The objective of this study was to assess total concentration and chemical fractionation of trace metals in the industrial wastewater and sludge collected from seven different types of industries in Dhaka City, Bangladesh. The sludge from industries is either dumped on landfills or reused as secondary resources in order to preserve natural resources. Metals were analyzed using inductively coupled plasma mass spectrometry (ICP-MS). The ranges of Cr, Ni, Cu, As, Cd, and Pb in the sludges were 1.4–9,470, 4.8–994, 12.8–444, 2.2–224, 1.9–46.0 and 1.3–87.0 mg/kg, respectively. As a whole, the average concentrations of trace metals in samples were in the decreasing order of Cr > Ni > Cu > As > Pb > Cd. The results of the Community Bureau of Reference (BCR) sequential extraction showed that the studied metals were predominantly associated with the residual fraction followed by the oxidizable fraction. The study revealed that the mobile fractions of trace metals are poorly predictable from the total content, and bioavailability of all fractions of elements tends to decrease.

INTRODUCTION

Rapid urbanization is enlarging the size of mega cities like Dhaka City in terms of geographical area and population as a process of development. The greater Dhaka City is one of the most densely populated cities in the world, with about 12 million people in an area of 815.8 km2 (Mohiuddin et al. 2011; Islam et al. 2015a). The industrial waste problem has become one of the prime concerns of the city corporation for a number of environmental, social, and aesthetic reasons. Many industries have been set up in and around the city during the last decade, and the number of new industries are continually increasing. The rapid development of various industries has created environmental problems that pose a serious threat to the environment (Ahmad et al. 2010). Industrialization and unplanned urbanization have greatly transformed the natural environment of Dhaka City (Bhuiyan et al. 2011). In recent times, the environment has become hostile, posing a threat to health and welfare due to the release of pollutants from industries and urban sewage (Ntengwe 2006). The management of sludge produced during wastewater treatment processes is becoming an issue of growing importance, because sludge treatment and disposal may account for up to 60% of the total operating costs in wastewater treatment plants (Teh et al. 2016). Due to the lack of advanced technology for the management of industrial wastewater and sludge, the disposal of industrial sludge can be carried out to land and water bodies. However, the application of sewage sludge may result in trace metal accumulation in cultivated soils, and should receive more attention (Fuentes et al. 2004). Therefore, the occurrence of trace metals and metalloids in the disposable sludge and wastewater is of interest because they are often present at considerable levels and can have severe effects on the environment and public health (Cantinho et al. 2016). According to Vochozka et al. (2016), research into efficient sludge treatments is essential to ensure proper management of sewage sludge and minimization of costs.

Urban population growth and economic development accelerate the consumption of commodities, and as a result increase the waste generation in developing countries (Islam et al. 2015b). Different factors such as spiraling urban population, economic development, consumption patterns, climate, culture and the institutional framework play a significant role in municipal solid waste generation (Islam et al. 2015b). Municipal sludge that is disposed from different industries contains trace metals, organic compounds, macronutrients, micronutrients, organic micro pollutants, microorganisms and eggs of parasitic organisms (Yuan et al. 2011). So the accumulation of industrial sludge poses a growing environmental problem, and the disposal of these wastes of bioavailable fraction may result in secondary environmental pollution. Thus, contamination of the aquatic environment by toxic metals from untreated wastewater and the sludge of various industries is a worldwide environmental problem. Mining, electroplating, metal processing, textile, battery manufacturing, tanneries, petroleum refining, paint manufacture, pesticides, pigment manufacture, printing and photographic industries are the main sources of trace metals in the environment (Ahmaruzzaman 2011). Metals such as chromium, nickel, copper, arsenic, cadmium and lead have been recognized as hazardous trace metals (Ahmaruzzaman 2011). Unlike organic wastes, trace metals are non-biodegradable and they can be accumulated in living tissues, causing various diseases and disorders; therefore, they must be removed before discharge to the environment.

Xu & Lancaster (2008) reported that the residues and byproducts of the thermo-chemical reaction of sewage sludge should be analyzed, while utilization of the sludge-derived residues should be investigated. Very few studies have focused on the present state of solid waste and monitoring of trace metals in industrial waste in Bangladesh (Bhuiyan et al. 2011; Islam et al. 2015b). However, to the best of our knowledge, no extensive study on the characteristics of trace metals in industrial sludge has been reported so far. This is the first study to monitor the contamination level of trace metals in the sludge of various industries. To evaluate the environmental impact of industrial sludges that are disposed of to the aquatic environment, it is necessary to identify the content and mobility of trace metals. Although total metal concentrations may indicate the overall level of metals in sludge, it is generally recognized that the specific chemical form of a metal in the matrix determines its mobilization capacity and behavior in the environment (Tandy et al. 2009). Sequential extraction provides information about the differentiation of the relative bonding strength of trace metal on various solid phases and about their potential reactivity under different physicochemical environmental conditions. Therefore, the quantification of different chemical fractions of trace metals in sludge is necessary for information on metal mobility, as well as on their bioavailability or eco-toxicity (Chen et al. 2008). Therefore, the main objectives of this study are to evaluate total concentrations of trace metals (Cr, Ni, Cu, As, Cd and Pb) in the sludge of different industries and to assess the chemical forms and mobility of trace metals in sludge.

MATERIALS AND METHODS

Sample collection and pre-treatment

Sampling industries were established based on the site survey during August and September 2013. Approximately 57 wastewater and sludge samples were collected from the effluent disposal landfill sites of seven different types of industries in Dhaka City, Bangladesh (Figure 1). Dhaka generates approximately 1.65 million metric tons of solid waste annually. Waste collection is particularly insufficient in the slum areas of Dhaka City, which are home to approximately half of the city's poor and where government services are minimal. Collected waste from different industries is transported on hand trolleys from dense neighborhoods to consolidation locations and is dumped at the landfill. The industries were tanneries, dye chemicals, textile, paper mill, jute mill, metal processing and battery manufacturing. After collection, samples were brought to the Department of Fisheries, University of Dhaka, Bangladesh. Wastewater samples were filtered immediately after collection using an ADVANTEC® 0.45 μm sterile syringe filter for estimation of dissolved metals and were transferred immediately into acid cleaned 100 mL polypropylene bottles. After filtration, samples were preserved in the refrigerator until other chemical analysis was carried out. The sludge samples were dried at 105 °C to attain constant weight (Venkateswaran et al. 2007). The dried samples were crumbled and pulverized with a porcelain mortar and pestle, sieved through a 2 mm nylon sieve and stored in an airtight clean zip lock bag in freezer conditions until chemical analysis was carried out. The physico-chemical parameters such as pH, organic carbon, total N, total K, total P, and cation exchange capacity (CEC) values were determined following the standard analytical methods (Chen et al. 2008).
Figure 1

Map of the sludge sampling location of different industries in Dhaka City, Bangladesh.

Figure 1

Map of the sludge sampling location of different industries in Dhaka City, Bangladesh.

The sequential extraction and metal analysis

Sequential extraction was performed using the BCR three-step procedure recommended by the Community Bureau of Reference in which metals are divided into acid soluble/exchangeable (F1), reducible-fraction (F2) and oxidizable-fraction (F3). The analysis of the residual fractions (F4) was supplemented as step four. The detailed geochemical fractionation procedure of sludge is presented in Table 1. A blank was also run at the same time and no detectable concentration was observed when aliquots of the sequential extraction reagents were processed and analyzed with the samples. The concentrations of Cr, Ni, Cu, As, Cd and Pb in different fractions and the resultant solutions of step four were determined by using inductively coupled plasma mass spectrometry (ICP-MS, Agilent 7700 series). Each experiment was conducted in triplicate and the results reported in this study are the average values with standard deviation.

