Original Contamination Assessment of Heavy Metals in Sediment Cores from De Montigny Lake around Siscoe-Sullivan Former Mining Sites, Val-d’Or, Canada

Seven sediment cores were collected from De Montigny Lake in order to determine concentrations, and contamination assessment of heavy metals such as Cr, Zn, Ni, Pb, Cu, Co and Cd. The mean concentrations of heavy metals are as follows: 48.3 mg/kg for Cr, 36.4 mg/kg for Zn, 20.6 mg/kg for Ni, 14.7 mg/kg for Pb, 10.2 mg/kg for Cu, 6.7 mg/kg for Co and 0.1 mg/kg for Cd. Based on the sediment quality guidelines, the mean concentration metals such as Cr, Cu and Ni exceeded the US Environmental Protection Agency (USEPA) guideline. However, the concentration of Cr was more than the Canadian Water Quality Guidelines for Protection of Aquatic Life (CCME), and Threshold Effect Level (TEL) guidelines. The metal contamination in the sediments was also evaluated using Enrichment Factor (EF) and geoaccumulation index (Igeo) to assess natural and anthropogenic factors. The results of enrichment factor methods demonstrated that sediments from De Montigny Lake were moderately to high enriched, mainly controlled by through anthropogenic activities. According to Sediment Quality Guidelines (SQGs), the concentrations metals from the core sediment of De Montigny Lake are classified as having moderate impacts with potential adverse biotoxic effects.


Introduction
Metals and metalloids are hazardous contaminants in the environment. Metal Contamination of sediments may be due to the natural sources (for example processes of alteration and dissolution of minerals in parent rocks and soils), or by anthropogenic activities (for example mining and agricultural activities) (Xuelu & Chen-Tung, 2012;Kalloul et al., 2012;Keshavarzi et al., 2015). Sediments are considered as the final destination of the large proportion of metal contaminants, or the source of metal contamination in aquatic systems (Zahir et Shikazono, 2011;Liu et al., 2013). Furthermore, due to adsorption, desorption, remobilization, hydrolysis, precipitation, diffusion, chemical reactions, biological activity, heavy metals are predominantly dissolved as ions remains in water (Boughriet et al., 2007;Kalnejais et al., 2010;Suresh et al., 2015), and therefore the effective means of monitoring's state of the aquatic ecosystem (Islam et al., 2018. Siscoe-Sullivan former mining sites may contribute to metal contamination of the water and sediments of the De Montigny Lake. In addition, it is recognized that the mining activities are known to be a source of metal contaminants in aquatic system (Riba et al., 2002;Ahn et al., 2005;Kapoor & Singh, 2020). Therefore, it was essential to study the levels of contamination in the sediments from De Montigny Lake by heavy metals (Pb, Zn, Co, Cr, Cu, Ni and Cd), and to define the natural and/or anthropogenic sources of heavy metals. The basic objectives of this study were as follows: (1) determine the vertical spatial distribution of heavy metals in sediments; (2) assess the natural and/or anthropogenic sources by using the Enrichment Factor (EF), the geo-accumulation index (Igeo), CCME SQG guidelines (1999) and the quality of sediment based on Sediment quality guidelines (SQGs) (Smith et al., 1996); (3) define the natural and/or anthropogenic sources of metal contamination by using statistical analyses: Pearson's correlation matrix and Principal Component Analysis (PCA).

Study Area
De Montigny Lake is one of the most important lakes in the Milky sub-basin that is included in the Hurricana River basin. The study area is bounded by latitudes (48 ° 6 '15" N to 48 ° 10 '10" N) and longitudes (77 ° 57 '30" W to 77 ° 50 '00" W). De Montigny Lake is located north of Route 117, west-northwest of Val d´Or (Figure 1). Along the De Montigny Lake, we have the Kiena mining complex owned by Wesdome Gold Mines. The climate of the study area is boreal with snow cover on the ground from mid-November to mid-April, with rather dry winters and a short frost season of around 80 days.

Analysis of Samples
The segments of sediment cores were selected as (0-5 cm, 5-15 cm, 15-25 cm, and 25-40 cm). For the analysis of heavy metals (total), 0.5 g from each sample were treated with aqua regia (HNO3 + 3HCl) in a closed Teflon vessel (100 mL). The samples were digested in the microwave digestion system, and

Assessment of Sediment Contamination
The assessment of contamination is very often based on comparing data with the background references level (Turekian et Wedepohl, 1961;Varol, 2011;Haynes, 2016). To evaluate the contamination extent of sediment cores through heavy metals, Enrichment Factor (EF) and geo-accumulation index (Igeo) have been calculated to determine different contamination levels. In sediment contaminants (Zhuang et al., 2020).

