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Phase II; III rd Objective: Assessment of sediment column quality with respect to heavy metals

PHASE I LULC

4.6. Phase II; III rd Objective: Assessment of sediment column quality with respect to heavy metals

Materials and methods Chapter | 4

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where 𝐻𝑖 and π»π‘–π‘šπ‘Žπ‘₯ represent the monitored and permissible values of the ith parameter, respectively. Classification of the water samples for HEI is based on the multiples of the mean value obtained.

4.6. Phase II; III

rd

Objective: Assessment of sediment column quality

VaverkovΓ‘ et al. 2018). All the analyses were carried out using Atomic Absorption Spectro- photometer (AAS) (Varian-Spectra 55B), and all the measurements were taken in triplicates.

All the standards were prepared under controlled conditions. The absorbance values of the standards were well within the acceptable limits, and the values obtained for the blanks were always less than the minimum detection limits (MDLs). The standard deviation of all the trip- licates was observed to be less than 5%.

The details of the clustering process, principal component analysis, and positive matrix factorization model have already been explained in section 4.4. Details of other methodolo- gies adopted are presented in the following sub-sections.

4.6.1. Metal contamination and risk assessment

Various tools were employed to determine the heavy metal contamination of the sediment samples of Deepor Beel, as well as its potential ecological risk corresponding to each heavy metal. A detailed description of the indices is as follows:

a. Contamination Factor (CF)

The contamination factor (CF) proves to be the first step towards the risk assessment, which is estimated as the ratio of the observed metal concentration to its corresponding reference value (Eq. 4. 49) (Islam et al. 2015a). In the present study, the background concentrations of the metals are considered to be the reference values (Fukue et al. 2006). It is usually esti- mated to determine a metal’s contamination level.

𝐢𝐹 =πΆπ‘š

𝐢𝑏 4. 49

where πΆπ‘š and 𝐢𝑏 indicate the observed metal concentration and its corresponding back- ground value. The CF is categorized as:

𝐢𝐹 = {

< 1 π‘™π‘œπ‘€ π‘π‘œπ‘›π‘‘π‘Žπ‘šπ‘–π‘›π‘Žπ‘‘π‘–π‘œπ‘› 1 βˆ’ 3 π‘šπ‘œπ‘‘π‘’π‘Ÿπ‘Žπ‘‘π‘’ π‘π‘œπ‘›π‘‘π‘Žπ‘šπ‘–π‘›π‘Žπ‘‘π‘–π‘œπ‘› 3 βˆ’ 6 π‘π‘œπ‘›π‘ π‘–π‘‘π‘’π‘Ÿπ‘Žπ‘π‘™π‘’ π‘π‘œπ‘›π‘‘π‘Žπ‘šπ‘–π‘›π‘Žπ‘‘π‘–π‘œπ‘›

β‰₯ 6 π‘£π‘’π‘Ÿπ‘¦ β„Žπ‘–π‘”β„Ž π‘π‘œπ‘›π‘‘π‘Žπ‘šπ‘–π‘›π‘Žπ‘‘π‘–π‘œπ‘›

4. 50

b. Pollution Load Index (PLI)

The pollution load index is determined based on Eq. 4. 51. It provides a picture of the overall pollution of a particular site or locality by providing its toxicity state (Angulo 1996;

Dhamodharan et al. 2019). It is categorized as sites having no pollution (PLI ≀ 1), slight pol- lution (1 ≀ PLI ≀ 2), moderate pollution (2 ≀ PLI ≀ 3), or highly polluted (PLI > 3) (Liu et al.

2016a; Liu et al. 2016b).

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𝑃𝐿𝐼 = βˆšπΆπΉπ‘ 1Γ— 𝐢𝐹2Γ— 𝐢𝐹3Γ— … Γ— 𝐢𝐹𝑝 4. 51

where CF indicates the contamination factor for each p (7 in this case) heavy metals.

c. Enrichment Factor (EF) and Geo-accumulation index (Igeo)

The enrichment factor (EF) is a well-established technique for estimating the degree of con- taminants in the environment (Liaghati et al. 2004; Franco-UrΓ­a et al. 2009), given by Eq. (4.

