Iron Contamination in Groundwater: Risk Assessment and Remediation Techniques in Egypt’s New Valley

Abstract

This study evaluates water quality (surface and deep wells as well as tap water) within villages of the El-Kharga Oasis (New Valley), focusing on their chemical composition, Fe contents, and potential hazards quantifying human exposure to Fe through different pathways, i.e., ingestion and dermal contact. Generally, the water quality meets the standards of the WHO guidelines for most sites, except for Fe, whose total and soluble contents in surface and ground waters exceed the permissible levels. Fe was higher in surface wells than in the deeper ones. Moreover, total Fe was higher than the permissible level in tap water, indicating potential health hazards for children living therein (hazardous index > 1). Another lab experiment was conducted to assess the efficacy of using dolomite, calcite, glauconite, and biochar for Fe removal from solutions artificially contaminated with Fe at a rate of 1000 mg Fe L⁻¹. Generally, Fe solubility decreased with increasing the pH of media from two to seven. Dolomite exhibited the highest efficiency for removing Fe from the solution for five successive cycles, with slight reductions in efficiency from 100% to 93.67% between the first and fifth cycle. Overall, Fe removal efficiencies followed the order of calcite > dolomite > biochar > glauconite. This sorption fitted the Langmuir isotherm model, and its kinetics (5–20 min) followed a pseudo-second order model. Furthermore, Fe recovery from dolomite was high, ranging from 100%, while decreased slightly to 92.93% in the fifth cycle. Although the results for calcite were also promising, our results showed its higher erodibility rate compared to dolomite. These findings offer valuable insights towards managing water quality and developing solutions for treating contaminated water sources, with a specific emphasis on the efficacy of dolomite and calcite for removing Fe from Fe-contaminated water.

1. Introduction

Global demand for freshwater is ever-increasing to meet rapid population growth and sustain the goals of development [1,2,3]. In water-stressed countries and regions, groundwater represents an important resource for drinking and agricultural and industrial activities [1,4,5,6]. Egypt is an example of a water-stressed country, i.e., the water share per capita does not exceed 560 m³ annually [7]. The New Valley Governorate is one of the promising desert border provinces in Egypt [8], which is marked by vast stretches of the Sahara Desert [9]. This area depends on the Nubian Sandstone Aquifer as the sole source of freshwater [10].

Groundwater quality may generally be affected by various factors, including their contents of potentially toxic elements (PTEs) [5]. Iron (Fe) is among the main contaminants in the groundwater of New Valley (Egypt). Its elevated levels pose significant environmental and health challenges [10], such as gastrointestinal discomfort, organ damage, and increased risk of chronic diseases [11,12]. The World Health Organization (WHO) has, therefore, set standards limiting iron concentrations up to 0.3 mg L⁻¹ in drinking water based on considerations of color and staining potential [11]. Additionally, iron-rich water can cause clogging of irrigation systems and impact plant growth and soil health [13,14].

Concentrations and mobility of iron in groundwater are influenced by various factors, including geological substrate, redox conditions, and pH levels [15]. Various technologies were used successfully in remediating iron-contaminated water, including filtration, oxidation, ion exchange, and biological methods [16,17,18]. Among these techniques, biochar emerges as a safe, cheap, and sustainable approach for removing iron from water via sorption mechanisms [19,20]. This carbon-rich product is produced via the pyrolysis of organic residues under limited oxygen conditions [21]. Because of its porous structure and high CEC; this additive can immobilize PTEs, hence reducing their solubility in water [22].

Two other ecofriendly and economic approaches can help in deironing wastewaters. For example, clay minerals have a high capability for the removal of contaminants that exist in wastewater [23,24], especially the expandable 2:1 ones, such as glauconite [25]. This mineral (glauconite) has high cation exchange capacity and exhibits high chemical and mechanical stability [26]. Also, chemical precipitation of PTEs may effectually downgrade their concentrations in wastewaters [27]. In particular, dolomite and calcite are excellent candidates for the successful removal of PTEs from wastewaters [27,28,29].

El-Khargais is the biggest oasis of the New Valley, Egypt. Its groundwater contains high levels of Fe, which may pose potential risks to the surroundings [10]. Accordingly, this study aims at (1) monitoring the total and soluble levels of Fe in water samples collected from seven different sites comprising shallow and deep wells across the villages of the El-Kharga Oasis, to estimate health hazards and potential environmental risks associated with using such waters for drinking and irrigation purposes. Tap water was also collected from the same sampling sites for data comparison. Moreover, this study evaluates (2) the efficiencies of using natural safe economic additives, i.e., organic/inorganic adsorbents (biochar and glauconite) and traditional chemical precipitation techniques (calcite and dolomite) for the removal of Fe from aqueous solutions. Sorption isotherms and kinetic models were applied to depict Fe sorption pathways by the investigated materials. Also, the sorbent regeneration after five successive cycles of Fe sorption and desorption was a matter of concern herein. We believe that this integrant study has not yet been performed before in such detail. These objectives are consistent with the Egyptian Sustainable Development 2030 goals, which contribute to sustainable water resource management in the region and ensuring the health and well-being of its inhabitants and the environmental integrity of its ecosystems.

2. Methodology

2.1. Study Location

Water samples were collected from 7 different sites comprising shallow and deep wells across the villages of El-Kharga Oasis (New Valley): El-Monira (7 sites), El-Sherka (9 sites), El-Kharga (9 sites), Porsaied (5 sites), Ganah (5 sites), Bolak (8 sites), and Germashen (6 sites). Additionally, tap-water samples were collected from the abovementioned sites (Figure 1). These samples completely filled sterilized containers, which were tightly closed to avoid Fe oxidation, properly labeled, preserved at 4 °C to stop changes in water chemistry, and transported to the laboratory within 4 h of collection

2.2. Water Analyses

The water samples underwent a comprehensive chemical and physical analysis following methodologies by Abdelhafez and Li [20]. The key parameters for evaluating water quality in this study were pH, electrical conductivity (Cole-Parmer PC100 pH/Conductivity Meter, Shanghai, China), and turbidity (TB1 Portable Turbidimeter, Velp, Usmate, Italy). For field analysis, the samples were collected after two hours of well operation to ensure representative water quality. Analytical grade reagents (Sigma Aldrich, St. Louis, MO, USA, products of USA) and rigorously acid-washed glassware were used to ensure precise results. All analyses were conducted in triplicate, including blanks and spiked samples as quality controls, with recovery rates between 97.6 and 98.82%, indicating high accuracy and precision. Cation and anion concentrations were assessed per Baird et al. [30]. Soluble and total Fe concentrations were quantified following digestion with concentrated nitric acid by using an Inductively Coupled Plasma instrument (Jobin Yvon Horiba Ultima 2 Inductively Coupled Plasma, Palaiseau, France). The results were then compared to the WHO and FAO guidelines as international water quality benchmarks.

