Geographic Information System and Contamination Indices for Environmental Risk Assessment of Landfill Disposal Sites in Central Saudi Arabia

Abstract

Landfills pollute air, soil, and surface and groundwater worldwide. The present work aims to assess the environmental risks of 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 (11,532 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 from Al Kharj road landfill (RL3). However, the average values of all HMs were lower than those from most worldwide soils and backgrounds, except for 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 Cu showed EF ˃ 2, which might be indicative of anthropogenic activities, especially in RL3. Additionally, very high contamination and a high effects range—median were reported in individual samples, especially for Pb, As, and Zn, indicating 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.

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 are commonly used worldwide for the disposal of municipal solid waste (MSW). In the United States, 52.6% of MSW is discarded in landfills [4], while in Brazil the figure is 59.1% [5]. In the Kingdom of Saudi Arabia (KSA), the percentage is 85% [6], in Malaysia it is 94.5% [7], and in China it is 79% [8]. In Venezuela, sanitary landfills account for 32%, controlled disposal for 43%, and non-controlled disposals or open dumps for 24% [9]. In Mexico, sanitary landfills account for 65%, while uncontrolled and open dumps account for 30% [10]. Lastly, in Thailand, the percentage is 27% [11,12]. 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 [13]. 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. 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 landfills 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 [12,14,15,16].

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., [17,18,19,20,21,22]. The field investigations revealed that landfills receive a wide variety of waste, representing diverse municipal solid waste, including food scraps, packaging materials, paper, cardboard, plastics, glass, textiles, grass clippings, leaves, branches, old furniture, mattresses, and appliances. Additionally, industrial wastes 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 crop residues, and other organic materials from agricultural activities, as well as pesticide containers, plastic sheeting, and other materials used in modern agriculture. Special waste encompasses used and discarded tires, batteries, and sludge. This study aimed to monitor spatial changes and the expansion of three landfill sites over time in central Saudi Arabia—for the first time—and to assess their environmental risks using GIS tools, soil quality guidelines, and various contamination indices.

2. Materials and Methods

Three landfills were selected for this study in southern Riyadh using Esri basemaps and satellite imagery from Google Earth (Figure 1). The authors particularly focused on landfills located in the southern part of Riyadh due to their proximity to industrial areas, raising concerns about potential environmental risks. Riyadh landfill site 1 (RL1) is located in the northeast of the Noor–Sulay industrial district, at latitudes 24.6340–24.6485° N and longitudes 46.8046–46.8213° E. Riyadh landfill site 2 (RL2) is situated in the Al Birriyyah district in northeast of the second industrial city, at 24.5687–24.5456° N, and 46.9095–46.9329° E, while 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. Three field trips were made to the three landfills in April and May, 2024, during which all different types of waste within each landfill were observed, and 12 soil samples were collected from each one. Sample coordinates were recorded using a GPS device. The samples were taken from the original surface soil between piles of solid waste to study the extent to which this soil has been affected by the presence of waste piles after exposure to rainfall or wind.

Samples were preserved in plastic bags and maintained at 4 °C until analysis. All samples were washed with distilled water and subsequently dried at 100 °C. Dried samples are homogenized by grinding with a non-metallic mortar and pestle to achieve a consistent fine particle size. Iron, aluminum, lead, zinc, manganese, chromium, copper, nickel, vanadium, arsenic, and cobalt were evaluated via inductively coupled plasma-atomic emission spectrometry (ICP-AES) at the ALS Geochemistry Laboratory in Jeddah, Saudi Arabia. A 0.50 g sample was subjected to digestion with aqua regia (a combination of one part nitric acid and three parts hydrochloric acid) for 45 min on a hot plate with sand, at temperatures between 60 and 120 °C, until the complete disintegration of mineral matrices and the liberation of metals occurred [22]. The processed sample was subsequently filtered, diluted with deionized water to a volume of 50 mL, and prepared for ICP-AES analysis.

The sample solution is drawn into an argon plasma torch operating at temperatures exceeding 6000 °C. Elements are atomized and ionized, emitting light at specific wavelengths. The intensity of emitted light correlates directly with the concentration of the element in the sample. The ICP-AES is calibrated with certified multi-element standards of known quantities, manufactured in an analogous acid matrix to the sediment samples. Certified Reference Materials (CRMs) with established composition, matrix-matched to sediments, are analyzed alongside samples to verify the method’s correctness. Duplicate samples or sample divisions are examined to guarantee accuracy and reproducibility. Validation parameters improve the reliability and accuracy of the ICP-AES analysis [23,24].

