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Metal Enrichment and Contamination in River and Estuary Sediments of Tamirabarani, South India
ISSN: 2157-7617

Journal of Earth Science & Climatic Change
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Metal Enrichment and Contamination in River and Estuary Sediments of Tamirabarani, South India

Mukesh MV*, Chandrasekaran A, Premkumar R and Keerthi BN
Department of Earth Sciences, Annamalai University, Annamalainagar, Tamil Nadu, India
*Corresponding Author: Mukesh MV, Department of Earth Sciences, Annamalai University, Annamalainagar, Tamil Nadu, India, Tel: 919443133843, Email: [email protected]

Received: 19-Sep-2018 / Accepted Date: 18-Oct-2018 / Published Date: 30-Oct-2018 DOI: 10.4172/2157-7617.1000497 /

Keywords: Tamirabarani; River and estuary; Sediments; Heavy metals; Enrichment factors; Contamination factor; Geo-accumulation index; Pollution Load Index

Introduction

In recent past, there have been increasing interests regarding heavy metal contaminations in the environments, apparently due to their toxicity and perceived persistency within the aquatic systems [1]. There are basically three reservoirs of metals in the aquatic environment: water, sediment and biota [2]. The analysis of river sediment is a useful method of studying heavy metals to assess environmental pollution [3,4]. Heavy metals accumulate in the sediments through complex physical and chemical adsorption mechanisms depending on the nature of the sediment matrix and the properties of the adsorbed compounds [5]. Atmospheric particles generated by the natural sources are found to be accumulated as atmospheric metal load. In isolated areas, the amount of metal load by natural processes is higher, while the other side it may be due to anthropogenic sources. Aeolian process carries the soil particles on global scale to the atmosphere and end up in rivers that transport metal containing particles to lakes and to the ocean. Volcanoes eruption discharged materials is also a prime source for certain amount of cadmium in the air. As well as the metals that are part of vegetation can be released and extend through forest fires. Heavy metal pollution of an aquatic ecosystem has become a potential global problem today and these heavy metals are among the most common environmental pollutants, as well as their occurrence in waters and sediments is originated from natural or anthropogenic sources. A trace amount of heavy metals is always present in fresh waters from terrigenous sources, such as weathering of rocks, which may be recycled through chemical and biological contaminates in sediments in these ecosystems [6-10]. Heavy metal contamination in sediments could affect the quality and bio-assimilation and bioaccumulation of metals in an aquatic ecosystem. Further, these metals are immobilised within the sediments and thus might be involved in absorption, co-precipitation and complex creation [9-13].

Materials and Methods

Study area

Tamirabarani River originates from western Ghat hills flows all along the East coast and drains at Bay of Bengal. The present estuarine region falls in the part of Thoothukudi districts, east coast of Tamil Nadu state, It lies in the SOI toposheet Nos. 58 L/2 and located in between 8°25’ N and 9°10’ N latitudes and 77°10’ E and 78° 15’ E longitudes, with an area of (169.226 Sq. km) (Figure 1). The study area is blessed with deltaic system with different active and inactive distributaries. The southwestern part is dominated by river and the northern part by the sea [14].

earth-science-climatic-change-area

Figure 1: Study area base map.

Sediments sampling and analysis

In the study area, twenty-four sediment samples were collected at the river mouth estuary and distributary channels for two seasons (summer and winter) (Figure 2). The sampling locations were identified and recorded using a hand-held GPS (Magellan); surface sediment’s samples collected and packed in thick polyethylene bags. In the laboratory, the collected samples were frozen at -4°C to avoid soil contamination. The freezing of the samples below -4°C, avoid the growth of microbes or bacteria, which can result in the variation of metal in sediments. These samples were then dried in a hot-air oven and after homogenized using pestle and mortar. Dry sieving is done in 2 mm mesh sieve and stored for further analysis [10,15,16]. The sediment’s samples were digested and extracted based on the procedure of Manasrah et al. [17] and subjected for the assessment of trace metals using AAS with specific flame and wavelength (Atomic Absorption Spectrometer, (Elico make) using a series of solution over the range 2–10 mg/l. The concentration of the metals was normalised and inferred for the following parameter.

earth-science-climatic-change-location

Figure 2: Study location map.