Table 1

Geochemical fractionation procedure of trace metals in sludge samples

Fraction Procedure 
Fraction 1 (exchangeable) About 0.5 g sludge sample extracted at room temperature for 1 h with 7.5 mL of 0.05 M ammonium acetate with continuous agitation 
Fraction 2 (bound to carbonates) Residue from fraction 1 extracted with 10.0 mL of 0.17 M acetic acid (pH, 7.0) for 5 h with continuous agitation 
Fraction 3 (reducible) Residue from fraction 2 extracted with 20.0 mL of hydroxyl ammonium chloride in 25% (v/v) acetic acid (pH, 5.0), at 96 ± 3 °C with occasional agitation for 5 h 
Fraction 4 (oxidizable) Residue from fraction 3 extracted with 5.0 mL of 0.02 M nitric acid and 5.0 mL of 3% hydrogen peroxide at 85 ± 2 °C for 2 h with occasional agitation. Followed by the addition of 6.0 mL of hydrogen peroxide as above for 3 h. After cooling, 5.0 mL of 3.2 M ammonium acetate in 20% (v/v) nitric acid with continuous agitation for 30 min 
Fraction 5 (residual) Residue from 4 extracted with a hydrofluoric/nitric acid (1:1, v/v) mixture and digested under pressure and temperature in closed vessel 
Fraction Procedure 
Fraction 1 (exchangeable) About 0.5 g sludge sample extracted at room temperature for 1 h with 7.5 mL of 0.05 M ammonium acetate with continuous agitation 
Fraction 2 (bound to carbonates) Residue from fraction 1 extracted with 10.0 mL of 0.17 M acetic acid (pH, 7.0) for 5 h with continuous agitation 
Fraction 3 (reducible) Residue from fraction 2 extracted with 20.0 mL of hydroxyl ammonium chloride in 25% (v/v) acetic acid (pH, 5.0), at 96 ± 3 °C with occasional agitation for 5 h 
Fraction 4 (oxidizable) Residue from fraction 3 extracted with 5.0 mL of 0.02 M nitric acid and 5.0 mL of 3% hydrogen peroxide at 85 ± 2 °C for 2 h with occasional agitation. Followed by the addition of 6.0 mL of hydrogen peroxide as above for 3 h. After cooling, 5.0 mL of 3.2 M ammonium acetate in 20% (v/v) nitric acid with continuous agitation for 30 min 
Fraction 5 (residual) Residue from 4 extracted with a hydrofluoric/nitric acid (1:1, v/v) mixture and digested under pressure and temperature in closed vessel 

After each extraction, samples were centrifuged, liquid-fraction-decanted and 3 × 10.0 ml of Milli-Q water was added to the residue (sample-centrifuged and water-removed) before proceeding with the next extraction.

Statistical analysis

The data were statistically analyzed using the statistical package, SPSS 16.0 (SPSS, USA). The means and standard deviations of trace metal concentrations in the sludge were calculated. Multivariate Post-hoc Tukey test was performed to detect significant differences in sludge metal concentration dependent on the various industries.

RESULTS AND DISCUSSION

Physico-chemical properties in sludge samples from selected industries

The data contained in Table 2 show that the physico-chemical properties of sludge from selected industries in Dhaka City, Bangladesh varied widely. Among the industries, the pH ranged from 5.4 to 8.9. All of the sludge samples of the studied industries were slightly acidic except textile (pH 8.9), indicating that it was slightly alkaline (Table 2) which could be due to a high amount of sodium. During our sampling, we observed that the operation process of the textile industry used lime as an acid neutralizing agent which might result in alkaline wastewater. The concentrations were in the range of 30.4–64.1% for organic C, 1.8–3.6% for total N, 1.9–3.7% for total P, 0.9–2.0% for total K and 33.9–79.6 cmol/kg for CEC. Although the properties of the sludge samples from the industries varied from each other, compared with the agricultural soil collected from the study area (Islam et al. 2014), the industrial sludge generally had high organic contents and was rich in N, suggesting high potential agricultural benefits for practical application after bioremediation (Wong et al. 2000) or chemical remediation treatment (Veeken & Hamelers 1999).

Table 2

Physico-chemical properties of sludge samples collected from different industries in Dhaka City, Bangladesh

Industry pH Organic C (%) Total N (%) Total P (%) Total K (%) CEC (cmol/kg) 
Tannery 5.9 64.1 2.1 3.6 1.1 79.6 
Dye-chemical 5.4 35.6 3.0 2.2 2.0 66.1 
Textile 8.9 49.1 1.9 2.1 1.5 63.3 
Paper mill 7.4 58.7 2.0 3.1 1.0 52.4 
Jute mill 6.5 44.1 1.8 3.7 0.9 68.9 
Metal processing 6.9 36.9 2.6 3.0 1.7 37.1 
Battery manufacturing 6.0 30.4 3.6 1.9 1.1 33.3 
Industry pH Organic C (%) Total N (%) Total P (%) Total K (%) CEC (cmol/kg) 
Tannery 5.9 64.1 2.1 3.6 1.1 79.6 
Dye-chemical 5.4 35.6 3.0 2.2 2.0 66.1 
Textile 8.9 49.1 1.9 2.1 1.5 63.3 
Paper mill 7.4 58.7 2.0 3.1 1.0 52.4 
Jute mill 6.5 44.1 1.8 3.7 0.9 68.9 
Metal processing 6.9 36.9 2.6 3.0 1.7 37.1 
Battery manufacturing 6.0 30.4 3.6 1.9 1.1 33.3 

Organic C: Organic carbon; Total N: Total nitrogen; Total P: Total phosphorus; Total K: Total potassium; CEC: Cation exchange capacity.

Total content of trace metals in wastewater and sludge samples

The total contents of trace elements, namely Cr, Ni, Cu, As, Cd and Pb of wastewater and sludge samples are presented in Tables 3 and 4. The concentration of trace metals showed a wide variation. The highest concentration of Cr was observed in the wastewater of the tannery industry (7,910 ± 3,151 and 1,994 ± 435 mg/L for total and dissolved, respectively) followed by the dye industry (mean: 8.4 ± 0.91 and 3.8 ± 1.6 mg/L for total and dissolved, respectively). The highest concentration of Ni was observed in the wastewater of the battery manufacturing industry (11 ± 3.7 and 5.2 ± 2.2 mg/L for total and dissolved, respectively) followed by the metal processing industry (8.8 ± 4.6 and 3.9 ± 1.8 mg/L for total and dissolved, respectively). A considerable amount of Cu was observed in the wastewater of the tannery, metal processing and battery manufacturing industries, which might be attributed to the use of Cu-containing chemicals for tanning or battery manufacturing process (Mohiuddin et al. 2012; Islam et al. 2015c). The highest concentration of As was observed in the wastewater of the tannery industry (16 ± 6.9 and 5.7 ± 2.8 mg/L for total and dissolved, respectively) followed by the dye-chemical industry (9.0 ± 0.78 and 3.2 ± 1.1 mg/L for total and dissolved, respectively) (Table 3). Lead is a well-known metal toxicant, and it is gradually being phased out of the materials that humans regularly use. The highest concentration of Pb was observed in the wastewater of the battery manufacturing industry (11 ± 3.5 and 4.5 ± 1.4 mg/L for total and dissolved, respectively) followed by the metal processing industry (9.4 ± 2.8 and 3.5 ± 1.4 mg/L for total and dissolved, respectively).

