Determination of Magnetic Susceptibility and Metal Enrichment Sediments Traps of High Altitude Himalayan Lake, The Chandratal Spiti, Himachal Pradesh, India

doi:10.21203/rs.3.rs-2719627/v1

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Determination of Magnetic Susceptibility and Metal Enrichment Sediments Traps of High Altitude Himalayan Lake, The Chandratal Spiti, Himachal Pradesh, India

https://doi.org/10.21203/rs.3.rs-2719627/v1

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High Altitude Lake have a complex mechanism because they are influenced by glacial climatic conditions, weathering of bedrocks and river transportation and deposition, which causes enrichment of metal concentration and magnetic components in the zone. The present study investigated the magnetic properties and their relation between geochemistry of 11 surface sediment samples and 01 core sediment sample in the High Altitude Himalayan Lake, The Chandratal Spiti. The Geoaccumulation Index of the all metals concentration shows extremely high values than standard ranges > 5 (extremely polluted). The Magnetic susceptibility of χLF substantial higher at surface sampling point 8 and core sediment at depth of 42 to 44 cm and 80 to 82 cm. Simultaneously the χFD% (< 2% - No super paramagnetic grains/multi domain grain size) shows drastically decrease at χLF maximum points. With the XRD mineralogy analysis shows mostly Zircon, Illite and Quartz minerals proves the lake sedimentology. The χLF / χFD ratio were found to be an obvious parameter for identifying areas of sediment traps and metal enrichment in the surface sediment and temporal sediments of High Altitude Lake. The high χLF / χFD at surface sampling point 8 and at depth as 42 to 44 cm and 84 to 86 cm probably arose because the point is in large magnetic sediment traps zone. The Pb²¹⁰ and Cs¹³⁷ has linearly correlated with the χLF / χFD sediment trapped peak of the core sediment at the depth 42 to 44 cm infers the age as 1991 and 1993 years.

Metal Enrichment

Geoaccumulation Index

Magnetic Susceptibility

Pb210 and Cs137 Radioisotopes

Sedimentation traps

High Altitude Himalayan Lake.

In the recent decade, the researcher concentrated primarily on the variation in the glacial lake of the Himalayan regions. Estimating heavy metal contamination and related ecological concerns can be assessed using consensus-based indices because sediments are known as storehouses for heavy metals (Addo et al., 2012; Nilin et al., 2013; Atibu et al., 2016; Benson et al., 2017). A watershed's land use and land cover may significantly impact the amount of metal that reaches a lake (Paul et al., 1996). Lake sediments primarily absorb heavy metals, although they can also be transported to the overlying water in the lakes (Thevenon, F. et al., 2011; Varol, M. & Sen, B., 2012). In order to prevent changes and deleterious effects on the sustainability of living organisms and their ecosystems, environmental monitoring is essential (Chandrasekaran et al., 2020; Kumari et al., 2020).

Heavy metals' toxicity and susceptibility to bioaccumulation in aquatic biota constitute a significant threat to aquatic ecosystems (Sakan et al., 2009; Harikrishnan et al., 2017; Bessa et al., 2018; Slukovskii et al., 2020; Adikaram et al., 2021). Due to their toxicity, persistence, and problems with bioaccumulation, heavy metals constitute the primary toxins in the environment (Pekey, 2006; Nouri et al., 2006). Sediment core analysis has proven to be a highly effective method for determining the effects of anthropogenic and natural processes on the depositional environment (Vinodhini & Narayanan, 2008; Nadia, 2009). As a result, the top few centimeters of the sediments reflect the continuously changing degree of contamination in the present, while the sediments at the bottom preserve their history. Several authors have published outstanding work on the significant metal geochemistry and environmental factors in various lakes (Michelutti N et al., 2015; Remor M.B et al., 2018; Brinkmann, R., 2020).

