Preconcentration of Gold from Mining Waste Samples Using the Solidified Floating Organic Drop Microextraction and Determination by Flow Injection–Flame Atomic Absorption Spectrometry

Abstract

The increasing demand for gold necessitates the development of sustainable and environmentally friendly recovery methods, particularly from mining waste. In this study, trace and ultra-trace levels of gold ions were preconcentrated using solidified floating organic drop microextraction (SFODME) and quantified by flow injection–flame atomic absorption spectrometry (FI-FAAS). Sodium diethyldithiocarbamate was used as the chelating agent. Key parameters, including the pH, buffer volume, complexing agent concentration, salt effect, extraction time, stirring speed, temperature, and final volume, were optimized using univariate analysis, yielding an enhancement factor of 42.6. The method demonstrated linearity between 20 and 450 µg/L, with limits of detection and a quantification of 5.03 µg/L and 16.76 µg/L, respectively. In order to evaluate the applicability and reliability of the developed method, the method was applied to certified reference samples (Rocklabs CRM SE114, OREAS CRM 61 f, OREAS CRM 231, and OREAS CRM 235) and real mining samples (mining waste samples from an open pit gold–silver mine in the Aegean Region and tailing samples from an underground gold–silver mine in the Aegean Region) after the real sample preparation procedure. The method was further evaluated for the environmental impact using the Analytic GREEnness (AGREE) metric, based on the 12 principles of green chemistry.

1. Introduction

Gold, one of the most well-known precious metals, has been highly valued for its rarity, luster, and malleability throughout human history [1]. Found naturally in a relatively pure state, gold’s unique properties make it resistant to corrosion and oxidation, further enhancing its desirability [2]. Precious metals, a broader category that includes silver, gold, platinum, and palladium, are typically rare, with significant economic and industrial value [3,4]. These metals are used not only in jewelry and currency but also in various technological applications such as electronics, catalysis, and medical devices due to their conductive, catalytic, and durable properties [5]. The growing global demand for gold has made it increasingly important to recover this valuable metal from the rising volume of mining waste products [6,7,8]. As gold mining generates substantial waste material, often containing residual amounts of gold, efficient recovery processes can significantly reduce the environmental impact and enhance resource sustainability. Recovering gold from mining waste not only minimizes the ecological footprint by reducing the need for new extraction but also maximizes the economic value of mined materials [9,10]. This approach is critical in meeting the rising demand for gold while promoting more sustainable and environmentally responsible mining practices.

Gold is naturally present at trace concentrations, often less than 5.0 ng/g, necessitating highly sensitive analytical techniques for its accurate detection and quantification [11]. Advanced instruments such as electrothermal atomic absorption spectrometry (ETAAS) [12,13], inductively coupled plasma–mass spectrometry (ICP-MS) [14,15], and instrumental neutron activation analysis (INAA) [16,17] have the capability to detect gold at ultra-trace levels. Although flame atomic absorption spectrometry (FAAS) is widely used due to its simplicity and robustness, it lacks the sensitivity of these advanced techniques and can typically detect gold only at parts-per-million concentrations [18]. Several extraction techniques have been developed to isolate gold from complex matrices and enhance its signal through preconcentration. These approaches are broadly categorized into liquid–liquid extraction (LLE) and solid-phase extraction (SPE). Over recent years, advancements in minimizing the volumes of extraction solvents and sorbents have resulted in the emergence of liquid-phase microextraction (LPME) and solid-phase microextraction (SPME) methodologies [19]. Dispersive liquid–liquid microextraction (DLLME), initially introduced in 2006 for the detection of polycyclic aromatic hydrocarbons in aqueous matrices, has been subsequently extended to various organic and inorganic analytes, including gold [20]. Additionally, a novel technique has been established for the quantification of gold ions in water samples, employing microextraction via the ultrasound-assisted emulsification of solidified floating organic drops, followed by flame atomic absorption spectrometry. Solidified floating organic drop microextraction (SFODME) offers several advantages, including a high extraction efficiency, simplicity, and rapid processing. The method requires only small amounts of low-toxicity organic solvents, making it environmentally friendly. Unlike conventional techniques, it eliminates the need for dispersive solvents while maintaining a high sensitivity. Its simplicity and minimal solvent use make it ideal for the sensitive and efficient determination of gold ions in aqueous samples [21].

