neutral salt solution for metals from sludgeamended soils. Higher extractability of EDTA than DTPA may be ascribed to higher concentration of EDTA (0.05 M) over DTPA (0.005 M). In addition, EDTA has a stronger chelating ability to extract metals from an organically bound pool (Gleyzes et al. 2002). Dry matter yield and metal content in spinach Dry matter yield of spinach increased significantly by 62.3 to 88.9 % due to application of sludge over control in acid soil, and corresponding values for alkaline soil ranged from 38.3 to 377 % (Table 2). At lower rates of sludge addition, dry matter yield of spinach was higher in acid soil as compared to that in alkaline soil. However, reverse trend was observed at higher rates of sludge addition. These may be ascribed to both inherent fertility status as well as differential solubility of metals in these two soils. Biomass yield was declined possibly due to metal toxicity at high rates of sludge addition in acid soil. Earlier reports also indicated substantial increase in biomass yield of spinach on similar soil due to application of sludge at the rate of 22.4 g kg−1 of soil (Roy et al. 2013). However, they did not fix any permissible limit of sludge addition. Significant increase in Zn content in shoot of spinach was recorded at ≥2.23 g kg−1 of applied rates of sludge over control in acid soil (Table 6), whereas a significant increase in plant Zn content was observed at ≥8.93 g kg−1 of applied sludge over control in alkaline soil. In the case of acid soil, at higher rates of sludge application (≥71.4 g kg−1), there was a significant decrease in plant Zn content as compared to preceding lower doses of sludge application. On the contrary, plant Zn content was progressively increased with increase in similar rates of added sludge in the case of alkaline soil. Significant increase in Fe content in shoot of spinach grown on acid soil was observed up to 17.8 g kg−1 of sludge addition over control. There was reduction in Fe content in spinach grown on acid soil by 8.0, 11.3, 12.8 and 26.7 % over control due to application of sludge at the rate of 35.8, 71.6, 142 and
Environ Monit Assess (2014) 186:8541–8553
8546 Table 3 Effect of sludge addition on EDTA-extractable metals (mg kg−1) in acid and alkaline soils
Soil
Rates of sludge addition (g kg−1)
Zn
Acid
0
5.96a
1.12 2.23
Alkaline
Values followed by common letters are not significantly different at P≤0.05
EDTA-extractable metals (mg kg−1)
Treatment
Cu
Fe
Mn
Ni
Cd
Pb
6.36a
487a
86.1a
0.67a
0.04a
3.84a
6.13a
6.71a
524ab
91.8b
0.94b
0.04a
3.92a
10.3ab
8.18b
559b
99.0cd
1.33c
0.06ab
4.30b
4.46
11.4b
8.64bc
651c
102de
1.47d
0.07b
4.81de
8.93
12.3b
8.95c
781d
106e
1.65e
0.08b
4.97ef
17.8
18.5c
11.1d
821de
113f
1.73f
0.11c
5.08f
35.7
34.7d
13.4e
882ef
123g
1.90g
0.15d
6.51g
71.4
55.9e
18.9f
935fg
135h
2.09h
0.23e
4.17bg
142
95.5f
26.7g
983g
160i
2.22i
0.41f
4.54c
38.6h
285
171g
1,360h
231j
2.93j
0.82g
4.74cd
0
3.33a
3.50a
84.9a
54.4a
0.61a
0.01a
3.16f
1.12
5.04a
3.93ab
108ab
65.9b
0.65ab
0.02ab
3.20f
2.23
6.23ab
4.48bc
126abc
73.5c
0.68b
0.03abc
2.94e
4.46
7.87ab
5.00cd
161bc
82.9d
0.75c
0.04bcd
2.72cd
8.93
10.9b
5.30de
165bc
97.2e
0.81cd
0.05cde
2.76de
17.8
16.8c
5.75e
177c
115f
0.85de
0.06de
1.54a
35.7
25.1d
6.74f
192c
125g
0.89ef
0.07e
1.62a
71.4
36.6e
8.26g
284d
134h
0.93f
0.10f
1.85b
142
54.0f
13.2h
360e
147i
1.08g
0.20g
2.52c
285
104g
17.7i
448f
184j
1.92h
0.53h
2.69cd
285 g kg−1, respectively. Significant increases in Fe content with increased rate of sludge addition from 4.46 to 285 g kg−1 were recorded in alkaline soil. In the case of acid soil, at higher rates of sludge application (≥8.93 g kg−1), there was significant decrease in concentration of plant Ni as compared to preceding lower dose of sludge application. Plant Ni content was progressively increased with increase in similar rates of added sludge in the case of alkaline soil. The application of sludge could not change the Cu content in shoot of spinach significantly grown on alkaline soil with respect to control. On the contrary, a concomitant increase in Cu content in shoot of spinach was recorded in acid soil when sludge was applied at the rate of ≥8.93 g kg−1. There was a concomitant increase in Mn content in shoot of spinach with the increasing rates of sludge addition on both acid and alkaline soils. A significant increase in Cd content was recorded with increasing rates of sludge addition in both acid and alkaline soils. No systematic influence of rates of sludge
addition on plant Pb content in shoot of spinach was observed in both the soils. In general, increase in plant metal content with sludge application has been reported in a number of studies (Antonious et al. 2011; Ray et al. 2013; Roy et al. 2013). In the case of acid soil, plant Zn, Cu, Fe and Ni decreased at higher rates of sludge application. This can be explained based on the fact that values of soil pH were increased progressively with increasing rates of sludge addition. Increase in pH might have decreased the solubility of these metals in soil which in turn, resulted in a decrease in plant metal content. But it is difficult to explain why this phenomenon was not observed in the case of Mn, Cd and Pb, also, why such declining solubility of Zn, Cu, Fe and Ni was not reflected in extractable metal content. While implementing free ion activity model, Hough et al. (2005) reported that soil to solution transfer factors of metal were highly pH dependent, which may suggest a significant competition between trace metals and
Environ Monit Assess (2014) 186:8541–8553 Table 4 Effect of sludge addition on DTPA-extractable metals (mg kg−1) in acid and alkaline soils
DTPA-extractable metals (mg kg−1)
Treatment Soil
Rates of sludge addition (g kg−1)
Zn
Cu
Fe
Mn
Ni
Cd
Pb
Acid
0
1.96a
4.37a
50.9a
25.8a
0.35ab
0.02a
1.76c
1.12
2.03a
5.01b
69.9b
26.0a
0.37b
0.02a
2.64f
2.23
2.83a
5.18b
83.1c
29.8a
0.37b
0.03b
3.22h
4.46
3.29a
5.78c
98.9d
39.5b
0.34a
0.03b
1.42b
8.93
5.24b
6.33d
109e
45.8c
0.36ab
0.04c
2.87g
17.8
5.71bc
7.13e
120f
48.1c
0.40c
0.05d
1.77c
35.7
7.13c
7.59e
138g
58.8d
0.40c
0.06e
1.86d
71.4
11.9d
8.55f
164h
64.2e
0.56d
0.07f
2.10e
142
24.0e
11.0g
188i
70.4f
0.54d
0.08g
1.17a
285
43.4f
17.1h
238j
101g
0.88e
0.12h
1.36b
0
1.41a
2.09a
4.98a
9.39a
0.35c
0.01a
0.70ab
1.12
1.67ab
2.26a
5.72ab
10.1a
0.23a
0.01a
0.65a
2.23
2.75abc
2.74b
6.22ab
11.4ab
0.24a
0.02b
0.73bc
4.46
3.01bcd
3.18bc
9.59ab
13.0ab
0.29b
0.02b
1.48g
8.93
3.88cd
3.63c
12.0abc
15.1b
0.29b
0.03c
1.47g
17.8
4.31ed
4.26d
15.1bcd
20.7c
0.30b
0.03c
0.87ef
35.7
5.75e
4.91e
20.4cd
25.5cd
0.35c
0.04d
0.84def
71.4
10.2f
6.46f
24.1de
29.3d
0.43d
0.06e
0.79cd
142
20.7g
9.16g
31.9e
46.7e
0.49e
0.08f
0.80cde
285
36.1h
14.4h
46.1f
65.6f
0.70f
0.10g
0.91f
Alkaline
Values followed by common letters are not significantly different at P≤0.05
8547
protons for sorption sites on roots. Based on this analogy, one can envisage that metal uptake should be increased with increase in pH. On the other hand, solubility of metal decreases with increase in pH. Prediction of metal content in shoot of spinach Efficacy of extractants, viz. EDTA, DTPA and CaCl2 to predict metal content in plant was evaluated by simple correlation analysis (Table 7). There were clear differences between metals in the extract to which the concentrations of metals in shoots reflected in soils. Results indicate that none of the extractants could extract proportionate amounts of Zn and Fe from soil in relation to their content in plant. However, EDTA-extractable Cu, Mn, Ni, Cd and Pb showed a significant positive relationship with plant Cu, Mn, Ni, Cd and Pb content. In the case of DTPA, extractable Cu, Mn and Cd contributed significantly and positively towards plant content of these metals. More or less similar relationships