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 20 February 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 was 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. For each specific year, landfill expansion was digitized to accurately track spatial changes and expansion. This allowed for accurate area calculations for each year in each landfill.

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. 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 < 1	Low contamination factor
	1 ≤ Cf <3	Moderate contamination factor
	3 ≤ Cf < 6	Considerable contamination factor
	Cf ≥ 6	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 contamination
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

present the calculation procedures and classification of these contamination indices and the parameters utilized in this work [25,26,27].

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

(1)

I-geo = Log2 (Cn/(1.5 × Bn))

(2)

CF = M/X

(3)

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

(4)

Erⁱ = Trⁱ × Cfⁱ

(5)

RI = Ʃ (Trⁱ × Cfⁱ)

(6)

M represents the concentrations of the analyzed metal, while X signifies the levels of a normalizer element (Fe). Iron is used as a reference element due to its abundance in the Earth’s crust, providing a stable and reliable baseline. Additionally, it remains largely immobile across various environmental conditions and is considered a conservative element, generally unaffected by human activities [28]. 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 [27].

3. Results and Discussion

3.1. Landfill Variation Through Time

3.1.1. Noor–Sulay Landfill (RL1)

The Noor–Sulay district landfill is characterized by 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 are also included. In 2014, the site appeared to be a warehouse or a car maintenance workshop complex, and it had 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 square area. 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. Al Birriyyah Landfill (RL2)

The Al Birriyyah district landfill comprises diverse municipal solid wastes including 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 3). By August 2024, the site’s use as a landfill reached approximately 46.8%, with the utilized area expanding to about 1.93 km².

3.1.3. Al Kharj Road Landfill 3 (RL3)

The Al Kharj Road landfill is surrounded by various industrial activities, including wood and steel furniture manufacturing, leather tanning, and electrical wire and conductor production, alongside a scrap metal recycling plant processing metals from old products and structures. It is characterized by diverse wastes including cardboard, old furniture, used tires and car oils, concrete, bricks, copper cables, 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 long-term presence of HMs in ecosystems can cause extensive harm to local flora, fauna, and entire ecosystems. HMs like lead, cadmium, mercury, and arsenic are particularly toxic because they bioaccumulate and magnify within food webs, creating far-reaching ecological disruptions. In plants, HMs can inhibit growth, photosynthesis, and soil health, reducing biodiversity and altering natural regeneration processes. Terrestrial predators, such as birds and mammals, suffer neurological and reproductive issues due to bioaccumulation, which thus poses a severe risk to biodiversity and ecosystem balance [29]. The concentration of HMs (mg/kg, dry weight) in the investigated landfills is shown in

Table 2. The concentration of HMs (mg/kg) from three investigated landfills.