Table 3

Total and dissolved concentration of heavy metals (mg/L) in wastewater samples

Industries   Cr
 
Ni
 
Cu
 
As
 
Cd
 
Pb
 
  Total Dissolved Total Dissolved Total Dissolved Total Dissolved Total Dissolved Total Dissolved 
Tannery Mean ± SD 7,910 ± 3,151 1,994 ± 435 3.6 ± 2.8 1.9 ± 1.9 10 ± 7.4 4.4 ± 2.9 16 ± 6.9 5.7 ± 2.8 2.9 ± 2.2 1.1 ± 0.80 2.9 ± 2.3 1.1 ± 0.84 
Range 3,288–11,807 1,424–2,485 0.67–9.2 0.28–6.5 0.69–23 0.68–9.0 4.6–24 1.7–10 0.07–6.0 0.08–2.1 0.42–8.1 0.14–2.9 
Dye-chemical Mean ± SD 8.4 ± 0.91 3.8 ± 1.6 2.9 ± 1.7 1.1 ± 0.54 4.4 ± 4.4 1.3 ± 0.88 9.0 ± 0.78 3.2 ± 1.1 4.7 ± 3.0 1.5 ± 1.2 0.81 ± 0.71 0.40 ± 0.47 
Range 7.4–9.1 2.1–5.3 1.0–4.4 0.53–1.6 0.88–9.3 0.47–2.2 8.2–9.8 2.2–4.4 2.0–8.0 0.51–2.8 0.31–1.6 0.08–0.94 
Textile Mean ± SD 4.9 ± 0.92 2.0 ± 0.67 3.8 ± 4.2 1.6 ± 1.8 7.4 ± 2.7 3.5 ± 2.0 4.5 ± 0.75 1.3 ± 0.45 0.08 ± 0.07 0.04 ± 0.04 0.22 ± 0.02 0.07 ± 0.01 
Range 4.2–5.9 1.3–2.6 1.1–8.6 0.51–3.7 4.2–9.0 1.3–5.2 3.6–4.9 0.81–1.7 0.01–0.16 0.01–0.07 0.19–0.24 0.06–0.07 
Paper mill Mean ± SD 1.5 ± 0.37 1.0 ± 0.30 1.6 ± 1.4 0.82 ± 0.71 6.1 ± 2.8 2.0 ± 1.2 1.7 ± 0.64 0.49 ± 0.28 4.1 ± 2.0 1.3 ± 0.61 3.4 ± 1.4 1.1 ± 0.29 
Range 1.1–1.9 0.76–1.3 0.11–3.0 0.04–1.4 4.1–9.2 1.3–3.4 1.0–2.2 0.29–0.81 2.0–6.1 0.90–2.0 2.2–4.9 0.84–1.4 
Jute mill Mean ± SD 1.7 ± 0.62 1.1 ± 0.18 1.5 ± 0.14 1.0 ± 0.13 7.0 ± 2.8 2.1 ± 0.57 1.6 ± 0.17 0.54 ± 0.014 3.0 ± 1.5 0.78 ± 0.36 1.2 ± 0.54 0.39 ± 0.07 
Range 1.3–2.1 0.96–1.2 1.4–1.6 0.90–1.1 5.0–9.0 1.7–2.5 1.4–1.7 0.53–0.54 1.9–4.0 0.53–1.0 0.78–1.5 0.34–0.44 
Metal processing Mean ± SD 2.3 ± 0.4 2.1 ± 0.34 8.8 ± 4.6 3.9 ± 1.8 13 ± 1.9 6.4 ± 1.5 2.4 ± 1.0 1.2 ± 0.46 3.8 ± 2.3 1.3 ± 0.92 9.4 ± 2.8 3.5 ± 1.4 
Range 1.9–2.9 1.7–2.5 3.3–15 1.4–5.5 10–14 4.3–8.0 1.5–3.5 0.77–1.8 1.4–6.9 0.52–2.6 7.0–13 2.2–5.2 
Battery manufacturing Mean ± SD 5.0 ± 3.6 2.7 ± 1.4 11 ± 3.7 5.2 ± 2.2 12 ± 4.1 4.7 ± 2.3 2.7 ± 1.8 0.85 ± 0.80 9.3 ± 3.8 3.7 ± 1.8 11 ± 3.5 4.5 ± 1.4 
Range 1.9–9.5 1.5–4.8 5.1–15 2.9–8.0 4.2–15 2.2–7.7 0.88–5.1 0.26–2.0 3.5–13 1.0–5.6 7.4–15 2.6–6.3 
Industries   Cr
 
Ni
 
Cu
 
As
 
Cd
 
Pb
 
  Total Dissolved Total Dissolved Total Dissolved Total Dissolved Total Dissolved Total Dissolved 
Tannery Mean ± SD 7,910 ± 3,151 1,994 ± 435 3.6 ± 2.8 1.9 ± 1.9 10 ± 7.4 4.4 ± 2.9 16 ± 6.9 5.7 ± 2.8 2.9 ± 2.2 1.1 ± 0.80 2.9 ± 2.3 1.1 ± 0.84 
Range 3,288–11,807 1,424–2,485 0.67–9.2 0.28–6.5 0.69–23 0.68–9.0 4.6–24 1.7–10 0.07–6.0 0.08–2.1 0.42–8.1 0.14–2.9 
Dye-chemical Mean ± SD 8.4 ± 0.91 3.8 ± 1.6 2.9 ± 1.7 1.1 ± 0.54 4.4 ± 4.4 1.3 ± 0.88 9.0 ± 0.78 3.2 ± 1.1 4.7 ± 3.0 1.5 ± 1.2 0.81 ± 0.71 0.40 ± 0.47 
Range 7.4–9.1 2.1–5.3 1.0–4.4 0.53–1.6 0.88–9.3 0.47–2.2 8.2–9.8 2.2–4.4 2.0–8.0 0.51–2.8 0.31–1.6 0.08–0.94 
Textile Mean ± SD 4.9 ± 0.92 2.0 ± 0.67 3.8 ± 4.2 1.6 ± 1.8 7.4 ± 2.7 3.5 ± 2.0 4.5 ± 0.75 1.3 ± 0.45 0.08 ± 0.07 0.04 ± 0.04 0.22 ± 0.02 0.07 ± 0.01 
Range 4.2–5.9 1.3–2.6 1.1–8.6 0.51–3.7 4.2–9.0 1.3–5.2 3.6–4.9 0.81–1.7 0.01–0.16 0.01–0.07 0.19–0.24 0.06–0.07 
Paper mill Mean ± SD 1.5 ± 0.37 1.0 ± 0.30 1.6 ± 1.4 0.82 ± 0.71 6.1 ± 2.8 2.0 ± 1.2 1.7 ± 0.64 0.49 ± 0.28 4.1 ± 2.0 1.3 ± 0.61 3.4 ± 1.4 1.1 ± 0.29 
Range 1.1–1.9 0.76–1.3 0.11–3.0 0.04–1.4 4.1–9.2 1.3–3.4 1.0–2.2 0.29–0.81 2.0–6.1 0.90–2.0 2.2–4.9 0.84–1.4 
Jute mill Mean ± SD 1.7 ± 0.62 1.1 ± 0.18 1.5 ± 0.14 1.0 ± 0.13 7.0 ± 2.8 2.1 ± 0.57 1.6 ± 0.17 0.54 ± 0.014 3.0 ± 1.5 0.78 ± 0.36 1.2 ± 0.54 0.39 ± 0.07 
Range 1.3–2.1 0.96–1.2 1.4–1.6 0.90–1.1 5.0–9.0 1.7–2.5 1.4–1.7 0.53–0.54 1.9–4.0 0.53–1.0 0.78–1.5 0.34–0.44 
Metal processing Mean ± SD 2.3 ± 0.4 2.1 ± 0.34 8.8 ± 4.6 3.9 ± 1.8 13 ± 1.9 6.4 ± 1.5 2.4 ± 1.0 1.2 ± 0.46 3.8 ± 2.3 1.3 ± 0.92 9.4 ± 2.8 3.5 ± 1.4 
Range 1.9–2.9 1.7–2.5 3.3–15 1.4–5.5 10–14 4.3–8.0 1.5–3.5 0.77–1.8 1.4–6.9 0.52–2.6 7.0–13 2.2–5.2 
Battery manufacturing Mean ± SD 5.0 ± 3.6 2.7 ± 1.4 11 ± 3.7 5.2 ± 2.2 12 ± 4.1 4.7 ± 2.3 2.7 ± 1.8 0.85 ± 0.80 9.3 ± 3.8 3.7 ± 1.8 11 ± 3.5 4.5 ± 1.4 
Range 1.9–9.5 1.5–4.8 5.1–15 2.9–8.0 4.2–15 2.2–7.7 0.88–5.1 0.26–2.0 3.5–13 1.0–5.6 7.4–15 2.6–6.3 
Table 4

Total concentration of trace metals (mg/kg) in the sludge of different industries