between soil and plant content of these metals were obtained in the case of CaCl2. Metal- and crop-specific model parameters (C, β1 and β2) of integrated solubility-free ion activity model along with prediction coefficient (R2) are presented in (Table 8). Results indicate that as high as 62, 68, 50, 44, 50 and 77 % variation in Zn, Cu, Fe, Mn, Ni and Cd content in spinach could be explained by pH and MC (EDTA-extractable metals assumed to be adsorbed on Walkley-Black organic carbon), respectively. The model produced values of prediction coefficient as 0.54 for Zn, 0.38 for Cu, 0.51 for Fe, 0.68 for Mn, 0.48 for Ni, 0.68 for Cd and 0.25 for Pb when DTPA-extractable metals were used as an estimate of labile pool. As high as 60, 90, 57, 49, 73 and 50 % variation in Zn, Cu, Fe, Ni, Cd and Pb content in plant, respectively, could be explained by this model based on CaCl2 extractable metals. In the case of Pb and Cu, the model based on CaCl2 extractable metal had clear-cut edge in predicting plant metal content over model based on either EDTA or
8548 Table 5 Effect of sludge addition on CaCl2-extractable metals (mg kg−1) in acid and alkaline soils
Environ Monit Assess (2014) 186:8541–8553
Soil
Rates of sludge addition (g kg−1)
Zn
Cu
Fe
Mn
Ni
Cd
Pb
Acid
0
0.31ab
0.32a
0.79a
0.49a
0.03b
0.002a
0.23a
1.12
0.59c
0.39b
1.00b
0.52ab
0.03b
0.003b
0.26abc
2.23
0.27a
0.47c
1.32c
0.59bc
0.03b
0.004c
0.29c
4.46
0.30a
0.54d
1.35c
0.62cd
0.02a
0.006d
0.28bc
8.93
0.39b
0.72e
1.61d
0.59bc
0.02a
0.006d
0.24ab
17.8
0.24a
0.83f
1.75e
0.71e
0.02a
0.007e
0.25abc
35.7
0.30a
1.03g
1.86f
0.71e
0.03b
0.009f
0.23a
71.4
0.28a
1.25h
2.10g
0.69de
0.03b
0.010g
0.24ab
142
0.32ab
1.65i
2.21h
0.74e
0.03b
0.011h
0.24ab
Alkaline
Values followed by common letters are not significantly different at P≤0.05
CaCl2-extractable metals (mg kg−1)
Treatment
285
0.26a
1.85j
2.45i
0.73e
0.03b
0.068i
0.28bc
0
0.36c
0.12a
0.50a
0.17a
0.02b
0.001a
0.18a
1.12
0.28abc
0.16ab
0.51a
0.13a
0.01a
0.001a
0.22abc
2.23
0.30abc
0.19b
0.52a
0.17a
0.02b
0.002b
0.21ab
4.46
0.22a
0.24c
0.53ab
0.13a
0.02b
0.003c
0.24bc
8.93
0.32bc
0.28c
0.52a
0.14a
0.02b
0.003c
0.24bc
17.8
0.34c
0.34d
0.54ab
0.10a
0.02b
0.004d
0.26c
35.7
0.25ab
0.40e
0.52a
0.15a
0.02b
0.005e
0.22abc
71.4
0.23a
0.44e
0.57ab
0.27b
0.02b
0.005e
0.22abc
142
0.33bc
0.53f
0.63b
0.35b
0.02b
0.007f
0.26c
285
0.32bc
0.62g
0.75c
0.55c
0.03c
0.009g
0.31d
DTPA. By and large, solubility-free ion activity model was more effective in predicting metal content in plant as compared to regression equation based on extractable metal only. Earlier study also indicated that pH and organic carbon are among the important soil properties which control the solubility of metals in contaminated soil (Rang Zan et al. 2013). Rang Zan et al. (2013) also reported that the EDTA-extractable metals were more useful as an input of solubility model as compared to DTPA-extractable and CaCl2 extractable metals. DTPA (0.005 M) is the most commonly used soil test for assessing the bioavailability of metals in both normal and contaminated soils (Datta et al. 2000; Rattan et al. 2005; Brennan et al. 2008; Ray et al. 2013; Roy et al. 2013). European Commission calibrated and standardized much higher concentration of chelating agents (0.05 M EDTA as compared to 0.005 M DTPA) for assessing bioavailability of metals in contaminated soils (Quevauviller 1998). In a few studies, CaCl2 was also successfully used as an extractant for available metal in
soil (Disla et al. 2010). In the present study, poor relationship of extractable metals with their content in plant can be explained based on the fact that effect of change in soil pH due to sludge addition was not reflected on extractable metals, particularly in acid soil. There was a declining trend in uptake of metals (e.g. Zn, Fe, Ni) by spinach at higher rates of sludge application in acid soil. This mismatch between extractable metals in soil and plant metal content resulted into poor relationships. On the other hand, solubility-free ion activity model could successfully predict metal uptake by spinach because this model has provision of accounting the effect of pH and organic carbon on metal solubility. Hazard quotient and permissible limit of sludge addition A substantial amount of Zn, Cu, Fe, Mn, Ni, Cd and Pb was added to soil through sludge, where spinach was grown as a test crop. Intake of these metals at toxic level
Environ Monit Assess (2014) 186:8541–8553 Table 6 Effect of sludge addition on metal content (mg kg−1) in Indian spinach grown on acid and alkaline soils
8549 Total metal content (mg kg−1)
Treatment Soil
Rates of sludge addition (g kg−1)
Zn
Cu
Fe
Mn
Ni
Cd
Pb
Acid
0
167b
23.3ab
512cd
48.0a
0.80a
0.54a
0.08
1.12
174b
21.0a
548de
49.4a
0.95b
0.56ab
0.07
2.23
210c
22.8ab
590e
61.7a
1.02b
0.58ab
0.12
4.46
236d
26.5bc
652f
84.8a
1.89e
0.60bc
0.12
Alkaline
Values followed by common letters are not significantly different at P≤0.05
8.93
265e
32.6d
716g
131b
2.96h
0.64c
0.15
17.8
289f
40.2e
577e
185c
2.53g
0.71d
0.14
35.7
300f
33.7d
471bc
384d
2.11f
0.74d
0.15
71.4
272e
29.9cd
454bc
498e
1.91e
0.80e
0.12
142
242d
31.2d
446b
649f
1.66d
0.82e
0.18
285
144a
33.3d
375a
705g
1.36c
0.97f
0.13
0
65.4a
15.2a
261a
43.0a
0.59a
0.27a
0.06
1.12
65.7a
16.7a
296ab
60.6ab
0.60a
0.32b
0.07
2.23
72.2ab
15.8a
317ab
85.7b
0.63a
0.35b
0.09
4.46
74.9ab
17.0a
341b
125b
0.66a
0.42c
0.07
8.93
80.6b
16.5a
343b
221c
0.78b
0.45c
0.08
17.8
94.0c
18.0a
450c
241cd
0.81b
0.52d
0.08
35.7
105cd
17.3a
497cd
271d
0.84bc
0.52d
0.08
71.4
112de
16.5a
531de
278d
0.90cd
0.54de
0.08
142
122ef
16.6a
545de
345e
0.98d
0.58e
0.10
285
127f
16.7a
588e
395f
1.38e
0.58e
0.09
by human beings results in several physiological and metabolic disorders (Rattan et al. 2009). Hazard quotient for intake of these metals through consumption of this green vegetable was calculated using USEPA protocol (IRIS 2014). Table 7 Simple correlation coefficient of determination (r2) of extractable metal in soils with plant metal content Extractable metal in soil
Extracted by EDTA
DTPA
CaCl2
Zn
0.01
0.002
0.003
Cu
0.30*
0.20*
0.55**
Fe
0.12
0.06
0.07
Mn
0.78**
0.71**
0.21*
Ni
0.43**
0.03
0.06
Cd
0.50**
0.62**
0.45**
Pb
0.55**
0.14
0.07
*Values of r2 are significant at 5 % probability level; **values of r2 are significant at 1 % probability level
Results indicate that HQ ranged from 0.05 to 0.23 for Zn, 0.01 to 0.02 for Cu, 0.20 to 0.56 for Fe, 0.07 to 1.18 for Mn, 0.01 to 0.03 for Ni, 0.06 to 0.23 for Cd and 0.04 to 0.12 for Pb across the various treatments of sludge (Table 9). Values of HQ equal to or more than 1 indicates that consumption of food materials may be hazardous to humans due to intake of a particular metal. In the present study, values of HQ exceeded 1 in the case of Mn only and Fe also showed relatively higher values as compared to other metals. Implication of such higher value (HQ=1) is aggravated by the fact that green vegetables constitute only a small portion of diet. Food materials other than leafy green vegetables, drinking water and inhalation of dust are likely to be contributed significantly towards total intake of metals by human beings. Based on this analogy, the safe limit of HQ can be considered as 0.5 in risk assessment of contaminated soils. Critical scrutiny of data on HQ indicates that values of HQ for Fe exceeded 0.5 when sludge was applied at 8.93 g kg−1 in acid soil, whereas application of sludge at 142 g kg−1 produced a value of HQ more than 0.5 for Mn in alkaline soil. Hence, the safe limits of
