Phytoremediation of heavy metals in a tropical ... - Springer Link

Environ Monit Assess (2010) 165:529–537 DOI 10.1007/s10661-009-0964-z

Phytoremediation of heavy metals in a tropical impoundment of industrial region Prabhat Kumar Rai

Received: 25 August 2008 / Accepted: 18 April 2009 / Published online: 9 May 2009 © Springer Science + Business Media B.V. 2009

Abstract Aquatic pollution pose a serious challenge to the scientific community worldwide, since lakes or reservoirs find multifarious use and most often their water is used for drinking, bathing, irrigation, and aquaculture. Nine metals and several physicochemical parameters, from four sampling sites in a tropical lake receiving the discharges from a thermal power plant, a coal mine, and a chlor-alkali industry, were studied from 2004 to 2005. Pertaining to metal pollution, the site most polluted with heavy metals was Belwadah, i.e., waters and sediments had the highest concentration of all the metals examined. The reference site was characterized by the presence of low concentrations of metals in waters and sediments. Following the water quality monitoring, 2-month field phytoremediation experiments were conducted using large enclosures at the discharge point of different polluted sites of the lake. During field phytoremediation experiments using aquatic macrophytes, marked percentage reduction in metals concentrations were recorded. The percentage decrease for different metals was in the range of 25% to 67.90% at Belwadah (with Eichhornia crassipes and Lemna minor), 25% to 77.14% at Dongia nala

P. K. Rai (B) Environmental Sciences (FEBES), Mizoram University, Tanhril, P.B. 190, Aizawl, Mizoram, India 796009 e-mail: [email protected]

(with E. crassipes, L. minor and Azolla pinnata), and 25% to 71.42% at Ash pond site of G.B. Pant Sagar (with L. minor and A. pinnata). Preliminary studies of polluted sites are useful for improved microcosm design and for the systematic extrapolation of information from experimental ecosystems to natural ecosystems. Keywords Heavy metals · Water pollution · Phytoremediation · Eichhornia · Coal mines

Introduction Most of the pollutants and heavy metals discharged in industrial effluents ultimately find their way to aquatic ecosystems, i.e., rivers, ponds, and lakes. The presence of heavy metal pollutants in waterbodies poses risk to the health of humans and ecosystems. In recent years, there has been increased global concern over the deteriorating state of waterbodies due to heavy metal pollution (Rai 2008c). Several techniques have been developed to remove heavy metals from the waterbodies with mixed success. Most techniques proved to be partially effective and too costly to be adopted in feasible manner. Most of the modern technologies used to treat wastewaters have their own implications, as these technologies are quite costly, concomitantly, posing threats to aquatic life (Rai 2008c). Researchers are currently searching for

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Environ Monit Assess (2010) 165:529–537

technologies which could be employed to treat heavy metal contaminated waters in a feasible manner (Rai 2008a). Most developing countries like India may not be able to afford the huge expenditure required to treat the heavy metal pollution by modern technologies (Rai and Tripathi 2007b; Rai 2008b). In the recent past, utilization of aquatic plants for the wastewater treatment has been reported as an economical device for the treatment of heavymetal-contaminated wastewater. Several research works demonstrated heavy metal removal under artificial conditions (Rai et al. 1995; Rai 2007a, b, 2008a, b, c, d; Rai and Tripathi 2007a, b, 2009). There is still a paucity of data on the comparative efficiency of different aquatic plants for heavy metal removal under natural conditions, especially in tropical regions. Methods using living aquatic plants to remove metals from water can be a viable alternative process. Rai (2008c) extensively reviewed the utility of macrophytes in heavy metals polluted industrial effluents. A number of previous laboratory experiments proved that wetland plants can accumulate heavy metals in their tissues (Rai et al. 1995, 2007; Rai 2007a, b, 2008a, b, c, d; Rai and Tripathi 2007b, 2008, 2009). However, very few studies on phytoremediation potential of aquatic macrophytes have been carried out under field conditions (Cymerman and Kempers 2001; Cardwell et al. 2002; Deng et al. 2004; Rai 2008a).

and the area of submergence is 46,600 ha (Rai et al. 2007). G.B. Pant Sagar is of great importance to the people of the area not only to the Singrauli but also to the entire Eastern Uttar Pradesh. The water of the reservoir is used for drinking, irrigation, fish farming, and bathing. Figure 1 represents the location of sampling sites in the surrounding of G.B. Pant Sagar. Belwadah site receives the discharge from Anpara Thermal Power Plant, Dongia nala receives the discharge from a cholr-alkali industry preparing agrochemicals and Ash pond receives the effluent of Bina coal mine. Rihand dam was the Reference site. Since water of G.B. Pant Sagar is used for different purposes, it was considered important to know the details of its water pollution status and eco-management options.