Industries   Cr Ni Cu As Cd Pb 
Tannery Mean ± SD 5,805 ± 287a 20.8 ± 11.5c 277 ± 52.2a 134 ± 74.6- 22.2 ± 15.3ab 20.1 ± 13.9a 
Range 827 − 9,470 4.8 − 43.7 213 − 377 13.6 − 224 5.1 − 46.0 8.1 − 53.2 
Dye Mean ± SD 303 ± 84.2b 29.4 ± 13.4c 90.9 ± 21.5b 66.8 ± 24.3b 27.4 ± 12.0a 21.9 ± 8.6a 
Range 221 − 472 7.2 − 44.4 12.9 − 100 31.3 − 96.6 8.0 − 42.0 9.0 − 31.6 
Textile Mean ± SD 65.1 ± 16.2c 48.9 ± 23.8c 88.7 ± 29.9b 60.6 ± 25.5b 10.6 ± 6.9b 14.4 ± 11.2a 
Range 31.6 − 84.6 11.6 − 82.2 31.3 − 122 10.3 − 88.0 2.0 − 21.9 1.3 − 30.3 
Paper mill Mean ± SD 41.3 ± 15.7c 33.5 ± 15.0c 74.6 ± 28.0b 26.1 ± 10.5b 15.0 ± 7.9ab 16.7 ± 8.7a 
Range 14.0 − 55.3 11.8 − 53.0 20.5 − 101 11.0 − 41.2 4.1 − 22.7 2.2 − 24.9 
Jute mill Mean ± SD 68.7 ± 27.1c 35.8 ± 18.8c 187 ± 19.1a 15.5 ± 10.0b 13.9 ± 10.5ab 10.0 ± 3.5a 
Range 22.2 − 91.7 5.7 − 54.3 161 − 205 4.3 − 28.0 1.9 − 23.9 4.3 − 13.5 
Metal processing Mean ± SD 12.9 ± 9.8c 641 ± 264a 248 ± 137a 19.8 ± 11.4b 20.5 ± 12.6ab 67.8 ± 20.0b 
Range 2.4 − 32.2 149 − 994 74.6 − 444 2.2 − 33.5 5.5 − 42.3 23.0 − 87.0 
Battery manufacturing Mean ± SD 4.6 ± 3.2c 343 ± 184b 281 ± 135a 17.2 ± 8.9b 11.5 ± 7.2ab 17.5 ± 6.5a 
Range 1.4 − 9.5 65.1 − 565 84.0 − 415 4.2 − 31.2 1.9 − 22.0 9.0 − 29.0 
Industries   Cr Ni Cu As Cd Pb 
Tannery Mean ± SD 5,805 ± 287a 20.8 ± 11.5c 277 ± 52.2a 134 ± 74.6- 22.2 ± 15.3ab 20.1 ± 13.9a 
Range 827 − 9,470 4.8 − 43.7 213 − 377 13.6 − 224 5.1 − 46.0 8.1 − 53.2 
Dye Mean ± SD 303 ± 84.2b 29.4 ± 13.4c 90.9 ± 21.5b 66.8 ± 24.3b 27.4 ± 12.0a 21.9 ± 8.6a 
Range 221 − 472 7.2 − 44.4 12.9 − 100 31.3 − 96.6 8.0 − 42.0 9.0 − 31.6 
Textile Mean ± SD 65.1 ± 16.2c 48.9 ± 23.8c 88.7 ± 29.9b 60.6 ± 25.5b 10.6 ± 6.9b 14.4 ± 11.2a 
Range 31.6 − 84.6 11.6 − 82.2 31.3 − 122 10.3 − 88.0 2.0 − 21.9 1.3 − 30.3 
Paper mill Mean ± SD 41.3 ± 15.7c 33.5 ± 15.0c 74.6 ± 28.0b 26.1 ± 10.5b 15.0 ± 7.9ab 16.7 ± 8.7a 
Range 14.0 − 55.3 11.8 − 53.0 20.5 − 101 11.0 − 41.2 4.1 − 22.7 2.2 − 24.9 
Jute mill Mean ± SD 68.7 ± 27.1c 35.8 ± 18.8c 187 ± 19.1a 15.5 ± 10.0b 13.9 ± 10.5ab 10.0 ± 3.5a 
Range 22.2 − 91.7 5.7 − 54.3 161 − 205 4.3 − 28.0 1.9 − 23.9 4.3 − 13.5 
Metal processing Mean ± SD 12.9 ± 9.8c 641 ± 264a 248 ± 137a 19.8 ± 11.4b 20.5 ± 12.6ab 67.8 ± 20.0b 
Range 2.4 − 32.2 149 − 994 74.6 − 444 2.2 − 33.5 5.5 − 42.3 23.0 − 87.0 
Battery manufacturing Mean ± SD 4.6 ± 3.2c 343 ± 184b 281 ± 135a 17.2 ± 8.9b 11.5 ± 7.2ab 17.5 ± 6.5a 
Range 1.4 − 9.5 65.1 − 565 84.0 − 415 4.2 − 31.2 1.9 − 22.0 9.0 − 29.0 

Note: Superscript letters a, b and c indicate significant difference at <0.05 level among different industries.

As a whole, the average concentration of trace metals in sludge samples were in the following decreasing order: Cr > Ni > Cu > As > Pb > Cd. In general, the total concentrations of trace metals in samples showed a wide variation. A similar wide variation in the concentration ranges of trace metals has been reported by Liu & Sun (2013). This difference in concentration of metals among the industries may be due to the nature of raw materials and the composition used in their operation processes (Venkateswaran et al. 2007). A statistically significant difference (P < 0.05) was observed for the Cr concentration in the sludge of the tannery and dye industries along with the textile, paper mill, jute mill, metal processing and battery manufacturing industries (Table 4). The highest concentration of Cr was observed in the sludge of the tannery industry (mean: 5,805 ± 287 mg/kg, range: 827–9,470 mg/kg) followed by the dye industry (mean: 303 ± 84.2 mg/kg, range: 221–472 mg/kg). Chromium compounds are used as pigments, mordants and dyes as a tanning agent in leather (Lokhande et al. 2011). This study has provided the evidence that effluents discharged from the tanneries, dyeing and auxiliary industries were the main sources of Cr in the deposited sludge (Ahmad et al. 2010; Islam et al. 2016).

The highest mean concentration of Ni was observed in sludge of the metal processing industry (mean: 641 ± 264 mg/kg, range: 149–994 mg/kg) followed by the battery manufacturing industry (mean: 343 ± 184 mg/kg, range: 65.1–565 mg/kg) (Table 4). A statistically significant difference (P < 0.05) was observed for Ni concentration in sludge of the metal processing and battery manufacturing industries along with the tannery, dye, textile, paper mill and jute mill industries (Table 4). A considerable amount of Cu was observed in the sludge of the tannery, jute mill, metal processing and battery manufacturing industries. However, a high level of Cu in sludge indicates its higher input, which may originate from the urban and industrial wastes of these industries (Mohiuddin et al. 2012). Statistically significant difference (P < 0.05) was observed for As concentration in sludge of the tannery industry along with the dye, textile, paper mill, jute mill, metal processing and battery manufacturing industries (Table 4). The highest concentration of As was observed in the sludge of the tannery industry (mean: 134 ± 74.6 mg/kg, range: 13.6–224 mg/kg) followed by the dye industry (mean: 66.8 ± 24.3 mg/kg, range: 31.3–96.6 mg/kg). High levels of As in sludge might be attributed to the treatment of wood by using copper arsenate (Pravin et al. 2012) and tanning in relation to arsenic sulfide (Bhuiyan et al. 2011).

The highest mean concentration of Cd was observed in sludge of the dye industry (mean: 27.4 ± 12.0 mg/kg, range: 8.0–42.0 mg/kg) and the lowest was found in the textile industry (mean: 10.6 ± 6.9 mg/kg, range: 2.0–21.9 mg/kg) (Table 4). The highest concentration of Pb was observed in the sludge of the metal processing industry (mean: 67.8 ± 20.0 mg/kg, range: 23.0–87.0 mg/kg) followed by jute mill (mean: 10.0 ± 3.5 mg/kg, range: 4.3–13.5 mg/kg). The higher concentrations of Pb from the metal processing industrial sludge might be due to the effect from chemical manufacturing and steel works (Mohiuddin et al. 2011). A rough comparison of trace metals in the industrial sludge of Bangladesh and that of some other countries worldwide are presented in Table 5. Our findings revealed that the concentrations of some trace metals were lower than India and China, whereas it was higher than the sludge samples of Spain, the Netherlands and Poland and in agreement with some previous studies. The higher concentrations of trace metals in the sludge of some industries suggested that effluent from certain industries does not meet specified discharge standards. As a consequence, these pollutants settled and accumulated in the sludge and have contributed to high concentrations of trace metal in the environment. From the point of view of environmental protection and present environmental characteristics in Dhaka City, Bangladesh, taking strict management and implementing clean production is necessary to improve the environment in the study area.