8550
Environ Monit Assess (2014) 186:8541–8553
Table 8 Model parameters for predicting uptake of Zn, Cu, Fe, Mn, Ni, Cd and Pb by Indian spinach as a function of pH, Walkley-Black organic carbon and extractable metals Extractant EDTA
DTPA R2
Model parameters C
β1
Zn
−3.63
0.15
Cu
−3.00
Fe
−3.25
Mn
CaCl2 R2
Model parameters
β2
C
β1
R2
Model parameters
β2
β1
C
0.15
0.62
−3.81
0.15
0.30
0.54
−1.69
0.15
0.02
0.78
0.68
−2.90
0.03
0.64
0.38
−3.55
0.09
−0.12
0.50
−3.11
0.06
0.02
0.51
−2.53
0.98
−0.04
−3.96
0.44
−3.61
−0.38
2.96
0.68
Ni
−2.68
0.05
0.83
0.50
3.48
0.10
−1.31
Cd
−1.57
0.04
0.38
0.77
−3.34
0.04
Pb
0.91
0.05
−0.09
0.14
1.21
0.07
β2 −0.42
0.60
−0.002
0.70
0.90
0.10
−0.28
0.57
−0.66
0.01
−0.52
0.01
0.48
2.87
0.12
−0.84
0.49
0.77
0.63
−2.26
0.03
0.44
0.73
−0.21
0.25
2.53
0.05
−0.47
0.50
The values of R2 >0.20 are significant at 5 % probability level
Table 9 Hazard quotient (HQ) for intake of metals through consumption (human) of spinach grown on sludge-treated soils
Treatment
Hazard quotient (HQ)
Soil
Rates of sludge addition (g kg−1)
Zn
Cu
Fe
Mn
Ni
Cd
Pb
Acid
0
013
0.0109
0.40
0.08
0.0094
0.1275
0.05
1.12
0.14
0.0098
0.43
0.08
0.0111
0.1310
0.05
2.23
0.16
0.0107
0.46
0.10
0.0119
0.1359
0.08
4.46
0.18
0.0124
0.50
0.14
0.0222
0.1396
0.08
8.93
0.21
0.0153
0.56
0.22
0.0346
0.1492
0.10
17.8
0.23
0.0188
0.45
0.31
0.0297
0.1670
0.09
35.7
0.23
0.0158
0.37
0.64
0.0247
0.1736
0.10
71.4
0.21
0.0140
0.35
0.83
0.0224
0.1867
0.08
142
0.19
0.0146
0.35
1.09
0.0194
0.1909
0.12
285
0.11
0.0156
0.29
1.18
0.0159
0.2266
0.09
Alkaline
0
0.05
0.0071
0.20
0.07
0.0070
0.0623
0.04
1.12
0.05
0.0078
0.23
0.10
0.0070
0.0738
0.05
2.23
0.06
0.0074
0.25
0.14
0.0074
0.0813
0.06
4.46
0.06
0.0080
0.27
0.21
0.0077
0.0977
0.05
8.93
0.06
0.0077
0.27
0.37
0.0091
0.1052
0.05
17.8
0.07
0.0084
0.35
0.40
0.0095
0.1207
0.05
35.7
0.08
0.0081
0.39
0.45
0.0098
0.1225
0.05
71.4
0.09
0.0077
0.41
0.47
0.0106
0.1265
0.05
142
0.10
0.0078
0.43
0.58
0.0114
0.1349
0.07
285
0.10
0.0078
0.46
0.66
0.0162
0.1359
0.06
Minimum
0.05
0.01
0.20
0.07
0.01
0.06
0.04
Maximum
0.23
0.02
0.56
1.18
0.03
0.23
0.12
Environ Monit Assess (2014) 186:8541–8553
sludge addition, as emerged in this study, are 4.48 and 71.6 g kg−1 for acid and alkaline soils, respectively. However, further monitoring of metal uptake by crop is needed as the 90-day period may not be sufficient for the release of the entire amount of metals from sludge. There are a few guidelines for judging the suitability of sludge for application to agricultural lands based on metal contents in sludge (e.g. Harrison et al. 1999; Water Security Agency 2004). Recently, Passuello et al. (2012) attempted to develop a land classification tool to determine the suitability of different agricultural areas to be amended with sewage sludge. Several researchers also attempted to fix permissible limit of sludge based on different criteria (Oleszczuk 2006; Domene et al. 2008; Carbonell et al. 2009; Jin et al. 2011; Roig et al. 2012). For example, Oleszczuk (2006) recommended the rate of sludge application as ≤75 Mg ha−1 year−1, considering the degradation of polycyclic aromatic hydrocarbons present in sludge. Jin et al. (2011) worked out the permissible limit of sludge as 22 Mg ha−1 year−1 in respect to water pollution by nitrate from sludgeamended soil. Roig et al. (2012) suggested a maximum dose for application of sludge as 40 Mg ha−1 year−1 for calcareous soil, beyond which soil properties do not improve, and may even worsen. In the present study, the permissible rate of sludge was fixed based on health hazard associated with human beings for intake of metal through consumption of leafy vegetables grown on sludge-amended soils. While doing so, important soil properties like pH and organic carbon were also taken into account, in addition to extractable metals in soil. Since solubility-free ion activity model could predict the metal uptake by spinach to a reasonably good extent, as presented in the previous section, similar agreement between actual and modelled HQ was also obtained (data not shown). Since HQ is a derived parameter based on plant metal content, solubility-free ion activity model is equally effective in predicting HQ based on soil pH, organic carbon and EDTA-extractable metals. This implies that this model, after proper calibration, can be used as a tool to fix maximum permissible limit of sludge addition to agricultural lands.
Conclusions Safe rates of sludge application could be worked out as 4.48 and 71.6 g kg−1 for acid and alkaline soils, respectively, in relation to risk associated with human health
8551
for intake of metals through consumption of spinach grown on sludge-amended soils. Since this experiment was conducted for 90 days, uptake of metals from sludge-amended soil to plant needs further monitoring to arrive at a concrete conclusion. Safe rates of sludge addition will be varied with metal content in sludge. Nevertheless, the protocol developed here will definitely be useful for establishing the permissible limit of sludge application to agricultural lands. Acknowledgments This study was made possible by the financial support provided by the Indian Council of Agricultural Research in the form of a Junior Research Fellowship to the first author during his M.Sc. programme.
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Environ Monit Assess (2014) 186:8541–8553 forage productivity and soil quality implications in South Florida, USA. Environmental Science and Pollution Research International, l12, 80–88. Singh, A., Sharma, R. K., Agrawal, M., & Marshall, F. M. (2010). Risk assessment of heavy metal toxicity through contaminated vegetables from waste water irrigated area of Varanasi, India. Journal of Tropical Ecology, 51, 375–387. Walkley, A., & Black, I. A. (1934). An examination of the Degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil Science, 37, 29–38. Water Security Agency. (2004). Land application of municipal sewage sludge guidelines: EPB 296. 3211 Albert Street Regina SK S4S 0B1, Canada. WHO. (1982). World Health Organization. Toxicological evaluation of certain food additives, Joint FAO/WHO expert
8553 committee on food additives.WHO Food Additive Series No. 683(Geneva World Health Organization). Yamur, M., Kaydan, D., & Arvas, O. (2005). Effects of sewage biosolid application on seed protein ratios, seed NP contents, some morphological and yield characters in lentil (Lens culinaris Medic.). Research Journal of Agriculture and Biological Sciences, 1, 308–314. Zhuang, P., McBride, M. B., Xia, H., Li, N., & Li, Z. (2009). Health risk from heavy metals via consumption of food crops in the vicinity of Dabaoshan mine, South China. Science of the Total Environment, 407, 1551–1561. Zoubi, M. M. A., Arslan, A., Abdelgawad, G., Pejon, N., Tabbaa, M., & Jouzdan, O. (2008). The effect of sewage sludge on productivity of a crop rotation of wheat, maize and vetch and heavy metals accumulation in soil and plant in Aleppo Governorate. American-Eurasian Journal of Agricultural & Environmental Sciences, 3, 618–625.
