GIS and Contamination Indices for Environmental Risk Assessment of Landfill Disposal Sites in Central Saudi Arabia

Landfills pollute air, soil, surface and groundwater worldwide. Present work aims to assessment environmental Risks three landfills in southern Riyadh using GIS, soil quality guidelines, and contamination indices. GIS tools indicated an increase in the area of the landfill sites with time. The concentration of heavy metals (HMs) in the investigated landfills had the following descending order: Fe (11532 mg/kg) ˃ Al (5405 mg/kg) ˃ Pb (561.7 mg/kg) ˃ Zn (356.8 mg/kg) ˃ Mn (165 mg/kg) ˃ Cr (74.8 mg/kg) ˃ Cu (42.7 mg/kg) ˃ Ni (22.4 mg/kg) ˃ V (21.8 mg/kg) ˃ As (5.16 mg/kg) ˃ Co (4.08 mg/kg). The highest values of Al, As, Co, Ni, Pb, V, and Zn were recorded in Riyadh landfill 3, at the third industrial city. However, average values of all HMs decrease those from most worldwide soils and background, except Zn, Cu, Cr, and Pb. Results of enrichment factor and statistical analysis indicated deficiency to minimal enrichment and geogenic sources for Al, Co, Mn, and V, while those of As, Cr, Pb, Zn, and Ni showed EF ˃ 2 implied anthropogenic activities, especially in in Riyadh landfill 3. Additionally, very high contamination and high effects range-median were reported in individual samples, especially for Pb, As, and Zn, indicated frequent adverse effects for these HMs. The difference in contamination for the HMs in the studied landfill sites might be attributed to the difference in the magnitude of input for each metal into the landfill site and/or the difference in the removal rate of each metal from it.

Keywords:

Subject: Environmental and Earth Sciences - Environmental Science

1. Introduction

There is a growing annual increase in the quantity of waste produced. Landfilling is the primary technique of waste disposal in the majority of countries due to its cost-effectiveness. Landfills present a significant environmental challenge due to the production of several hazards, such as gas and leachate, during landfill operations [1,2]. The content of leachate varies significantly from one dump to another, depending on the specific characteristics of each site. Heavy metals are among the most dangerous substances found in leachate. There is an increasing apprehension about the accumulation of heavy metals in soil and groundwater. Various types of garbage contribute to the prevalence of heavy metals in landfills. According to [3], the presence of heavy metals in landfills is heightened by sources such as electronic trash, painting waste, and spent batteries.

Landfills and open dumpsites were commonly used worldwide for the disposal of municipal solid waste (MSW). In the United States, 52.6% of MSW was discarded in landfills (Sun et al., 2019), while in Brazil the figure was 59.1% (Costa et al., 2019). In the Kingdom of Saudi Arabia (KSA), the percentage was 85% [4], in Malaysia it was 94.5% [5], and in China it was 79% [6]. In Venezuela, sanitary landfills accounted for 32%, controlled disposal for 43%, and non-controlled disposals or open dumps for 24% [7]. In Mexico, sanitary landfills accounted for 65%, while uncontrolled and open dumps accounted for 30% [8]. Lastly, in Thailand, the percentage was 27% [9,10]. The primary sources of emissions from landfill sites include the waste materials upon arrival, emissions from transportation, waste dispersed by wind, dust formed from the landfill surface, landfill gas production, and leachate generation.

The primary distinction between a dump and a landfill is in the absence of any effort to segregate the garbage from the underlying soil or rock layers in a dump. Additionally, in cases when the hole extends below the groundwater level, waste is directly deposited into the groundwater [11]. On the other hand, a sanitary landfill is a man-made construction that includes bottom liners, systems for collecting and removing leachate, and final covers (Figure 2). Landfills are specifically engineered to serve as storage facilities for waste materials, as well as to undergo treatment processes. The significant risk associated with MSW landfill arises mostly from the movement of polluted leachate and landfill gas. Consequently, the environmental consequences of the numerous landfills present worldwide must not be disregarded. Significant emissions, including as leachates and biogas, are released from biological activities that occur within them. If municipal solid waste (MSW) is deposited in a landfill without any pre-treatment, emissions are generated during the operation of the landfill. These emissions continue to be produced even after the landfill has been closed [10,12,13,14].