S.N.	Al	As	Co	Cr	Cu	Fe	Mn	Ni	Pb	V	Zn
1	4300	3.00	3.00	20.0	41.0	11,100	138	14.0	60.0	23.0	85.0
2	5800	4.00	5.00	30.0	75.0	24,400	346	27.0	27.0	24.0	93.0
3	4800	5.00	5.00	32.0	68.0	29,000	290	25.0	28.0	23.0	94.0
4	5600	4.00	5.00	26.0	29.0	14,200	201	22.0	39.0	24.0	152
5	7100	4.00	5.00	26.0	34.0	11,100	187	25.0	55.0	27.0	328
6	2700	2.00	3.00	25.0	50.0	12,400	144	12.0	81.0	13.0	131
7	4600	3.00	4.00	22.0	51.0	11,000	157	20.0	50.0	20.0	217
8	3800	4.00	3.00	19.0	44.0	9200	132	16.0	64.0	21.0	74.0
9	1900	1.50	2.00	15.0	9.0	7900	106	12.0	39.0	5.0	185
10	2800	2.00	2.00	15.0	10.0	8200	136	11.0	20.0	15.0	60.0
11	5000	3.00	4.00	21.0	40.0	11,200	167	20.0	20.0	21.0	117.0
12	2200	2.00	1.00	10.0	11.0	3900	59	7.00	9.00	10.0	30.0
13	3700	2.00	3.00	13.0	16.0	7000	103	14.0	10.0	16.0	35.0
14	6100	3.00	4.00	42.0	17.0	9200	149	22.0	57.0	22.0	200
15	7400	3.00	5.00	26.0	11.0	10,500	164	27.0	17.0	24.0	37.0
16	7400	4.00	6.00	904	118	13,200	191	47.0	120	25.0	363
17	4400	5.00	3.00	20.0	302	8000	114	23.0	1045	16.0	53.0
18	3000	2.00	2.00	23.0	15.0	6500	93	12.0	63.0	11.0	65.0
19	4400	2.00	3.00	18.0	6.00	7000	104	15.0	20.0	23.0	36.0
20	2800	2.00	2.00	10.0	4.00	5300	93	10.0	7.0	18.0	22.0
21	6800	4.00	4.00	24.0	13.0	10,700	174	22.0	34.0	40.0	70.0
22	6400	3.00	4.00	18.0	10.0	8800	158	22.0	19.0	25.0	35.0
23	3500	2.00	2.00	13.0	6.0	6500	93	13.0	13.0	14.0	32.0
24	4100	2.00	3.00	15.0	8.0	7800	109	14.0	14.0	15.0	33.0
25	4100	4.00	5.00	46.0	89.0	20,300	281	28.0	85.0	17.0	2230
26	10,000	5.00	10.0	46.0	55.0	18,900	283	50.0	75.0	41.0	1625
27	3000	2.00	2.00	14.0	8.00	7200	89	13.0	11.0	13.0	385
28	7600	3.00	5.00	28.0	28.0	11,000	161	31.0	18.0	29.0	194
29	5600	2.00	3.00	35.0	10.0	9600	150	20.0	11.0	20.0	67.0
30	8800	3.00	6.00	35.0	22.0	17,800	238	33.0	45.0	31.0	1920
31	7500	3.00	5.00	27.0	15.0	11,900	185	27.0	60.0	26.0	85.0
32	6100	41.0	4.00	125	25.0	7300	132	27.0	8960	18.0	128
33	10,400	5.00	7.00	40.0	27.0	15,700	247	40.0	179	33.0	144
34	8100	4.00	5.00	32.0	21.0	15,100	193	29.0	45.0	40.0	1515
35	3600	6.00	3.00	86.0	16.0	6300	103	12.0	950	11.0	397
36	7700	4.00	6.00	26.0	13.0	10,100	192	34.0	29.0	30.0	68.0
Min.	1900	1.50	1.00	10.0	4.0	3900	59	7.0	7.0	5.0	22.0
Max.	10,400	41.00	10.00	904.0	302.0	29,000	346	50.0	8960	41.0	2230
Aver.	5405	5.16	4.08	74.8	42.7	11,532	165	22.4	561.7	21.8	356.8

and Figure S1. The HMs’ average values had the following descending order: Fe (11,532) ˃ 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 represent decreases from those in worldwide soils [30], Earth’s crust [31], the continental crust [32], and the recommended levels of HMs [33]. However, average values of Zn and Pb exceed the averages of the abovementioned worldwide soils. Moreover, average values of Cu and Cr are decreased compared to those of the worldwide soils except those found in [30] and the recommended levels of HMs [33]. Figure 5 and Table S1 imply that most of the highest values of the HMs were recorded in RL3, at the third industrial city; for instance, Al (10,400 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. The highest values for Fe and Mn were recorded in RL1 at the Al Sulay industrial district (29,000 and 346 mg/kg). However, the lowest HMs were recorded in RL2: Al, As, and V in sample 9; Co, Fe, Mn, and Ni in sample 12; and Cr, Cu, Pb, and Zn in sample 20 (Figure 5, Table S1).

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 Riyadh landfill disposal sites, the following factors were taken into consideration.

3.3.1. Enrichment Factor (EF)

This method is proposed by [34] to estimate the anthropogenic impact of HMs using a normalization element (Fe) 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 [35,36,37,38,39]. The minimum, maximum, and average EF values for the HMs are presented in Table S1. Results of EF analysis 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, which were found to entirely originate from the crustal materials or natural processes, while As, Cr, Pb, Zn, and Cu, with EF ˃ 2, are most likely the product of anthropogenic activities [38].

Figure 5 represents the spatial distribution of EF per sample locations for Pb, As, Zn, Cu, and Cr in the three landfills. Four samples in RL3 (25, 26, 30, 34) showed EF ˃ 40 for Zn, and three samples (17, 32, 35) 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, and 2 samples for Cr and Cu (

Table 3. 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 contamination	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	-

). 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 [39,40].