With significant advantages, magnetic methods are utilized as a stand-in for heavy metal pollution in urban dust, river sediments, and cultivated soils. These procedures are non-destructive, affordable, quick, sensitive, and scalable (Chaparro et al., 2008; Dong et al., 2014), whereas previous geochemical techniques are more complex, time-consuming, and restricted to point samples (Zhang et al., 2011; Chaparro et al., 2017b). Sediment sorting and lithology significantly impact magnetic characteristics; hence, care should be taken when using magnetic methods to evaluate fluvial sediment sources (Mzuza et al., 2017; Singh et al., 2021). Significant relationships between specific magnetic properties and heavy metal concentrations imply that they may be a reliable indicator of heavy metal contamination in places with a significant human impact (Dong et al., 2014; Guo et al., 2015). The assessment of mineral properties and the source of those minerals will be made possible by measuring both magnetic parameters and heavy metal concentrations in contaminated environments (Chaparro et al., 2017b; Magiera et al., 2018).

Radioisotopes from both natural and artificial sources can be found in lake sediments. The radioisotopes 137Cs (Cesium-137) and 210Pb (Lead-2110) have been discovered to be particularly helpful for dating sediments that deposit in lakes and reservoirs out of all the radioisotopes that occur naturally and artificially in the environment (Robbins et al., 1975; Ritchie & Mc Honry, 1985; Edington et al., 1991; Bhismkumar et al., 2007; Semertzidou P., 2019; Singh et al., 2021). Anthropogenic ¹³⁷Cs and natural radionuclide ²¹⁰Pb were used to estimate the current sedimentation rate in lake sediments (Edington et al., 1991; Putyrskaya V et al., 2020; Strakhovenko V, 2020).

The main motto of this paper is to establish the sediment traps relationship between the Magnetic susceptibility, Geochemistry of the surface & core sediments. This is the first study to correlate the core sediment's magnetic susceptibility, Geochemistry with the radioactive isotopes to identify the temporal variation of sedimentation rate to decode the metal traps at paleo-ages of the Chandratal Lake, Himalayan region. The main reason to choose the lake is to assess the metal concentration status of the high altitude region lake with the natural and anthropogenic processes and its mitigation measures to protect the ecological status and aquatic organisms of the lakes from the enrichment of concentration.

The study area “Chandratal Lake” (Chandertal or Chandratal or The Moon Lake or Tsochikgma) is a glacial lake located in the Spiti part of Lahul and Spiti District of Himachal Pradesh in the middle Himalaya of Holocene age (Fig. 1). It is situated at an altitude of about 4,300 meters (14,100ft). It exhibits a coordinate of 32.475180 N latitude and 77.617060E longitude. The geology of the study area includes Palaeozoic to younger Neoproterozoic formations. The Geomorphological features of the study area such as glacial moraines, ridges, valleys, cirques, talus, Pediment slopes, flood plain. Sedimentary rocks include limestone, siltstone, sandstone, Quartzite, conglomerate, shale, dark green and black amphiboles, and migmatites.

The sampling points are shown as 11 points in the spatial view and 01 core point at the outlet of the study area in Fig. 2. The core sediment samples are separated into 50 subsamples by 2 cm intervals. The sediment samples were collected using the sediment grabben and gravity corer of the Chandratal Lake and transported in plastic containers. Sediments dried at 60˚C in the Hot air Oven for about 24 hours. From the dried sediments, the samples have been analyzed. The sediment samples were analyzed for mineralogy using X-Ray Diffraction. About 1.2 mg of the sediment samples were taken for the elemental analysis. EDX-ray fluorescence techniques considerable to destructive analytical methods can perform the geochemical elemental investigation for the presently studied samples. Metal enrichment of the sediments derived from the geoaccumulation index (I _geo). The formula for the I _geo index is mentioned as,

I _geo = log₂ (Cn / 1.5 Bn), where Cn – Metal concentration of the sampling point; Bn – Geological Background value of the sampling elements. …………… .Eq. (1)