The soil in the Kingdom of Saudi Arabia is diverse due to its large area and the variation in climate across different regions of the Kingdom (eastern, western, northern, southern, and central). In general, in recent years, a number of studies have emerged focusing on evaluating the quality of the Kingdom's soil (e.g. [15,16,17,18,19,20,21,22]). The field investigations revealed that landfills in Riyadh receive a wide variety of waste, representing the diverse municipal solid waste of the city, including food scraps, packaging materials, paper, cardboard, plastics, glass, textiles, grass clippings, leaves, branches, old furniture, mattresses, and appliances. Additionally, industrial waste such as scrap metals, plastics, chemicals, concrete, bricks, wood, chemicals, paints, and solvents, as well as electronic waste like computers, mobile phones, televisions, and other electronic devices, are also disposed of in these landfills. E-waste refers to electronic waste, while medical waste includes used syringes, bandages, gloves, and expired or unused medications. Agricultural waste consists of animal manure, crop residues, and other organic materials from agricultural activities in Riyadh, as well as pesticide containers, plastic sheeting, and other materials used in modern agriculture. Special waste encompasses used and discarded tires, batteries, and sludge. The present aimed to assess the environmental risks of three landfill disposal sites in southern Riyadh, central Saudi Arabia using GIS tools, soil quality guidelines and several contamination indices.

2. Materials and Methods

Three landfills were selected for this study in southern Riyadh (Figure 1). The Riyadh landfill site 1 (RL1), is located in the northeast of a Noor - Sulay industrial district, at latitudes 24.6340 - 24.6485 N and longitudes 46.8046 - 46.8213 E. The Riyadh landfill site 2 (RL2) is situated in Al Birriyyah district in northeast of the second industrial city, at 24.5687 - 24.5456 N, and 46.9095 - 46.9329 E, while the Riyadh landfill site 3 (RL3) is located in Al Kharj Road in the southeast of the third industrial city, at 24.4948 - 24.4620 N and 46.9349 - 46.9571 E. This extensive study used satellite imagery to examine how three landfill sites in Riyadh changed over time. The images were obtained from Esri's World Imagery, which provides global satellite images dating back to February 20, 2014. Each version in the archive shows the state of the World Imagery map on the date it was published. This service is beneficial for temporal analyses, allowing users to access and compare past imagery that may have been updated or replaced in the current dataset.

In order to obtain the necessary images, the Wayback service through the ArcGIS Online platform were accessed. The historical layers for 2014, 2018, 2022, and 2024 were identified and retrieved. These layers are organized in a timeline and a list format within the Wayback interface, making it easy to select specific dates. It is worth noting that versions resulting in local changes are highlighted, which helps identify relevant imagery updates for the study area. Utilizing this archive ensured consistent data sourcing for each time point under investigation. Access to previous imagery allowed for a detailed assessment of the landfill sites' expansion, contraction, and other changes over the selected years.

Various single and integrated contamination indices, including the enrichment factor (EF), geoaccumulation index (Igeo), contamination factor (CF), potential ecological risk index (RI), and pollution load index (PLI), were used in this study to evaluate the contamination levels and ecological risks of PTEs. Equations (1) ̶ (6) and Table 1 present the calculation procedures and classification of these contamination indices and the parameters utilized in this work [23,24,25].

EF = (M/X) sample /(M/X) background

(1)

I-geo= Log2 (Cn/ (1.5 × Bn))

(2)

CF = Co /Cb

(3)

PLI = (CF1 × CF2 × CF3 × CF4…. × CFn)1/n

(4)

Eri = Tri × Cfi

(5)

RI = Ʃ (Tri × Cfi)

(6)

M and Co represent the concentrations of the analyzed metal, while X and Cb signify the levels of a normalizer element (Fe). Cn is the measured concentration of metal (n) in the soils, Bn is the geochemical background concentration of the metal (n) in shale, and 1.5 is introduced to minimize the effects of possible variations in the background values. Eri indicates the potential ecological risk factor of an individual element, Tri represents the biological toxic response factor of an individual element, and Cfi denotes the contamination factor for each single element. The toxic response factor for metals follows this order: Zn = Co = Mn = 1, Cr = 2, Ni = 6, Cu = Pb = Ni = 5, As = 10. Table 1 provides the classification of the contamination indices applied in this study [25].