Predicting bioavailability of metals from sludge-amended soils Debasis Golui & S. P. Datta & R. K. Rattan & B. S. Dwivedi & M. C. Meena
Received: 15 March 2014 / Accepted: 21 August 2014 / Published online: 3 September 2014 # Springer International Publishing Switzerland 2014
Abstract We attempted to develop a protocol for fixing the maximum permissible limit of sludge in agricultural lands based on transfer of metals from sludge-amended soils to human food chain. For this purpose, spinach was grown as a test crop on acid and alkaline soils with graded doses of sludge (0, 1.12, 2.24, 4.48, 8.96, 17.9, 35.8, 71.6, 142 and 285 g kg−1 of soil) in a pot experiment. Biomass yield of spinach was increased due to sludge application in both acid and alkaline soils. Among the chemical extractants, EDTA extracted the highest amount of metals from sludge-amended soil followed by diethylenetriaminepentaacetic acid (DTPA) and CaCl2. Elevated levels of Zn, Cu, Fe, Mn, Ni, Cd and Pb in spinach were observed due to sludge application over control. Application of sludge was more effective in increasing metal content in spinach grown on acid soil than alkaline soil. Solubility-free ion activity model as a function of pH, organic carbon and extractable metal was far more effective in predicting metal uptake by spinach grown on sludge-amended soils as compared to that of chemical extractants. Risk in terms of hazard quotient (HQ) for intake of metals through consumption of spinach by humans grown on sludge-treated soils was computed for different metals separately. In a 90-day pot experiment, safe rates of sludge application were worked out as 4.48 and 71.6 g kg−1 for acid and alkaline soils, respectively.
D. Golui : S. P. Datta (*) : R. K. Rattan : B. S. Dwivedi : M. C. Meena Division of Soil Science and Agricultural Chemistry, Indian Agricultural Research Institute, New Delhi 110012, India e-mail: [email protected]
Keywords Sludge . Agricultural lands . Permissible limit . Solubility-free ion activity model . Acid and alkaline soils
Introduction About 15,644 million litres per day (MLD) of sewage water has been generated from 35 metropolitan cities (more than 10 Lac populations) in India (CPCB, 2013). Land application of sewage sludge is becoming more popular due to the possibility of recycling valuable plant nutrients like N, P, K, etc. (Martinez et al. 2002; Samaras et al. 2008; Roy et al. 2013). Besides, sludge has a large amount of organic matter that can improve soil physical and chemical properties. Application of sludge has also been capable of changing soil pH, which opens up the possibility of its use in reclamation of acid and sodic soils (Samaras et al. 2008). Positive response of various crops, such as lentil (Yamur et al. 2005), wheat (Khan et al. 2007), maize (Zoubi et al. 2008) and spinach (Ngole 2010), to sludge application has widely been reported. Long-term use of sludge may lead to accumulation of heavy metals in agricultural soils and plants (Rattan et al. 2002; Sigua et al. 2005; Nabulo et al. 2011). Although some of the heavy metals such as Zn, Cu, Fe, Mn and Ni act as micronutrients at lower concentrations, they become toxic at higher concentrations. There is a growing body of evidence that food grown on urban and peri-urban sites may exceed statutory or advisory limits whether measured as metal concentrations in
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produce or expressed as projected daily intakes (Adekunle et al. 2009; Zhuang et al. 2009; Singh et al. 2010; Nabulo et al. 2011). This underlines the need for precise assessment of bioavailability of metals in sludge-amended soils. Arable land to which sewage sludge is applied must be managed with metal concentrations below toxic levels. Several researchers attempted to assess the phyto-availability of metals in soils using chemical extractants such as strong chelating agents, mild neutral salts and dilute acids (Paulose et al. 2007; Ray et al. 2013). Such tests, however, tend to be metal, soil or crop species specific, which have even not been adequately evaluated for sludge-amended soils (Paulose et al. 2007). It is evident from the literature that prediction of metal uptake by plants can also be made using solubility-free ion activity model (Datta and Young 2005; Hough et al. 2005; Rang Zan et al. 2013). However, the applicability of such models has not been studied in soils receiving a large amount of sludge. Intake of food materials grown on metalcontaminated soils is an important path of metal toxicity to human beings. Usually, risk to human health for intake of metals through consumption of food crops grown on contaminated soils is expressed in terms of hazard quotient (HQ) (Datta and Young 2005; Rattan et al. 2005; Singh et al. 2010; Giri et al. 2012; Chang et al. 2014). It seems to be rational and feasible that the maximum permissible limit of sludge application can be fixed based on the values of HQ. Specific objectives of this investigation are to (i) assess the impact of sludge addition on extractable metal content in acid and alkaline soils, (ii) predict the metal uptake by Indian spinach (Beta vulgaris) grown on sludge-amended soils and (iii) assess the maximum permissible limit of sludge addition to soils in respect to transfer of metal to human food chain using spinach as a test crop.
Materials and methods Characterization of soil and sludge Two bulk surface (0–15 cm) soil samples were collected from Cooch Behar district, West Bengal, and experimental farm of Indian Agricultural Research Institute (IARI), New Delhi. Soil sample collected from Cooch Behar district belongs to Typic Fluvaquent located in the humid (precipitation >3,500 mm annually) tropical Tarai agro-climatic zone (26° 19′ N, 89° 23′ E; 43 m
above mean sea level). Soil of IARI farm belongs to Typic Haplustept in sub-tropical semi-arid agro-climatic zone (annual rainfall 651 mm) of the Upper Gangetic Plain (28° 30′ N, 77° 10′ E; 250 m above mean sea level). Soil samples were air dried, ground and sieved with a 2-mm nylon sieve. Soil samples were analysed for pH (soil/water, 1:2) and electrical conductivity, organic carbon and cation exchange capacity following standard procedures (Jackson 1973). Soil texture was determined by the hydrometer method (Bouyoucos 1962). Soil samples were digested using Aqua-regia (75 % concentration HCl and 25 % concentration HNO3) and analysed using flame atomic absorption spectrophotometer (FAAS). Soil samples were also extracted with diethylenetriaminepentaacetic acid (DTPA) for available metals (Lindsay and Norvell 1978). Sludge samples were collected from Okhla sewage treatment plant, New Delhi. After processing, it was digested in diacid mixture (HNO3/HClO4, 9:3) (Jackson 1973) and metal content in the extract was determined using FAAS or graphite furnace atomic absorption spectrometry (GFAAS). Initial characteristics of experimental soils and sludge were given in Table 1. Pot experiment A pot experiment was conducted to study the effect of sludge application on metal uptake by spinach grown on acid and alkaline soils. For this purpose, plastic pots were filled with 4 kg of soil. The sludge was added at the rates of 0, 1.12, 2.24, 4.48, 8.96, 17.9, 35.8, 71.6, 142 and 285 g kg−1 of soil, which are equivalent to field application of 0, 2.5, 5, 10, 20, 40, 80, 160, 320, 640 t ha−1. All 20 treatment combinations (2 soils × 10 levels of sludge) were replicated thrice and experiments were laid out in a completely randomized design. The sludge-amended soil was then irrigated with tap water to maintain field capacity. After 1 month, a uniform basal dose of 11.2 mg N, 11.2 mg P2O5 and 22.3 mg K2O kg−1 soil were added through urea, diammonium phosphate and muriate of potash, respectively. About 15 seeds of spinach were sown in each pot, and after 10 days of germination, a uniform population of 10 plants in each pot was maintained. Pots were irrigated daily to return the moisture close to field capacity. Plants were harvested at 65 days after sowing. After harvesting, fresh weight of the plant samples was recorded and plant samples were dried in a hot air oven at 60±5 °C for 72 h. Dried plant samples were ground and digested in a
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Table 1 Initial characteristic of experimental soils and sludge Parameter
Acid soil
Alkaline soil
Sludge
pH
4.52
8.44
6.71
EC (dS m−1)
0.81
0.29
3.32
Mechanical composition Clay (%)
22.8
12.3
Silt (%)
16.5
22.5
Sand (%)
62.7
63.2
Texture
Sandy clay loam 0.78
Sandy loam 0.57
43.3 –
Organic carbon (%)
Modelling solubility and plant uptake of metals
Cation exchange capacity [cmol(p+)kg−1] Available N (kg ha−1)
15.5
12.6
337
227
1.03*
Olsen P (kg ha−1)
19.5
26.8
0.45* 0.47*
Available K (kg ha−1)
185
371
E-Zn (mg kg−1)
2.01
1.52
–
E-Cu (mg kg−1)
4.21
2.29
–
E-Fe (mg kg−1)
52.2
4.80
–
E-Mn (mg kg )
30.7
9.60
–
E-Ni (μg kg−1)
371
220
–
E-Cd (μg kg−1)
18.1
10.5
–
E-Pb (mg kg−1)
1.56
0.92
–
−1
−1
and Norvell 1978), 0.05 M EDTA (Quevauviller 1998), 0.01 M CaCl2 (Houba et al. 2000) and metal concentrations in the extract were determined with FAAS or GFAAS. The pH of soil samples was determined in 1:2 (soil/water) suspensions with a glass electrode (Datta et al. 1997). Organic carbon content in soil was determined following the procedure of Walkley and Black (1934).