The raw samples were used for the magnetic susceptibility to quantify the magnetic contents. The Magnetic susceptibility estimation was completed by utilizing a Magnetic susceptibility meter. Bartington Instrument Ltd connected to MS2B dual-frequency sensor (0.47 kHz and 4.7 kHz). The High-frequency mass-based magnetic susceptibility (χHF) and its low-frequency mass-based magnetic susceptibility (χLF). The frequency dependence magnetic susceptibility (χFD %) could be calculated from the following equation,

χFD = (χLF – χHF/ χLF) …………………………………………........Eq. (2)

χFD% = (χLF – χHF / χLF) * 100% (Dearing JA et.al, 1996)……..….Eq. (3)

The radiogenic isotopes of ¹³⁷Cs and ²¹⁰Pb were analyzed for sedimentation rate in the core samples by the 1K multi-channel Analyzer NETS-3M/U and Alpha spectrometer – PAS-01 (ORTEC, OCTAT) in Bhabha Atomic Research Centre (BARC), Government of India, Mumbai. Statistical interpretation is carried out in SPSS software to correlate the analyzed data (Hamdan et al., 2020).

In developing countries, particularly India, ecotoxicology assessments and studies establish background levels for sediments. So for this study, globally accepted Geoaccumulation, Magnetic susceptibility, and radioactive isotope methods were used instead of sediment traps of metal enrichments. The studied result of the XRF analysis is shown in Table 1a & 1b. Metal concentration for each sample of surface and core sediments includes Ti, Mn, Fe, Zr, Co, Sr, Rb, Mo, Pb, Zn, Cr, Ni, Cu, and Ba (Fig. 3). The Mean metal concentration of the sampling points decreases in the order of Fe (24267 ppm) > Ti (3276 ppm) > Mn (595 ppm) > Co (289 ppm) > Ba (335 ppm) > Zr (232 ppm) > Rb (131 ppm) > Cr (98 ppm) > Zn (35 ppm) > Sr (50 ppm) > Pb (24 ppm) > Cu (20 ppm) > Ni (23 ppm) > Mo (14 ppm). In temporal, the mean metal concentration is arranged in order of Fe (8266.7 ppm) > Ti (1400 ppm) > Ba (199 ppm) > Mn (141 ppm) > Co (106 ppm) > Zr (101 ppm) > Cr (70 ppm) > Rb (42 ppm) > Sr (27 ppm) > Ni (22 ppm) > Mo (16 ppm) > Zn (11 ppm) > Cu (17 ppm) > Pb (8.9 ppm) shown in Fig. 4.

Table 1

a Metal Concentration in surface sediment samples
Elements	Ti	Mn	fe	Zr	Co	Sr	Rb	Mo	Pb	Zn	Cr	Ni	Cu	Ba
Maximum	7322	1074	45926	328	607	90	187	21	58	100	174	23	24	605
Minimum	1299	100	5853	76	80	21	19	8	7	11	62	23	16	182
Average	3942	593	24516	227	297	50	126	13	25	38	101	23	19	361
Table 1b Metal Concentration in Core sediment samples
Maximum	2692	298	14059	159	201	63	89	29	23	24	95	42	23	258
Minimum	435	41	4061	61	53	13	14	7	6	7	57	18	15	163
Average	1400	141	8266	101	105	26.94	41.64	15.52	8.86	11.44	69.74	22.44	17.08	199.06
Table 1c Heavy Metal Geoaccumulation Index (Igeo) for the Surface Sediment Samples
Maximum	24.42	19.22	30.43	15.09	12.91	14.14	14.09	5.19	9.59	12.63	13.35	10.03	9.49	17.84
Minimum	21.93	15.79	27.46	12.98	9.98	12.04	10.79	3.79	6.54	9.44	11.86	10.03	8.91	16.10
Average	23.36	17.91	29.26	14.40	11.61	13.15	13.19	4.52	7.99	10.90	12.49	10.03	9.21	16.96
Table 1d Heavy Metal Geoaccumulation Index for the Core Sediment Samples
Maximum	22.98	17.37	28.72	14.05	11.31	13.62	13.02	5.65	8.26	10.57	12.48	10.89	9.43	16.61
Minimum	20.35	14.50	26.93	12.67	9.39	11.34	10.35	3.60	6.32	8.79	11.74	9.67	8.81	15.94
Average	21.92	16.14	27.88	13.35	10.31	12.34	11.74	4.68	6.81	9.41	12.03	9.99	9.00	16.23