2.3. Risk Assessment

Potential human health hazards were evaluated by quantifying exposure levels to Fe through ingestion and dermal contact. Based on the average daily dose (ADD) and toxicity indices for Fe (

Table 1. Input parameters and toxicity index to characterize the ADD and HI values.

Parameter	Description	Unit	Adult	Children
C	Contaminant concentration in water	μg L−1	--	--
IR	Ingestion rate	L day−1	2.2	1.8
EF	Exposure frequency	L day−1	350
ED	Exposure duration	Years	30.0	6.0
BW	Body weight	Kg	70.0	15
AT	Average time	Days	10,500	2100
SA	Exposure skin area	cm2	28,000	6600
ET	Exposure time	h day−1	0.6	1.0
CF	Unit conservation factor	L/cm3	0.001
Kp, Dermal permeability coefficient		cm h−1	0.001
Fe oral and dermal reference dose		μg kg−1 day−1	700,000

), non-carcinogenic risk assessment was estimated according to Abdelhafez and Li [31] and USEPA [32], and as outlined below. This structured approach incorporating diverse reputable sources ensured a robust evaluation of potential health risks from heavy metal exposure in the studied areas.

$$\mathrm{A}\mathrm{D}\mathrm{D} \mathrm{w}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{r} \mathrm{i}\mathrm{n}\mathrm{g}\mathrm{e}\mathrm{s}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}=\frac{C\times IR\times ED\times EF}{BW\times AT}$$

(1)

$$\mathrm{A}\mathrm{D}\mathrm{D} \mathrm{w}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{r} \mathrm{d}\mathrm{e}\mathrm{r}\mathrm{m}\mathrm{a}\mathrm{l} \mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{a}\mathrm{c}\mathrm{t}=\frac{C\times SA\times ABS\times EF\times ED}{BW\times AT}$$

(2)

where ADD is the average daily dose of Fe, C is the metal concentration in the water (mg L⁻¹), IR is the ingestion rate per unit time, ED is the exposure duration, EF is the exposure frequency, BW is human body weight, AT is the averaging time, SL is the skin adherence factor, SA is the surface area of contact, and ABS is the absorption factor.

The calculated ADD values will then be used to determine the hazard quotient (HQ) and the hazard index (HI), which are as follows:

$$HQ=\frac{ADD}{RfD}$$

(3)

$$\mathrm{HI}=\sum HQ$$

(4)

where RfD is the reference dose, which is defined as the maximum daily intake of the contaminant without a deleterious health effect [31]. If ADD > RfD, there will be a possible deleterious health impact.

2.4. Efficiency of Different Sorbent Materials for Fe Removal from Aqueous Solution

Various materials were evaluated for their efficiencies in removing Fe from aqueous solutions, including biochar, dolomite, calcite, and glauconite. Biochar was produced from date palm waste via pyrolysis at <500 °C [33]. Extensive analyses were also set to characterize the properties of the used sorbents, i.e., pH, EC, organic content, and FTIR bonding structures. Dolomite was processed to 1–3 mm, rinsed, and dried. Its recyclability and hardness avoid the disintegration issues of calcite, enhancing efficiency and sustainability. Calcite and glauconite were carefully collected from a controlled agricultural setting, ensuring authenticity. All materials underwent meticulous preparation for uniformity and accurate comparison.

2.4.1. Preparation of Fe Solutions

Solutions containing iron (Fe) ions (1000 mg Fe L⁻¹ stock solution) were prepared for sorption and kinetic experiments using FeSO₄·7H₂O (Sigma Aldrich, ACS reagent > 99.9%). This stock was then diluted to prepare a series of solutions with concentrations ranging from 5 to 400 mg L⁻¹ Fe using distilled water.

2.4.2. Batch Adsorption Studies

Batch experiments were conducted in the lab to investigate the effects of pH, contact time, and initial Fe concentration on Fe sorption using the materials that were mentioned above, and their efficiencies for removing contaminants from aqueous solutions were evaluated. The experiments utilized a series of 100 mL capped plastic flasks for shaking the samples with a mechanical shaker. The pH of the Fe solutions was carefully adjusted using 0.1 M of either NaOH or HNO₃ to range from 2 to 7, as pH values significantly influence Fe ionization in solutions and its sorption behavior [18].

Time-course experiments were also conducted for periods ranging from 5 to 240 min after adding sorbents at a fixed rate of 1 g L⁻¹. Then, the mixtures were agitated at 120 rpm for each time and centrifuged at 5000 rpm for 10 min to separate the supernatants to determine Fe by using a spectrophotometer using UV2400 dual split-beam UV-VIS. Fe quantification was meticulously carried out in accordance with the ASTM E394 standard test method. This method involved the utilization of the 1,10-Phenanthroline method [34]. The Fe removal efficiency was then calculated using the following equations:

$$\mathrm{R}\mathrm{e}\mathrm{m}\mathrm{o}\mathrm{v}\mathrm{a}\mathrm{l} \mathrm{e}\mathrm{f}\mathrm{f}\mathrm{i}\mathrm{c}\mathrm{i}\mathrm{e}\mathrm{n}\mathrm{c}\mathrm{y}\left(\%\right)=\frac{\mathrm{C}0-\mathrm{C}\mathrm{e}}{\mathrm{C}\mathrm{e}}\times 100$$

(5)

where C0 is the concentration of the applied Fe ions, and Ce is the Fe ions concentration at equilibrium, respectively. Fe ions adsorbed (mg g⁻¹) on the biochar were calculated for each sorbent by the following equation:

$$qe=\frac{\mathrm{C}0-\mathrm{C}\mathrm{e}}{\mathrm{V}}$$

(6)

where qe is the amount of adsorbed Fe ions (mg Fe g⁻¹), V is the applied Fe ions solution volume (L), and W is the adsorbent weight (g).

2.4.3. Adsorption Isotherms

Several isotherms were tested to understand the main mechanism beyond Fe removal from aqueous solutions i.e., Freundlich and Langmuir models [20].

$$\mathrm{The} \mathrm{Freundlich} \mathrm{model} \mathrm{is} \mathrm{as} \mathrm{follows}: {\mathrm{q}}_e={K_F{C}_e}^{\frac{1}{n}}$$

(7)

where q_e is adsorbed metal per adsorbent mass, K_F and n are empirical constants, and C_e is the equilibrium concentration. Its linearized form is:

$$\log q_e=\log K+\frac{1}{n}{\log C}_e$$

(8)

The Langmuir model is [35]:

$$q_e=\frac{Q_{\max {bC}_e}}{1+{bC}_e}$$

(9)

where Q_max is the maximum adsorption capacity and b indicates the binding affinity. Qmax and b were calculated from the linear plot of Ce/qe vs. Ce.

The dimensionless separation factor RL predicts favorable/unfavorable adsorption [36]:

$$RL=\frac{1}{1+{bC}_e}$$

(10)

RL values imply >1 unfavorable, 1 linear, 0–1 favorable, 0 irreversible.