Result And Discussion

Enrichment factor

Enrichment factor (EF) is the proportional abundance of the chemical elements that helps to assess the degree of contamination. EF computed relative to the abundance of species in source material found in the Earth’s crust is considered as a better method for understanding the geochemical trends [8,9,18]. According to Harikuma et al., Sekabira et al., and Chandrasekaran et al. [8-10] has derived six categories as background concentration 1, depletion to minimal enrichment 1–2, moderate enrichment 2–5, significant enrichment 5–20, very high enrichment and 20–40 extremely high enrichment 40 (Table 1). It was found that the entire samples plunge below 1 and thus it is inferred that they represent the background concentration [19-21]. Moreover, the samples with higher Cd and Pb concentration are found in all locations of the study area comparatively higher than others due to the sea interface, which has high pH and salinity (Tables 1-3) and (Figures 3 and 4).

earth-science-climatic-change-factor

Figure 3: Enrichment factor – Summer.

earth-science-climatic-change-winter

Figure 4: Enrichment factor – Winter.

Enrichment Factor                      Status
<1 No enrichment
1-2 Depletion to Minor enrichment
2-5 Moderate enrichment
5-20 Significant enrichment
20-40 Very high enrichment
>40 Extremely high enrichment

Table 1: Enrichment factor standard values.

Location Cu Ni Cr Pb Zn Cd
1 0.534 0.534 0.534 0.534 0.534 0.534
2 0.46 0.46 0.46 0.46 0.46 0.46
3 0.421 0.421 0.421 0.421 0.421 0.42
4 0.524 0.524 0.524 0.524 0.524 0.524
5 0.468 0.468 0.468 0.468 0.468 0.468
6 0.488 0.488 0.488 0.488 0.488 0.488
7 0.46 0.46 0.46 0.46 0.46 0.46
8 0.455 0.455 0.455 0.455 0.455 0.455
9 0.436 0.437 0.437 0.436 0.437 0.437
10 0.453 0.453 0.324 0.453 0.453 0.453
11 0.517 0.516 0.517 0.517 0.517 0.517
12 0.605 0.605 0.605 0.605 0.605 0.605
13 0.688 0.688 0.688 0.688 0.688 0.688
14 0.674 0.669 0.674 0.674 0.674 0.674
15 0.603 0.603 0.603 0.603 0.603 0.603
16 0.517 0.516 0.516 0.516 0.516 0.516
17 0.601 0.6 0.601 0.601 0.601 0.6
18 0.64 0.639 0.637 0.639 0.639 0.64
19 0.563 0.562 0.563 0.562 0.562 0.562
20 0.775 0.774 0.775 0.775 0.775 0.773
21 0.854 0.854 0.854 0.853 0.854 0.853
22 0.812 0.811 0.812 0.811 0.812 0.812
23 0.873 0.872 0.872 0.872 0.867 0.871
24 0.91 0.911 0.912 0.91 0.91 0.954

Table 2: Enrichment factor-Summer.

Location Cu Ni Cr Pb Zn Cd
1 0.432 0.432 0.432 0.432 0.433 0.433
2 0.388 0.388 0.388 0.388 0.388 0.388
3 0.36 0.36 0.36 0.36 0.36 0.36
4 0.403 0.403 0.403 0.403 0.403 0.402
5 0.378 0.378 0.378 0.378 0.378 0.378
6 0.362 0.369 0.369 0.369 0.369 0.369
7 0.38 0.38 0.38 0.38 0.38 0.38
8 0.371 0.371 0.371 0.371 0.371 0.371
9 0.336 0.336 0.336 0.336 0.336 0.336
10 0.369 0.369 0.369 0.369 0.369 0.369
11 0.396 0.396 0.396 0.396 0.396 0.396
12 0.431 0.431 0.431 0.431 0.431 0.431
13 0.443 0.443 0.443 0.443 0.444 0.443
14 0.413 0.413 0.413 0.413 0.413 0.411
15 0.428 0.428 0.428 0.428 0.428 0.428
16 0.402 0.402 0.402 0.402 0.402 0.403
17 0.429 0.429 0.429 0.429 0.429 0.428
18 0.409 0.409 0.409 0.409 0.409 0.409
19 0.388 0.388 0.388 0.387 0.388 0.388
20 0.72 0.751 0.721 0.72 0.721 0.721
21 0.609 0.609 0.609 0.609 0.609 0.61
22 0.663 0.663 0.663 0.663 0.663 0.663
23 0.59 0.59 0.59 0.59 0.597 0.589
24 0.694 0.694 0.694 0.694 0.694 0.694

Table 3: Enrichment factor-Winter.