Sediment Quality Guidelines (SQGs)
The Sediment Quality Guidelines (SQGs) were used to assess individual heavy metal substances by comparing the metal concentration with the quality guidelines to evaluate the degree to which the sediment associated chemical status might adversely affect marine organisms (Ke et al., 2017;Maanan et al., 2015). The SQG-based ecological risk assessment index for multiple heavy metals, known as the mean Sediment Quality Guidelines Quotient (SQG-Q), SQG-Q is computed as follows (Long et al., 1998): where PEL-Q i is the Probable Effects Level (PEL) quotient for the i-th metal; C i is the concentration of the i-th metal in sediments; is the PEL for the i-th metal; and n is the number of heavy metals (here 5). The value of the PEL comes from the potential effect concentration/critical effect concentration (PEL/TEL) benchmark proposed by Smith et al. (1996) (Table 2). According to Long at al. (1998), when TEL > C i unfavourable biotoxic effects rarely occur; when PEL< C i unfavourable biotic effects occur frequently, and when the heavy metal concentrations are between the TEL and PEL, unfavourable biotic effects occur occasionally. The ecological risk levels of the heavy metals in the sediments based on the values of SQG-Q can be categorized as follows: no impact with adverse biotic effects (SQG -Q ≤ 0.1); moderation impact with potential adverse biotic effects (0.1 < SQG -Q ≤ 1.0); and strong impact with extremely strong adverse biotic effects (SQG -Q > 1.0).

Enrichment Factor (EF)
The enrichment Factor (EF) is used to differentiate between natural sources and anthropogenic sources in a site, and thus to define the intensity of pollution (Radakovitch et al., 2008;Maanan et al., 2015;Decena et al., 2018;Remeikaite-Nikiene et al., 2018). The enrichment factor (EF) was calculated using Al as an immobile element due to its natural abundance in the earth's crust, and by its concentration which is not altered by anthropogenic causes Maanan et al., 2015). The reference material (Average shale) used is recognized worldwide as the reference background values of unpolluted areas (Turekian & Wedepohl, 1961;Haynes, 2016 metal is entirely crystallized in the sediment while the higher FE values to 1.5 or 2 suggest anthropogenic sources (Garcia et al., 2008;Abreu et al., 2016). According to the EF of an element, Loska et al. (2004) and Guan et al. (2016) classified the enrichment factor (EF) into five levels: no or slight enrichment (EF < 2), moderate enrichment (2 ≤ EF < 5), significant enrichment (5 ≤ EF < 20), high enrichment (20 ≤ EF < 40) and extremely high enrichment (EF > 40).

Geoaccumulation Index (I geo )
The geoaccumulation index (Geo) proposed by Müller (1969) is used to determine and define the metal contamination in sediments by comparing a given concentration of the heavy metal versus a value considered as the local background value of metal. The geoaccumulation index (Igeo) is expressed as follows: where C n is the measured concentration of heavy metals in sediments; B gn is the geochemical background value in average shale of element n; 1.5 is the background factor correction used because of variations in the background caused by lithology or natural variation of the geochemical background (Lu et al., 2009;Orani et al., 2019). The geoaccumulation index values (I geo ) values for heavy metals is classified in seven classes as follows: Class 0 (Igeo ≤ 0), uncontaminated; Class 1 (0 < Igeo ≤ 1), uncontaminated to moderately contaminated; Class 2 (1 ≤ Igeo ≤ 2), moderately contaminated; Class 3 (2 < Igeo ≤ 3), moderately contaminated to strongly contaminated; Class 4 (3 < Igeo ≤ 4), strongly contaminated; Class 5 (4 < Igeo ≤ 5), strongly contaminated to extremely contaminated; and Class 6 (Igeo > 5), extremely contaminated (Müller, 1979;Ji et al., 2015;Dai et al., 2018;Liu et al., 2021).

Statistical and Graphical Analysis
The data were statistically analyzed using XLSTAT version 2020, Excel (2019) and R software, which is free on www.r-project.org (accessed on 27 October 2021). Principal Component Analysis (PCA) correlations using varimax rotation were applied to verify significant relationships among the heavy metals of core sediments, and to identify contamination sources (natural and/or anthropogenic). The Kaiser-Meyer-Olkin (KMO) test (Hutcheson & Sofroniou, 1999) with a > 0.5 KMO (0.5), and the Bartlett sphericity test (p <0.0005) with test significance Bartlett's (p = 0.000) were used to measure the sampling adequacy.

Metal Levels in Sediment Core
The concentration of heavy metals measured in sediment cores of De Montigny Lake as well as the The vertical distribution of metal concentrations along cores collected from the seven sampling sites (S1, S2, S3, S4, S5, S6, and S7) showed different patterns in the concentrations of heavy metals with depth. In the cores S1, S2, S5, and S6, the focus was placed on Cr for which the highest concentrations showed that the concentrations of heavy metal in the present study were globally lower than other those of other World lakes (Table 2). Although, the concentration of Cr, which present a pollution risk to aquatic environment, was higher than the Karachi Coast (Chaudhary et al., 2021) and Rewalsar Lake (Meena et al., 2017).  (Smith et al., 1996). f PEL: probable effect level (Smith et al., 1996).