52). Here, iron (Fe) is used as a tracer distinguishing natural and anthropogenic contamina- tion.

𝐸𝐹 = {πΆπ‘š

𝐢𝐹𝑒}

π‘ π‘Žπ‘šπ‘π‘™π‘’

{πΆπ‘š

𝐢𝐹𝑒}

𝐡𝐺

4. 52

where BG corresponds to the background concentration of the heavy metal; πΆπ‘š and 𝐢𝐹𝑒 correspond to the concentrations of the metal and iron, respectively. EF is responsible for determining whether a particular site is affected by anthropogenic contamination. Thus, EF is categorized as:

𝐸𝐹 = {

≀ 1 𝐡𝐺 π‘π‘œπ‘›π‘π‘’π‘›π‘‘π‘Ÿπ‘Žπ‘‘π‘–π‘œπ‘› 1 βˆ’ 2 π‘€π‘–π‘›π‘–π‘šπ‘’π‘š π‘’π‘›π‘Ÿπ‘–π‘β„Žπ‘šπ‘’π‘›π‘‘ 2 βˆ’ 5 π‘€π‘œπ‘‘π‘’π‘Ÿπ‘Žπ‘‘π‘’ π‘’π‘›π‘Ÿπ‘–π‘β„Žπ‘šπ‘’π‘›π‘‘ 5 βˆ’ 20 π‘†π‘–π‘”π‘›π‘–π‘“π‘–π‘π‘Žπ‘›π‘‘ π‘’π‘›π‘Ÿπ‘–π‘β„Žπ‘šπ‘’π‘›π‘‘ 20 βˆ’ 40 π‘‰π‘’π‘Ÿπ‘¦ β„Žπ‘–π‘”β„Ž π‘’π‘›π‘Ÿπ‘–π‘β„Žπ‘šπ‘’π‘›π‘‘

> 40 𝐸π‘₯π‘‘π‘Ÿπ‘’π‘šπ‘’π‘™π‘¦ β„Žπ‘–π‘”β„Ž π‘’π‘›π‘Ÿπ‘–π‘β„Žπ‘šπ‘’π‘›π‘‘

4. 53

The geo-accumulation index (Igeo) (Eq. 4. 54) is a widely accepted tool for determining the heavy metal contamination of the sediment samples and comparing the current contamina- tion levels to that of the pre-industrial levels (Muller 1969; Chakravarty & Patgiri 2009; El- Amier et al. 2017). The categorization adopted for Igeo is shown through Eq. 4. 55

πΌπ‘”π‘’π‘œ= log2{ 𝐢𝑝 1.5𝐡𝑝

} 4. 54

πΌπ‘”π‘’π‘œ=

{

≀ 0 π‘π‘œπ‘‘ π‘π‘œπ‘™π‘™π‘’π‘‘π‘’π‘‘

0 βˆ’ 1 π‘π‘œ π‘‘π‘œ π‘šπ‘œπ‘‘π‘’π‘Ÿπ‘Žπ‘‘π‘’ π‘π‘œπ‘™π‘™π‘’π‘‘π‘–π‘œπ‘› 1 βˆ’ 2 π‘€π‘œπ‘‘π‘’π‘Ÿπ‘Žπ‘‘π‘’ π‘π‘œπ‘™π‘™π‘’π‘‘π‘–π‘œπ‘› 2 βˆ’ 3 π‘€π‘œπ‘‘π‘’π‘Ÿπ‘Žπ‘‘π‘’ π‘‘π‘œ π‘ π‘‘π‘Ÿπ‘œπ‘›π‘” π‘π‘œπ‘™π‘™π‘’π‘‘π‘–π‘œπ‘› 3 βˆ’ 4 π‘†π‘‘π‘Ÿπ‘œπ‘›π‘” π‘π‘œπ‘™π‘™π‘’π‘‘π‘–π‘œπ‘› 4 βˆ’ 5 π‘†π‘‘π‘Ÿπ‘œπ‘›π‘” π‘‘π‘œ 𝑒π‘₯π‘‘π‘Ÿπ‘’π‘šπ‘’ π‘π‘œπ‘™π‘™π‘’π‘‘π‘–π‘œπ‘›