T-Zn (mg kg )
125
130
1,600
T-Cu (mg kg−1)
62.0
53.0
203
T-Fe (%)
3.08
2.97
1.20
T-Mn (mg kg−1)
750
660
214
T-Ni (mg kg−1)
7.17
8.21
40.0
T-Cd (mg kg−1)
0.41
0.37
5.38
T-Pb (mg kg−1)
13.5
11.2
64.5
*Expressed in percentage E DTPA-extractable metal, T total metal
diacid mixture of HNO3:HClO4 (9:4) (Jackson 1973) and analysed for Zn, Cu, Fe, Mn, Ni, Cd and Pb using FAAS or GFAAS. Standard metal solution of Merck KGaA, 64271 Darmstadt, Germany, was used to calibrate the AAS. Soil analysis After harvest of crop, soil was taken out from each of the pot and mixed thoroughly. Soil samples were dried, ground and sieved through a 2-mm nylon sieve. Soil samples were extracted with 0.005 M DTPA (Lindsay
Metal uptake by Indian spinach was predicted by integrated solubility-free ion activity model without actually measuring free ion activity in soil pore water. Metal solubility was predicted by following a simple pH-dependent Frundlich equation (Jopony and Young 1994; Datta and Young 2005; Rang Zan et al. 2013): p½M C þ k 1 þ k 2 pH p M 2þ ¼ nF
ð1Þ
where (M2+) is the free metal ion activity in soil pore water; MC is the labile pool of metal in soil assumed to be exclusively adsorbed on humus (mol kg−1 carbon); k1 and k2 are the empirical, metal-specific constants; and nF is the power term from the Freundlich equation. This model predicts the free ion activity of trace metal in soil pore water from labile soil metal content and pH with the simplifying assumption that the whole amount of metal is adsorbed on humus. In the present study, 0.005 M DTPA, 0.05 M EDTA and 0.01 M CaCl2 extractable metals were used as estimates of labile pool of metals. Metal uptake is often characterized by a soil to plant transfer factor (TF) (Datta and Young 2005; Hough et al. 2005). However, the free ion activity model suggests that uptake of metals may be controlled by metal ion activity in the soil pore water (Parker and Pedler 1997). Therefore, transfer factor was expressed as the quotient of metal concentration in the plant [MPlant] to metal ion activity in soil pore water (M2+) derived from Eq. 1. TF ¼ log
½M Plant M 2þ
TF ¼ log½M Plant −log M 2þ
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Environ Monit Assess (2014) 186:8541–8553
‐log½M Plant ¼ −log M 2þ −TF p½M Plant ¼ p M 2þ −TF
By substituting the value of p M 2þ in Eq. 1, we can write p½M Plant ¼
p½M C þ k 1 þ k 2 pH −TF nF
p½M Plant ¼
p½M c k 1 k 2 pH þ −TF þ nF nF nF
p½M Plant ¼ C þ β1 p½M C þ β2 pH
ð2Þ
where C ¼ nk 1F −TF; β1 ¼ n1F ; β2 ¼ nk 2F where C, β1 and β2 are the empirical metal- and plant-specific coefficients. Equation 2 was parameterized by non-linear error minimization using the “SOLVER” facilities in Microsoft Excel 2007. Risk assessment Risk to human health for dietary intake of metals through consumption of spinach grown on sludgetreated soils was computed in terms of hazard quotient (HQ) following US Environmental Protection Agency (USEPA) protocol (IRIS 2014). Hazard quotient is the ratio of the average daily dose (ADD; mg kg−1 day−1) of metals to their reference dose (RfD; mg kg−1 day−1). RfD is defined as the maximum tolerable daily intake of the specific metal that does not result in any deleterious health effects: HQ ¼
ADD RfD
The values of RfD used for Zn, Mn, Ni and Cd were 0.3, 0.14, 0.02 and 0.001 mg kg−1 day−1, respectively (IRIS 2014). For Cu, provisional maximum tolerance daily intake (PMTDI) of 0.5 mg kg−1 day−1 was used in place of RfD (WHO 1982; Alam et al. 2003). The RfD value for Fe was used as 0.3 mg kg−1 day−1, which is the EPA provisional reference dose. Reference dose for Pb was used as 0.00035 mg kg−1 day−1, which is the recommended value for UK risk assessment (Hough et al. 2005). Daily intake of green vegetable was
assumed to be 0.2 kg day−1 which is the recommended amount from a nutritional point of view. A factor of 0.082 was used to convert the fresh to dry weight of spinach. Average body weight for an adult was assumed to be 70 kg. Thus, the HQ for an adult was calculated as HQ ¼
M Plant W F RfD 70
where MPlant is the metal content (mg kg−1) of Indian spinach, W is the daily intake of green vegetable and F is the factor of conversion of fresh to dry weight. Assessment of risk as computed here is not complete. Since metal accumulation to soil organisms, ground water and surface water are direct uptake by humans from soil and animals, some of the other risks have not been considered here. Moreover, intake of metals through food materials other than leafy green vegetables, drinking water and inhalation of dust was not considered here. Statistical analysis Analysis of variance method was followed to assess the effect of sludge on extractable metals, plant metal content and dry matter yield of spinach using the SPSS statistical package (IBM SPSS statistics). Simple correlation and regression analyses were carried out to evaluate the suitability of chemical extractants to predict phyto-availability of heavy metals.