3. Results and Discussion

3.1. Landfill Variation through Time

3.1.1. Riyadh Landfill 1 (RL1)

RL1 in a Noor – Sulay district is characterized diverse municipal solid wastes, including packaging materials, paper, cardboard, plastics, textiles, old furniture, scrap metals, plastics, chemicals, concrete, bricks, and wood. Moreover, discarded tires, batteries, and sludge. In 2014, the site appears to be a warehouse or a car maintenance workshop complex, and it has been in this state since around April 2005. Before this date, it was an open space with small, scattered landfills around its edges. The site was surveyed in August 2015, and it began being used as a landfill in March 2016. In December 2018, the use of the northern part of the site expanded to an area of approximately 418,066 m², which is about 25.5% of the total area of the square. In December 2020, all parts of the site were used as a landfill, with the utilized areas expanding to reach about 1 km², representing 59.3% of the square's area (Figure 2). By August 2024, the site's use as a landfill had increased to about 78.1%, with the utilized area expanding to approximately 1.3 km².

3.1.2. Riyadh Landfill 2 (RL2)

RL2 in Al Birriyyah district showed diverse municipal solid wastes of packaging materials, paper, wood, plastics, glass, textiles, old furniture, scrap metals, chemicals, concrete, bricks, chemicals, paints, and solvents. In December 2014, the total utilized area reached approximately 736,980 m², representing 17.9% of the total site area, which has been the same since around 2004, as no images are available prior to 2004. In December 2018, the site's use as a landfill reached approximately 39.7%, with the utilized areas expanding to about 1.64 km². In December 2022, the site's use as a landfill reached approximately 44.9%, with the utilized areas expanding to about 1.85 km² (Figure 2). By August 2024, the site's use as a landfill reached approximately 46.8%, with the utilized area expanding to about 1.93 km².

Figure 3. Change in RL2 area from 1014 to 2024.

3.1.3. Riyadh Landfill 3 (RL3)

RL3 in Al Kharj Road is characterized by diverse solid and liquid wastes including cardboard, old furniture, used tires and car oils, concrete, bricks, wood, chemicals, paints, and solvents, as well as electronic and medical wastes. In December 2014, the total utilized area at that time was approximately 521,962 m², representing 12.3% of the total site surface area, which had remained the same since around 2004, as no images are available before 2004. In December 2018, the site's use as a landfill reached approximately 17.7%, with the utilized areas expanding to about 0.75 km². In December 2022, the site's use as a landfill reached approximately 51.5%, with the utilized areas expanding to about 2.18 km² (Figure 4). By August 2024, the site's use as a landfill reached approximately 52.3%, with the utilized area expanding to about 2.21 km².

3.2. Concentration and Distribution of HMs

The concentration of HMs (mg/kg, dry weight) in the investigated landfills is shown in Table S.1. The HMs average values had the following descending order: Fe (11532) ˃ Al (5405) ˃ Pb (561.7) ˃ Zn (356.8) ˃ Mn (165) ˃ Cr (74.8) ˃ Cu (42.7) ˃ Ni (22.4) ˃ V (21.8) ˃ As (5.16) ˃ Co (4.08). Our average values of Ni, Al, V, As, Co, Fe, and Mn decrease those from worldwide soils [26], Earth’s crust [27], continental crust [28], and the recommended levels of HMs [29]. However, Zn and Pb average values exceed the averages of the last mentioned worldwide soils. Moreover, Cu and Cr average values decrease those of the worldwide soils except that of [26] and the recommended levels of HMs [29]. Figure 5 and Table S.1 implied that most of the highest values of the HMs were recorded in RL3, at the third industrial city, for instant Al (10400 mg/kg), As (41.0 mg/kg), Co (10.0 mg/kg), Ni (50.0 mg/kg), Pb (8960 mg/kg), V (41.0 mg/kg), and Zn (2230 mg/kg). The highest values of Cr and Cu were recorded in RL2 (904 and 302 mg/kg, respectively), at the second industrial city. Fe and Mn highest values were recorded in RL1 at Al Sulay industrial district (29000 and 346 mg/kg). However, the lowest HMs were recorded in RL2, Al, As, and V in sample R9; Co, Fe, Mn, Ni in sample R12; Cr, Cu, Pb, and Zn in sample R20 (Figure 5, Table S.1).