Study area and location of sampling sites

Heavy metal analysis in effluent, water, and sediments

The Singrauli region (lies in 24◦ 15 E to 82◦ 40.9 N) straddles the border between the states of Madhya Pradesh (MP) and Uttar Pradesh (UP) in Northern India (Rai and Tripathi 2006). The region is now one of India’s most important energy centers. Eleven open-cast mining sites, occupying nearly 200 km2 , fuel six thermal power stations that generate 6,800 MW or about 10% of India’s installed generation capacity (Rai et al. 2007). A chlor-alkali industry, thermal power plants, and coal mines are responsible for discharge of various metals into Govind Ballabh Pant Sagar (G.B. Pant Sagar). G.B. Pant Sagar is one of the Asia’s largest man made reservoirs developed at Rihand dam

Materials and methods For analysis of the physicochemical characteristics of the effluent, triplicate water samples from different sampling points were collected at monthly intervals in the second week of each month from January 2004 to December 2005. Triplicate 2-l samples were collected in plastic bottles between 8 a.m. and 12 p.m. from various effluent generation points and brought to the laboratory in ice boxes for the analysis of various physicochemical characteristics (APHA 2000).

A total of nine metals (Cu, Cr, Fe, Mn, Ni, Pb, Zn, Hg, and Cd) were investigated. Samples for heavy metal analysis were collected quarterly in triplicate during the months of March, June, September, and December. Filtered water samples from all sampling sites were wet digested in HNO3 /HClO4 (3:1, v/v) mixtures at 80◦ C and oven dried sieved sediments (top 15 cm sediment were collected) from all sites were wet digested in HNO3 /HClO4 (3:1, v/v) mixtures at 80◦ C. The concentrations of heavy metals in filtrate of water and sediment samples were determined with particle induced X-ray emission (PIXE). PIXE


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Fig. 1 Location of different sampling sites in the surrounding of G.B. Pant Sagar (Rai and Tripathi 2009)

has been proven as analytical tool capable of detecting elemental concentrations down to parts per million (Murozono et al. 1999). PIXE was successfully used for heavy metal analysis because of its very high sensitivity for study of wastewater and plant tissue analysis (Mireles et al. 2004). For PIXE spectrum analysis a least square fitting computer program based on the pattern analysis method (Murozono et al. 1999) was used. During field phytoremediation experiments with aquatic macrophytes, metal concentrations were recorded in water and calculated as percentage removal by subtracting values from initial metals concentration without macrophytes. Statistical analysis Pearson correlation coefficients were calculated between metals in effluent, water, and sediments which were further used to construct correlation

matrices. Analyses of variance (ANOVA) were computed between months, sampling sites, and sampling sites × months (interaction) for each parameter. Student’s t test was applied between different sampling sites.

Results and discussion The values of different physicochemical parameters recorded in effluent are given in Table 1, while Table 2 represents the concentration of metals recorded in effluent samples. In the present study, at several sites and seasons, the heavy metals in industrial effluent and reservoir water were above the permissible limit as prescribed by EPA, WHO, CPCB, and BIS (Rai et al. 2007). All the metals analyzed in wastewaters followed the same seasonal trend, i.e., high during the summer season, from March until June, low

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Table 1 Physicochemical characteristics of effluents discharged into G.B. Pant Sagar

Physicochemical parameters

Anpara Lowest value Highest value

Kannoria Lowest value Highest value

Bina Lowest value Highest value

Temperature (◦ C)

27 ± 1.2 41 ± 1.4 995 ± 22.8 2750 ± 144 510 ± 17.4 850 ± 26.2 7.53 ± 0.3 8.55 ± 0.2 210 ± 4.8 630 ± 9.3 138 ± 4.8 175 ± 7.3 21 ± 1.2 40 ± 1.4 110 ± 8.1 330 ± 4.3 370 ± 11.1 593 ± 10.3 354 ± 21.6 633 ± 23.7 43 ± 9.6 159 ± 11.3 3.3 ± 0.3 9.2 ± 0.7

25 ± 1.1 39 ± 1.4 98 ± 2.8 329 ± 3.1 390 ± 20.4 725 ± 34 2.9 ± 0.12 4.3 ± 0.2 810 ± 41 1990 ± 105 74 ± 6.9 98 ± 7.6 121 ± 11.7 489 ± 14.0 63 ± 8.0 117 ± 1.9 990 ± 33 2500 ± 99.3 690 ± 3.9 980 ± 47 37.8 ± 1.8 68.4 ± 1.3 2.2 ± 0.3 7.3 ± 0.7