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 [25,41,42]. Results of CF in Table S2 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 found to have low contamination of Co, Fe, Al, Mn, Ni, and V. A very high contamination was recorded in five samples of the landfill disposal sites (16, 17, 32, 33, 35) for Pb, four samples (25, 26, 30, 34) for Zn, and one sample (16, 17) for Cu and Cr, respectively. However, considerable contamination was reported in seven samples for Pb, four samples for Zn, and one sample for As (Table 3).

3.3.3. Geoaccumulation Index (Igeo)

The geoaccumulation index (Igeo) is a common criterion used for evaluating the HM pollution in soil [27], where HM contamination was determined by comparing their current concentration levels with those from preindustrial times. Results of Igeo in Table S3 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, moderate to strong contamination, strong to extreme contamination, and extremely high contamination for Pb were reported in two samples (16, 33), two samples (17, 35), and one sample (32), respectively (Table 3).

3.3.4. Potential Risk Index (RI)

Potential ecological risk was introduced by [25] for the assessment of the degree of ecological risk caused by HM concentrations in the water, air, and soil. This index covers various environmental effects, such as toxicology, environmental chemistry, and ecology, and can evaluate ecological risks caused by heavy metals [27,42,43]. The RI is calculated on the basis of three indices: single index of ecological risk factor (E_rⁱ), the pollution coefficient of a single element (C_fⁱ), and toxic response factor of individual metals (T_rⁱ). 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 32, high ecological risk in samples 17 and 35, and moderate ecological risk in sample 33 (Table 3 and Table S4). The average RI values varied from 5.35 in sample 20 to 2281 in sample 32, with an average of 154.95. This finding indicates moderate ecological risk due to the presence of HMs in the landfill soils. However, few individual samples showed high potential and significantly high ecological risks (Table S4).

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) [44,45].

Table 4. Distribution of samples in the ranges established by the SQG according to the HM levels (mg/kg).

HMs	Mean Concentration	Sediment Quality Guideline [46]		% of Samples Within Ranges of the Sediment Quality Guideline
		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)

illustrates the range of ERL and ERM values for samples quality guidelines (SQG) of [46] for Cu, Ni, Zn, As, Cr, and Pb along with the percentage of samples falling within these SQG ranges. A total of 35 samples (97.22%) were <ERL and one sample was >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 four 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 1 sample, and Cr in 1 sample revealed occasional adverse effects for these HMs (Table 4).

Results of Pearson’s correlation (

Table 5. 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 **	.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).

) 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), and Co–V (r = 0.786), implying similar sources for these pairs [47]. Occurrence of Fe, Al, and Mn in such correlations indicated natural sources for these HMs; in particular, Al, Co, Mn, and V showed average EF values less than 2 [40,43]. Differently, the strong positive correlation between As and Pb may be indicative of anthropogenic sources related to agricultural and industrial wastes [21]. This suggestion is supported by results of the contamination indices for these two HMs.

The results of Pearson’s correlation are supported to a great extent by principal component analysis (PCA) which extracted three PCs, accounting for 47.78%, 20.73%, and 12.56% of the total variance, respectively (

Table 6. Principal component loadings and variance percentage for the three extracted 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

, Figure 6). PC1 showed high loading for Al, Co, Fe, Mn, Ni, V, and Zn, which entirely originate from crustal materials or natural processes. PC2 showed high loading for Pb and As, while PC3 presented high loading for Cr and Cu, which might reveal different sources of anthropogenic factors.

This study has several limitations, including the limited number of landfill sites investigated, the absence of temporal data on HM concentrations, the scarcity of high-resolution satellite images and historical data for central Saudi Arabia, and the inaccessibility of certain remote landfill sites, which complicates regular on-ground surveys. Additionally, the high temperatures, particularly in summer, further limit the ability to conduct landfill surveys and collect soil samples.

4. Conclusions

The current study highlighted the environmental risks associated with the presence of three landfills in central Saudi Arabia. The study’s findings can be summarized as follows: GIS tools have shown a substantial increase in the area of these landfills from 2014 to 2024, with average expansion rates rising from 12.3% to 78.1%. Pollution indices and soil quality guidelines have proven that the soil in these landfills is deficiency to minimal enriched with Al, Co, Mn, and V, and contaminated with certain HMs such as Pb, As, Zn, Cu, and Cr. These pollutants may either flow along the valleys or seep into the ground layers. However, the contamination with Pb, Zn, Cu, and Cr may be attributed to the high concentrations of these HMs in five specific samples (16, 17, 25, 32, and 35). If these samples were excluded from the study for statistical rule that involves excluding outliers or handling them, the average concentrations of these HMs would decrease to more typical levels. 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.