Results and discussion pH, organic carbon and extractable metal There was a concomitant increase in pH with the increasing rates of sludge addition on acid soil (Table 2). However, a reverse trend was observed in the case of alkaline soil, where a substantial decrease in pH was observed with increase in sludge addition. Organic carbon content in both the soils was enhanced as a result of sludge application (Table 2). This is related to addition of substantial amount of organic carbon through sludge. EDTA-extractable Zn, Cu, Fe, Mn, Ni, Cd and Pb were increased by 28.6, 6.07, 2.79, 2.68, 4.37, 20.5 and 1.23 times, respectively, at the highest level of sludge addition (285 g kg−1 of soil) over control in acid soil (Table 3). In alkaline soil, EDTA-extractable Zn, Cu, Fe, Mn, Ni and Cd increased by 31.2, 5.05, 5.28, 3.38, 3.15 and 53 times in sludge-amended soils (285 g kg−1
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Table 2 Effect of sludge addition on dry matter yield of Indian spinach and change in pH and organic carbon (mg kg−1) of acid and alkaline soils Soil
Acid
Alkaline
Rates of sludge addition (g kg−1)
Dry matter yield (g pot−1)
pH
Organic carbon (%)
0
5.98a
4.36a
0.76a
1.12
5.69a
4.52b
0.85b
2.23
6.29a
4.64bc
0.89bc
4.46
6.90a
4.72c
0.93c
8.93
9.71b
5.10d
1.02d
17.8
9.46b
5.70e
1.11e
35.7
8.95b
5.93f
1.26f
71.4
11.1c
6.23g
1.76g
142
12.3c
6.52h
1.99h
285
11.3c
6.71i
2.61i
0
4.09a
8.30h
0.61a
1.12
4.40ab
7.94g
0.62a
2.23
4.64ab
7.72f
0.66ab
4.46
5.66bc
7.55e
0.73b
8.93
6.57cd
7.42de
0.85c
17.8
7.45d
7.38d
0.99d
35.7
7.82d
7.34cd
1.16e
71.4
9.67e
7.24c
1.45f
142
16.7f
7.09b
1.80g
285
19.5g
6.81a
1.88h
Values followed by common letters are not significantly different at P≤0.05
of soil), respectively, over control. The mean EDTAextractable Zn, Cu, Fe, Mn, Ni, Cd and Pb was 56.2, 98.6, 278, 15.7, 83.8, 79.8 and 87.6 %, respectively, higher in acid soil as compared to that of alkaline soil. Application of sludge was more effective in enhancing the EDTA-extractable Zn, Cu, Fe, Mn, Ni, Cd and Pb in acid soil than that of alkaline soil. More or less similar trend of DTPA and CaCl2 extractable metals was obtained (Tables 4 and 5). In spite of the fact that acid soil had higher values of clay, organic carbon and cation exchange capacity as compared to alkaline soil, both EDTA and DTPA could extract higher amount of metals from acid soil than that from alkaline soil. This suggests that pH is the most important factor controlling the solubility and extractability of metals in soil. EDTA extracted the highest amount of metals, followed by DTPA and CaCl2. In general, chelating agents such as EDTA and DTPA
extracted much higher amounts of metal from soil as compared to weaker extractants like Ca-salts (e.g. Brennan et al. 2008). Neutral salt solution is able to extract weakly sorbed metal species, particularly those retained on soil surface by relatively weak electrostatic force and those that can be released through exchangeable process (Gleyzes et al. 2002). Recently, Ray et al. (2013) reported similar extractability of chelating agents and neutral salt solution for metals from sludgeamended soils. Higher extractability of EDTA than DTPA may be ascribed to higher concentration of EDTA (0.05 M) over DTPA (0.005 M). In addition, EDTA has a stronger chelating ability to extract metals from an organically bound pool (Gleyzes et al. 2002). Dry matter yield and metal content in spinach Dry matter yield of spinach increased significantly by 62.3 to 88.9 % due to application of sludge over control in acid soil, and corresponding values for alkaline soil ranged from 38.3 to 377 % (Table 2). At lower rates of sludge addition, dry matter yield of spinach was higher in acid soil as compared to that in alkaline soil. However, reverse trend was observed at higher rates of sludge addition. These may be ascribed to both inherent fertility status as well as differential solubility of metals in these two soils. Biomass yield was declined possibly due to metal toxicity at high rates of sludge addition in acid soil. Earlier reports also indicated substantial increase in biomass yield of spinach on similar soil due to application of sludge at the rate of 22.4 g kg−1 of soil (Roy et al. 2013). However, they did not fix any permissible limit of sludge addition. Significant increase in Zn content in shoot of spinach was recorded at ≥2.23 g kg−1 of applied rates of sludge over control in acid soil (Table 6), whereas a significant increase in plant Zn content was observed at ≥8.93 g kg−1 of applied sludge over control in alkaline soil. In the case of acid soil, at higher rates of sludge application (≥71.4 g kg−1), there was a significant decrease in plant Zn content as compared to preceding lower doses of sludge application. On the contrary, plant Zn content was progressively increased with increase in similar rates of added sludge in the case of alkaline soil. Significant increase in Fe content in shoot of spinach grown on acid soil was observed up to 17.8 g kg−1 of sludge addition over control. There was reduction in Fe content in spinach grown on acid soil by 8.0, 11.3, 12.8 and 26.7 % over control due to application of sludge at the rate of 35.8, 71.6, 142 and
Environ Monit Assess (2014) 186:8541–8553
8546 Table 3 Effect of sludge addition on EDTA-extractable metals (mg kg−1) in acid and alkaline soils
Soil
Rates of sludge addition (g kg−1)
Zn
Acid
0
5.96a
1.12 2.23
Alkaline
Values followed by common letters are not significantly different at P≤0.05
EDTA-extractable metals (mg kg−1)
Treatment
Cu
Fe
Mn
Ni
Cd
Pb
6.36a
487a
86.1a
0.67a
0.04a
3.84a
6.13a
6.71a
524ab
91.8b
0.94b
0.04a
3.92a
10.3ab
8.18b
559b
99.0cd
1.33c
0.06ab
4.30b
4.46
11.4b
8.64bc
651c
102de
1.47d
0.07b
4.81de
8.93
12.3b
8.95c
781d
106e
1.65e
0.08b
4.97ef
17.8
18.5c
11.1d
821de
113f
1.73f
0.11c
5.08f
35.7
34.7d
13.4e
882ef
123g
1.90g
0.15d
6.51g
71.4
55.9e
18.9f
935fg
135h
2.09h
0.23e
4.17bg
142
95.5f
26.7g
983g
160i
2.22i
0.41f
4.54c
38.6h
285
171g
1,360h
231j
2.93j
0.82g
4.74cd
0
3.33a
3.50a
84.9a
54.4a
0.61a
0.01a
3.16f
1.12
5.04a
3.93ab
108ab
65.9b
0.65ab
0.02ab
3.20f
2.23
6.23ab
4.48bc
126abc
73.5c
0.68b
0.03abc
2.94e
4.46
7.87ab
5.00cd
161bc
82.9d
0.75c
0.04bcd
2.72cd
8.93
10.9b
5.30de
165bc
97.2e
0.81cd
0.05cde
2.76de
17.8
16.8c
5.75e
177c
115f
0.85de
0.06de
1.54a
35.7
25.1d
6.74f
192c
125g
0.89ef
0.07e
1.62a
71.4
36.6e
8.26g
284d
134h
0.93f
0.10f
1.85b
142
54.0f
13.2h
360e
147i
1.08g
0.20g
2.52c
285
104g
17.7i
448f
184j
1.92h
0.53h
2.69cd
285 g kg−1, respectively. Significant increases in Fe content with increased rate of sludge addition from 4.46 to 285 g kg−1 were recorded in alkaline soil. In the case of acid soil, at higher rates of sludge application (≥8.93 g kg−1), there was significant decrease in concentration of plant Ni as compared to preceding lower dose of sludge application. Plant Ni content was progressively increased with increase in similar rates of added sludge in the case of alkaline soil. The application of sludge could not change the Cu content in shoot of spinach significantly grown on alkaline soil with respect to control. On the contrary, a concomitant increase in Cu content in shoot of spinach was recorded in acid soil when sludge was applied at the rate of ≥8.93 g kg−1. There was a concomitant increase in Mn content in shoot of spinach with the increasing rates of sludge addition on both acid and alkaline soils. A significant increase in Cd content was recorded with increasing rates of sludge addition in both acid and alkaline soils. No systematic influence of rates of sludge