26 ± 1.4 36 ± 1.3 199 ± 2.2 570 ± 4.1 760 ± 8.9 1430 ± 101 5.8 ± 0.11 7.5 ± 2.0 193 ± 5.2 550 ± 3.9 129 ± 7.9 158 ± 8.3 19.9 ± 1.9 37.9 ± 2.6 87.5 ± 1.6 290 ± 1.4 269 ± 6.4 430 ± 9.2 290 ± 7.1 489 ± 12.3 149 ± 1.9 391 ± 18.7 4.1 ± 0.7 10.4 ± 0.9

TSS (mg L−1 ) TDS (mg L−1 ) pH Electrical conductivity (μS cm−1 ) BOD Total acidity (mg L−1 ) Alkalinity (mg L−1 ) Chloride (mg L−1 ) Hardness (mg L−1 CaCO3 ) Nitrate (mg L−1 ) Phosphate (mg L−1 )

during the rainy month, starting from September, which may be explained as a rain-dilution effect. The most polluted site was Belwadah, i.e., waters and sediments had the highest concentration of all the relevant metals. The reference site was characterized by the presence of low concentrations of metals in waters and in sediments (Tables 3, 4). Seasonal variations in metal

concentration (in effluent, water, and sediments) recorded during present investigation were in accordance with the findings of Ali et al. (1999). At some sites, minimum metal concentrations in sediment were recorded during the month of June. Most heavy metals in aquatic ecosystems eventually become associated with particulate matter, which settles and accumulate in the bottom

Table 2 Metals concentration in effluent before being discharged into G.B. Pant Sagar Metals examined

Anpara

Kannoria

Bina

Standard (CPCB)

Standard (EPA)

Cu Cr Fe Mn Ni Pb Zn Hg Cd

39 ± 3.1 44 ± 4.6 94 ± 9.5 98 ± 11.0 54 ± 8.9 19.8 ± 3.4 38 ± 8.4 6.5 ± 1.4 6.0 ± 1.0

5.9 ± 1.0 7.9 ± 1.1 16.5 ± 1.4 18.9 ± 1.6 3.7 ± 0.8 5.9 ± 0.7 4.9 ± 0.5 9.8 ± 2.5 3.1 ± 0.3

17.5 ± 1.4 3.9 ± 0.7 18 ± 1.3 15 ± 1.7 8.6 ± 1.4 3.0 ± 0.4 12.0 ± 1.0 0.4 ± 0.01 3.0 ± 0.7

3.0 0.10 3.0 5.0 3.0 0.10 5.0 0.01 2.0

5.0 2.0 100 5.0 5.0 0.10 5.0 0.01 1.0

All values in mg L−1 CPCB Central Pollution Control Board, Government of India, New Delhi (1998), EPA Environmental Protection Agency (USA)


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Table 3 Metal concentrations in G.B. Pant Sagar water Month

Cu

Belwadah March 22 ± 2.1 June 27 ± 1.4 Sept. 16 ± 1.4 Dec. 24 ± 1.8 Dongia Nala March 0.9 ± 0.1 June 1.2 ± 0.2 Sept. 0.6 ± 0.1 Dec. 0.8 ± 0.2 Ash Pond March 5.4 ± 1.3 June 6.8 ± 1.1 Sept. 4.3 ± 1.2 Dec. 4.9 ± 0.9 Rihand dam March 0.01 ± .01 June 0.02 ± .02 Sept. 0.01 ± 0.0 Dec. 0.1 ± 0.03