2.4.4. Adsorption Kinetics Models

Pseudo-first-order and pseudo-second-order models were used to analyze the adsorption kinetics of Fe onto the tested materials [37].

$$\mathrm{The} \mathrm{pseudo}-\mathrm{first}-\mathrm{order} \mathrm{model} \mathrm{is} \log \left(q_e-q_t\right)=log{q}_e-\frac{K_1.ads}{2.303}t$$

(11)

where q_e and q_t (mgg⁻¹) are the amount of metal ions adsorbed at equilibrium (mgg⁻¹) and t (mins), respectively, and K₁ is the rate constant of the equation (mins⁻¹).

$$\mathit{The}\mathit{pseudo}-\mathit{second}-\mathit{order} \mathit{is} \frac{dq}{dt}-{\left(q_{eq-}q\right)}^2$$

(12)

$$\mathrm{Its} \mathrm{integration} \mathrm{is} \frac{t}{q}-\frac{1}{K_{2{adsqe}^2}}+\frac{t}{q_e}$$

(13)

where t (min.) is the contact time; q_eq (mg g⁻¹) and q (mg g⁻¹) are the amount of Fe ions adsorbed at equilibrium and at any time of reaction t.

2.5. Regeneration

Batch regeneration experiments were conducted on the used materials via 0.1 M of HCl at 1 g L⁻¹ to release adsorbed Fe for 5 successive cycles of adsorption–desorption under the optimal pH value to attain successful Fe removal. The desorption rate and removal efficiency were determined to evaluate the sustainable performance of the selected sorbent materials.

2.6. Data Analysis

The statistical analysis involved ANOVA and DMRT for mean separation (p < 0.05) to assess differences between treatments. This rigorous methodology enhances scientific precision and reliability.

3. Results and Discussion

3.1. Chemical Analyses of Water

As shown in

Table 2. Chemical and physical characteristics of tested water samples in the studied locations.

Village	Well	Depth, m	pH	EC dS m−1	Turbidity, NTU
El-Monira	El-Monira 2 old (M1)	706	7.07 ± 0.02	0.60 ± 0.02	16.4 ± 0.12
	El-Monira- country (M2)	550	7.19 ± 0.03	0.69 ± 0.02	2.36 ± 0.31
	El-Monira5 (M3)	304	7.05 ± 0.04	0.67 ± 0.0	7.03 ± 1.80
	El-Monira- Om ELkosour (M4)	290	7.34 ± 0.02	0.46 ± 0.0	5.31 ± 0.10
	El-Monira- 1/9 (M5)	386	7.03 ± 0.0	0.66 ± 0.01	12.55 ± 0.92
	El-Monira-surface 1 (MS1)	<100	6.81 ± 0.01	1.07 ± 0.0	29.55 ± 1.62
	El-Monira- surface 2 (MS2)	<100	7.48 ± 0.11	0.55 ± 0.0	2.19 ± 0.16
	El-Monira- drinking water (MD)	--	7.19 ± 0.02	0.96 ± 0.0	5.90 ± 0.21
El-Sherka	El-Sherka- 55	703	7.15 ± 0.01	0.54 ± 0.0	10.11 ± 0.42
	El-Sherka- 4	696	7.04 ± 0.002	0.51 ± 0.01	3.91 ± 0.11
	El-Sherka- 8	643	7.80 ± 0.001	0.56 ± 0.04	1.28 ± 0.06
	El-Sherka- 21/34	405	7.19 ± 0.00	0.72 ± 0.0	1.40 ± 0.08
	El-Sherka- 5	332	7.08 ± 0.00	0.47 ± 0.0	7.17 ± 1.03
	El-Sherka- 7	302	7.42 ± 0.05	0.723 ± 0.07	0.805 ± 0.06
	El-Sherka- surface 1	<100	7.13 ± 0.02	1.63 ± 0.0	21.60 ± 3.40
	El-Sherka- surface 2	<100	7.33 ± 0.00	0.68 ± 0.01	1.80 ± 0.57
	El-Sherka- surface 3	<100	7.22 ± 0.0	0.62 ± 0.0	1.32 ± 0.37
	El-Sherka- drinking water	--	7.78 ± 0.02	0.72 ± 0.39	0.48 ± 0.08
El-Kharga	El-Kharga- 41	762	6.78 ± 0.06	0.36 ± 0.0	16.35 ± 3.61
	El-Kharga- 38	740	6.94 ± 0.06	0.35 ± 0.0	26.90 ± 0.71
	El-Kharga- 12	509	6.95 ± 0.01	0.31 ± 0.02	34.25 ± 1.06
	El-Kharga- 23	322	7.03 ± 0.01	0.44 ± 0.01	28.60 ± 0.71
	El-Kharga- 24	283	6.90 ± 0.08	0.48 ± 0.01	39.05 ± 3.48
	El-Kharga- 26	278	6.82 ± 0.02	0.60 ± 0.01	36.90 ± 0.28
	El-Kharga- surface 1	<100	6.99 ± 0.09	0.51 ± 0.0	24.90 ± 0.14
	El-Kharga- surface 2	<100	6.42 ± 0.03	1.76 ± 0.02	69.70 ± 1.98
	El-Kharga- surface 3	<100	6.64 ± 0.03	1.70 ± 0.01	80.15 ± 2.47
	El-Kharga- drinking water	--	7.04 ± 0.09	0.82 ± 0.29	0.78 ± 0.07
Porsaied	Porsaied- Nassir new south	573	6.75 ± 0.05	0.80 ± 0.0	34.70 ± 1.27
	Porsaied- Nassir new north	512	6.76 ± 0.04	0.75 ± 0.02	44.852.19
	Porsaied- Nassir tourist	563	7.09 ± 0.04	0.48 ± 0.02	19.10 ± 0.14
	Porsaied- new	323	7.18 ± 0.01	0.32 ± 0.0	6.72 ± 0.0
	Porsaied- surface	<100	6.78 ± 0.05	0.34 ± 0.0	16.45 ± 1.91
	Porsaied- drinking water	--	7.265 ± 0.08	0.34 ± 0.0	0.89 ± 0.29
Ganah	Ganah- 5	800	6.82 ± 0.03	0.54 ± 0.0	42.80 ± 0.57
	Ganah- 2/4	804	6.85 ± 0.02	0.39 ± 0.0	26.35 ± 6.15
	Ganah- 11/16	791	7.43 ± 0.03	0.38 ± 0.0	7.93 ± 0.30
	Ganah- 20 country	453	7.04 ± 0.15	0.61 ± 0.0	25.5 ± 14.42
	Ganah- surface	<100	7.04 ± 0.04	0.35 ± 0.0	17.95 ± 1.20
	Ganah- drinking water	--	7.32 ± 0.04	0.34 ± 0.0	0.77 ± 0.02
Bolak	Bolak- 3 new	813	7.14 ± 0.03	0.47 ± 0.02	10.00 ± 0.57
	Bolak- 25	782	6.75 ± 0.04	0.91 ± 0.04	34.55 ± 2.76
	Bolak- 20	633	6.65 ± 0.06	0.96 ± 0.0	18.53 ± 14.81
	Bolak- 4/23	424	6.71 ± 0.01	0.94 ± 0.0	47.45 ± 2.90
	Bolak- 6	346	6.87 ± 0.01	0.65 ± 0.0	27.6 ± 3.25
	Bolk- palm relief	150	6.76 ± 0.0	0.73 ± 0.03	31.4 ± 2.83
	Bolak- surface 1	<100	6.60 ± 0.30	1.15 ± 0.04	5.82 ± 3.27
	Bolak- surface 2	<100	6.87 ± 0.04	1.00 ± 0.01	12.1 ± 0.71
	Bolak- drinking water	--	6.89 ± 0.01	1.05 ± 0.0	0.82 ± 0.04
Germashen	Germashen- 8	495	6.95 ± 0.02	0.91 ± 0.0	35.1 ± 0.71
	Germashen- 25	554	6.92 ± 0.03	0.84 ± 0.03	30.3 ± 2.69
	Germashen- 1	495	7.09 ± 0.02	0.55 ± 0.02	15.95 ± 0.92
	Germashen- 2G	532	7.10 ± 0.04	0.60 ± 0.0	9.35 ± 3.05
	Germashen- 16	573	6.91 ± 0.06	0.54 ± 0.01	23.3 ± 0.14
	Germashen- surface	<100	6.80 ± 0.0	0.69 ± 0.0	21.15 ± 2.62
	Germashen- drinking water	--	6.89 ± 0.12	0.64 ± 0.01	0.48 ± 0.02
WHO standard (drinking)		--	6.5–8.5	<1.5	--
FAO standard (irrigation)		--	6.5–8.5	<3.0	--