Index of Heavy Metals Pollution in Sediments
To evaluate the sediment heavy metal contamination degree, we used two parameters: Enrichment Factor (EF) and the Geoaccumulation index (I geo ).

Enrichment Factor (EF)
The calculated enrichment factor values of seven investigated heavy metals are illustrated in Figure 3.
Significant enrichment was found for Cd, Cr, Cu and Zn especially in the surface sediments samples (depth 0 -5 cm); Pb showed significant enrichment in all layers of sediment cores S5, S6 and S7. Sediment cores S1, S2, S3, S4, S5, S6, and S7 showed moderate enrichment with Co, Mn and Ni in all layers of sediment cores. The high values of EF suggest that the De Montigny Lake is polluted mainly by Pb and Cr, which indicates anthropogenic sources in the study area.

Geo-Accumulation (I geo )
The calculated I geo of the heavy metals in sediment cores is shown in Figure 5.

Statistical Analysis
Pearson's correlation analysis was applied to analyze the relationships between metals, and to determine the possible sources and dynamics of metals in sediments (Franco-Uria et al., 2009;Wang et al., 2012;Remeikaite-Nikiene et al., 2018, Yi et al., 2020. Correlation coefficients between heavy metals in sediment cores of study area are summurized in Table 3. Based on Pearson's correlation coefficients (r) values, Liu et al. (2013) have proposed the classification as follows: strong (> 0.75), moderate (0.75-0.50), and poor (0.50-0.30). Pearson matrix shows heavy metals association, such as: a strong positive correlation was evidenced between Cd and Zn (r = 0.82), and Co and Ni (r = 0.77). The strong correlations between pairs of heavy metals indicate similar contamination degree and common sources in sediment cores (Malvandi, 2017), most likely related to anthropogenic activities that may be the consequence of the past and present mining activities. Although, it should be noted that metals with significant correlations were not mainly derived from the same source, which would depend on the source and the interrelation between the elements (Pandey et al., 2015;Ma et al., 2016). In addition, moderate correlation was also between Al-Co (r = 0.64), Co-Pb (r = 0.55), Cu-Zn (r = 0.67). A positive http://www.scholink.org/ojs/index.php/se Sustainability in Environment Vol. 6, No. 4, 2021 27 Published by SCHOLINK INC.
correlation with Al and Pb (r = 0.32), Cd and Cu (r = 0.50), Cr and Ni (r = 0.49), Co and Pb (r = 0.55), and Ni and Zn (r = 0.48), while Cr did not show any correlation with other metals.  Bold characters indicate the significant correlations, usually grater than 0.6 and bold italic shows the correlation less that 0.6 value

Discussion
The contribution of past and present mining activities in the pollution of De Montigny Lake is not limited, there are mining activities with Kiena and Goldex Mines, and the presence of mining wastes from Siscoe-Sullivan former mining in the Milky sub-basin. Siscoe  and Sullivan  mines located around the De Montigny Lake continued to add heavy metals in the lake.
Although the two mines ceased activities since 1934 and 1967, respectively; over a long period of time, they discharged raw wastewater directly into De Montigny Lake. The high levels of Cr observed in seven sediment cores, should probably be associated with ultramafic (komatiite) and mafic (basalt) rocks in soil. Furthermore, the vertical distribution of Cr along the seven sediment cores showed that high concentration persists from bottom to upward surface layer, denotes hisrorical deposition. In any case, Cr is generally regarded as being of no negligible risk in terms of toxicity to human, animal and plant species. The significant Cd, Cr, Cu, Pb, and Zn enrichment of sampling sites S5, S6, and S7, as well as the moderate Co, Mn and Ni enrichment of sampling sites S1, S2, S3, S4, S5, S6 and S7, could be attributed to past and present mining activities.

Conclusions
This is the first on vertical distribution and contamination assessment in sediment cores of De The Enrichment Factor (EF) stated minimal to significant enrichment for Cd, Cr, Cu and Pb, and geo-accumulation (Igeo) indicated sediments quality was uncontaminated for all heavy metals. Based on sediment quality guidelines, the sediments have moderate impacts with potential adverse biotic effects. According to Pearson's correlation matrix and Principal component analysis, heavy metals (Zn, Cd) have common anthropogenic origin and main contributors of heavy metals in the lake. Hence, control measures and management of contamination of Cr in nearby cities should be strengthened for protecting the De Montigny Lake environment and carcinogenic risk to children. The present study could be useful, serving as a baseline for evaluating the potential impacts of future development in the area.