Cr

Fe

Mn

Ni

Pb

Zn

Hg

Cd

29 ± 2.7 34 ± 4.1 19 ± 1.6 32 ± 1.8

33 ± 2.4 41 ± 2.9 22 ± 2.2 37 ± 2.7

18 ± 1.4 22 ± 1.9 11 ± 1.1 19 ± 1.0

26 ± 1.9 36 ± 3.1 16 ± 1.2 29 ± 1.8

13 ± 0.9 17 ± 1.7 8 ± 0.79 15 ± 1.2

13 ± .01 21 ± 1.1 11 ± 0.9 14 ± 1.1

1.8 ± 0.1 2.0 ± 0.3 1.1 ± 0.3 1.7 ± 0.3

4.1 ± 0.6 4.5 ± 0.9 2.9 ± 0.4 3.7 ± 0.8

0.7 ± 0.2 0.8 ± 0.2 0.3 ± .01 0.5 ± .09

4.6 ± .06 5.1 ± 0.4 1.2 ± 0.1 3.9 ± 0.9

2.9 ± 0.7 3.1 ± 0.9 1.8 ± 0.2 2.6 ± 0.1

0.9 ± 0.1 1.3 ± 0.2 0.4 ± .09 0.6 ± .07

0.7 ± 0.1 1.1 ± 0.2 0.3 ± .01 0.4 ± .09

3.0 ± 0.1 3.2 ± 0.3 1.9 ± .09 1.7 ± 0.1

3.9 ± 0.3 4.1 ± 0.4 2.7 ± 0.1 2.9 ± 0.1

0.7 ± .09 0.9 ± 0.1 0.3 ± .05 0.5 ± .03

0.18 ± .01 0.2 ± .01 .09 ± .01 0.1 ± .04

41.3 ± 1.7 38 ± 3.1 27.5 ± 1.4 34 ± 2.7

0.2 ± .01 0.4 ± .09 .02 ± 0.0 0.3 ± .04

3.2 ± 0.6 3.7 ± .7 1.9 ± 0.4 2.1 ± 0.9

0.9 ± 0.1 1.1 ± 0.2 0.3 ± .09 0.4 ± 0.1

4.2 ± 0.90 5.1 ± 0.8 2.9 ± 0.30 3.2 ± 0.4

.17 ± .01 .19 ± .01 .01 ± 0.0 0.1 ± .01

1.0 ± 0.3 1.2 ± 0.2 0.6 ± 0.01 0.8 ± 0.1

.02 ± .021 .03 ± .031 – 0.01 ± .01

1.1 ± 0.2 1.2 ± 0.4 0.9 ± 0.1 1.1 ± 0.2

1.3 ± 0.4 1.5 ± 0.2 1.1 ± 0.2 1.4 ± 0.3

.07 ± .01 .09 ± .01 .01 ± 0.0 .08 ± .01

.06 ± .01 .08 ± .01 .02 ± 0.0 .09 ± .01

1.0 ± 0.2 1.2 ± 0.3 0.8 ± 0.1 0.9 ± 0.1

– – – –

0.01 ± 0.0 0.02 ± 0.0 .01 ± 0.00 0.01 ± 0.01

All values in mg L−1

sediments (Rai and Tripathi 2009; Rai 2008d). The accumulation of pollutants in the bottom sediments of water bodies and the remobilization

of these substances from the sediments are considered as two most important mechanisms in the regulation of pollutant concentrations in an

Table 4 Metal concentrations in G.B. Pant Sagar sediments Month

Cu

Cr

Belwadah March 20 ± 2.1 30 ± 2.3 June 17 ± 1.9 19 ± 2.1 Sept. 14 ± 1.7 16 ± 1.9 Dec. 18 ± 1.3 27 ± 1.7 Dongia Nala March 3.6 ± 1.1 1.4 ± 0.9 June 2.4 ± 0.5 1.2 ± 0.7 Sept. 1.9 ± 0.6 0.7 ± 0.1 Dec. 2.5 ± 0.9 1.3 ± 0.3 Ash Pond March 28 ± 2.7 8.5 ± 1.2 June 26 ± 2.3 7.9 ± 1.0 Sept. 17 ± 2.0 3.9 ± 0.9 Dec. 21 ± 2.1 4.1 ± 0.9 Rihand dam (reference Site) March 0.6 ± 0.1 0.5 ± 0.1 June 0.4 ± 0.09 0.4 ± 0.9 Sept. 0.6 ± 0.1 0.3 ± 0.1 Dec. 0.5 ± 0.1 0.4 ± 0.08 All values in mg L−1