Table 5

Comparison of metals in sludge (mg/kg) with different international guidelines and other studies in the world (mean (range))

City and country Cr Ni Cu As Cd Pb References 
Dhaka, Bangladesh 1,086 (1.4–9,470) 189 (4.8–994) 159 (12.8–444) 53.1 (2.2–224) 18.0 (1.9–46.0) 26.5 (1.3–87.0) Present study 
Madrid, Spain 119 42.5 220 NA 3.5 179 Walter et al. (2006)  
Chennai, India 7,822 695 2,980 NA 8.1 219 Venkateswaran et al. (2007)  
Changsha, China NA NA 225 (67–659) NA 189 (7.2–904) 329 (71.8–1,270) Chen et al. (2008)  
Guangzhou, China 57.4 97.7 908 NA 3.9 59.2 Liu & Sun (2013)  
The Netherlands 731 466 3,720 12 13 69 Tervahauta et al. (2014)  
Torun, Poland 303.4 402.8 240.4 NA 13 38.1 Sprynskyy (2009)  
Melaka, Malaysia 500 NA 80 NA 8.0 10.0 Haroun et al. (2009)  
City and country Cr Ni Cu As Cd Pb References 
Dhaka, Bangladesh 1,086 (1.4–9,470) 189 (4.8–994) 159 (12.8–444) 53.1 (2.2–224) 18.0 (1.9–46.0) 26.5 (1.3–87.0) Present study 
Madrid, Spain 119 42.5 220 NA 3.5 179 Walter et al. (2006)  
Chennai, India 7,822 695 2,980 NA 8.1 219 Venkateswaran et al. (2007)  
Changsha, China NA NA 225 (67–659) NA 189 (7.2–904) 329 (71.8–1,270) Chen et al. (2008)  
Guangzhou, China 57.4 97.7 908 NA 3.9 59.2 Liu & Sun (2013)  
The Netherlands 731 466 3,720 12 13 69 Tervahauta et al. (2014)  
Torun, Poland 303.4 402.8 240.4 NA 13 38.1 Sprynskyy (2009)  
Melaka, Malaysia 500 NA 80 NA 8.0 10.0 Haroun et al. (2009)  

NA: Not available.

The speciation of trace metals in the industrial sludge

The sequential extraction of industrial sludge samples provided detailed data on the potential mobility of trace metals in sludge. Sequential extraction methods may provide useful information on the association of metals with different phases of sludge (Vemic et al. 2015). The presence of trace metals in the mineral-rich industrial sludge, even at low concentrations, can cause detrimental effects on the ecosystem due to their accumulative behavior and toxicity effects (McGrath et al. 2010). The mobility/bioavailability and eco-toxicity of metals mainly depend on their speciation in sludge (Table 6) (Chen et al. 2008). The first fraction (F1) acid soluble/exchangeable presents a high bioavailability of the associated metals, as metal adsorption is related to changes in the ionic composition of water, which may affect the processes of adsorption–desorption and the mobility of metals. Meanwhile, the reducible fraction (F2) occupies second place regarding the mobility of the metals, because metals associated with this fraction are thermodynamically unstable and could also remain available under anoxic conditions (Fuentes et al. 2008). Therefore, these two fractions (F1 and F2) should be identified as having a direct effect on the environment. The oxidizable fraction (F3) in oxidizing condition is easily mobilized and transformed into F1 or F2. Soluble metallic forms are liberated when organic matter is attacked in oxidant conditions (Yao et al. 2010). Therefore, the potential toxicity of trace metals should not be ignored, and the oxidizable fraction can be identified as a fraction with a potential effect on the environment. The metals bound to the residual fraction (F4) contain mainly primary and secondary minerals, which may hold metals within their crystal structure, and so this fraction (F4) is identified as a stable fraction (Fuentes et al. 2008). These metals are not expected to be released in solution over a reasonable time span under the conditions normally encountered in nature (Lasheen & Ammar 2009).

Table 6

The relation among fraction of trace metals, eco-toxicity and bioavailability

Fraction of trace metals Eco-toxicity Bioavailability 
Acid soluble/exchangeable fraction (F1) Direct toxicity Direct effect fraction 
Reducible fraction (F2)   
Oxidizable fraction (F3) Potential toxicity Potential effect fraction 
Residual fraction (F4) No toxicity Stable fraction 
Fraction of trace metals Eco-toxicity Bioavailability 
Acid soluble/exchangeable fraction (F1) Direct toxicity Direct effect fraction 
Reducible fraction (F2)   
Oxidizable fraction (F3) Potential toxicity Potential effect fraction 
Residual fraction (F4) No toxicity Stable fraction 

The relative distribution of trace metals estimated by BCR extraction procedure in the industrial sludge, represented as a percentage of total concentrations, are shown in Figure 2 and the results of each fraction of trace metals in samples are listed in Table 7. A considerable proportion of Ni, Cu and Pb were present in the residual fraction, which indicated that primary and secondary minerals might hold these metals within their crystalline structure (Szolnoki & Farsang 2013). The metals associated with different fractions in sludge followed the descending order of Cr = residual > exchangeable > reducible > oxidizable; Ni = residual > oxidizable > reducible > exchangeable; Cu = residual > oxidizable > reducible > exchangeable; As = residual > oxidizable > reducible > exchangeable; Cd: residual > oxidizable > exchangeable > reducible; and Pb = residual > oxidizable > exchangeable > reducible.
Table 7

Metal concentration (mg/kg) [mean ± SD] in total and each fraction of the samples