addition on plant Pb content in shoot of spinach was observed in both the soils. In general, increase in plant metal content with sludge application has been reported in a number of studies (Antonious et al. 2011; Ray et al. 2013; Roy et al. 2013). In the case of acid soil, plant Zn, Cu, Fe and Ni decreased at higher rates of sludge application. This can be explained based on the fact that values of soil pH were increased progressively with increasing rates of sludge addition. Increase in pH might have decreased the solubility of these metals in soil which in turn, resulted in a decrease in plant metal content. But it is difficult to explain why this phenomenon was not observed in the case of Mn, Cd and Pb, also, why such declining solubility of Zn, Cu, Fe and Ni was not reflected in extractable metal content. While implementing free ion activity model, Hough et al. (2005) reported that soil to solution transfer factors of metal were highly pH dependent, which may suggest a significant competition between trace metals and
Environ Monit Assess (2014) 186:8541–8553 Table 4 Effect of sludge addition on DTPA-extractable metals (mg kg−1) in acid and alkaline soils
DTPA-extractable metals (mg kg−1)
Treatment Soil
Rates of sludge addition (g kg−1)
Zn
Cu
Fe
Mn
Ni
Cd
Pb
Acid
0
1.96a
4.37a
50.9a
25.8a
0.35ab
0.02a
1.76c
1.12
2.03a
5.01b
69.9b
26.0a
0.37b
0.02a
2.64f
2.23
2.83a
5.18b
83.1c
29.8a
0.37b
0.03b
3.22h
4.46
3.29a
5.78c
98.9d
39.5b
0.34a
0.03b
1.42b
8.93
5.24b
6.33d
109e
45.8c
0.36ab
0.04c
2.87g
17.8
5.71bc
7.13e
120f
48.1c
0.40c
0.05d
1.77c
35.7
7.13c
7.59e
138g
58.8d
0.40c
0.06e
1.86d
71.4
11.9d
8.55f
164h
64.2e
0.56d
0.07f
2.10e
142
24.0e
11.0g
188i
70.4f
0.54d
0.08g
1.17a
285
43.4f
17.1h
238j
101g
0.88e
0.12h
1.36b
0
1.41a
2.09a
4.98a
9.39a
0.35c
0.01a
0.70ab
1.12
1.67ab
2.26a
5.72ab
10.1a
0.23a
0.01a
0.65a
2.23
2.75abc
2.74b
6.22ab
11.4ab
0.24a
0.02b
0.73bc
4.46
3.01bcd
3.18bc
9.59ab
13.0ab
0.29b
0.02b
1.48g
8.93
3.88cd
3.63c
12.0abc
15.1b
0.29b
0.03c
1.47g
17.8
4.31ed
4.26d
15.1bcd
20.7c
0.30b
0.03c
0.87ef
35.7
5.75e
4.91e
20.4cd
25.5cd
0.35c
0.04d
0.84def
71.4
10.2f
6.46f
24.1de
29.3d
0.43d
0.06e
0.79cd
142
20.7g
9.16g
31.9e
46.7e
0.49e
0.08f
0.80cde
285
36.1h
14.4h
46.1f
65.6f
0.70f
0.10g
0.91f
Alkaline
Values followed by common letters are not significantly different at P≤0.05
8547
protons for sorption sites on roots. Based on this analogy, one can envisage that metal uptake should be increased with increase in pH. On the other hand, solubility of metal decreases with increase in pH. Prediction of metal content in shoot of spinach Efficacy of extractants, viz. EDTA, DTPA and CaCl2 to predict metal content in plant was evaluated by simple correlation analysis (Table 7). There were clear differences between metals in the extract to which the concentrations of metals in shoots reflected in soils. Results indicate that none of the extractants could extract proportionate amounts of Zn and Fe from soil in relation to their content in plant. However, EDTA-extractable Cu, Mn, Ni, Cd and Pb showed a significant positive relationship with plant Cu, Mn, Ni, Cd and Pb content. In the case of DTPA, extractable Cu, Mn and Cd contributed significantly and positively towards plant content of these metals. More or less similar relationships
between soil and plant content of these metals were obtained in the case of CaCl2. Metal- and crop-specific model parameters (C, β1 and β2) of integrated solubility-free ion activity model along with prediction coefficient (R2) are presented in (Table 8). Results indicate that as high as 62, 68, 50, 44, 50 and 77 % variation in Zn, Cu, Fe, Mn, Ni and Cd content in spinach could be explained by pH and MC (EDTA-extractable metals assumed to be adsorbed on Walkley-Black organic carbon), respectively. The model produced values of prediction coefficient as 0.54 for Zn, 0.38 for Cu, 0.51 for Fe, 0.68 for Mn, 0.48 for Ni, 0.68 for Cd and 0.25 for Pb when DTPA-extractable metals were used as an estimate of labile pool. As high as 60, 90, 57, 49, 73 and 50 % variation in Zn, Cu, Fe, Ni, Cd and Pb content in plant, respectively, could be explained by this model based on CaCl2 extractable metals. In the case of Pb and Cu, the model based on CaCl2 extractable metal had clear-cut edge in predicting plant metal content over model based on either EDTA or
8548 Table 5 Effect of sludge addition on CaCl2-extractable metals (mg kg−1) in acid and alkaline soils
Environ Monit Assess (2014) 186:8541–8553
Soil
Rates of sludge addition (g kg−1)
Zn
Cu
Fe
Mn
Ni
Cd
Pb
Acid
0
0.31ab
0.32a
0.79a
0.49a
0.03b
0.002a
0.23a
1.12
0.59c
0.39b
1.00b
0.52ab
0.03b
0.003b
0.26abc
2.23
0.27a
0.47c
1.32c
0.59bc
0.03b
0.004c
0.29c
4.46
0.30a
0.54d
1.35c
0.62cd
0.02a
0.006d
0.28bc
8.93
0.39b
0.72e
1.61d
0.59bc
0.02a
0.006d
0.24ab
17.8
0.24a
0.83f
1.75e
0.71e
0.02a
0.007e
0.25abc
35.7
0.30a
1.03g
1.86f
0.71e
0.03b
0.009f
0.23a
71.4
0.28a
1.25h
2.10g
0.69de
0.03b
0.010g
0.24ab
142
0.32ab
1.65i
2.21h
0.74e
0.03b
0.011h
0.24ab
Alkaline
Values followed by common letters are not significantly different at P≤0.05
CaCl2-extractable metals (mg kg−1)
Treatment
285
0.26a
1.85j
2.45i
0.73e
0.03b
0.068i
0.28bc
0
0.36c
0.12a
0.50a
0.17a
0.02b
0.001a
0.18a
1.12
0.28abc
0.16ab
0.51a
0.13a
0.01a
0.001a
0.22abc
2.23
0.30abc
0.19b
0.52a
0.17a
0.02b
0.002b
0.21ab
4.46
0.22a
0.24c
0.53ab
0.13a
0.02b
0.003c
0.24bc
8.93
0.32bc
0.28c
0.52a
0.14a
0.02b
0.003c
0.24bc
17.8
0.34c
0.34d
0.54ab
0.10a
0.02b
0.004d
0.26c
35.7
0.25ab
0.40e
0.52a
0.15a
0.02b
0.005e
0.22abc
71.4
0.23a
0.44e
0.57ab
0.27b
0.02b
0.005e
0.22abc
142
0.33bc
0.53f
0.63b
0.35b
0.02b
0.007f
0.26c
285
0.32bc
0.62g
0.75c
0.55c
0.03c
0.009g
0.31d
DTPA. By and large, solubility-free ion activity model was more effective in predicting metal content in plant as compared to regression equation based on extractable metal only. Earlier study also indicated that pH and organic carbon are among the important soil properties which control the solubility of metals in contaminated soil (Rang Zan et al. 2013). Rang Zan et al. (2013) also reported that the EDTA-extractable metals were more useful as an input of solubility model as compared to DTPA-extractable and CaCl2 extractable metals. DTPA (0.005 M) is the most commonly used soil test for assessing the bioavailability of metals in both normal and contaminated soils (Datta et al. 2000; Rattan et al. 2005; Brennan et al. 2008; Ray et al. 2013; Roy et al. 2013). European Commission calibrated and standardized much higher concentration of chelating agents (0.05 M EDTA as compared to 0.005 M DTPA) for assessing bioavailability of metals in contaminated soils (Quevauviller 1998). In a few studies, CaCl2 was also successfully used as an extractant for available metal in
soil (Disla et al. 2010). In the present study, poor relationship of extractable metals with their content in plant can be explained based on the fact that effect of change in soil pH due to sludge addition was not reflected on extractable metals, particularly in acid soil. There was a declining trend in uptake of metals (e.g. Zn, Fe, Ni) by spinach at higher rates of sludge application in acid soil. This mismatch between extractable metals in soil and plant metal content resulted into poor relationships. On the other hand, solubility-free ion activity model could successfully predict metal uptake by spinach because this model has provision of accounting the effect of pH and organic carbon on metal solubility. Hazard quotient and permissible limit of sludge addition A substantial amount of Zn, Cu, Fe, Mn, Ni, Cd and Pb was added to soil through sludge, where spinach was grown as a test crop. Intake of these metals at toxic level
Environ Monit Assess (2014) 186:8541–8553 Table 6 Effect of sludge addition on metal content (mg kg−1) in Indian spinach grown on acid and alkaline soils
8549 Total metal content (mg kg−1)
Treatment Soil
Rates of sludge addition (g kg−1)
Zn
Cu
Fe
Mn
Ni
Cd
Pb
Acid
0
167b
23.3ab
512cd
48.0a
0.80a
0.54a
0.08
1.12
174b
21.0a
548de
49.4a
0.95b
0.56ab
0.07
2.23
210c
22.8ab
590e
61.7a
1.02b
0.58ab
0.12
4.46
236d
26.5bc
652f
84.8a
1.89e
0.60bc
0.12
Alkaline
Values followed by common letters are not significantly different at P≤0.05