Fe

Mn

Ni

Pb

Zn

Hg

Cd

69 ± 5.0 48 ± 4.9 40 ± 3.7 65 ± 6.2

110 ± 7.1 90 ± 6.2 78 ± 6.7 105 ± 7.8

35 ± 3.3 31 ± 3.0 23 ± 2.9 33 ± 2.8

10.0 ± 1.0 9.0 ± 0.7 6.0 ± 0.9 8.0 ± 0.5

55 ± 3.9 51 ± 3.3 47 ± 3.1 49 ± 3.7

1.2 ± 0.3 1.2 ± 0.2 1.0 ± 0.2 0.8 ± 0.1

1.4 ± 0.3 1.3 ± 0.2 1.1 ± 0.4 1.2 ± 0.1

12 ± 1.2 8.0 ± 1.0 6.0 ± 0.9 10 ± 1.3

12 ± 1.4 9.0 ± 1.5 7.0 ± 1.1 10 ± 1.0

0.8 ± 0.1 0.7 ± 0.1 0.4 ± 0.1 0.5 ± 0.1

3.1 ± 0.9 2.3 ± 0.7 1.2 ± 0.2 1.8 ± 0.3

7.9 ± 1.0 7.4 ± 0.9 6.1 ± 1.1 6.8 ± 0.7

6.8 ± 0.4 5.2 ± 0.4 4.1 ± 0.2 4.9 ± 0.6

1.2 ± 0.9 0.8 ± 0.2 0.4 ± 0.1 0.6 ± 0.1

85 ± 4.1 79 ± 4.0 42 ± 3.7 51 ± 3.9

133 ± 6.2 127 ± 7.1 90 ± 5.1 96 ± 5.3

27 ± 2.9 23 ± 2.6 12 ± 1.3 18 ± 1.7

7.5 ± 1.1 6.0 ± 1.0 5.3 ± 0.9 6.8 ± 0.8

57 ± 2.9 53 ± 2.7 40 ± 1.9 49 ± 2.3

3.2 ± 0.4 2.9 ± 0.5 1.0 ± 0.1 2.3 ± 0.3

4.6 ± 1.0 4.1 ± 0.7 2.7 ± 0.5 3.8 ± 0.9

1.9 ± 0.3 2.1 ± 0.4 1.2 ± 0.2 1.9 ± 0.3

2.1 ± 0.3 1.6 ± 0.2 2.3 ± 0.1 2.0 ± 0.1

0.3 ± 0.09 0.1 ± 0.08 0.4 ± 0.03 0.2 ± 0.01

0.2 ± 0.01 0.18 ± 0.01 0.3 ± 0.01 0.19 ± 0.01

1.7 ± 0.5 1.5 ± 0.4 1.9 ± 0.3 1.3 ± 0.1

0.05 ± 0.01 0.02 ± 0.0 0.01 ± 0.0 0.03 ± 0.01

.2 ± 0.09 .1 ± 0.01 .3 ± 0.08 .19 ± .07

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aquatic environment (Linnik and Zubenko 2000; Rai 2008d). The heavy metal pollution of aquatic ecosystems is often reflected in high metal levels in the sediments and macrophytes as compared to concentrations in water (Rai 2008d). However, water bodies with slow water-exchange rates (e.g., lakes and reservoirs) accumulate heavy metals in their bottom sediments in considerable quantities. This phenomenon has both positive and negative features. Bottom sediments promote selfpurification in the aquatic environment because of heavy metals accumulation. Heavy metals accumulation in the bottom sediments can be reversed causing adverse impact on water quality, especially in relation to heavy metals. Under certain conditions, bottom sediments can be a strong source of secondary water pollution (Linnik et al. 1993; Rai and Tripathi 2009). This is evident as release of heavy metals from bottom sediments is promoted, for example, by a deficit in dissolved oxygen or by decrease in pH and, thus, elevating metal concentrations in water (Rai 2008d). Probably, all these facts might have contributed for higher concentrations of metals in water than in sediments. In the present study, metals concentration in water with sediment was only correlated in the case of Hg, Ni, Pb, and Cr whereas others have not shown any such sort of correlation. These findings were in accordance with Morillo et al. (2002), who investigated partitioning of metals in sediments from the Odiel River (Spain) and reported that Pb, Fe, Cr, and Ni are strongly linked to the

sediments, while Cd, Zn, and Cu are the most mobile metals. One-way ANOVA between sites were significant ( p < 0.01) between groups and within groups for all the physicochemical parameters. Oneway ANOVA between months were also significant ( p < 0.01) between groups as well as within groups except BOD and COD. Pearson correlation coefficients revealed a significant positive correlation between metals in effluent with metals in water and sediments ( p < 0.01). The variation in various physicochemical characteristics between reference site and different polluted sites were tested for significance of difference using a t test. During different seasons, all the parameter values differed significantly ( p < 0.01). This showed that reservoir water quality was largely affected by various effluents discharged at the polluted sites, which caused the significant variations in water quality of G.B. Pant Sagar. Based on maximum permissible limits for these parameters, it may be concluded that the water of reservoir at different polluted sites is not suitable for drinking, bathing, wildlife, fisheries, recreation, irrigation, and industrial cooling.