Values higher than the WHO standard are highlighted in italics. Values higher than the FAO standard are underlined. Values higher than both the WHO and FAO standards are highlighted in bold.

, the pH levels were generally within the permissible levels according to the drinking-water guidelines (6.5–8.5) of the WHO [11], where the highest pH values were detected in the El-Sherka drinking water (7.8). The lowest one was in El-Kharga surface 2 (6.42). However, the EC varied considerably, and exceeded the WHO limit (1.50 dS m⁻¹) only at the following sites: El-Sherka surface 1 (1.63 dS m⁻¹) and El-Kharga surface 2 (1.76 dS m⁻¹) and 3 (1.70 dS m⁻¹) [11].

Turbidity levels were the highest in El-Kharga surface 2 (69.70 NTU) and the least in Germashen drinking water (0.48 NTU), indicating relative potential contamination occurred at El-Kharga. Overall, the turbidity in many locations exceeded the recommended ones of the WHO (five NTF), and this highlights the need for further treatments to improve water standards for human consumption.

Chemical characterization (

Table 3. Chemical characterization of irrigation and drinking-water samples.

Village	Well	HCO3−	Cl−	SO4−−	Na+	Ca++	Mg++	K+
					mmolc L−1
El-Monira	El-Monira- 2	0.70 ± 0.14	1.40 ± 0.28	6.48 ± 0.60	3.07 ± 0.03	2.83 ± 0.60	1.88 ± 0.39	0.82 ± 0.00
	El-Monira- 5	0.70 ± 0.14	1.60 ± 0.57	6.14 ± 0.55	3.20 ± 0.09	3.43 ± 0.11	1.00 ± 0.35	0.82 ± 0.00
	Om eLksor	1.30 ± 0.14	0.80 ± 0.0	2.74 ± 0.46	2.20 ± 0.03	1.10 ± 0.42	0.70 ± 0.14	0.84 ± 0.00
	Monira Balad	0.80 ± 0.0	1.40 ± 0.28	4.63 ± 1.29	3.35 ± 0.00	1.30 ± 0.14	1.40 ± 1.13	0.78 ± 0.02
	Monira 1-9	0.50 ± 0.14	1.40 ± 0.28	3.88 ± 0.19	3.37 ± 0.03	1.40 ± 0.00	0.20 ± 0.00	0.81 ± 0.02
	Monira surface- 1	0.80 ± 0.0	1.20 ± 0.0	8.25 ± 0.74	2.98 ± 0.03	4.33 ± 0.04	2.18 ± 0.67	0.77 ± 0.00
	Monira surface- 2	0.90 ± 0.14	1.20 ± 0.57	3.84 ± 0.93	3.00 ± 0.06	1.98 ± 0.10	0.43 ± 0.32	0.54 ± 0.00
	Monira drinking water	0.80 ± 0.0	2.00 ± 0.57	4.65 ± 0.74	4.50 ± 0.03	1.63 ± 0.04	0.28 ± 0.11	1.05 ± 0.00
El-Sherka	El-Sherka- 5	0.70 ± 0.14	0.80 ± 0.0	5.75 ± 0.69	2.22 ± 0.00	3.03 ± 0.04	1.10 ± 0.71	0.91 ± 0.13
	El-Sherka- 55	0.90 ± 0.14	1.20 ± 0.0	5.65 ± 0.18	2.76 ± 0.03	3.20 ± 0.07	1.00 ± 0.28	0.79 ± 0.00
	El-Sherka- 4	0.60 ± 0.0	1.00 ± 0.28	5.51 ± 0.04	2.57 ± 0.00	3.13 ± 0.04	0.60 ± 0.28	0.82 ± 0.00
	El-Sherka- 7	1.20 ± 0.0	1.40 ± 0.28	5.21 ± 0.14	3.52 ± 0.00	3.15 ± 0.00	0.50 ± 0.42	0.64 ± 0.00
	El-Sherka- 8	0.90 ± 0.14	1.20 ± 0.0	5.18 ± 0.18	2.44 ± 0.00	3.28 ± 0.04	0.80 ± 0.28	0.77 ± 0.00
	El-Sherka- 21-34	1.00 ± 0.57	1.60 ± 0.0	5.62 ± 0.31	3.74 ± 0.06	3.30 ± 0.07	0.50 ± 0.14	0.68 ± 0.02
	El-Sherka surface- G2	1.00 ± 0.28	3.60 ± 1.13	9.41 ± 1.38	5.92 ± 0.25	5.45 ± 0.21	1.90 ± 0.99	0.74 ± 0.00
	El-Sherka surface- H2	0.80 ± 0.0	1.60 ± 0.0	5.67 ± 0.67	3.61 ± 0.00	3.23 ± 0.04	0.70 ± 0.71	0.54 ± 0.00
	El-Sherka surface- I 2	2.10 ± 0.14	8.00 ± 0.0	26.65 ± 0.18	11.31 ± 0.0	14.43 ± 0.53	9.40 ± 0.57	1.61 ± 0.00
	El-Sherka drinking water	0.70 ± 0.14	1.60 ± 0.0	6.65 ± 0.19	3.55 ± 0.03	3.58 ± 0.04	1.00 ± 0.28	0.83 ± 0.02
El-Kharga	El-Kharga- 26	0.90 ± 0.14	1.00 ± 0.28	5.32 ± 1.36	1.09 ± 0.00	3.73 ± 0.04	1.35 ± 0.4	1.06 ± 0.02
	El-Kharga- 12	0.50 ± 0.14	0.80 ± 0.57	3.65 ± 0.42	1.13 ± 0.00	2.25 ± 0.00	0.80 ± 0.0	0.77 ± 0.00
	El-Kharga- 24	0.80 ± 0.28	1.40 ± 0.28	4.22 ± 0.89	1.02 ± 0.03	3.28 ± 0.04	0.98 ± 0.08	1.15 ± 0.00
	El-Kharga- 38	0.50 ± 0.14	1.60 ± 0.57	3.57 ± 0.73	1.26 ± 0.00	2.38 ± 0.04	1.23 ± 0.04	0.81 ± 0.02