8.93
265e
32.6d
716g
131b
2.96h
0.64c
0.15
17.8
289f
40.2e
577e
185c
2.53g
0.71d
0.14
35.7
300f
33.7d
471bc
384d
2.11f
0.74d
0.15
71.4
272e
29.9cd
454bc
498e
1.91e
0.80e
0.12
142
242d
31.2d
446b
649f
1.66d
0.82e
0.18
285
144a
33.3d
375a
705g
1.36c
0.97f
0.13
0
65.4a
15.2a
261a
43.0a
0.59a
0.27a
0.06
1.12
65.7a
16.7a
296ab
60.6ab
0.60a
0.32b
0.07
2.23
72.2ab
15.8a
317ab
85.7b
0.63a
0.35b
0.09
4.46
74.9ab
17.0a
341b
125b
0.66a
0.42c
0.07
8.93
80.6b
16.5a
343b
221c
0.78b
0.45c
0.08
17.8
94.0c
18.0a
450c
241cd
0.81b
0.52d
0.08
35.7
105cd
17.3a
497cd
271d
0.84bc
0.52d
0.08
71.4
112de
16.5a
531de
278d
0.90cd
0.54de
0.08
142
122ef
16.6a
545de
345e
0.98d
0.58e
0.10
285
127f
16.7a
588e
395f
1.38e
0.58e
0.09
by human beings results in several physiological and metabolic disorders (Rattan et al. 2009). Hazard quotient for intake of these metals through consumption of this green vegetable was calculated using USEPA protocol (IRIS 2014). Table 7 Simple correlation coefficient of determination (r2) of extractable metal in soils with plant metal content Extractable metal in soil
Extracted by EDTA
DTPA
CaCl2
Zn
0.01
0.002
0.003
Cu
0.30*
0.20*
0.55**
Fe
0.12
0.06
0.07
Mn
0.78**
0.71**
0.21*
Ni
0.43**
0.03
0.06
Cd
0.50**
0.62**
0.45**
Pb
0.55**
0.14
0.07
*Values of r2 are significant at 5 % probability level; **values of r2 are significant at 1 % probability level
Results indicate that HQ ranged from 0.05 to 0.23 for Zn, 0.01 to 0.02 for Cu, 0.20 to 0.56 for Fe, 0.07 to 1.18 for Mn, 0.01 to 0.03 for Ni, 0.06 to 0.23 for Cd and 0.04 to 0.12 for Pb across the various treatments of sludge (Table 9). Values of HQ equal to or more than 1 indicates that consumption of food materials may be hazardous to humans due to intake of a particular metal. In the present study, values of HQ exceeded 1 in the case of Mn only and Fe also showed relatively higher values as compared to other metals. Implication of such higher value (HQ=1) is aggravated by the fact that green vegetables constitute only a small portion of diet. Food materials other than leafy green vegetables, drinking water and inhalation of dust are likely to be contributed significantly towards total intake of metals by human beings. Based on this analogy, the safe limit of HQ can be considered as 0.5 in risk assessment of contaminated soils. Critical scrutiny of data on HQ indicates that values of HQ for Fe exceeded 0.5 when sludge was applied at 8.93 g kg−1 in acid soil, whereas application of sludge at 142 g kg−1 produced a value of HQ more than 0.5 for Mn in alkaline soil. Hence, the safe limits of
8550
Environ Monit Assess (2014) 186:8541–8553
Table 8 Model parameters for predicting uptake of Zn, Cu, Fe, Mn, Ni, Cd and Pb by Indian spinach as a function of pH, Walkley-Black organic carbon and extractable metals Extractant EDTA
DTPA R2
Model parameters C
β1
Zn
−3.63
0.15
Cu
−3.00
Fe
−3.25
Mn
CaCl2 R2
Model parameters
β2
C
β1
R2
Model parameters
β2
β1
C
0.15
0.62
−3.81
0.15
0.30
0.54
−1.69
0.15
0.02
0.78
0.68
−2.90
0.03
0.64
0.38
−3.55
0.09
−0.12
0.50
−3.11
0.06
0.02
0.51
−2.53
0.98
−0.04
−3.96
0.44
−3.61
−0.38
2.96
0.68
Ni
−2.68
0.05
0.83
0.50
3.48
0.10
−1.31
Cd
−1.57
0.04
0.38
0.77
−3.34
0.04
Pb
0.91
0.05
−0.09
0.14
1.21
0.07
β2 −0.42
0.60
−0.002
0.70
0.90
0.10
−0.28
0.57
−0.66
0.01
−0.52
0.01
0.48
2.87
0.12
−0.84
0.49
0.77
0.63
−2.26
0.03
0.44
0.73
−0.21
0.25
2.53
0.05
−0.47
0.50
The values of R2 >0.20 are significant at 5 % probability level
Table 9 Hazard quotient (HQ) for intake of metals through consumption (human) of spinach grown on sludge-treated soils
Treatment
Hazard quotient (HQ)
Soil
Rates of sludge addition (g kg−1)
Zn
Cu
Fe
Mn
Ni
Cd
Pb
Acid
0
013
0.0109
0.40
0.08
0.0094
0.1275
0.05
1.12
0.14
0.0098
0.43
0.08
0.0111
0.1310
0.05
2.23
0.16
0.0107
0.46
0.10
0.0119
0.1359
0.08
4.46
0.18
0.0124
0.50
0.14
0.0222
0.1396
0.08
8.93
0.21
0.0153
0.56
0.22
0.0346
0.1492
0.10
17.8
0.23
0.0188
0.45
0.31
0.0297
0.1670
0.09
35.7
0.23
0.0158
0.37
0.64
0.0247
0.1736
0.10
71.4
0.21
0.0140
0.35
0.83
0.0224
0.1867
0.08
142
0.19
0.0146
0.35
1.09
0.0194
0.1909
0.12
285
0.11
0.0156
0.29
1.18
0.0159
0.2266
0.09
Alkaline
0
0.05
0.0071
0.20
0.07
0.0070
0.0623
0.04
1.12
0.05
0.0078
0.23
0.10
0.0070
0.0738
0.05
2.23
0.06
0.0074
0.25
0.14
0.0074
0.0813
0.06
4.46
0.06
0.0080
0.27
0.21
0.0077
0.0977
0.05
8.93
0.06
0.0077
0.27
0.37
0.0091
0.1052
0.05
17.8
0.07
0.0084
0.35
0.40
0.0095
0.1207
0.05
35.7
0.08
0.0081
0.39
0.45
0.0098
0.1225
0.05
71.4
0.09
0.0077
0.41
0.47
0.0106
0.1265
0.05
142
0.10
0.0078
0.43
0.58
0.0114
0.1349
0.07
285
0.10
0.0078
0.46
0.66
0.0162
0.1359
0.06
Minimum
0.05
0.01
0.20
0.07
0.01
0.06
0.04
Maximum
0.23
0.02
0.56
1.18
0.03
0.23
0.12
Environ Monit Assess (2014) 186:8541–8553
sludge addition, as emerged in this study, are 4.48 and 71.6 g kg−1 for acid and alkaline soils, respectively. However, further monitoring of metal uptake by crop is needed as the 90-day period may not be sufficient for the release of the entire amount of metals from sludge. There are a few guidelines for judging the suitability of sludge for application to agricultural lands based on metal contents in sludge (e.g. Harrison et al. 1999; Water Security Agency 2004). Recently, Passuello et al. (2012) attempted to develop a land classification tool to determine the suitability of different agricultural areas to be amended with sewage sludge. Several researchers also attempted to fix permissible limit of sludge based on different criteria (Oleszczuk 2006; Domene et al. 2008; Carbonell et al. 2009; Jin et al. 2011; Roig et al. 2012). For example, Oleszczuk (2006) recommended the rate of sludge application as ≤75 Mg ha−1 year−1, considering the degradation of polycyclic aromatic hydrocarbons present in sludge. Jin et al. (2011) worked out the permissible limit of sludge as 22 Mg ha−1 year−1 in respect to water pollution by nitrate from sludgeamended soil. Roig et al. (2012) suggested a maximum dose for application of sludge as 40 Mg ha−1 year−1 for calcareous soil, beyond which soil properties do not improve, and may even worsen. In the present study, the permissible rate of sludge was fixed based on health hazard associated with human beings for intake of metal through consumption of leafy vegetables grown on sludge-amended soils. While doing so, important soil properties like pH and organic carbon were also taken into account, in addition to extractable metals in soil. Since solubility-free ion activity model could predict the metal uptake by spinach to a reasonably good extent, as presented in the previous section, similar agreement between actual and modelled HQ was also obtained (data not shown). Since HQ is a derived parameter based on plant metal content, solubility-free ion activity model is equally effective in predicting HQ based on soil pH, organic carbon and EDTA-extractable metals. This implies that this model, after proper calibration, can be used as a tool to fix maximum permissible limit of sludge addition to agricultural lands.
Conclusions Safe rates of sludge application could be worked out as 4.48 and 71.6 g kg−1 for acid and alkaline soils, respectively, in relation to risk associated with human health
8551
for intake of metals through consumption of spinach grown on sludge-amended soils. Since this experiment was conducted for 90 days, uptake of metals from sludge-amended soil to plant needs further monitoring to arrive at a concrete conclusion. Safe rates of sludge addition will be varied with metal content in sludge. Nevertheless, the protocol developed here will definitely be useful for establishing the permissible limit of sludge application to agricultural lands. Acknowledgments This study was made possible by the financial support provided by the Indian Council of Agricultural Research in the form of a Junior Research Fellowship to the first author during his M.Sc. programme.
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