The Geoaccumulation Index of the sediments shown in Table 1c indicates the surface sediments of the lake, and Table 1d infers subsamples of the core sediments. In the 11 points of the surface and sub-samples of core sediments, shows all metal concentrations of geoaccumulation Index are relatively higher than the standard ranges (> 5 – Extremely polluted). In spatial and core samples, there are no isolated, vulnerable zones, as it appears to be those elements very strongly pollute the whole lake.

In Tables 2 & 3 shows the Magnetic susceptibility results of Low frequency, High Frequency, and Frequency dependence. The outcomes of the analyses show that the values at each sampling point are different. In spatially, the extreme susceptibility peaks at point 8, and the χFD is drastically lower at point 8 in the study area (Fig. 5a). Temporally, the gradually increasing with maximum susceptibility value shows at 42 to 44 and 80 to 82 cm. The χFD infers drastically reduced at maximum value of susceptibility 42 to 44 and 80 to 82 cm (Fig. 5b).

Table 2

Magnetic Susceptibility Measurement data for Surface Sediment Samples
S.No	χLF (×10^− 8 m³.Kg)	χHF (×10^− 8 m³.Kg)	FD%
1	0.57	0.56	1.75
2	3.98	3.85	3.14
3	3.22	3.12	3.07
4	4.2	4.07	3.07
5	4.34	4.24	2.22
6	4.66	4.45	4.5
7	4.61	4.43	3.86
8	6.68	6.66	0.29
9	5.89	5.61	4.7
10	5.02	4.79	4.55
11	1.85	1.75	5.32

Table 3

Magnetic Susceptibility Data for Core sediment
Depth in cm	χLF(×10^− 8 m³.Kg)	χHF(×10^− 8 m³.Kg)	FD%	Lf/FD
2	0.86	0.71	18.18	5.73
4	0.81	0.46	42.86	2.31
6	0.53	0.47	11.54	8.83
8	0.84	0.53	36.59	2.71
10	0.55	0.37	32.14	3.06
12	0.89	0.58	34.78	2.87
14	0.37	0.25	31.58	3.08
16	0.46	0.27	41.67	2.42
18	0.76	0.38	50	2.00
20	0.67	0.26	61.76	1.63
22	0.56	0.32	42.31	2.33
24	0.63	0.41	34.38	2.86
26	0.57	0.41	28.57	3.56
28	0.42	0.32	23.81	4.20
30	1.28	1.2	6.06	16.00
32	1.63	1.22	25.3	3.98
34	1.82	1.55	14.89	6.74
36	1.69	1.44	14.44	7.04
38	1.36	0.66	51.35	1.94
40	1.83	1.39	23.96	4.16
42	1.92	1.91	0.98	96.00
44	1.5	1.38	7.89	12.50
46	1.33	1.15	13.24	7.39
48	1.53	1.06	30.67	3.26
50	2.05	1.75	14.55	6.83
52	2.18	1.67	23.53	4.27
54	1.5	1.19	20.99	4.69
56	1.45	1.14	21.33	4.68
58	1.17	0.8	31.67	3.16
60	1.1	0.87	20.69	4.78
62	1.27	0.78	38.46	2.59
64	1.47	1.19	18.75	5.44
66	1.55	1.16	25	3.97
68	1.5	1.23	17.5	5.77
70	1.52	1.16	23.53	4.22
72	1.08	0.85	21.67	4.70
74	1.54	1.34	12.94	7.70
76	1.13	0.65	42.86	2.31
78	1.25	0.71	42.86	2.36
80	2.26	2	11.54	8.69
82	2.17	1.62	25.22	3.95
84	2.36	2.29	2.99	33.71
86	2.14	1.84	13.91	7.13
88	2.55	2.28	10.64	9.44
90	3.17	2.95	6.9	14.41
92	1.54	1.38	10.71	9.06
94	1.93	1.66	14.29	6.89
96	1.94	1.65	15.09	6.69
98	1.7	1.4	17.78	5.67
100	2.15	1.48	31.03	3.21