	El-Kharga- 41	0.30 ± 0.14	1.00 ± 0.28	3.57 ± 0.65	1.24 ± 0.03	2.33 ± 0.04	0.50 ± 0.14	0.81 ± 0.02
	El-Kharga- 23	0.70 ± 0.42	1.80 ± 0.28	3.47 ± 0.34	0.94 ± 0.03	2.98 ± 0.04	1.00 ± 0.28	1.06 ± 0.01
	El-Kharga surface- D2	0.90 ± 0.14	1.20 ± 0.57	5.03 ± 0.70	1.11 ± 0.03	3.43 ± 0.04	1.60 ± 0.28	1.00 ± 0.00
	El-Kharga surface- E2	0.50 ± 0.14	2.40 ± 0.57	10.97 ± 0.72	5.98 ± 0.09	5.23 ± 0.03	2.10 ± 0.14	0.56 ± 0.00
	El-Kharga surface- F2	0.70 ± 0.42	2.60 ± 0.28	11.01 ± 0.29	6.18 ± 0.06	5.10 ± 0.07	2.50 ± 0.42	0.54 ± 0.00
	El-Kharga drinking water	0.70 ± 0.14	1.40 ± 0.28	3.39 ± 0.39	1.07 ± 0.03	2.38 ± 0.11	1.10 ± 0.14	0.95 ± 0.04
Porsaied	Porsaied Nasir new sud	0.50 ± 0.14	1.80 ± 0.28	6.69 ± 0.59	2.02 ± 0.03	4.50 ± 0.21	1.30 ± 0.65	1.16 ± 0.01
	Porsaied Nasir new south	0.40 ± 0.0	1.60 ± 0.0	6.95 ± 1.26	1.96 ± 0.00	4.33 ± 0.04	1.50 ± 0.09	1.16 ± 0.02
	Porsaied tourism	0.90 ± 0.14	1.20 ± 0.0	5.24 ± 0.55	1.48 ± 0.00	3.23 ± 0.04	1.70 ± 0.07	0.93 ± 0.03
	Porsaied new	0.60 ± 0.0	2.60 ± 0.28	1.77 ± 0.48	1.22 ± 0.00	2.48 ± 0.03	0.50 ± 0.14	0.78 ± 0.02
	Porsaied surface	0.60 ± 0.0	9.80 ± 1.98	17.35 ± 2.68	7.07 ± 0.95	10.88 ± 1.52	6.60 ± 1.70	3.21 ± 0.49
	Porsaied drinking water	0.30 ± 0.13	0.80 ± 0.0	3.76 ± 0.28	1.24 ± 0.03	2.38 ± 0.04	0.30 ± 0.14	0.95 ± 0.0
Ganah	Ganah 5	0.80 ± 0.0	1.23 ± 0.02	4.99 ± 0.18	1.61 ± 0.0	3.38 ± 0.04	1.10 ± 0.14	0.93 ± 0.01
	Ganah 2-4	0.50 ± 0.14	1.25 ± 0.01	3.31 ± 0.13	1.57 ± 0.0	2.50 ± 0.00	0.20 ± 0.00	0.79 ± 0.00
	Ganah 11-16	1.30 ± 0.14	1.51 ± 0.08	2.22 ± 0.25	1.39 ± 0.06	2.53 ± 0.03	0.30 ± 0.01	0.81 ± 0.02
	Ganah 20	0.60 ± 0.0	1.30 ± 0.01	5.75 ± 1.06	1.26 ± 0.00	3.68 ± 0.04	1.70 ± 0.09	1.01 ± 0.02
	Ganah-surface	0.40 ± 0.0	1.24 ± 0.14	4.11 ± 1.42	1.28 ± 0.03	2.55 ± 0.00	1.10 ± 0.03	0.82 ± 0.04
	Ganah drinking water	0.60 ± 0.28	1.31 ± 0.02	3.11 ± 0.05	1.22 ± 0.00	2.45 ± 0.07	0.40 ± 0.02	0.95 ± 0.00
Bolak	Bolak 3 new	0.50 ± 0.14	1.20 ± 0.0	4.94 ± 0.14	1.72 ± 0.03	3.13 ± 0.04	1.00 ± 0.28	0.79 ± 0.00
	Bolak dates	0.70 ± 0.13	2.20 ± 0.28	5.57 ± 0.08	2.07 ± 0.03	4.48 ± 0.03	0.80 ± 0.21	1.13 ± 0.00
	Bolak 25	0.50 ± 0.12	2.60 ± 0.25	8.56 ± 0.11	2.76 ± 0.02	5.00 ± 0.00	2.80 ± 0.00	1.10 ± 0.00
	Bolak 4-32	0.80 ± 0.28	2.40 ± 0.0	8.23 ± 0.39	2.89 ± 0.09	5.03 ± 0.18	2.50 ± 0.42	1.01 ± 0.02
	Bolak 6	0.20 ± 0.0	1.80 ± 0.23	7.01 ± 1.06	2.11 ± 0.01	4.03 ± 0.04	1.90 ± 0.71	0.97 ± 0.00
	Bolak 20	0.50 ± 0.11	2.80 ± 0.57	7.60 ± 2.14	2.94 ± 0.01	5.05 ± 0.07	1.80 ± 0.17	1.11 ± 0.02
	Bolak surface 1	0.70 ± 0.10	3.40 ± 0.20	8.35 ± 0.29	3.59 ± 0.09	5.38 ± 0.03	2.60 ± 0.00	0.88 ± 0.02
	Bolak surface 2	0.70 ± 0.09	3.20 ± 0.52	7.47 ± 1.72	3.20 ± 0.02	5.03 ± 0.04	2.20 ± 0.14	0.95 ± 0.18
	Bolak drinking water	0.90 ± 0.11	3.40 ± 0.21	7.90 ± 0.68	2.89 ± 0.03	5.25 ± 0.14	2.70 ± 0.42	1.36 ± 0.00
Germashen	Germashen 8	0.40 ± 0.0	3.00 ± 0.26	9.90 ± 0.04	2.94 ± 0.08	4.98 ± 0.46	4.40 ± 0.28	0.98 ± 0.05
	Germashen 25	0.50 ± 0.14	2.80 ± 0.53	8.68 ± 0.58	2.65 ± 0.0	4.63 ± 0.04	3.90 ± 0.09	0.81 ± 0.02
	Germashen 1	0.40 ± 0.0	1.60 ± 0.0	6.07 ± 0.25	1.98 ± 0.03	3.45 ± 0.0	1.80 ± 0.28	0.84 ± 0.0
	Germashen 2 G	0.70 ± 0.13	1.80 ± 0.28	5.71 ± 0.88	2.54 ± 0.02	3.50 ± 0.0	1.30 ± 0.42	0.87 ± 0.0
	Germashen 16	0.60 ± 0.28	1.60 ± 0.48	5.71 ± 0.44	2.28 ± 0.01	3.30 ± 0.0	1.50 ± 0.14	0.83 ± 0.02
	Germashen- Surface	0.80 ± 0.25	2.20 ± 0.28	6.32 ± 0.07	2.33 ± 0.02	4.18 ± 0.04	2.00 ± 0.0	0.82 ± 0.0
	Germashen drinking water	0.60 ± 0.20	2.00 ± 0.0	6.05 ± 0.0	2.13 ± 0.0	3.75 ± 0.0	1.80 ± 0.28	0.97 ± 0.0
		6.56	7.05	0.38	8.70	3.7	2.057	0.31
		2.0	<3.0	<4.0	<3.0	20	5.02	2.0