Phytoremediation studies In order to evaluate the treatability of G.B. Pant Sagar at selected polluted sites using aquatic

Table 5 Phytoremediation at Belwadah site (May–June 2006) Macrophytes

Metals concentrations (mg L−1 )

at Belwadah

Natural quality of water (before growth of macrophytes)

After growth of Lemna and Eichhornia

Percentage decrease

Distance (m) L. minor and E. crassipes


40 m

80 m

120 m

40 m

80 m

120 m

40 m

80 m

120 m

20 24 27 15 21 11 12 1.2 2.6

17.5 20 22.8 13.1 16.2 8.9 9.3 0.8 1.8

15.3 16.5 21.5 11.9 14.3 7.3 7.5 0.5 1.2

9.3 9.6 10.8 9.5 8.7 5.3 5.1 0.4 1.2

7.5 7.9 8.3 8.6 7.2 4.9 4.6 0.3 1.1

6.2 6.8 6.9 7.5 6.9 4.4 4.4 0.2 0.9

53.50 60.0 60.0 36.66 58.57 51.81 57.50 66.60 53.84

57.14 60.50 63.59 34.35 55.55 44.94 50.53 62.50 38.88

59.47 58.78 67.90 36.97 51.74 39.72 41.33 60.0 25.0


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Table 6 Phytoremediation at Dongia nala site (May–June 2006) Macrophytes


at Dongia nala


After growth of Lemna, Azolla, and Eichhornia

Percentage decrease

Distance (m) L. minor, A. pinnata, and E. crassipes


40 m

80 m

120 m

40 m

80 m

120 m

40 m

80 m

120 m

0.6 0.4 2.5 1.8 0.4 0.3 1.2 2.3 0.3

0.5 0.28 2.1 1.6 0.30 0.21 0.9 2.1 0.28

0.4 0.20 1.7 1.3 0.21 0.17 0.7 1.7 0.20

0.2 0.2 1.3 0.7 0.2 0.1 0.8 0.6 0.1

0.2 0.1 0.7 0.6 0.10 0.1 0.7 0.48 0.09

0.1 0.1 0.5 0.4 0.11 0.1 0.5 0.29 0.07

66.66 50.0 48.0 61.11 50.0 66.66 33.33 73.91 66.66

60 64.28 66.66 62.50 66.66 52.38 25.0 77.14 67.85

75 50 70.58 69.23 47.61 41.17 28.57 82.94 65.0

macrophytes, a field experiment using natural microcosm was conducted in the month of May and June 2006 because during the months of May and June, the volume and velocity of reservoir water was found highly and significantly reduced. Studies also revealed high density and frequency of selected potent macrophytes, e.g., E. crassipes, L. minor, and A. pinnata during these months. During April 2006, transparent plastic curtains (impermeable to water) were put over the stretch of 120 m lengthwise along the reservoir bank covering 10 m width at effluent discharge point of different polluted sampling sites, i.e., Belwadah, Dongia nala, and Ash pond. Thus, three enclosure systems (120 × 10 m) were established 2 m away from the effluent discharge point at different pol-

luted sites. Prior to this, during March 2006, all the macrophytes were removed over this stretch selected for the field experiment. The construction of enclosure system was finished during the April of 2006. The enclosures did not allow exchange with the surrounding lake water. However, ten perforations of 4 cm2 size were made (eight along the length of the bank and two along width of enclosure) to allow slight flow of water, particularly at selected sampling points. Therefore, the aquatic environment of enclosure was almost totally isolated with prolonged water stagnation. Metals concentrations were recorded three times (14, 21, and 28 March) at 40, 80, and 120 m in the enclosure systems without macrophytes, and their average value is shown in Tables 5, 6, 7.