The XRD analysis result shows in Fig. 6. The data shows that the mineral composition of the lake consists of Zircon, illite, and quartz. The anticipated result proves the similar mineralogical properties of the lake sedimentation. Table 4 radioactive isotopes ¹³⁷Cs and ²¹⁰Pb analyses show the result of 1.6 ± 0.02 (cm/y) and 1.75 ± 0.04 (cm/y) sedimentation rate of the lake for the last six decades with the marker age. The ²¹⁰Pb radioactive isotopes decode the age of the core sediment ranged from 1953 to 2016. The ¹³⁷Cs isotopes decode the age as 1954 to 2014.

Based on the investigation in Table 1a, the surface metal concentrations such as Fe, Mn, Cr, Cu, and Zn tend to be increased at point 8 at NW due to the lake's shape and its bathymetry. The Meandering shape and bathymetry value (8.5m to 17m) are vital in depositing the sediments at point 8. The actual main river inlet was at sampling point 7, due to the lake's meandering shape and its lower bathymetry induced the sediments' deposition at location 8 shown in Fig. 7 (S.P Rout., 2021). The river’s water input plays a role in swirling movement of sediment to shift in the location. Additionally, the minor tributary also plays a significant role in the deposition of sediment at point 8. The metal concentration of Pb, Ti, and Zr tends to decrease at sampling point 8. The concentration of Pb, Ti, and Zr is higher at the SE zone of the lake. In temporal division, most of the metal concentration of the sub-samples is significantly higher at a depth of 82 to 84 cm.

The mechanisms of speciation, precipitation, solubilization, diffusion, and advection control the distributions of metals in surface sediment. Any of these processes can be physical, chemical, or biological ones that take place in the water column (Dessai et al., 2009; Moechtar et al., 2009 & De Souza Machado et al., 2016). Metal in the lake could result from geological weathering and the release of agricultural, residential, and waste materials (Chen et al., 2001; Priya et al., 2016; Reitermajer et al., 2011; Wu et al., 2012)).

The physicochemical characteristics of the lake have a significant impact on the gradient for metal enrichment. The Fe from geological weathering sediments likely dominates the Fe content of the sediments (Esteller et al., 2017). The Ti and Zr concentration is characterized as the most resistant and immobile during the chemical weathering process, so the concentration is high in the freshwater state (Taylor & McLennan, 1985). The Co metal concentration is essential for the N₂ fixation by free-living bacteria, blue-green algae, and symbiotic systems, e.g., rhizobium in the root nodules of legumes (Nagpal, N. K. 2004). The higher concentration of Cobalt in the Chandratal can be inferred by the presence of plentiful cyanobacteria in the lake as an indicator. Cu and Ba have the same source to sink into the lake by lithogenic or biogenic (Salomons & Forstnes., 1980). Sr is more reactive during chemical weathering, whereas Rb is more inert (Zeng et al.,2012).