> 5 𝐸π‘₯π‘‘π‘Ÿπ‘’π‘šπ‘’ π‘π‘œπ‘™π‘™π‘’π‘‘π‘–π‘œπ‘›

4. 55

TH-2896_176104004

where Cp and Bp indicate the observed and background concentration of the pth heavy metal. The number 1.5 is used as a background correction of the matrix.

d. Potential ecological risk (PER)

The potential ecological risk (PER) is introduced for assessing the impact of one or more ele- ments on the ecology of a particular study area. The method considers the risk index (RI), which reflects the sensitivity of the biological community and their toxicity response (Islam et al. 2015b). The primary governing equations involved are represented by Eq. (4. 56 - 4. 58).

𝑅𝐼 = βˆ‘ πΈπ‘Ÿπ‘

𝑛

𝑝=1

4. 56

where,

πΈπ‘Ÿπ‘= 𝐢𝐹𝑝× π‘‡π‘Ÿπ‘ 4. 57

π‘‡π‘Ÿπ‘= {

10 𝐴𝑠

30 𝐢𝑑

2 πΆπ‘Ÿ

5 𝐢𝑒, 𝑃𝑏 π‘Žπ‘›π‘‘ 𝑁𝑖

1 𝑍𝑛

40 𝐻𝑔

4. 58

The basic nomenclatures involved in estimating the PER are as follows:

πΈπ‘Ÿπ‘ indicates the potential ecological risk index for each heavy metal (Yi et al. 2011); CF is the contamination factor; π‘‡π‘Ÿπ‘ is the toxicity response coefficient for each element given in Eq.

4. 58 (Islam et al. 2015a; Lu et al. 2015). 4 metals (Cr, Cd, Cu, and Pb) were investigated for assessing the potential ecological risk of the wetland through the sediment contamination as the values of π‘‡π‘Ÿπ‘ for other metals were unavailable. Therefore, another term called the inte- grated pollution degree (𝐢𝑑) has been coined as follows:

𝐢𝑑= βˆ‘ 𝐢𝐹𝑝

𝑛

𝑝=1

4. 59

𝐢𝑑 is categorized as given in Eq. 4. 60 (Fu et al. 2009).

𝐢𝑑= {

< 5 πΏπ‘œπ‘€ π‘π‘œπ‘™π‘™π‘’π‘‘π‘–π‘œπ‘› 5 βˆ’ 10 π‘€π‘œπ‘‘π‘’π‘Ÿπ‘Žπ‘‘π‘’ π‘ƒπ‘œπ‘™π‘™π‘’π‘‘π‘–π‘œπ‘› 10 βˆ’ 20 π»π‘–π‘”β„Ž π‘ƒπ‘œπ‘™π‘™π‘’π‘‘π‘–π‘œπ‘›

β‰₯ 20 π‘‰π‘’π‘Ÿπ‘¦ β„Žπ‘–π‘”β„Ž π‘π‘œπ‘™π‘™π‘’π‘‘π‘–π‘œπ‘›

4. 60

RI and πΈπ‘Ÿπ‘ can be categorized as given in Eq. 4. 61 (Guo et al. 2010).