Contamination factor (CF)

The levels of contamination in sediment by metals are frequently expressed in terms of a contamination factor (CF). If CF, CF >3 means moderate contamination; 3>CF >6 indicates considerable contamination and CF >6 specifies very high contamination. The complete analysis of this contamination factor value of the metals in the study area is compared with the background and toxicological reference values of sediments. It appears that all the metals are low to moderately contaminated, except Cd, which shows very high contamination in all locations than summer. Especially locations from 5 to 18 in downstream area has observed Cd contamination ranging from 78.35 to 106.25 and considerable absorption of Pb is found in downstream (Location 2 to 12) due to variation in salinity, which governs the formation of non-bio available Cd chloride complex, anthropogenic inputs and industrial wastage (Tables 4 and 5) and (Figures 5 and 6).

earth-science-climatic-change-summer

Figure 5: Contamination factor – Summer.

earth-science-climatic-change-contamination

Figure 6: Contamination factor – Winter.

Location Cu Ni Cr Pb Zn Cd
1 0.43 0.184 0.198 1.308 0.291 32.15
2 0.61 0.189 0.288 1.939 0.468 48.3
3 0.539 0.24 0.268 2.296 0.495 43.25
4 0.599 0.381 0.294 1.466 0.552 47.15
5 0.548 0.282 0.272 1.42 0.577 42.6
6 0.523 0.261 0.315 1.488 0.596 51.05
7 0.487 0.286 0.289 1.664 0.497 43.35
8 0.603 0.221 0.355 1.744 0.551 45.75
9 0.592 0.189 0.294 1.176 0.574 52.6
10 0.5 0.301 0.402 1.712 0.635 56.25
11 0.487 0.218 0.384 2.592 0.566 42.35
12 0.579 0.167 0.273 1.936 0.412 46.75
13 0.531 0.258 0.381 2.18 0.426 38.95
14 0.365 0.237 0.397 1.144 0.467 32.05
15 0.332 0.185 0.348 1.112 0.588 37.8
16 0.307 0.179 0.389 1.008 0.401 34.15
17 0.322 0.162 0.397 1.128 0.354 29.1
18 0.341 0.208 0.387 1.008 0.289 33.7
19 0.298 0.17 0.277 1.056 0.264 28.95
20 0.132 0.097 0.146 0.672 0.127 15.9
21 0.154 0.089 0.132 0.632 0.132 13.55
22 0.176 0.103 0.129 0.544 0.126 18.65
23 0.159 0.074 0.147 0.618 0.133 11.4
24 0.166 0.057 0.134 0.694 0.109 15.6

Table 4: Contamination factor-Summer.

Location Cu Ni Cr Pb Zn Cd
1 0.469 0.25 0.418 1.74 0.397 52.15
2 0.68 0.264 0.864 4.896 0.532 68
3 0.594 0.298 1.042 4.193 0.552 71.25
4 0.69 0.421 0.97 4.192 0.596 61.65
5 0.651 0.375 0.866 4.432 0.662 87.6
6 0.614 0.357 0.545 4.296 0.69 93.05
7 0.556 0.366 0.589 4.192 0.568 78.35
8 0.694 0.328 0.542 4.112 0.623 87.25
9 0.687 0.309 0.612 4.368 0.581 92.6
10 0.596 0.408 1.026 4.896 0.692 106.25
11 0.578 0.327 0.964 4.384 0.623 92.35
12 0.663 0.295 0.897 4.096 0.54 97.25
13 0.613 0.272 0.405 2.536 0.549 88.95
14 0.493 0.304 0.642 2.107 0.567 83.55
15 0.441 0.29 0.383 1.832 0.667 87.8
16 0.428 0.33 0.416 1.785 0.552 81.7
17 0.413 0.322 0.446 1.64 0.498 76.6
18 0.469 0.277 0.404 1.808 0.446 83.7
19 0.407 0.296 0.347 1.856 0.35 63.95
20 0.314 0.19 0.194 1.152 0.263 40.9
21 0.336 0.183 0.189 1.354 0.276 39.55
22 0.321 0.197 0.189 1.266 0.24 43.15
23 0.349 0.167 0.194 1.418 0.261 38.4
24 0.331 0.177 0.184 1.31 0.248 42.1

Table 5: Contamination factor-Winter.