The correlation of surface sediments shows significant metals with other metals concentration for sampling points 5 to 8. Based on the Fig. 8, Mn and Fe levels exhibits a significant correlation (R² = 0.877) in the area suspected of being the accumulated zone. The Fe/Mn infers that significant redox condition due to absorption, complexions and solubility (Oldham et al., 2017). The increase in Fe and Mn concentration at sampling point 8 can be caused by abundance of the Mn²⁺ dissolves at high-oxygenated water conditions (De Souza Machado et al., 2016). The Ti have significant positive correlation with Fe (R²₌ 0.75), Co (R²₌ 0.86), Zn (R²₌ 0.70), Ba (R²₌ 0.78), and Mo (R²₌ 0.75) metals. The Ti/Fe correlation infers that iron carbonate content in the sediment dissolves to form red colour layer with the most resistant from the source rocks. The Ti/Co shows that the lake have dominant cynobacteria, so the Co absorption in the lake with the sediment particles along with the immobile and high resistance metals (Singh, O et.al 2013). The Ti/Zn shows that the Zn significantly depend on the input of the sediments, so only it shows high concentration at sampling point 8. The Fe/Zn have the strongly positive regression value of 0.93 implies the both metals enriches in the lake from the input of the river sediments (Esteller et al., 2017).

The Fe/Co have the significant positive correlation (R² = 0.86) infers that Co²⁺ constitution substitute the Fe²⁺ which are same in charge and ionic charges. The Fe shows strong correlation (R² = 0.83) with Mo signifies that lake indicated as deposition of the river input from the neighbouring bedrock weathering sources. The Mn/Sr shows correlation (R² = 0.82) value because absorption characteristic of sediment with more reactive elements (Zeng et al., 2012). The Cu and Cr show strong positive correlation (R² = 0.94 & 0.98) with the Mn metal infers that redox condition plays a vital role to absorb the Cu and Cr integrated with clay content (Salomons and Forstnes, 1980). The Zr/Pb correlation (R² = 0.83) significantly shows that lake appears as the freshwater state of sedimentation. The Mo have strongly correlated with Zn, Cr, Cu and Ba with regression greater than 0.9 infers the lake mostly depend on the sediments deposited from the river input at the sampling location 5 to 8.

In Fig. 9a shows, the intense transition of the χLF and χFD in the sampling point 8 compare with other points. The changes between the χLF and χFD particular at point 8 infers that study area geological condition is notable reason, respectively. The temporal variation of the χLF and χFD value at the depth of 42 to 44 cm and 84 to 86 cm. The magnitude of the susceptibility shows mostly coarse grain size. Therefore, it indicates that the fine grain sedimentation was not controlled the magnetic susceptibility. A slight positive correlation between χFD and χLF also shows moderate homogeneity in the magnetic mineralogy of the lake surface sediments and core sediments and particle size despite the change in land use referring to the obtained analogous outcomes (Sadiki et al. 2009). In surface sediments, Point 8 shows the metal enrichment zone from the river inputs. The increasing value of χLF indicates the abundance of magnetic minerals at that point 8. The low χFD value at point 8 indicates that the abundance of magnetic minerals arises from particles in the suspended multidomain size. Denser magnetic minerals are likely trapped at this point. In the Fig. 9a, the χLF / χFD plot shows that sampling point 8 indicate the highest peak than others. The high χLF / χFD at point 8 probably arose because the point is in large magnetic sediment traps zone. In temporally, the sediment at the depth 42 to 44 cm and 84 to 86 cm infers that high value of χLF and low value of χFD. In the Fig. 9b, the χLF / χFD plot shows the peak value at depth as 42 to 44 cm and 84 to 86 cm indicates the large magnetic sediment traps zone. From the inferences, the χLF / χFD helps to calculate the quantity of magnetic minerals in sediments with high magnetization. Consequently, the traps shows the most of metals concentration have been significant value at the certain depth.

Based on the radioactive isotopes the Table 4 shows, the Pb²¹⁰ and Cs¹³⁷ has linearly correlated with the χLF / χFD sediment trapped peak of the core sediment at the depth 42 to 44 cm infers the age as 1991 and 1993 years. Additionally, the secondary peak of χLF / χFD at 84 to 86 has been insignificantly correlated with the age result of Pb²¹⁰ and Cs¹³⁷ radioactive isotope in sediments.