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𝑅𝐼 = {

< 150 πΏπ‘œπ‘€ π‘Ÿπ‘–π‘ π‘˜ 150 βˆ’ 300 π‘€π‘œπ‘‘π‘’π‘Ÿπ‘Žπ‘‘π‘’ π‘Ÿπ‘–π‘ π‘˜ 300 βˆ’ 600 πΆπ‘œπ‘›π‘ π‘–π‘‘π‘’π‘Ÿπ‘Žπ‘π‘™π‘’ π‘Ÿπ‘–π‘ π‘˜

β‰₯ 600 π‘†π‘–π‘”π‘›π‘–π‘“π‘–π‘π‘Žπ‘›π‘‘ π‘Ÿπ‘–π‘ π‘˜

4. 61

πΈπ‘Ÿπ‘= {

< 40 πΏπ‘œπ‘€ π‘Ÿπ‘–π‘ π‘˜ 40 βˆ’ 80 π‘€π‘œπ‘‘π‘’π‘Ÿπ‘Žπ‘‘π‘’ π‘Ÿπ‘–π‘ π‘˜ 80 βˆ’ 160 πΆπ‘œπ‘›π‘ π‘–π‘‘π‘’π‘Ÿπ‘Žπ‘π‘™π‘’ π‘Ÿπ‘–π‘ π‘˜ 160 βˆ’ 320 π»π‘–π‘”β„Ž π‘Ÿπ‘–π‘ π‘˜

β‰₯ 320 π‘‰π‘’π‘Ÿπ‘¦ β„Žπ‘–π‘”β„Ž π‘Ÿπ‘–π‘ π‘˜

4.6.2. Heavy metal fractionation of sediment column

Chemical proportioning of heavy metals for the sediment samples was carried out using the procedure laid down by Tessier et al. (1979). Five different fractional speciations were ob- tained, the details of which are given in Table 4. 8 (Gibbs 1973; Salomons & FΓΆrstner 1980).

Table 4. 8. Speciation of heavy metals in sediments and their extraction procedures.

Frac-

tion Form Extraction protocol

F1 Exchangeable *Sample is first extracted with 7.5mL of 0.05M ammonium acetate (Duration of 1 h).

F2 Bound to Carbonates *Residue obtained from F1 is extracted with 10mL of 0.17M acetic acid at pH 7.0 (Duration of 5 h).

F3 Reducible (iron and manganese oxides)

**F2 residue obtained is extracted with 20mL of hydroxyl ammo- nium chloride in 25% (v/v) acetic acid at pH 5.0, at 96Β±3 Β°C (Dura- tion of 5 h).

F4 Oxidizable Bound to organic matter and sulphide

**F3 residue obtained is extracted with 5mL of 0.02M nitric acid and 5mL of 3% hydrogen peroxide at 85Β±2 Β°C (Duration of 2 h).

*This is followed by the addition of 6mL of hydrogen peroxide (Du- ration of 3 h). After cooling, 5mL of 3.2M ammonium acetate is added with 20% (v/v) nitric acid (Duration of 30 min).

F5 Residual (lattice) F4 residue obtained is extracted with a mixture of hydrofluoric and nitric acid (1:1, v/v) and then is subjected to digestion under pres- sure and temperature in a closed container.

* Continuous agitation is provided.

**Occasional agitation is provided.

After each extraction, the samples were centrifuged, and the supernatant was decanted before pro- ceeding to the subsequent extraction process.

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4.6.3. Elemental analyses

XRD analysis was carried out for three samples (powdered); (i) samples from the central zone, (ii) Boragaon landfill site and (iii) industrial zone to determine the forms in which the HMs are present in the samples. SEM-EDS quantitative analyses were furthermore carried out to determine the morphology and the elemental composition of the sediment samples. Two representative samples (powdered) were chosen; one from the eastern part of the wetland (proximate to the Boragaon landfill) and the other from the western part (industrial zone).

Elemental mapping of the samples was done to determine the weight percentages of the HMs present in those samples.

4.7. Phase II; IV

th

Objective: Understanding the dynamics of heavy

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