The incorporation of green chemistry principles into laboratory practices represents a significant advancement in modern chemistry. This approach focuses on re-engineering experimental procedures to emphasize the use of environmentally sustainable materials while promoting the adoption of efficient waste management strategies. New frameworks have been established to assess the efficiency of green chemistry methods in comparison to traditional techniques. A key challenge in chemistry is the development of sample preparation methods that enhance the efficiency while reducing the environmental impact. The Green Analytical Chemistry (GAC) framework is influenced by various factors, including sample collection, preparation, reagent utilization, instrumentation, and the overarching methodology. A comprehensive understanding of these elements is crucial for assessing the environmental impact of any analytical procedure. Within GAC, sample preparation is particularly crucial for concentrating trace analytes and removing interfering substances [22]. The SFODME method is notable for its minimal requirement for the extraction solvents, ease of use, cost-effectiveness, reduced reliance on organic solvents, minimum use or absence of chelating agents, and high enhancement factor, setting it apart from conventional methods in terms of both environmental sustainability and operational efficiency.

This study introduces a novel approach for the determination of gold ions in real mining waste samples by solidified floating organic drop microextraction (SFODME), with quantification achieved by using flame atomic absorption spectrometry (FAAS). Sodium diethyldithiocarbamate (DDTC) is utilized as a chelating agent, while 1-dodecanol serves as the extraction solvent. Based on a comprehensive literature review, this method marks the first use of SFODME for gold extraction from real mining waste samples. Also, the flow injection–flame atomic absorption spectrometer combination of SFODME for the gold analysis and preconcentration is novel according to our literature review so far. The technique has been evaluated for its limit of detection (LOD), limit of quantification (LOQ), and precision, all of which demonstrate excellent performance. It also provides linearity at trace concentrations and the successful preconcentration of gold. As there is increasing interest in more sustainable microextraction methods, this approach aligns well with green chemistry principles. It requires a minimal sample volume, uses low quantities of toxic organic solvents, consumes little energy, offers short extraction times, and is cost-effective with a strong enhancement factor. This method offers a highly efficient means for trace-level gold preconcentration and determination from real mining waste using FI-FAAS.

2. Materials and Methods

2.1. Reagents and Materials

All of the chemicals utilized in this experiment were of analytical reagent grade. Deionized water with a conductivity of 18.2 MΩ, produced using a Barnstead Nanopure Diamond purification system (Los Angeles, CA, USA), was employed for the solution preparation. The gold solution used in the study was prepared from a stock standard solution (1000 mg/L) of gold ions, procured from Custom Grade Standard (Inorganic Ventures, Christiansburg, VA, USA). Working standard solutions were obtained through precise dilutions of the stock solution. The extraction solvent, 1-dodecanol, and sodium diethyldithiocarbamate (DDTC) were sourced from Merck (Darmstadt, Germany). A buffer solution with a pH of 3 was prepared using potassium hydrogen phthalate and hydrochloric acid from Sigma-Aldrich (St. Louis, MO, USA), with concentrations adjusted as necessary. Potassium iodide was purchased from Merck (Darmstadt, Germany). Ethanol from Merck (Darmstadt, Germany) was utilized as a diluent to reduce the viscosity of the organic extract and improve the nebulization efficiency of the flame. Quantitative blue ribbon filter paper (ashless, Grade 589/3, pore size: <2 μm) was purchased from Whatman^® (Maidstone, UK). The concentrated acid solutions used in the microwave digestion procedure (nitric, hydrochloric, and hydrofluoric acids) were purchased from Merck (Darmstadt, Germany). All of the laboratory glassware was soaked overnight in 10% nitric acid, and then thoroughly rinsed with deionized water and dried in a dust-free environment. Certified reference materials from Rocklabs (Auckland, New Zealand) and OREAS Gold Ore reference materials from ORE RESEARCH & EXPLORATION (Bayswater North, Australia) were used for the method validation.