Values higher than the WHO standard are highlighted in italics. Values higher than the FAO standard are underlined. Values higher than both WHO and FAO standards are highlighted in bold.

) also showed non-detected carbonate contents in the water samples. Although variable bicarbonate (0.50–2.10 mmol_c L⁻¹) concentrations were detectable among the studied sites, yet, these concentrations were almost less than the permissible levels for drinking purposes.

Sulfate ions exceeded the allowable levels in most sites. In the case of chloride, high contents were detected on the Porsaied surface (9.80 mmol_c L⁻¹). Sodium was also high on the Porsaied surface (7.07 meq L⁻¹), and this result was consistent with prior reports on elevated ion concentrations in surface wells versus deeper ones [38]. Likewise, Ca and Mg contents were higher in surface wells than in deeper ones. Most water sources met Mg²⁺ standards; nevertheless, some exhibited higher Ca²⁺, Na⁺, SO₄²⁻, and Cl⁻ levels, exceeding the limits per the WHO and FAO [11,39]. This indicates the need for targeted interventions, especially for surface wells where Na⁺ and Cl^- exceeded recommended levels [38].

3.2. Total and Soluble Fe Contents

Significant variations were detectable in the Fe (total and available) concentrations among the seven sites under investigation, where the Fe total and soluble contents were generally higher in surface wells than in deeper ones. Both contained higher Fe contents than the permissible levels. Maybe, anthropogenic activities are beyond such increases. For example, discharges from industrial activities (rich in Fe) found their way into the groundwater and, thus, enriching it with Fe [40]. During the penetration of this water through the soil column, substantial concentrations of Fe were sorbed on soil colloids and, then, subjected to oxidation [41]. For this reason, the total and available concentrations of Fe seemed to be significantly higher in surface-well waters versus the deep ones (Figure 2).

High total contents of Fe were detected in all water samples of El-Monira, where the highest Fe content was found in its surface wells (3218.75 μg L⁻¹). Nevertheless, soluble Fe seemed to be much lower and did not exceed the permissible level. This might indicate that Fe dominated in these waters mainly in the form of sparingly soluble Fe complexes. Nevertheless, this contaminant is subjected to potential runoff and possesses sediment pollution [42].

Elevated total Fe content was also observed in the El-Sherka surface (2915.00 μg L⁻¹) and deep wells (1821.50 μg L⁻¹), which might be evidence of the presence of anthropogenic activities [11]. In the case of El-Kharga, an alarmingly high total Fe was found in all water samples, exceeding the permissible levels. Likewise, the soluble Fe content was higher than the safe levels in its well samples, while being marginal in drinking water. this could pose long-term health risks [11]. A moderate total Fe level was monitored at Portsaied, particularly within the surface wells (1643.50 μg L⁻¹), and an elevated soluble Fe concentration was detected in its deeper wells (536.8543 μg L⁻¹), which might occur due to geological and/or soil sources [39].

Ganah exhibited high total and soluble Fe contents in both the surface- and deep-well water samples, while the Fe concentration did not exceed the safe level in drinking water, which indicates natural or infrastructure influences.

Relatively moderate total Fe content was found in the Bolak surface water (1778.75 μg L⁻¹). On the other hand, Germashen contained the lowest total Fe, especially in deep wells (548.08 μg L⁻¹), which indicates minimal anthropogenic inputs [43]. Overall, the soluble Fe, but not its total contents, was within the permissible levels in all drinking-water samples. Two possible explanations might explain the increases that occurred in total Fe in drinking water: (1) the water pipers in use were made of Fe and/or (2) there were breaks in the water pipes that allowed the seepage of groundwater. In this concern, high water pressure in water pipes might lessen the seepage of groundwater to the water pipes, but if the water supply in such pipes was not regular, then groundwater might enter within through the pipe breaks and find its way to humans through ingesting water. High levels of Fe in El-Kharga and El-Sherka require urgent intervention. Accordingly, regular monitoring and effective treatment are critical to address Fe issues in water sources.

3.3. Risk Assessment Study

The hazard Index (HI) values of iron (Fe) were assessed in all the water samples according to the calculations of the WHO [44] (Figure 3). The calculated values were generally below the permissible levels for adult consumption; yet, the waters of the surface and deep wells could pose potential hazards for children in nearly all water resources. In this context, El-Monira, El-Sherka, and El-Kharga recorded the highest child HI values, especially within their surface wells. Moreover, El-Kharga contained the highest HI value in the drinking water, suggesting urgent procedures should be taken to lessen these contaminants.

Potsaied, Ganah, and Bolak exhibited moderate HIs in their water resources, while child risk remained unsafe in their wells. Therefore, more precautions should be considered while utilizing these waters. Germashen had the lowest HIs, yet potential child risk still existed in surface wells. This highlights the need for risk management and monitoring to mitigate pediatric Fe-related risks [45]. Children showed consistently higher HI values than adults across the investigated sites and sources. Elevated child HIs in some areas underscore the urgent need for targeted strategies, regular monitoring, and public health interventions to address Fe-related health risks. Maintaining safe Fe limits set by health organizations is crucial for both adult and child well-being.

3.4. Characterization of Calcium Carbonate Soilds and Biochar

3.4.1. Fourier-Transform Infrared Spectroscopy (FTIR) Analysis

Fourier-transform infrared spectroscopy (FTIR) offered insights into the chemical composition of sorbent materials that were used for iron (Fe) removal from the water samples (Figure 4). This technique enables us to select the most efficient and sustainable water remediation approaches [46].