Geo-accumulation index (Igeo)

Enrichment of metal absorption was calculated by adopting geoaccumulation [22] methods, termed the geo-accumulation index (Igeo). This method provides the metal pollution in terms of seven (0 to 6) enrichment classes ranging from background concentration to very heavily polluted. (Table 6). Based on the classification system Igeo factors for all samples displays strongly to extremely polluted index for Cd and moderately polluted index for Pb. This higher value is chiefly owing to the salinity factor, comparatively higher than summer. The Igeo ‘‘uncontaminated’’ label is clearly appropriated for overall description of the heavy metals in sediments of estuary. The diagrammatic view of Igeo illustrate that higher values of Cd are distinguished in the estuarine part of the study area and it decreases in upstream area (Tables 7 and 8) and (Figures 7 and 8).

earth-science-climatic-change-accumulation

Figure 7: Geo-accumulation Index – Summer.

earth-science-climatic-change-index

Figure 8: Geo-accumulation Index – Winter.

Igeo value Sediment Quality Location
Cu Ni Cr Pb Zn Cd
< 0 Unpolluted - - - - - -
0-1 From unpolluted to moderately polluted - - - - - -
1-2 Moderately polluted - - - 2 to 12 - -
2-3 From moderately polluted to strongly polluted - - - - - -
3-4 Strongly polluted - - - - - -
4-5 From strongly to extremely polluted - - - - - 20, 21, 22, 23, 24
>5 Extremely polluted - - - - - 1 to 19

Table 6: Geo-accumulation index standard values.

Location Cu Ni Cr Pb Zn Cd
1 -1.797 -3.026 -2.916 0.196 -2.362 4.421
2 -1.295 -2.986 -2.375 0.368 -1.677 5.006
3 -1.471 -2.641 -2.481 0.611 -1.598 4.847
4 -1.322 -1.973 -2.348 0.029 -1.441 4.973
5 -1.451 -2.408 -2.461 0.076 -1.375 4.827
6 -1.518 -2.518 -2.249 0.009 -1.328 5.086
7 -1.621 -2.388 -2.375 0.149 -1.591 4.856
8 -1.312 -2.76 -2.076 0.215 -1.441 4.93
9 -1.338 -2.98 -2.348 0.348 -1.455 5.129
10 -1.581 -2.315 -1.897 0.189 1.235 5.229
11 -1.621 -2.78 -1.963 0.787 -1.401 4.817
12 -1.368 -3.159 -2.455 0.365 -1.863 4.96
13 -1.495 -2.534 -1.973 0.538 -1.813 4.697
14 -2.036 -2.657 -1.916 -0.388 -1.681 4.415
15 -2.172 -3.016 -2.106 -0.428 -1.348 4.654
16 -2.285 -3.063 -1.946 -0.571 -1.9 4.508
17 -2.215 -3.205 -1.913 -0.408 -2.079 4.275
18 -2.132 -2.85 -1.95 -0.571 -2.372 4.488
19 -2.328 -3.139 -2.435 -0.504 -2.504 4.269
20 -3.501 -3.943 -3.358 -1.156 -3.554 3.405
21 -3.279 -4.059 -3.504 -1.245 -3.495 3.172
22 -3.086 -3.853 -3.538 -1.458 -3.571 3.634
23 -3.229 -4.328 -3.348 -1.275 -3.495 2.923
24 -3.172 -4.694 -3.475 -1.109 -3.774 3.378

Table 7: Geo-accumulation Index Summer.