2.2. Instrumentation

The quantification of Au(III) in both standard and sample solutions was performed using a PerkinElmer AAnalyst 800 Atomic Absorption Spectrophotometer (Waltham, MA, USA). The instrument is outfitted with a FIAS 400 flow injection system, which was utilized for sample loading and transfer. This system incorporates two peristaltic pumps, a two-position five-port valve, and a 200 µL sample loop, enabling precise and efficient sample handling. Additionally, the instrument is equipped with a deuterium background corrector and operates with an air–acetylene flame. A gold hollow cathode lamp served as the radiation source, calibrated to an optimal wavelength of 242.8 nm with a slit width of 0.7 nm, to ensure accurate measurements. The absorbance was recorded at air and acetylene flow rates of 18.0 and 1.4 L per minute, respectively. Adjustments to the nebulizer flow and burner height were made to enhance the absorbance, with the analyte aspirated in an ethanol solution. In the digestion procedure, the CEM Corporation MARS 5 (Matthews, NC, USA) microwave digestion system was used.

2.3. Preparation of Real Samples

To perform the microwave digestion on the mining samples, following EPA Method 3052, the preparation of the real sample (tailings and mining waste samples) procedure began by weighing approximately 0.25 g of the sample and placing it in a microwave digestion vessel. Amounts of 9 mL of concentrated nitric acid (HNO₃) and 3 mL of hydrochloric acid (HCl) were added. The samples contained silicates and required additional digestion power, since 2 mL of hydrofluoric acid (HF) was added. The vessels were sealed and placed into the microwave digestion system. The microwave was set to a power of 600–1200 watts, and the sample was heated to a temperature of 180–200 °C over 10–20 min, with the pressure inside of the vessel reaching up to 1000 psi. After the digestion cycle, the vessels were allowed to cool before being carefully vented. The digested solutions were transferred to a clean container, the vessels were rinsed with deionized water, and then rinsed together with the sample. The solutions were diluted with deionized water to a final volume of 50 mL. The 50 mL samples were then passed through blue ribbon filter paper. The preparation of the real samples for the SFODME procedure was then completed. Finally, the filtered samples were ready for the SFODME procedure and were used directly.

2.4. Procedure

For the SFODME procedure, 50 mL aliquots containing either the sample or standard gold solution were prepared and placed in beakers equipped with magnetic stir bars. After adjusting the pH to 3 using 1 mL of phthalate buffer, 2 mL of a 2.5% (w/v) sodium DDTC solution, 0.7 g of potassium iodide (KI), and 200 µL of 1-dodecanol were added sequentially. The mixture was then stirred using a magnetic stirrer for 45 min at 45 °C and 400 rpm. Under these conditions, a droplet of organic solvent, floating atop the aqueous solution due to its lower density, was formed. During this stirring phase, gold ions were efficiently extracted into the 1-dodecanol. Upon completion of the extraction, the beaker was placed in a refrigerator at 4 °C to solidify the organic phase. Given that the melting point of 1-dodecanol is close to room temperature (approximately 24 °C), the solidified droplet formed within 10 min. The solidified droplet was meticulously transferred into a conical vial using a mini spatula and diluted to a final volume of 1000 µL with ethanol. Subsequently, a 200 µL sample loop of the FIAS 400 system was loaded with the diluted organic phase while the valve was in the fill position. The valve was then switched to the inject position, enabling the direct introduction of the solution into the FAAS nebulizer, with ethanol serving as the carrier solution. The outlined procedure is illustrated in Figure 1.

3. Results

3.1. Selection of Extraction Solvent

The choice of a suitable extraction solvent is critical for optimizing the SFODME method. The solvent must possess a low volatility, limited solubility in water, a melting point near room temperature, and must not interfere with the analytical techniques used for the analyte determination. Based on these criteria, several solvents could be considered, including 1-undecanol, 1-dodecanol, 2-dodecanol, 1-bromohexadecane, n-hexadecane, 1,10-dichlorodecane, and 1-chlorooctadecane. In this study, 1-dodecanol was selected as the extraction solvent due to its lower cost relative to the alternatives. The experimental results demonstrated that 1-dodecanol achieved an extraction efficiency of 99%.