Element Fractions Tannery Dye chemical Textile Paper mill Jute mill Metal processing Battery manufacturing 
Cr F1 1,998 ± 729 145 ± 70.4 18.4 ± 13.6 2.5 ± 2.7 10.8 ± 3.1 2.3 ± 2.0 1.0 ± 1.0 
F2 1,145 ± 331 67.9 ± 42.7 12.1 ± 12.2 10.9 ± 11.6 21.5 ± 11.8 3.4 ± 4.0 0.6 ± 0.5 
F3 1,251 ± 786 38.2 ± 34.9 17.5 ± 16.0 11.4 ± 9.3 11.2 ± 3.3 3.8 ± 0.6 1.5 ± 1.4 
F4 1,443 ± 1,035 59.7 ± 31.5 19.2 ± 14.0 20.1 ± 14.1 29.1 ± 28.2 5.6 ± 4.1 1.7 ± 1.7 
Total 5,805 ± 287 303 ± 84.2 65.1 ± 16.2 41.3 ± 15.7 68.7 ± 27.1 12.9 ± 9.8 4.6 ± 3.2 
Ni F1 3.6 ± 2.0 3.2 ± 3.6 7.0 ± 6.4 5.8 ± 4.7 2.7 ± 1.8 152 ± 78.6 140 ± 63.1 
F2 5.8 ± 3.1 10.3 ± 8.2 8.3 ± 6.4 10.1 ± 3.3 10.1 ± 8.6 118 ± 110 29.9 ± 7.3 
F3 5.6 ± 3.1 8.8 ± 9.8 5.6 ± 3.1 11.8 ± 6.7 9.6 ± 7.4 251 ± 133 79.9 ± 29.9 
F4 9.7 ± 3.7 18.7 ± 10.3 29.6 ± 18.9 10.2 ± 4.8 13.4 ± 12.0 134 ± 119 94.6 ± 63.2 
Total 20.8 ± 11.5 29.4 ± 13.4 48.9 ± 23.8 33.5 ± 15.0 35.8 ± 18.8 641 ± 264 343 ± 184 
Cu F1 33.3 ± 35.7 9.6 ± 4.5 9.3 ± 6.8 5.8 ± 4.8 24.4 ± 14.0 36.7 ± 31.5 59.0 ± 25.6 
F2 9.3 ± 4.3 18.8 ± 12.4 5.0 ± 4.5 10.7 ± 6.7 8.7 ± 7.5 28.0 ± 13.3 97.5 ± 35.3 
F3 116 ± 53.4 25.7 ± 24.4 19.5 ± 11.1 25.3 ± 8.2 34.6 ± 17.3 126 ± 45.3 52.5 ± 22.5 
F4 118 ± 61.3 35.8 ± 36.4 57.9 ± 29.3 37.2 ± 20.5 123 ± 84.7 59.0 ± 23.5 77.4 ± 35.2 
Total 277 ± 52.2 90.9 ± 21.5 88.7 ± 29.9 74.6 ± 28.0 187 ± 19.1 248 ± 137 281 ± 135 
As F1 68.5 ± 41.4 30.1 ± 17.1 6.6 ± 2.6 4.7 ± 2.4 3.7 ± 0.9 2.0 ± 0.6 2.7 ± 2.1 
F2 24.7 ± 19.6 13.4 ± 14.7 13.4 ± 9.9 9.6 ± 3.6 2.5 ± 0.3 8.3 ± 5.5 3.8 ± 3.0 
F3 28.5 ± 16.7 7.4 ± 5.0 12.0 ± 11.0 10.3 ± 8.0 4.5 ± 4.4 6.6 ± 10.8 4.7 ± 3.9 
F4 40.4 ± 25.7 17.2 ± 16.8 33.3 ± 20.6 5.3 ± 2.7 5.9 ± 3.4 4.5 ± 6.9 8.7 ± 7.9 
Total 134 ± 74.6 66.8 ± 24.3 60.6 ± 25.5 26.1 ± 10.5 15.5 ± 10.0 19.8 ± 11.4 17.2 ± 8.9 
Cd F1 7.8 ± 4.1 11.7 ± 5.8 2.1 ± 3.2 1.9 ± 1.9 1.9 ± 1.5 2.9 ± 2.1 3.9 ± 3.4 
F2 4.5 ± 3.1 6.2 ± 5.5 2.1 ± 2.1 2.5 ± 2.3 2.5 ± 1.4 2.6 ± 2.1 3.6 ± 1.3 
F3 6.0 ± 4.2 3.6 ± 0.9 2.9 ± 1.4 4.9 ± 4.1 4.8 ± 2.2 6.9 ± 3.1 1.7 ± 1.4 
F4 5.9 ± 3.8 7.4 ± 2.7 5.0 ± 3.7 5.7 ± 3.3 6.8 ± 2.6 7.8 ± 3.8 2.5 ± 3.2 
Total 22.2 ± 15.3 27.4 ± 12.0 10.6 ± 6.9 15.0 ± 7.9 13.9 ± 10.5 20.5 ± 12.6 11.5 ± 7.2 
Pb F1 1.1 ± 1.0 2.8 ± 1.6 2.4 ± 1.6 4.6 ± 3.2 0.7 ± 0.5 9.5 ± 7.8 7.7 ± 5.0 
F2 2.2 ± 1.6 1.8 ± 1.8 3.8 ± 3.7 4.4 ± 3.7 1.7 ± 0.8 10.8 ± 7.3 3.4 ± 3.5 
F3 6.8 ± 3.5 3.2 ± 2.1 3.6 ± 1.6 2.7 ± 1.4 2.6 ± 1.5 27.8 ± 13.6 2.6 ± 2.2 
F4 13.4 ± 6.3 14.2 ± 4.0 4.6 ± 3.0 6.1 ± 3.9 4.8 ± 3.5 20.1 ± 13.7 4.0 ± 4.0 
Total 20.1 ± 13.9 21.9 ± 8.6 14.4 ± 11.2 16.7 ± 8.7 10.0 ± 3.5 67.8 ± 20.0 17.5 ± 6.5 
Element Fractions Tannery Dye chemical Textile Paper mill Jute mill Metal processing Battery manufacturing 
Cr F1 1,998 ± 729 145 ± 70.4 18.4 ± 13.6 2.5 ± 2.7 10.8 ± 3.1 2.3 ± 2.0 1.0 ± 1.0 
F2 1,145 ± 331 67.9 ± 42.7 12.1 ± 12.2 10.9 ± 11.6 21.5 ± 11.8 3.4 ± 4.0 0.6 ± 0.5 
F3 1,251 ± 786 38.2 ± 34.9 17.5 ± 16.0 11.4 ± 9.3 11.2 ± 3.3 3.8 ± 0.6 1.5 ± 1.4 
F4 1,443 ± 1,035 59.7 ± 31.5 19.2 ± 14.0 20.1 ± 14.1 29.1 ± 28.2 5.6 ± 4.1 1.7 ± 1.7 
Total 5,805 ± 287 303 ± 84.2 65.1 ± 16.2 41.3 ± 15.7 68.7 ± 27.1 12.9 ± 9.8 4.6 ± 3.2 
Ni F1 3.6 ± 2.0 3.2 ± 3.6 7.0 ± 6.4 5.8 ± 4.7 2.7 ± 1.8 152 ± 78.6 140 ± 63.1 
F2 5.8 ± 3.1 10.3 ± 8.2 8.3 ± 6.4 10.1 ± 3.3 10.1 ± 8.6 118 ± 110 29.9 ± 7.3 
F3 5.6 ± 3.1 8.8 ± 9.8 5.6 ± 3.1 11.8 ± 6.7 9.6 ± 7.4 251 ± 133 79.9 ± 29.9 
F4 9.7 ± 3.7 18.7 ± 10.3 29.6 ± 18.9 10.2 ± 4.8 13.4 ± 12.0 134 ± 119 94.6 ± 63.2 
Total 20.8 ± 11.5 29.4 ± 13.4 48.9 ± 23.8 33.5 ± 15.0 35.8 ± 18.8 641 ± 264 343 ± 184 
Cu F1 33.3 ± 35.7 9.6 ± 4.5 9.3 ± 6.8 5.8 ± 4.8 24.4 ± 14.0 36.7 ± 31.5 59.0 ± 25.6 
F2 9.3 ± 4.3 18.8 ± 12.4 5.0 ± 4.5 10.7 ± 6.7 8.7 ± 7.5 28.0 ± 13.3 97.5 ± 35.3 
F3 116 ± 53.4 25.7 ± 24.4 19.5 ± 11.1 25.3 ± 8.2 34.6 ± 17.3 126 ± 45.3 52.5 ± 22.5 
F4 118 ± 61.3 35.8 ± 36.4 57.9 ± 29.3 37.2 ± 20.5 123 ± 84.7 59.0 ± 23.5 77.4 ± 35.2 
Total 277 ± 52.2 90.9 ± 21.5 88.7 ± 29.9 74.6 ± 28.0 187 ± 19.1 248 ± 137 281 ± 135 
As F1 68.5 ± 41.4 30.1 ± 17.1 6.6 ± 2.6 4.7 ± 2.4 3.7 ± 0.9 2.0 ± 0.6 2.7 ± 2.1 
F2 24.7 ± 19.6 13.4 ± 14.7 13.4 ± 9.9 9.6 ± 3.6 2.5 ± 0.3 8.3 ± 5.5 3.8 ± 3.0 
F3 28.5 ± 16.7 7.4 ± 5.0 12.0 ± 11.0 10.3 ± 8.0 4.5 ± 4.4 6.6 ± 10.8 4.7 ± 3.9 
F4 40.4 ± 25.7 17.2 ± 16.8 33.3 ± 20.6 5.3 ± 2.7 5.9 ± 3.4 4.5 ± 6.9 8.7 ± 7.9 
Total 134 ± 74.6 66.8 ± 24.3 60.6 ± 25.5 26.1 ± 10.5 15.5 ± 10.0 19.8 ± 11.4 17.2 ± 8.9 
Cd F1 7.8 ± 4.1 11.7 ± 5.8 2.1 ± 3.2 1.9 ± 1.9 1.9 ± 1.5 2.9 ± 2.1 3.9 ± 3.4 
F2 4.5 ± 3.1 6.2 ± 5.5 2.1 ± 2.1 2.5 ± 2.3 2.5 ± 1.4 2.6 ± 2.1 3.6 ± 1.3 
F3 6.0 ± 4.2 3.6 ± 0.9 2.9 ± 1.4 4.9 ± 4.1 4.8 ± 2.2 6.9 ± 3.1 1.7 ± 1.4 
F4 5.9 ± 3.8 7.4 ± 2.7 5.0 ± 3.7 5.7 ± 3.3 6.8 ± 2.6 7.8 ± 3.8 2.5 ± 3.2 
Total 22.2 ± 15.3 27.4 ± 12.0 10.6 ± 6.9 15.0 ± 7.9 13.9 ± 10.5 20.5 ± 12.6 11.5 ± 7.2 
Pb F1 1.1 ± 1.0 2.8 ± 1.6 2.4 ± 1.6 4.6 ± 3.2 0.7 ± 0.5 9.5 ± 7.8 7.7 ± 5.0 
F2 2.2 ± 1.6 1.8 ± 1.8 3.8 ± 3.7 4.4 ± 3.7 1.7 ± 0.8 10.8 ± 7.3 3.4 ± 3.5 
F3 6.8 ± 3.5 3.2 ± 2.1 3.6 ± 1.6 2.7 ± 1.4 2.6 ± 1.5 27.8 ± 13.6 2.6 ± 2.2 
F4 13.4 ± 6.3 14.2 ± 4.0 4.6 ± 3.0 6.1 ± 3.9 4.8 ± 3.5 20.1 ± 13.7 4.0 ± 4.0 
Total 20.1 ± 13.9 21.9 ± 8.6 14.4 ± 11.2 16.7 ± 8.7 10.0 ± 3.5 67.8 ± 20.0 17.5 ± 6.5 
Figure 2

Speciation of trace metals in sludge of tannery, dye, textile, paper mill, jute mill, metal processing and battery manufacturing industries in Dhaka City, Bangladesh. F1–F4 represent the acid soluble/exchangeable fraction (F1), reducible fraction (F2), oxidizable fraction (F3) and residual fraction (F4).