Location Cu Ni Cr Pb Zn Cd
1 -1.674 -2.578 -1.84 0.212 -1.916 5.119
2 -1.139 -2.501 -0.794 1.704 -1.491 5.501
3 -1.335 -2.325 -0.524 1.481 -1.438 5.568
4 -1.116 -1.183 -0.627 1.481 -1.328 5.358
5 -1.202 -1.996 0.79 1.561 -1.176 5.867
6 -1.285 -2.069 -1.458 1.521 -1.118 5.953
7 -1.428 -2.033 -1.345 1.481 -1.398 5.704
8 -1.109 -2.192 -1.468 1.451 -1.265 5.86
9 -1.122 -2.275 -1.292 1.541 -1.365 5.946
10 -1.328 -1.877 -0.544 1.704 -1.112 6.146
11 -1.375 -2.196 -0.637 1.544 -1.265 5.943
12 -1.176 -2.342 -0.74 1.448 -1.471 6.016
13 -1.289 -2.461 -1.887 0.757 -1.448 5.89
14 -1.601 -2.302 -1.222 0.488 -1.401 5.797
15 -1.76 -2.365 -1.966 0.285 -1.166 5.87
16 -1.803 -2.182 -1.847 0.249 -1.438 5.767
17 -1.857 -2.215 -1.474 0.126 -1.588 5.674
18 -1.674 -2.435 -1.89 0.269 -1.744 5.8
19 -1.877 -2.335 -2.109 0.305 -2.099 5.411
20 -2.252 -2.973 -2.95 -0.378 -2.508 4.767
21 -2.219 -3.033 -2.986 -0.146 -2.438 4.72
22 -2.219 -2.926 -2.986 -0.242 -2.641 4.843
23 -2.102 -3.159 -2.95 -0.077 -2.518 4.677
24 -2.176 -3.073 -3.023 -0.192 -2.594 4.81

Table 8: Geo-accumulation index-Winter.

Pollution Load Index

Tomlinson et al. [23] has employed a simple method for Pollution Load Index (PLI) to assess the extent of pollution in metals of estuarine sediments. It is given as, if, PLI >1 as “polluted” and if < 1 as “no pollution”. In the study area, pollution load index values exhibited gives valuable information for the policy and decision makers on the pollution level of the area. The highest PLI values were observed in lower part of the river or estuary were water interchanges area of the river. The river with more water gives an idea about comparatively lower PLI values.

The PLI values for summer and winter for Pb are (1.240 and 2.566) and Cd (2,615 and 69.963) describes higher PLI in winter than summer. It is noted that Pb and Cd are the major pollutants contributing elevated PLI values in the study area (Table 9).

Metals Seasons Standard value Remarks
Summer Winter
Cu 0.367 0.498 >1 Unpolluted
Ni 0.179 0.282 >1 Unpolluted
Cr 0.269 0.476 >1 Unpolluted
Pb 1.240 2.566 <1 Polluted
Zn 0.349 0.472 >1 Unpolluted
Cd 2.615 69.963 <1 Polluted

Table 9: Pollution load index.

Conclusion

It is estimated that EF of all samples in the study area go down below 1 and thus it is inferred that they represent the background concentration. Moreover, the samples with higher Cd and Pb concentration are found in all locations. This enrichment factors suggest minor to moderate enhancement of Cd and Pb is present in the sediments. Higher concentration of Cd and Pb are observed in winter season is due to high pH, salinity and anthropogenic activity in seaward and in downstream direction as a result of sea interface. The comprehensive analysis of the contamination factor for the average values of the metals in the study is compared with the background and toxicological reference values of sediments. It appears that all the metals are low to moderately contaminated, except Cd, which shows very high contamination. The element contribution and enrichment of metals compared with the toxicological levels shows that Tamirabarani River and estuary sediments are moderately polluted. The spatial distributions of contamination factor illustrate higher values for Cd is nearer the estuary region with varied salinity and tidal fluctuation, which is in agreement with the earlier interpretations. Based on the classification system proposed for Igeo factors, all samples have strongly to extremely polluted index for Cd and moderately polluted index for Pb. This upper value is mainly due to the salinity factor in summer. Spatial representation of Igeo shows that higher values of Cd are noted in estuarine part of the study area and decreases towards inland followed by Pb. Hence, it is inferred that the variation of this metal is mainly due to the variation in physico-chemical factors in the estuary. The highest PLI values were observed in lower part of the estuary, by outstanding massive mixing of sea and river water. The main streams with enormous water illustrate relatively lower PLI values. The PLI values for most of the sites confirm higher values in winter than in summer and Pb and Cd are the major pollutants contributing high PLI values. The results could be used as a baseline data for future prediction of anthropogenic effects, which can be utilized to assess and defined to establish a better management decision plan to reduce pollution.

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Citation: Mukesh MV, Chandrasekaran A, Premkumar R, Keerthi BN (2018) Metal Enrichment and Contamination in River and Estuary Sediments of Tamirabarani, South India. J Earth Sci Clim Change 9: 497. DOI: 10.4172/2157-7617.1000497

Copyright: © 2018 Mukesh MV, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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