3.2. Selection of pH Buffer and Added Buffer Amount

In this study, the impact of the pH on the preconcentration of gold(III) ions was investigated across a range from 2.2 to 9.4, as depicted in Figure 2. The following buffer solutions were employed for the pH adjustment: 0.1 mol/L of potassium hydrogen phthalate with 0.1 mol/L of hydrochloric acid for a pH of 2.2 to 4.0; 0.1 mol/L of potassium hydrogen phthalate with 0.1 mol/L of sodium hydroxide for pH of 4 to 6; 0.1 mol/L of tris(hydroxymethyl) aminomethane with 0.2 mol/L of hydrochloric acid for a pH of 7 to 8.7; 0.025 mol/L of sodium borate decahydrate with 0.1 mol/L of sodium hydroxide for higher pH values. The optimal extraction of the gold complex was achieved at a pH of 3.0, leading to the use of this pH for all of the subsequent samples. Deviations from the optimal pH resulted in the complex likely acquiring a charge, which hindered its transfer into the organic phase. The volume of buffer solution used during extraction plays a crucial role in the efficiency of the Au(III) ion preconcentration. To identify the optimal buffer volume, different amounts—0.2 mL, 0.5 mL, 1 mL, 2 mL, and 5 mL—were tested, each evaluated for its ability to maintain the target pH and ensure the high extraction of Au(III) ions. The results showed that 1 mL of buffer solution provided the most effective outcome (Figure 3), as it consistently maintained the optimal pH of 3.0, allowing for the high extraction of the Au(III)-DDTC complex. Smaller volumes, such as 0.2 mL and 0.5 mL, were insufficient in stabilizing the pH, resulting in incomplete extractions. Conversely, using larger volumes, like 2 mL, 3.5 mL, or 5 mL, did not enhance the extraction efficiency and proved to be less practical. Therefore, 1 mL was determined to be the optimal buffer volume for the subsequent experiments, ensuring the consistent and efficient extraction of the gold ions.

3.3. Added Complexing Agent Amount

To enable the transfer of gold ions from the aqueous phase into a small volume of non-polar organic phase, it is imperative to impart a non-polar characteristic to the ions. This is typically accomplished by optimizing the pH and the other experimental conditions to promote the formation of an uncharged metal–ligand complex, which facilitates partitioning into the organic phase. In this investigation, sodium diethyldithiocarbamate (DDTC) served as the chelating agent. A 2.5% (w/v) DDTC solution was prepared by dissolving the reagent uniformly in ultrapure water. The experiments were conducted by varying the volume of the DDTC solution from 0 to 5 mL, and the corresponding absorbance values were measured. As shown in Figure 4, the absorbance increased sharply until the DDTC volume reached 2 mL, after which no significant change was observed. Therefore, the optimal concentration was determined to be 2 mL of the 2.5% (w/v) DDTC solution.

3.4. Effect of Salt

For the analyte to be efficiently extracted into the organic phase, gold ions in the aqueous solution must form a non-polar ion pair, allowing their transfer into the non-polar organic phase. This was achieved using DDTC and an appropriately adjusted pH environment. The addition of KI to the sample significantly enhances the ionic strength of the medium, leading to a decrease in the solubility of the ion pair in water due to the “salting-out” effect, which, in turn, increases the non-polarity of the uncharged ion pair. This accelerates its transfer into the organic phase. Therefore, the concentration of KI is a key factor influencing the extraction efficiency and must be carefully optimized. To investigate this, the KI amount in the aqueous solution was varied between 0 and 2.5 g, and was added to the 50 mL standard/sample solution while the other parameters were held constant, and the resulting absorbance values were measured. As shown in Figure 5, the highest absorbance was observed at an added KI amount of 0.7 g in 50 mL sample solution, which was identified as the pertinent value for the extraction efficiency.