3.3. Risk Assessment and Potential Sources of HMs

The anthropogenic contribution of the selected HMs in landfill disposal sites can be estimated from the metal enrichment relative to unpolluted reference materials or widely accepted background (pre-industrial) levels. For calculation of pollutant indicators of toxic metal pollution in in Riyadh landfill disposal sites, the following factors were taken into consideration.

3.3.1. Enrichment Factor (EF)

This method is proposed by Sinex and Helz (1981) to estimates the anthropogenic impact of HMs using a normalization element (Fe) to to normalize the data as normalization factor. The EF is a good tool to differentiate between the anthropogenic and natural sources of metals in environmental samples [29,30,31,32,33,34]. The Minimum, maximum and average EF values for the HMs are presented in Table S.2. Results of EF indicated the following descending averages: Pb (177.65) ˃ Zn (12.35) ˃ Cu (4.41) ˃ Cr (3.36) ˃ As (2.14) ˃ Ni (1.43) ˃ Co (0.92) ˃ Mn (0.82) ˃ V (0.76) ˃ Al (0.30). All samples collected from the landfill disposal sites showed EF ˂ 2 for Al, Co, Mn, and V, indicating deficiency to minimal enrichment for these HMs and were entirely originate from the crustal materials or natural processes, while those As, Cr, Pb, Zn, and Ni with EF ˃ 2 are most likely the product of anthropogenic activities [35].

Additionally, four samples (R25, R26, R30, R34) showed EF ˃ 40 for Zn, three samples (R17, R32, R35) showed EF ˃ 40 for Pb, implying extremely high enrichment with these two HMs. However, a significant enrichment was reported in 19 samples for Pb, 10 samples for Zn, 2 samples for Cr and Cu (Table 2). Generally, the difference in EF values for the different HMs in the studied landfill disposal sites may be attributed to the difference in the magnitude of input for each metal into the disposal site and/or the difference in the removal rate of each metal from the disposal site [36,37].

3.3.2. Contamination Factor (CF)

The contamination factor was also used to assess the level of contamination and the possible anthropogenic impact of contaminants in sediments [23,38,39,40]. Results of CF in Table S.3 indicated the following descending averages: Pb (28.09) ˃ Zn (3.76) ˃ Cu (0.95) ˃ Cr (0.83) ˃ As (0.40) ˃ Ni (0.33) ˃ Fe (0.24) ˃ Mn (0.19) ˃ V (0.17) ˃ Co (0.09) ˃ Al (0.07). The 36 investigated samples were low contaminated with Co, Fe, Al, Mn, Ni, and V. A very high contamination was recorded in 5 samples of the landfill disposal sites (R16, R17, R32, R33, R35) for Pb, 4 samples (R25, R26, R30, R34) for Zn, one sample (R16, R17 for Cu and Cr, respectively. However, a considerable contamination was reported in 7 samples for Pb, 4 samples for Zn and one sample for As (Table 2).

3.3.3. Geoaccumulation Index (Igeo)

The geoaccumulation index (Igeo) is a common criterion used for evaluating the HM pollution in soil [25], where HM contamination was determined by comparing their current concentration levels with those from preindustrial times. Results of Igeo in Table S.4 indicated the following descending averages: Pb (1.19) ˃ Zn (0.60) ˃ Cr (-0.84) ˃ Ni (-0.94) ˃ Cu (-1.58) ˃ As (-2.52) ˃ Fe (-2.78) ˃ Mn (-3.08) ˃ V (-3.31) ˃ Co (-4.23) ˃ Al (-4.62). All studied samples were uncontaminated with Al, Co, Cu, Ni, V, and Fe (Igeo < 0). However, moderately to strongly contamination, strongly to extremely contamination, and extremely high contaminated for Pb were reported in 2 samples (R16, R33), 2 samples (R17, R35), and one sample (R32), respectively (Table 2).