Table 7 Phytoremediation at ash pond site (May–June 2006) Macrophytes


at Ash pond


After growth of Lemna and Azolla

Percentage decrease

Distance (m) L. minor and A. pinnata


40 m

80 m

120 m

40 m

80 m

120 m

40 m

80 m

120 m

3.9 0.15 31 0.2 1.7 0.3 2.7 – 0.5

3.4 0.10 29.2 0.1 1.5 0.28 2.4 – 0.40

3.0 0.17 25.8 0.1 1.4 0.21 2.1 – 0.32

1.7 0.10 13 0.1 0.7 0.1 1.5 – 0.3

1.7 0.07 12.7 0.07 0.6 0.09 1.40 – 0.3

1.5 0.04 11.9 0.05 0.4 0.08 1.37 – 0.2

56.41 33.33 58.06 50.0 58.82 66.66 44.44 – 40.0

50.0 30.0 56.50 30.0 60.0 67.85 41.66 – 25

50.0 42.85 53.87 40.0 71.42 61.90 34.76 – 37.5

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Determination of metals concentrations at each distance marked the impact of dilution. During the month of April (last week) selected macrophytes scattered over the entire range of different sampling sites were collected. Dominant and potent macrophytes like E. crassipes, L. minor, and A. pinnata were artificially introduced into the enclosures. E. crassipes and L. minor were put at Belwadah (Table 5). L. minor, A. pinnata, and E. crassipes were put at Dongia nala (Table 6) while L. minor and A. pinnata were put at Ash pond in the area designed for microcosm phytoremediation experiment (Table 7). The selection of the macrophytes was entirely dependent on their abundance at that particular site and duration. Therefore, a macrophytic zone/bed was built for the microcosm field phytoremediation study. During the course of this 2-month experiment, metals of the G.B. Pant Sagar water were also analyzed after development of the macrophytic bed. Grab samples of water were taken in triplicate and mixed to get a composite sample for each site. During microcosm phytoremediation experiments (May–June), metal concentrations were recorded in reservoir water three times at alternate 20-day periods, and their average value was calculated (Tables 5–7). Marked percentage reduction in metal concentrations of reservoir water was recorded. The percentage decrease for different metals was in the range of 25% to 67.90% at Belwadah, 25% to 77.14% at Dongia nala, and 25% to 71.42% at Ash pond site of G.B. Pant Sagar (Tables 5–7). The percentage reduction recorded at 40, 80, and 120 m also took dilution factor into account. Since the aquatic environment of the enclosure was almost totally isolated with prolonged water stagnation as a consequence, we can postulate that these removals were almost entirely controlled by macrophytic processes, with a minor contribution of hydrodynamics. During the biological characterization of the reservoir, we also recorded that phytoplanktons were recorded only after 800 m to 1 km range, which nullify their role in the phytoremediation process in enclosures, which was only confined up to 120 m from the pollution source. To our knowledge, there has been no previous attempt to systematically quantify the heavy metal phytoremediation efficiency using macrophytes in


such enclosed experimental aquatic ecosystems. Earlier, Sagrario et al. (2005) also conducted a 3-month mesocosms experiment in a shallow lake to assess the submerged macrophyte abundance with contrasting loadings of N and P. Further, Snow and Ghaly (2008) evaluated the feasibility of using hydroponically grown water hyacinth, water lettuce, and parrot’s feather plants on wastewater from a recirculating aquaculture system as a component of fish feed as determined by their nutritive value. They marked the significant reduction in TSS, COD, and nitrate after 24 days retention time. Likewise, Qiu et al. (2001) also assessed the suitability of various macrophytes in different enclosure systems and marked the improvement in water quality. Viaroli et al. (1997) used dark and light cylindrical benthic chambers with a volume of 14 l and cross sectional area of 700 cm2 to assess the relationship between macrophyte cover and water quality. Our results suggest that field experiments appear to be a prerequisite for improved microcosm design and for the systematic extrapolation of information from experimental ecosystems to natural ecosystems.

References Ali, M. B., Tripathi, R. D., Rai, U. N., Pal, A., & Singh, S. P. (1999). Physico-chemical characteristics and pollution level of Lake Nainital (U.P., India): Role of macrophytes and phytoplankton in biomonitoring and phytoremediation of toxic metal ions. Chemosphere, 39(12), 2171–2182. APHA (2000). Standard methods for the examination of water and wastewater (10th ed.). Washington, DC: American Public Health Association. Cardwell, A. J., Hawker, D. W., & Greenway, M. (2002). Metal accumulation in aquatic macrophytes from south east Queensland, Australia. Chemosphere, 48, 653–663. Cymerman, A. S., & Kempers, A. J. (2001). Concentration of heavy metals and plant nutrients in water, sediments and aquatic macrophytes of anthropogenic lakes (former open cut brown coal mines) differing in stage of acidification. Science of the Total Environment, 281, 87–98. Deng, H., Ye, Z. H., & Wong, M. H. (2004). Accumulation of lead, zinc, copper and cadmium by 12 wetland plant species thriving in metal contaminated sites in China. Environmental Pollution, 132, 29–40.