Figure 2

Speciation of trace metals in sludge of tannery, dye, textile, paper mill, jute mill, metal processing and battery manufacturing industries in Dhaka City, Bangladesh. F1–F4 represent the acid soluble/exchangeable fraction (F1), reducible fraction (F2), oxidizable fraction (F3) and residual fraction (F4).

Chromium was principally distributed in the residual fraction accounted for (31%), suggesting that Cr had the strongest associations with the crystalline components of sludge and is less available to the aquatic fauna and has less chance of entering into the human food chain (Yuan et al. 2011). The proportion of Cr in the exchangeable fraction was 49% in sludge of the dye chemical industry (Figure 2), indicating that leaching of Cr to the environment from this industry may occur readily. Nickel had a higher percentage of residual fraction (20–59%) and the least proportion was observed in the exchangeable fraction (7.7–41%). The predominant form of Cu was observed in the residual fraction (25–69%), followed by the oxidizable (14–54%), reducible (2.2–33%) and exchangeable fractions (8.5–22%) (Figure 2). It is noted that the content of the F1 and F2 fraction of Cu was low in all sludge samples; in particular, the acid soluble/exchangeable fraction (F1) was low with an average of 12%, showing less direct toxicity to the environment. A considerable amount of total Cu was present in the oxidizable fraction (F3) in the sludge samples, and this result was in agreement with Bibak (1994). The higher stability constant of copper complexes with organic matter leads to higher organic fractions, and under strong oxidizing conditions Cu can be leached into the environment (Chen et al. 2008). However, the percentage of Cu associated with the organic matter fraction is primarily dependent on the quantity of Fe oxides in soil (Sliveira et al. 2006) and the evaluation of the bioavailability of metals to the environment is essential to predict changes in metal behavior in response to environmental conditions. Arsenic was primarily present in the residual fraction (18–51%) followed by the oxidizable fraction (11–34%). Among the industries, tannery and dye chemical may result in more serious potential eco-toxicity to the environment where a considerable proportion of As was observed in the acid soluble/exchangeable fraction (Figure 2). The distribution of Cd into various fractions showed different patterns for the sludge samples of each industry. Among the fractions, the higher percentage of Cd was found in the residual fraction (24–42%). Interestingly, a considerable proportion of Cd in the sludge of tannery (32%) and dye chemical (40%) industries was observed in the acid soluble/exchangeable fraction (Figure 2), indicating potential mobility and bioavailability of Cd from these two industries. The higher percentage of Cd in the F1 fraction from tannery and dye chemical industrial sludge may cause potential phyto-toxicity and bioavailability after application to agricultural fields. Lead was primarily present in the residual fraction (23–65%). The results were in good agreement with reports from other studies (Wong et al. 2001; Chen et al. 2008). It was reported that Pb can be immobilized by the presence of insoluble salts like phosphates (Walker et al. 2003) and the importance of organic matter in limiting Pb bioavailability has also been demonstrated (Strawn & Sparks 2000).

Concern for trace metals in industrial sludge is due to their non-biodegradability, toxicity and persistence in the environment. After liquefaction due to thermo-chemical reactions, the mobile fractions, such as acid soluble/exchangeable and reducible, were mainly transformed into low or no availability fractions (organic bound/oxidizable and residual forms). Therefore, the bioavailability and eco-toxicity of trace metals in residues of liquefaction industrial sludge to the environment were relieved, resulting in the trace metals becoming relatively stable. However, attention should also be paid to the fact that the percentage of oxidizable fraction (F3) in the liquefaction industrial sludge was raised, which has potential toxicity to the environment (Yuan et al. 2011).

In order to predict the metal contamination in the environment, the bioavailable concentration of trace metals in the sludge samples were compared with some toxicological reference values and data and is presented in Table 8. The bioavailable concentration of Cr, As and Cd in sludge of the tannery and dye industries were higher than the toxicity reference values (TRV) as well as the severe effect level (SEL), which indicated that these metals might cause severe metal pollution to the aquatic environment. Other metals like Ni and Cu from the metal processing and battery manufacturing industries were higher than the ASV, TRV and SEL values (Table 8), indicating that the bioavailable concentration of these two metals found in the sludge of metal processing and battery manufacturing industries might create an adverse effect on the surrounding ecosystem.

Table 8

Comparison of bio-available concentration (fraction 1 + fraction 2) of trace metals in sludge with guideline values (mg/kg)

Metals Bioavailable concentration (F1 + F2) of trace metals in samples for the present study
 
Standard value of trace metals
 
Tannery Dy Textile Paper mill Jute mill Metal processing Battery manufacturing ASVa TRVb LELc SELd 
Cr 3,143 213 30.5 13.4 32.3 5.7 1.6 90 26 26 110 
Ni 9.4 13.5 15.3 15.9 12.8 270 170 68 16 16 75 
Cu 42.6 28.4 14.3 16.5 33.1 64.7 157 45 16 16 110 
As 93.2 43.5 20 14.3 6.2 10.3 6.5 13 33 
Cd 12.3 17.9 4.2 4.4 4.4 5.5 7.5 0.3 0.6 0.6 10 
Pb 3.3 4.6 6.2 9.0 2.4 20.3 11.1 20 31 31 250 
Metals Bioavailable concentration (F1 + F2) of trace metals in samples for the present study
 
Standard value of trace metals
 
Tannery Dy Textile Paper mill Jute mill Metal processing Battery manufacturing ASVa TRVb LELc SELd 
Cr 3,143 213 30.5 13.4 32.3 5.7 1.6 90 26 26 110 
Ni 9.4 13.5 15.3 15.9 12.8 270 170 68 16 16 75 
Cu 42.6 28.4 14.3 16.5 33.1 64.7 157 45 16 16 110 
As 93.2 43.5 20 14.3 6.2 10.3 6.5 13 33 
Cd 12.3 17.9 4.2 4.4 4.4 5.5 7.5 0.3 0.6 0.6 10 
Pb 3.3 4.6 6.2 9.0 2.4 20.3 11.1 20 31 31 250 

aASV (Average shale value) (Turekian & Wedepohl 1961).

bTRV (Toxicity reference value) (USEPA 1999).

cLEL (Lowest effect level) (Persuad et al. 1993).

dSEL (Severe effect level) (Persuad et al. 1993).

Recovery rate of trace metals

During the sequential extraction procedure, the recovery of trace metals can be investigated by comparing the sum of each fraction's concentrations with the total metal concentrations. Recovery of trace metals is essentially quantitative within the precision of the method (Chen et al. 2008; Yuan et al. 2011). Verification of the results of the BCR sequential extraction procedure was performed by comparing the sum of the four fractions (F1, F2, F3 and F4) with the total concentrations of trace metals from the HCl, HNO3 and H2O2 digestion procedure. The detailed calculations were expressed as follows: 
formula
1
The results are shown in Figure 3. It can be seen clearly that the sum of the four steps (F1 + F2 + F3 + F4) was in good agreement with the total metal concentration with satisfactory recoveries (72–100%) similar to those recorded by other authors using the same procedure (Chen et al. 2008; Yuan et al. 2011). The results indicated that the modified BCR sequential extraction method used in detecting the speciation of Cr, Ni, Cu, As, Cd and Pb in the industrial sludge was accurate and reliable.
Figure 3

Recovery rate of trace metals in the industrial sludge samples to confirm the accuracy of the modified BCR sequential extraction method for detecting the speciation of trace metals.

Figure 3

Recovery rate of trace metals in the industrial sludge samples to confirm the accuracy of the modified BCR sequential extraction method for detecting the speciation of trace metals.