3.3.4. Potential Risk Index (RI)

Potential ecological risk was introduced by [23] for the assessment of the degree of ecological risk caused by HM concentrations in the water, air, as well as the soil. This index covers a various environmental effects, such as toxicology, environmental chemistry, and ecology, and can evaluate ecological risks caused by heavy metals [25,41,42]. The RI is calculated on the basis of 3 indices: single index of ecological risk factor (Eⁱ_r), the pollution coefficient of a single element (Cⁱ_f ), and toxic response factor of individual metals (Tⁱ_r). All samples collected from the landfill sites showed Erⁱ ˂ 40 for As, Co, Cr, Cu, Mn, Ni, Pb, V, and Zn, indicating low ecological risk for these HMs. However, Pb showed serious ecological risk in sample R32, high ecological risk in samples R17 and R 35, and moderate ecological risk in sample R33 (Table 2 and Table S.5). The average RI values varied from 5.35 in sample R20 to 2281 in sample R32, with an average of 154.95. This finding indicates that moderate ecological risk due to presence of HMs in the landfill soils. However, few individual samples showed high potential and significant high ecological risks (Table S.5).

3.3.5. Soil Quality Guidelines

Chemical concentrations of metals corresponding to the 10th and 50th percentiles of adverse biological effects were called the effects range-low (ERL) and effects range-median (ERM). There are three ranges in chemical concentrations, where adverse effects rarely (< ERL), occasionally (≥ ERL and < ERM), and frequently occur (≥ ERM) [43,44]. Table 3 illustrates the range of ERL and ERM values for samples quality guidelines (SQG) of [45] in Cu, Ni, Zn, As, Cr, and Pb along with the percentages of samples falling within these SQG ranges. 35 samples (97.22%) were <ERL and one sample >ERL and <ERM for As measurements, indicating that the samples under study do not pose a risk due to the presence of As except sample 32, which may cause some potential risk. However, Zn in 4 samples, Pb in two samples, Cu in one sample, and Cr in one sample indicated frequent adverse effects (>ERM). Additionally, Ni in 19 samples, Zn in 19 samples, Pb in 13 samples, Cu in 11 samples, As in one sample, and Cr in one sample revealed occasional adverse effects for these HMs (Table 3).

Results of Pearson’s correlation (Table 4) showed strongly positive correlations between some of the HM pairs, such as Al - Co (r = 0.886), Al – Mn (r = 0.620), Al - Ni (r = 0.887), Al - V (r = 0.877), As - Pb (r = 988), Co - Fe (r = 0.657), Co - Mn (r = 0.794), Co - Ni (r = 0.937), Co - V (r = 0.786), implying similar sources for these pairs [46]. Occurrence of Fe, Al, and Mn in such correlations indicated natural sources for these HMs, particularly Al, Co, Mn, and V showed average EF values less than 2 [40,47]. Differently, the strong positive correlation between As and Pb indicated anthropogenic sources related to agricultural and industrial wastes [48]. This suggestion is supported by results of the contamination indices for these two HMs.

Results of Pearson’s correlation is supported for a great extent by principal component analysis (PCA) which extracted three PCs, accounting 47.78%, 20.73%, and 12.56% of the total variance, respectively (Table 5, Figure 6). The PC1 showed high loading for Al, Co, Fe, Mn, Ni, V, and Zn, which were entirely originate from the crustal materials or natural processes. The PC2 showed high loading for Pb and As, while the PC3 presented high loading for Cr and Cu, revealing different sources of anthropogenic factors.