Environ Monit Assess (2010) 165:529–537 Linnik, P. M., & Zubenko, I. B. (2000). Role of bottom sediments in the secondary pollution of aquatic environments by heavy-metal compounds. Lakes and Reservoirs: Research and Management, 5, 11–21. Linnik, P. N., Zhuravleva, L. A., Samoilenko, V. N., & Yu, N. B. (1993). Influence of exploitation regime on quality of water in the Dnieper reservoirs and mouth zone of the Dnieper River. Gidrobiologicheskiy Zhurnal, 29(1), 86–99 (in Russian). Mireles, A., Solis, C., Andrade, E., Lagunas-Solar, M., Pina, C., & Flocchini, R. G. (2004). Heavy metal accumulation in plants and soil irrigated with wastewater from Mexico City. Nuclear Instruments & Methods in Physics Research. Section B, Beam Interactions with Materials and Atoms, 1(219–220), 187–190. doi:10.1016/j.nimb.2004.01.051. Morillo, J., Usero, J., & Gracia, I. (2002). Partitioning of metals in sediments from the Odiel River (Spain). Environmental Interpretation, 28, 263–271. Murozono, K., Ishii, K., Yamazaki, H., Matsuyama, S., & Iwasaki, S. (1999). PIXE spectrum analysis taking into account bremsstrahlung spectra. Nuclear Instruments & Methods in Physics Research. Section B, Beam Interactions with Materials and Atoms, 150, 76–82. Qiu, D., Wu, Z., Liu, B., Deng, J., Fu, G., & He, F. (2001). The restoration of aquatic macrophytes for improving water quality in a hypertrophic shallow lake in Hubei Province, China. Ecological Engineering, 18, 147–156. Rai, P. K. (2007a). Wastewater management through biomass of Azolla pinnata: An eco-sustainable approach. Ambio, 36(5), 426–428. Rai, P. K. (2007b). Phytoremediation of Pb and Ni from industrial effluents using Lemna minor: An eco-sustainable approach. Bulletin of Bioscience, 5(1), 67–73. Rai, P. K. (2008a). Heavy-metal pollution in aquatic ecosystems and its phytoremediation using wetland plants: An eco-sustainable approach. International Journal of Phytoremediation, 10(2), 133–160. Rai, P. K. (2008b). Phytoremediation of Hg and Cd from industrial effluents using an aquatic free floating macrophyte Azolla pinnata. International Journal of Phytoremediation, 10(5), 430–439. Rai, P. K. (2008c). Heavy metal phytoremediation from aquatic ecosystems with special reference to macrophytes. Critical Reviews in Environmental Science and Technology (in press). Rai, P. K. (2008d). Mercury pollution from chlor-alkali industry in a tropical lake and its bio-magnification

537 in aquatic biota: Link between chemical pollution, biomarkers and human health concern. Human and Ecological Risk Assessment: An International Journal, 14(6), 1318–1329. Rai, P. K., & Tripathi, B. D. (2006). Impact of thermal power effluent on aquatic environment. National Journal of Radiation Research, 3(4), 190–192. Rai, P. K., & Tripathi, B. D. (2007a). Microbial contamination in vegetables due to irrigation with partially treated municipal wastewater in a tropical city. International Journal of Environmental Health Research, 17(5), 389–395. Rai, P. K., & Tripathi, B. D. (2007b). Heavy metals removal using nuisance blue green alga Microcystis in continuous culture experiment. Environmental Science, 4(1), 53–59. Rai, P. K., & Tripathi, B. D. (2008). Heavy metals in industrial wastewater, soil and vegetables in Lohta village, India. Toxicology and Environmental Chemistry, 90(2), 247–257. Rai, P. K., & Tripathi, B. D. (2009). Comparative assessment of Azolla pinnata and Vallisneria spiralis in Hg removal from G.B. Pant Sagar of Singrauli Industrial region, India. Environmental Monitoring and Assessment, 148, 75–84. Rai, U. N., Sinha, S., Tripathi, P., & Chandra, P. (1995). Wastewater treatability potential of some aquatic macrophytes: Removal of heavy metals. Ecological Engineering, 5, 5–12. Rai, P. K., Sharma, A. P., & Tripathi, B. D. (2007). Urban environment status in Singrauli Industrial region and its eco-sustainable management: A case study on heavy metal pollution. In L. Vyas (Ed.), Urban planing and environment, strategies and challenges (pp. 213– 217). London: McMillan. Sagrario, M. A. G., Jeppesen, E., Goma, J., Sondergaard, M., Jensen, J. P., Lauridsen, T., et al. (2005). Does high nitrogen loading prevent clear-water conditions in shallow lakes at moderately high phosphorus concentrations? Freshwater Biology, 50, 27–41. Snow, A. M., & Ghaly, A. E. (2008). Assessment of hydroponically grown macrophytes for their suitability as fish feed. American Journal of Biochemistry and Biotechnology, 4(1), 43–56. Viaroli, P., Bartoli, M., Fumagalli, I., & Giordani, G. (1997). Relationship between benthic fluxes and macrophyte cover in a shallow brackish lagoon. Water, Air and Soil Pollution, 99, 533–540.