CONCLUSIONS

Wastewater and sludge collected from seven different types of industries in Dhaka City, Bangladesh had high organic carbon, and was rich in nutrients such as N, P and K. The concentrations of trace metals in wastewater and sludge varied widely among the selected industries. A considerable proportion of trace metals were observed in the oxidizable fraction, which indicates potential eco-toxicity to the environment during the oxidizing condition. The largest proportion of trace metal was found in the residual fraction and fractions more resistant to extraction, indicating that the metals were in a more stable form and consequently considered unavailable for plant uptake. The bioavailable concentration of the studied metals in tannery, dye chemical, metal processing and battery manufacturing industries were higher than the standard values, indicating their adverse effect to the surrounding ecosystem.

ACKNOWLEDGEMENTS

The samples collected in Bangladesh were brought into Japan based on the permission issued by the Yokohama Plant Protection Station (Import permit No. 25Y324 and 25Y1009). The authors are grateful for financial support from the Leadership Program in Sustainable Living with Environmental Risk (SLER) at Yokohama National University under the aid of Strategic Funds for the Promotion of Science and Technology from the Ministry of Education, Culture, Sports, Science and Technology and also for Research Collaboration Promotion Fund provided by Graduate School of Environment and Information Sciences, Yokohama National University, Japan. Furthermore, we are thankful for the kind help from the members of Dhaka University, Bangladesh during the field sampling.

REFERENCES

REFERENCES
Ahmad
M. K.
Islam
S.
Rahman
S.
Haque
M. R.
Islam
M. M.
2010
Heavy metals in water, sediment and some fishes of Buriganga River, Bangladesh
.
Int. J. Environ. Res.
4
,
321
332
.
Bhuiyan
M. A. H.
Suruvi
N. I.
Dampare
S. B.
Islam
M. A.
Quraishi
S. B.
Ganyaglo
S.
Suzuki
S.
2011
Investigation of the possible sources of heavy metal contamination in lagoon and canal water in the tannery industrial area in Dhaka, Bangladesh
.
Environ. Monit. Assess.
175
,
633
649
.
Cantinho
P.
Matos
M.
Trancoso
M. A.
dos Santos
M. M. C.
2016
Behaviour and fate of metals in urban wastewater treatment plants: a review
.
Int. J. Environ. Sci. Technol.
13
(
1
),
359
386
.
Chen
M.
Li
X. M.
Yang
Q.
Zeng
G. M.
Zhang
Y.
Liao
D. X.
Liu
J. J.
Hu
J. M.
Guo
L.
2008
Total concentrations and speciation of metals in municipal sludge from Changsha, Zhuzhou and Xiangtan in middle-south region of China
.
J. Hazard. Mater.
160
,
324
329
.
Fuentes
L.
Mercedes
J.
Sáez
A.
Soler
M. I.
Aguilar
J.
Ortuno
F.
Meseguer
V. F.
2004
Simple and sequential extractions of heavy metals from different sewage sludges
.
Chemosphere
54
,
1039
1047
.
Fuentes
A.
Lloréns
M.
Sáez
J.
Isabel Aguilar
M. A.
Ortuño
J. F.
Meseguer
V. F.
2008
Comparative study of six different sludges by sequential speciation of heavy metals
.
Bioresour. Technol.
99
,
517
525
.
Islam
M. S.
Ahmed
M. K.
Al-mamun
M. H.
Masunaga
S.
2014
Trace metals in soil and vegetables and associated health risk assessment
.
Environ. Monit. Assess.
186
,
8727
8739
.
Islam
M. S.
Ahmed
M. K.
Al-Mamun
M. H.
Masunaga
S.
2015b
Potential ecological risk of hazardous elements in different land-use urban soils of Bangladesh
.
Sci. Total Environ.
512–513
,
94
102
.
Islam
M. S.
Sultana
A.
Rasheduzzaman
M.
Kundu
G. K.
Kamal
A. K. I.
Uddin
M. K.
2015c
Assessment of the present state and economical prospects of solid waste at Amin Bazar Waste Dumping Site, Dhaka, Bangladesh
.
J. Sci. Res.
7
,
129
137
.
Islam
M. S.
Islam
S.
Al-Mamun
M. H.
Islam
S. A.
Eaton
D. W.
2016
Total and dissolved metals in the industrial wastewater: a case study from Dhaka Metropolitan, Bangladesh
.
Environ. Nanotechnol. Monit. Manag.
5
,
74
80
.
Lokhande
R. S.
Singare
P. U.
Pimple
D. S.
2011
Toxicity study of heavy metals pollutants in waste water effluent samples collected from Taloja industrial estate of Mumbai, India
.
Resour. Environ.
1
(
1
),
13
19
.
McGrath
S. P.
Micó
C.
Curdy
R.
Zhao
F. J.
2010
Predicting molybdenum toxicity to higher plants: influence of soil properties
.
Environ. Pollut.
158
,
3095
3102
.
Mohiuddin
K. M.
Ogawa
Y.
Zakir
H. M.
Otomo
K.
Shikazono
N.
2011
Heavy metals contamination in water and sediments of an urban river in a developing country
.
Int. J. Environ Sci. Technol.
8
,
723
736
.
Persuad
D.
Jaagumagi
R.
Hayton
A.
1993
Guidelines for the Protection and Management of Aquatic Sediment Quality in Ontario
.
Ontario Ministry of the Environment
,
Canada
.
Pravin
U. S.
Trivedi
P.
Ravindra
M. M.
2012
Sediment heavy metal contaminants in Vasai Creek of Mumbai: pollution impacts
.
Am. J. Chem.
2
,
171
180
.
Sliveira
M. L.
Alleoni
L. F.
O'Connor
G. A.
Chang
A. C.
2006
Heavy metal sequential extraction methods – a modification for tropical soils
.
Chemosphere
64
,
1929
1938
.
Tandy
S.
Healey
J. R.
Nason
M. A.
Williamson
J. C.
Jones
D. L.
2009
Heavy metal fractionation during the co-composting of biosolids, deinking paper fibre and green waste
.
Bioresour. Technol.
100
,
4220
4226
.
Teh
C. Y.
Budiman
P. M.
Shak
K. P. Y.
Wu
T. Y.
2016
Recent advancement of coagulation-flocculation and its application in wastewater treatment
.
Ind. Eng. Chem. Res.
55
(
16
),
4363
4389
.
Tervahauta
T.
Rani
S.
Leal
L. H.
Buisman
C. J. N.
Zeeman
G.
2014
Black water sludge reuse in agriculture: are heavy metals a problem?
J. Hazard. Mater.
274
,
229
236
.
Turekian
K. K.
Wedepohl
K. H.
1961
Distribution of the elements in some major units of the earth's crust
.
Geol. Soc. Am. Bull.
72
,
175
192
.
USEPA
1999
Screening Level Ecological Risk Assessment Protocol for Hazardous Waste Combustion Facilities
.
Vol. 3, Appendix E: Toxicity reference values. EPA 530-D99-001C. Available from: www.epa.gov/epaoswer/hazwaste/combust/eco-risk/voume3/appx-e.pdf
.
Veeken
A. M.
Hamelers
H. M.
1999
Removal of heavy metals from sewage sludge by extraction with organic acids
.
Water Sci. Technol.
40
,
129
136
.
Vemic
M.
Bordas
F.
Guibaud
G.
Joussein
E.
Labanowski
J.
Lens
P. N. L.
van Hullebusch
E. D.
2015
Mineralogy and metals speciation in Mo rich mineral sludges generated at a metal recycling plant
.
Waste Manag.
38
,
303
311
.
Venkateswaran
P.
Vellaichamy
S.
Palanivelu
K.
2007
Speciation of heavy metals in electroplating industry sludge and wastewater residue using inductively coupled plasma
.
Int. J. Environ. Sci. Tech.
4
(
4
),
497
504
.
Vochozka
M.
Maroušková
A.
Váchal
J.
Straková
J.
2016
Appraisal of changes in sewage sludge management
.
Int. J. Environ. Sci. Technol.
13
(
6
),
1607
1614
.
Wong
J. C.
Li
K.
Fang
M.
Su
D. C.
2001
Toxicity evaluation of sewage sludges in Hong Kong
.
Environ. Int.
27
,
373
380
.
Yuan
X.
Huang
H.
Zeng
G.
Li
H.
Wang
J.
Zhou
C.
Zhu
H.
Pei
X.
Liu
Z.
Liu
Z.
2011
Total concentrations and chemical speciation of heavy metals in liquefaction residues of sewage sludge
.
Bioresour. Technol.
102
,
4104
4110
.