Table. 5 shows the result of the Pearson correlation analysis, the value of χLF were substantially correlated with Fe, Co, Rb, and Cu. Additionally, the χLF linearly correlated with Mn, Zr, Sr, Zn, and Cr. The sampling point of 5 to 8 element concentration correlated between χLF values shown in Fig. 10. The χLF has significantly correlated with the metal concentration such as Fe (R² = 0.91), Mn (R² = 0.96), Sr (R² = 0.93), Cu (R² = 0.89), and Cr (R² = 0.92). The Fe-based magnetic mineral is the reason for significant value of χLF in the sampling points. The Fe accumulated in lake as iron carbonate and this oxidizes to hematite or limonite. Consequently, the χLF is strongly correlated spatially at point 8 and temporally at depth 42 to 44 cm and 84 to 86 cm with the Fe enriched sediments in lake (Canbay et al., 2010; Mariyanto et al., 2019; Sudarningsih et al., 2017). The Mn strongly correlated with the χLF shows spatial at point 8 and temporally at depth of 84 to 86 cm the Mn²⁺ have the 5 unpaired electrons and it easily attracted to magnetic frequency. The high concentration of Mn at the sampling point of 8 infers that sediments have high magnetism characteristics.

The Cu significantly correlated with the χLF infers that sources has been deposited in the two forms lithogenic and biogenic sediments (Salomons and Forstnes., 1980). The Cu²⁺ shows that unpaired electrons so it reacted as having the magnetic nature when the external magnetic field induced to the metals. The Sr²⁺ shows the 2 unpaired electrons in the orbital shell, so as like as Cu the external magnetic field induced the magnetic properties of Sr. The Cr has been reported as Antiferromagnetism properties, if the external heat (above 38˚ C) or external magnetic field it acted as paramagnetism. Mostly, the Cr is associated with the Fe in the studies lake.

Based on the XRD analysis (Fig. 5), the Mineralogical study shows the Zircon, Illite and quartz. From the inference of the results, the hematite or magnetite was not influence the lake sediments. Therefore, the strong Fe-oxides major responsible for the magnetic characteristic in the sampling point 8.

The Magnetic susceptibility’s frequency dependence (χFD %) of the surface sampling point 1 and 8 and temporally at depth as 42cm have < 2% indicates virtually no superparamagnetic grains with multi domain grain sizes. This interpretation validated by the previous discussion indicates that the point 8 have the direct inlet sediments from the river and point 1 shows at the lakeshore line zone infers the organic matters enrichment (Kanu et al., 2014; Ananthapadmanabha et al., 2014; Dearing., 1999). The Value of the surface sampling point at 2 to 7, 9 to 11 infers that 2% > χFD% < 10%. It shows superparamagnetic grain enrichment at these points. The abundance of superparamagnetic grains may have resulted from weathering of bedrocks and anthropogenic particles. It is possible by waste disposable and land use in this zone. In temporal χFD % infers significant depths have > 14%. It shows the weak samples or contamination samples (Dearing., 1999).