All calcium carbonate (CaCO₃) solids (calcite and dolomite) exhibited a high C=O (carbonyl) group, which exhibits a high affinity for binding metal ions like Fe [47]. Biochar and glauconite showed high levels of functional groups such as C=O (ether) in biochar, N-O (in biochar), and C=C (alkene) in glauconite. In addition, the O-H group (in the two abovementioned additives) demonstrates high hydrophilicity, which facilitates further PTE adsorption on the organic surfaces of biochar [46].

In the case of calcite and dolomite, the C=O group enabled them to form strong adsorption complexes within organic pollutants in the media, particularly potentially toxic elements (PTEs). Accordingly, calcite, dolomite, biochar, and glauconite could be suitable for broader water treatment applications targeting diverse contaminants based on their C=O, C=C, and O-H groups [19].

3.4.2. X-ray Diffraction Analysis (XRD) and Scanning Electron Microscopy (SEM) Analyses of Biochar Material

As shown in Figure 5, the surface of the produced biochar is smooth with a porous structure and high surface area. X-ray diffraction (XRD) analysis revealed that the structure of biochar is basically amorphous in nature but contains strongly conjugated aromatic compounds with some local crystalline structure. The biochar has almost 12 peaks of 2theta, as follows: 28.12, 29.20, 31.14, 35.74, 39.16, 40.14, 42.82, 47.26, 48.28, 50.10, 57.18, and 58.42. Strong cellulose peaks of around 60, 53, 40, and 25 have been reported to gradually lose strength and become wider by increasing charring temperatures of 100° to 300 °C, suggesting a gradual decrease in the cellulose contents of raw biomass due to pyrolysis.

3.5. Factors Affecting Sorption of Fe by the Investigated Materials

3.5.1. Sorbent Dosage

For evaluating Fe removal efficiencies by different sorbents, a clear dosage-dependent relationship was observed (Figure 6). Biochar demonstrated a gradual increase in its removal efficiency, starting from 24% at a 0.5 g L⁻¹ application dose up to complete removal (100% of Fe) at a dosage of 10 g L⁻¹. These results confirm the findings of Inyang et al. [19] who indicated that the efficiency of biochar for removing PTEs from aqueous solutions was highly influenced by the dose of applied biochar.

Dolomite and calcite were also noted to have remarkable effectiveness in Fe removal from the water media, as these two additives recorded 100% Fe removal using only a dosage of 1 g L⁻¹. Such promising results highlight the strong attributes of dolomite [48] and calcite for binding iron [49]. On the other hand, glauconite exhibited the least efficiency for Fe removal among the tested sorbents, with a maximum removal efficiency of only 66.22%. This efficiency was attained at a 10 g L⁻¹ dosage. Probably, it had low ion exchange capacity or trivial surface area constraints in adsorbing iron [29]. Based on the above results, biochar requires higher dosages for achieving high Fe removal efficiency from wastewaters, while dolomite and calcite were effective even at using lower dosages, and this offers practical advantages for water treatment applications.

3.5.2. Effect of pH

Figure 7 illustrates that Fe solubility generally decreased because of the increase in the pH of the aqueous solutions within the range of two to seven via adding either diluted hydrochloric acid (HCl) or sodium hydroxide (NaOH). Reduction in Fe solubility with an increasing pH of the media was also noticed by Silva et al. [50]. Additionally, Fe underwent oxidation in the alkaline media to change from Fe²⁺ to Fe³⁺, which has a lower solubility product and, thus, precipitated as Fe(OH)₃ salts [51] to attain a new level of equilibrium in the media [52]. Anyhow, the pH of the media was adjusted to five during the course of this study while testing the removal efficiencies of Fe from contaminated waters by the studied sorbent materials.

3.6. Efficiency of Sorbent Materials for Fe Removal

As shown in Figure 6 and Figure 8, the investigated sorbent materials could be arranged according to their efficiencies for the removal of Fe from aqueous solutions in the following descending order: calcite > dolomite > biochar > glauconite, and the latter exhibited very low removal efficiency for Fe from aqueous solutions. Thus, glauconite was excluded from further investigations, i.e., the isotherm and kinetic studies because of its low capability. The results obtained herein indicate that calcite exhibited higher efficiency than dolomite for Fe decontamination from aqueous solutions; yet, the latter product (dolomite) is more durable upon repeated use compared to calcite, which is highly erodible in acid media, and consequently undergoes significant material breakdown [53]. This makes dolomite a more practical and cost-effective choice for the treatment of irrigation systems.

3.6.1. Adsorption Isotherms

Data on Fe sorption from aqueous solutions were then fitted to both Langmuir and Freundlich isotherm models (Figure 9). Based on the highest r² values, Fe sorption data fitted successfully to the Langmuir isotherm model. This suggests the adsorption of a monolayer of iron ions on both biochar and carbonate surfaces [20]. Dolomite and calcite recorded the highest affinity constants (K_L) for iron sorption versus biochar, with mean values of 37.07 and 44.67 mg g⁻¹, respectively, corresponding to only 3.15 mg g⁻¹ for biochar. These results are consistent with Walker et al. [54], who found that the adsorption of Fe followed the Langmuir isotherm model, where the higher capacities for Fe sorption were found in carbonate sites versus biochar [54]. Likewise, the maximum adsorption capacity (q_L) was estimated for calcite at 333.33 mg g⁻¹, followed by dolomite at 238.10 mg g⁻¹, and then biochar at 40.00 mg g⁻¹ (Figure 8).

3.6.2. Kinetics of Fe Sorption

Figure 5 shows the efficiencies of the studied sorbent materials for iron removal from contaminated waters within time intervals ranging from 5 to 240 min. In this aspect, dolomite and calcite demonstrated the highest RE (removal efficiencies). They needed only 120 min to achieve a successful 100% RE. Different mechanisms might explain such high efficiencies, e.g., rapid ion exchange on the carbonate surfaces [48], followed by Fe oxidation and precipitation [29]. Regarding glauconite, its RE capability for removing Fe seemed to be low and could seem nearly constant from the beginning of the investigation (23–25.75%). This result reflects its low capability for ion immobilization [29].

Biochar showed an initial minimal affinity for removing Fe from aqueous solutions for up to 30 min. Then, its RE increased considerably with time, to achieve 89.30% after 240 min of contact with biochar. This indicates that biochar needs a long contact time to attain the efficient removal of Fe from water bodies [19].