4. Conclusions

The current study highlighted the environmental risks associated with the presence of three landfills in the central Saudi Arabia. The study's findings can be summarized as follows: GIS tools have demonstrated a significant increase in the area of these landfills over time. Due to the horizontal expansion of Riyadh, some of these landfills have become situated within urban areas, which might be pose an environmental risk. The locations of the landfills along valleys cause the leaching of contaminated liquids, which either flow along the valleys or seep into the ground layers, polluting groundwater reservoirs. Pollution indices and soil quality guidelines have proven that the soil in these landfills is contaminated with certain HMs such as Pb, As, Cu, and Cr, which were mostly caused by the diverse wastes in these landfills. Finally, the study recommends relocating these landfills to mountainous areas far from urban regions and future horizontal urban expansion. It also suggests that the landfills be developed using modern, investment-oriented methods, where plastic and metal materials are recycled, and methane gas is produced from the decomposition of organic materials in these landfills.

Supplementary Materials

The following supporting information can be downloaded at the website of this paper posted on Preprints.org, Table S1: The concentration of HMs (mg/kg) from three landfills in Riyadh; Table S2: The enrichment factor for HMs from three landfills in Riyadh; Table S3: The contamination factor for HMs from three landfills in Riyadh; Table S4: The geoaccumulation index for HMs from three landfills in Riyadh; Table S5: The ecological risk factor and potential risk index for HMs from three landfills in Riyadh.

Author Contributions

Conceptualization, T.A. and A.S.E; methodology, Y. S. and N.R.; software, Y. S. and N.R.; validation, T.A., A.S.E, Y. S. and N.R.; writing—original draft preparation, T.A., A.S.E, Y. S. and N.R.; writing—review and editing, T.A., A.S.E, Y. S. and N.R.; project administration, T.A.; funding acquisition, T.A. All authors have read and agreed to the published version of the manuscript.

Funding

Researchers Supporting Project number (RSPD2024R791), King Saud University, Riyadh, Saudi Arabia.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data generated or analyzed during this study are included in this published article and its Supplementary Information Files.

Acknowledgments

The authors extend their appreciation to Researchers Supporting Project number (RSPD2024R791), King Saud University, Riyadh, Saudi Arabia. Moreover, the authors thank the anonymous reviewers for their valuable suggestions and constructive comments.

Conflicts of Interest

The authors have no relevant financial or non-financial interests to disclose.

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Figure 1. Location map of the three studied landfills in Riyadh.

Figure 2. Change in surface area of RL1 from 1014 to 2024.

Figure 4. Change in RL3 surface area from 1014 to 2024.

Figure 5. Distribution of HMs per sample locations in the three investigated landfills.

Figure 6. Three component plots using the varimax method with the kaiser normalization.

Table 1. Classification of the contamination indices.


EF	EF < 2	Deficiency to minimal enrichment
	EF= 2–5	Moderate enrichment
	EF= 5–20	Significant enrichment
	EF= 20–40	Very high enrichment
	EF > 40	Extremely high enrichment
CF	Cf < 1D 1 ≤ Cf <3 3 ≤ Cf < 6 Cf ≥ 6	Low contamination factor
		Moderate contamination factor
		Considerable contamination factor
		Very high contamination factor
Igeo	Igeo < 0	Uncontaminated
	0 < Igeo < 1	Unpolluted to moderately contaminated
	1 < Igeo < 2	Moderately contaminated
	2 < Igeo < 3	Moderately to strongly contaminated
	3 < Igeo > 4	Strongly contaminated
	4 < Igeo < 5	Strongly to extremely contaminated
	Igeo > 5	Extremely high contaminated
RI	Er < 40	Low ecological risk
	40 < Er ≤ 80	Moderate ecological risk
	80 < Er ≤ 160	Considerable ecological risk
	160 < Er ≤ 320	High ecological risk
	Er > 320	Serious ecological risk
	RI < 150	Low ecological risk
	150 < RI < 300	Moderate ecological risk
	300 < RI < 600	High potential ecological risk
	RI ≥ 600	Significantly high ecological risk

Table 2. Class distribution (sample %) of contamination indices for HMs examined in the studied landfills.