Table 5

Pearson Correlation between Heavy metal concentration and Magnetic Susceptibility
	Ti (ppm)	Mn(ppm)	Fe(ppm)	Zr(ppm)	Co(ppm)	Sr(ppm)	Rb(ppm)	Mo(ppm)	Pb(ppm)	Zn(ppm)	Cr(ppm)	Cu(ppm)	Ba(ppm)	χLF	FD
Ti (ppm)	1.00
Mn(ppm)	0.13	1.00
Fe(ppm)	0.09	0.80	1.00
Zr (ppm)	-0.13	0.66	0.57	1.00
Co(ppm)	0.28	0.77	0.92	0.55	1.00
Sr (ppm)	0.14	0.91	0.76	0.51	0.83	1.00
Rb (ppm)	-0.09	0.76	0.70	0.63	0.70	0.76	1.00
Mo(ppm)	0.35	0.40	0.65	0.21	0.57	0.30	0.09	1.00
Pb (ppm)	-0.05	0.64	0.43	0.70	0.30	0.36	0.36	0.40	1.00
Zn(ppm)	0.26	0.71	0.80	0.35	0.86	0.82	0.55	0.63	0.12	1.00
Cr(ppm)	0.15	0.70	0.77	0.30	0.81	0.81	0.70	0.51	0.08	0.94	1.00
Cu(ppm)	0.15	0.65	0.83	0.48	0.73	0.57	0.65	0.66	0.42	0.65	0.63	1.00
Ba(ppm)	0.22	0.90	0.80	0.66	0.78	0.79	0.59	0.70	0.65	0.81	0.74	0.70	1.00
χLF	-0.15	0.57	0.86	0.51	0.77	0.65	0.72	0.35	0.12	0.68	0.68	0.74	0.50	1.00
FD	-0.54	-0.05	0.16	0.29	-0.05	-0.09	0.19	-0.29	0.12	-0.32	-0.30	0.14	-0.26	0.46	1.00

Based on the Table 5 shows that the χFD% significant negative correlation and regression value with all the metal concentration in the lake sediments. This is suspected of forming Fe-based magnetic minerals or those associated with Fe in the inlet deposition zone, and these comprise a multidomain or single domain and are not in a superparamagnetic form.

The paper present the results of Metal enrichment traps in the high Altitude Himalayan Lake, The Chandratal Spiti. The values of χLF, χHF, χFD and χLF /χFD can be proxies to identify the Metal enrichment traps zones in the Lake. The χLF /χFD value substantial increase at the surface sediment sampling point as 8 and temporally at depth as 42 to 44 and 84 to 86 cm. In surface sediments, the χLF value increased due to magnetic mineral enrichment at the point 8 of maximum deposition from the river inlets. Simultaneously, the χFD decreased at the point due to no superparamagnetic grains. The Metal enrichment of Fe considered as the reason for higher magnetic component in surface and core sediments. Additionally, the result of ²¹⁰Pb and ¹³⁷Cs core sediments shows the age of highest metal trap at depth of 42 to 44 cm is 1993 (²¹⁰Pb), 1991 (¹³⁷Cs) and 84 to 86 cm is 1976 (²¹⁰Pb), 1964 (¹³⁷Cs). Unlike industrial area, the Chandratal Lake, which is in the tectonic collisional upliftment high altitude area, and is surrounded by geological sedimentary formation in the form of minerals such as Zircon, Illite and Quartz that serves as carriers of magnetic minerals in the study region. The Outcome of the study help us to understand the magnetic susceptibility plays a significant role in geochemical, environmental studies both spatially and temporally in the high altitude lake without industrial and tourism development like as The Chandratal Spiti, Himalayan Lake.

Data Availability

The data that support the findings of this study are available from the corresponding author, Vasudevan S, upon reasonable request.

Acknowledgement

This research did not receive any specific grant funding agencies in the public, commercial, or not-for-profit sectors. The Authors thank Prof. Rakesh Kumar Singal from BARC (Mumbai) for allowing to access the Equipment for Generate geochemistry data. The Author thank Annamalai University for their valuable support for accessing the equipments for the research work.

Author Contributions

Sonam Priyadharshini Rout: Conceptualization, Interpretation, Writing Original Draft; Vasudevan S: Text Editing, discussion, supervision, Manuscript Review; Baranidharan S: Interpretation, Visualization, Writing Original Draft; Vigneshwar J: Reviewed the manuscript; Sathiyamoorthy G: Reviewed the manuscript.

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Conflict of interest

The authors declare no competing interests.

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Determination of Magnetic Susceptibility and Metal Enrichment Sediments Traps of High Altitude Himalayan Lake, The Chandratal Spiti, Himachal Pradesh, India

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