Concerning, the kinetics of Fe sorption via calcite, dolomite, and biochar materials, Fe sorption data were well fitted to pseudo-second-order kinetics, as evidenced by the higher r² values compared to the values obtained from fitting data to pseudo-first-order kinetics. For example, the pseudo-second-order rate constant (k²) was 0.000694 g/mg/min (0.694 mg/mg/min) when using biochar for Fe sorption, with an adsorption capacity (q_e) of 106.383 mg/g. Although the adsorption capacity of biochar for Fe could be relatively high, yet, the Fe sorption affinity seemed to be generally very low. Two mechanisms might take place together during the first period of Fe contact (up to 30 min) with biochar, i.e., sorption of Fe on the functional groups of biochar [55], which might lessen considerably the Fe solubility in water. At the same time, electrons were set free to aqueous solutions during the degradation of this organic additive, and these electrons could increase Fe reduction [56] and solubility in water. These two mechanisms, therefore, displayed low-affinity phenomena for Fe removal by biochar from contaminated waters throughout the first time period of contact (up to 30 min). Thereafter (>30 min), easily oxidized organic carbon lessened considerably. Thus, the first mechanism of Fe sorption on biochar surfaces dominated.

For dolomite and calcite, the k₂ values were 0.006126 and 0.026316 g/mg/min, respectively, with q_e values around 100 mg g⁻¹. These values characterize the fast and high sorption capacities of Fe by the carbonate minerals. The rapid kinetics and good fits suggest the raw adsorbents are suitable for efficient Fe removal from contaminated waters without modification.

Overall, the fitted sorption and kinetic modeling highlight that the main mechanisms beyond Fe removal by dolomite and calcite from contaminated waters were adsorption on Fe surfaces in the form of a single monolayer, followed by chemisorption, as denoted by the kinetic fittings [57]. Also, our results indicate that co-precipitation of Fe on carbonate surfaces could be more effective for the removal of Fe from contaminated solutions than Fe binding on the functional groups of biochar.

A point to note is that the calculated q_e parameter of the kinetic model aligned closely with the experimental Langmuir maximum adsorption capacity, confirming the applicability of the pseudo-second-order model to interpret adsorption mechanisms [20].

As shown in

Table 4. Kinetic parameters obtained from pseudo-first order and pseudo-second order for Fe ions adsorption by tested sorbent materials.

Sorbents	Pseudo-1st					Pseudo-2nd
	Slope	Intercept	R²	K1/K2	qe (mg g−1)	Slope	Intercept	R²	K1/K2	qe (mg g−1)
Biochar	0.0117	1.834	0.914	−0.03	68.23	0.009	0.1274	0.990	0.00	106.38
Dolomite	0.0289	1.5153	0.841	−0.07	32.76	0.01	0.016	0.999	0.006	101.01
Calcite	0.0215	0.729	0.584	−0.05	5.36	0.010	0.0038	1.000	0.026	100

. A summary of the adsorption isotherms, showing that the adsorption of iron onto biochar, dolomite, and calcite, is better described by the pseudo-second-order kinetic model, suggesting that chemisorption might be the rate-limiting step in the adsorption process. According to the model, the rate of adsorption relies on the availability of chemisorption sites on the solid adsorbents. It implies that the reaction between the adsorbent and the adsorbate involves a strong chemical bond formation, leading to a more stable adsorption process compared to physisorption, where weak forces dominate. The second-order kinetic model considers the concentration of both the adsorbate and the adsorbent in its equation, indicating a correlated behavior between the two. As a result, the rate of adsorption is not only influenced by the concentration of the adsorbate but also by the surface area and porosity of the adsorbents. This finding suggests that optimizing the chemisorption capacity and characteristics of biochar, dolomite, and calcite can enhance their efficiency as adsorbents for Fe removal in various applications, such as water treatment.

3.6.3. Regeneration

Figure 10 presents the efficacy of the three tested materials—biochar, dolomite, and calcite—in the removal and desorption of iron over five successive cycles of Fe sorption and desorption. Among the sorbents, dolomite exhibited the highest iron removal capacity in the first cycle, with a percentage reaching 100% compared to 86.69% for biochar and 99.93% for calcite. The high removal efficiency of dolomite could be attributed to its unique mineral composition and the porosity of this mineral [58]. The removal efficiency decreased over the successive cycles; nevertheless, the least decline was observed in dolomite, which was only 6.33% by the fifth cycle (RE = 93.67%).

Regarding Fe desorption from the studied materials, dolomite again showed the highest iron recovery, which was 99.97% in the first cycle. This percentage decreased slightly within the proceeding cycles to reach 92.93% by the fifth cycle. Calcite also showed a similar trend as dolomite with a lower adsorption/desorption recovery.

Biochar recorded the lowest removal efficiency, which was 86.69% (cycle 1) and decreased to 72.10% (cycle 5). The desorption recovery of Fe by biochar was also relatively low and ranged from 43.85% in cycle 1 to 38.55% in cycle 5. Biochar is characterized by its relatively high stability, owing to its recalcitrant carbon structure [19]. This stability guarantees that Fe is bound strongly within the pores of biochar, thus lessening Fe desorption. On the other hand, calcite exhibited the greatest weight loss during the regeneration steps reaching 13.67% in cycle 5. Dolomite had a weight loss of 6.23%, while biochar showed the least weight loss at 2.11% in cycle 5. The higher weight loss of calcite indicates high dissolution of the material during its regeneration with diluted HCl, and this could impact its reusability over successive cycles. Overall, dolomite seemed to be the optimum choice for Fe removal from wastewater.

4. Conclusions

This study was conducted to assess water quality in the El-Kharga Oasis (New Valley) by collecting water samples from surface and ground wells from five different villages across this area. Tap water was also collected from the same sites. The results reveal that the water quality of most sites was within the permissible levels of the WHO standards. Nevertheless, some sites exhibited high electrical conductivity (EC) and turbidity, notably in the surface wells of El-Kharga. Elevated levels of total and soluble Fe were detected in both shallow and deep wells of almost all sites, especially in El-Kharga, posing serious health risks, especially for children, as indicated by Hazard Index (HI) values.

Another investigation was carried out to ameliorate artificially contaminated water with Fe at a rate of 1000 mg Fe L⁻¹ using four natural safe materials, namely dolomite, calcite, glauconite, and biochar. The efficiencies of the first two additives were much higher than the others, as they both removed successfully 100% of Fe from the water samples within only 120 min, with superiority for dolomite because of its low erodibility rate versus calcite. The regeneration of dolomite via HCl (0.1 M) was also effective enough, exhibiting 99.97% iron recovery. For five successive cycles, dolomite exhibited the highest efficiency for the removal of Fe from aqueous solutions with a slight decrease in removal efficiency from 100% to 93.67% between cycles 1 and 5. Likewise, Fe recovery decreased slightly to 92.93% in the fifth cycle

It seems that the removal of Fe from aqueous solutions by both dolomite and calcite took place through rapid surface Fe adsorption on their surfaces in monolayers, followed by chemisorption, as denoted by the kinetic fittings. Overall, this study highlights the critical need for targeted interventions, continual monitoring, and the adoption of effective sorbents, like dolomite and calcite, to lessen Fe contamination in water and ensure water safety, particularly in high-risk areas.