Indices	Classes	Al	As	Co	Cr	Cu	Mn	Ni	Pb	V	Zn	Fe
EF	Deficiency to minimal enrichment	36	33	36	33	17	36	32	0	36	4	-
	Moderate enrichment	0	2	0	0	16	0	4	11	0	16	-
	Significant enrichment	0	0	0	2	2	0	0	19	0	10	-
	Very high enrichment	0	1	0	0	1	0	0	3	0	2	-
	Extremely high enrichment	0	0	0	1	0	0	0	3	0	4	-
CF	Low contamination factor	36	35	36	34	28	36	36	10	36	19	36
	Moderate contamination factor	0	0	0	1	7	0	0	14	0	9	0
	Considerable contamination factor	0	1	0	0	0	0	0	7	0	4	0
	Very high contamination factor	0	0	0	1	1	0	0	5	0	4	0
Igeo	Uncontaminated	36	35	36	33	36	31	36	7	36	13	36
	Unpolluted to moderately contaminated	0	0	0	2	0	4	0	12	0	12	0
	Moderately contaminated	0	1	0	1	0	1	0	12	0	7	0
	Moderately to strongly contaminated	0	0	0	0	0	0	0	2	0	0	0
	Strongly contaminated	0	0	0	0	0	0	0	0	0	4	0
	Strongly to extremely contaminated	0	0	0	0	0	0	0	2	0	0	0
	Extremely high contaminated	0	0	0	0	0	0	0	1	0	0	0
Erⁱ	Low ecological risk	-	36	36	36	36	36	36	32	36	36	-
	Moderate ecological risk	-	0	0	0	0	0	0	1	0	0	-
	Considerable ecological risk	-	0	0	0	0	0	0	0	0	0	-
	High ecological risk	-	0	0	0	0	0	0	2	0	0	-
	Serious ecological risk	-	0	0	0	0	0	0	1	0	0	-

Table 3. Distribution of samples in the ranges established by the SQG according to the HMs levels (mg/kg).

HMs	Mean concentration	Sediment quality guideline*		% of samples within ranges of the sediment quality guideline
HMs	Mean concentration	ERL	ERM	<ERL	>ERL and <ERM	>ERM
Cu	42.7	34	270	66.67 (24)	30.55 (11)	(1) 2.78
Ni	22.4	20.9	51.6	47.22 (17)	52.78 (19)	0
Zn	356.8	150	410	36.11 (13)	52.78 (19)	11.11 (4)
As	5.16	8.2	70	97.22 (35)	2.78 (1)	0
Cr	74.8	81	370	94.44 (34)	2.78 (1)	2.78 (1)
Pb	561.7	46.7	218	58.33 (21)	36.11 (13)	5.56 (2)

Table 4. Correlation matrix of the investigated HMs.

	Al	As	Co	Cr	Cu	Fe	Mn	Ni	Pb	V	Zn
Al	1
As	0.149	1
Co	0.886^**	0.112	1
Cr	0.197	0.114	0.236	1
Cu	0.023	0.044	0.142	0.265	1
Fe	0.444^**	-0.031	0.657^**	0.079	0.237	1
Mn	0.620^**	0.024	0.794^**	0.102	0.198	0.939^**	1
Ni	0.887^**	0.186	0.937^**	0.460^**	0.269	0.574^**	0.717^**	1
Pb	0.045	0.988^**	-0.009	0.092	0.058	-0.146	-0.101	0.079	1
V	0.877^**	0.013	0.786^**	0.076	-0.019	0.471^**	0.602^**	0.738^**	-0.104	1
Zn	0.350^*	-0.005	0.499^**	0.049	0.098	0.462^**	0.483^**	0.458^**	-0.057	0.358^*	1

**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).

Table 5. Principal component loadings and variance percentage for the extracted three components.

	Component
	PC1	PC2	PC3
Al	0.893	0.06	-0.258
As	0.123	0.967	-0.138
Co	0.96	-0.002	-0.082
Cr	0.297	0.243	0.606
Cu	0.22	0.113	0.805
Fe	0.754	-0.21	0.139
Mn	0.868	-0.154	0.043
Ni	0.947	0.128	0.102
Pb	-0.005	0.983	-0.105
V	0.830	-0.111	-0.326
Zn	0.572	-0.115	-0.001
% of Variance	47.78	20.73	12.56
Cumulative %	47.78	68.5	81.07

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