3.5. Stirring Time

In preconcentration processes, the extraction time is a pivotal parameter that directly influences the efficiency of the extraction. It is critical to select an appropriate duration to enhance the repeatability of the procedure and to ensure that the equilibrium between the aqueous and organic phases is reached. An insufficient extraction time can result in an incomplete emulsification and the failure to achieve equilibrium, thereby yielding a low extraction efficiency. On the other hand, excessively prolonged extraction times may render the method laborious, with the risk of the analyte re-entering the aqueous phase or disrupting the ion pair, thus compromising the extraction process. To assess the effect of the extraction time on the efficiency, and to establish the optimal duration, the extraction time was varied between 5 and 120 min, while the other experimental conditions were held constant. The results, depicted in Figure 6 as the absorbance versus the extraction time, indicate a sharp increase in the extraction efficiency and absorbance as time progresses. The absorbance increased steadily up to 45 min, after which it plateaued, with no further significant improvements. Accordingly, 45 min was selected as the pertinent extraction time, providing both efficient and reliable results.

3.6. Extraction Temperature

The effect of the temperature on the absorbance of the preconcentrated gold ions was examined over a range from 25 to 70 °C, as illustrated in Figure 7. The data reveal a steady increase in the absorbance from 25 °C to 45 °C. However, beyond 45 °C, the absorbance declines, with a significant reduction observed at higher temperatures, likely due to the increased solubility of the organic phase. Consequently, 45 °C was identified as the pertinent temperature for the extraction process.

3.7. Stirring Rate

In microextraction methods, mixing in the liquid phase plays a crucial role in reducing the extraction time by enhancing the transfer of the analyte between the aqueous and organic phases. However, excessive mixing speeds can cause the organic droplet to disperse and degrade, thereby negatively impacting the extraction process and reducing the overall yield. Thus, it is essential to optimize the mixing speed for efficient extraction. In this set of experiments, the mixing speed was varied between 100 and 1000 rpm, while all of the other parameters were held constant. As shown in Figure 8, an increase in the mixing speed led to a corresponding rise in the absorbance. The absorbance exhibited a linear increase up to 400 rpm, after which it began to decline. This decrease is attributed to the dispersion and degradation of the extraction droplet. At speeds of 800 rpm and above, the droplet’s structure deteriorated to the point where it could not be fully collected, preventing accurate absorbance measurements. Consequently, the data for speeds of 800 rpm and higher are excluded from the graph. The maximum extraction efficiency was observed at 400 rpm, which was therefore selected as the pertinent mixing speed.

3.8. Final Volume

At this stage, determining the appropriate dilution volume is a critical parameter requiring experimental evaluation. To investigate this, the solidified organic droplet was diluted with ethanol, and the effect of the final volume on the extraction efficiency was observed. Measurements were conducted by adjusting the final volume within the range of 300 μL to 1500 μL. Nevertheless, reducing the volume below 300 μL was impractical due to the quite high viscosity of the sample, which led to partial blockages in the tubing of the flow injection system, subsequently causing inaccurate absorbance measurements. Volumes of less than 300 μL produced unreliable analyte signals, impeding precise scans, so these values were not demonstrated in Figure 9. The results from the volume optimization scan indicated that the maximum absorbance, corresponding to the highest enhancement factor, was achieved at a volume of 500 μL. Besides this, quite high standard deviation values were obtained for both of the final volumes of 500 μL and 750 μL due to high viscosity and partial blockages in the tubing system. By making the necessary sacrifices in the enhancement value, 1000 μL, with low standard deviation and good reproducibility values, was selected as optimum. At larger volumes, the absorbance values declined, likely due to the dilution of the analyte concentration within the organic phase.

3.9. Effect of Interferences

To assess the selectivity of the method, the influence of foreign ions on the recovery of gold was investigated, with a summary of the findings presented in

Table 1. The effect of ions that could potentially interfere with the extraction efficiency.

	20-Fold		50-Fold		>100-Fold
Added Ion	Absorbance	Relative Error	Absorbance	Relative Error	Absorbance	Relative Error
Mn2+	0.0341	−1.49	0.0326	3.12	0.0322	4.32
(CO3)2−	0.0333	0.89	0.0331	1.64	0.0321	4.46
Fe3+	0.0329	2.08	0.0331	1.49	0.0325	3.42
Mg2+	0.0327	2.83	0.0330	1.93	0.0324	3.57
Ca2+	0.0339	−0.89	0.0330	1.93	0.0322	4.32
Rh3+	0.0329	2.23	0.0345	−2.68	0.0328	2.38
NO3−	0.0329	2.08	0.0325	3.42	0.0322	4.17
K+	0.0335	0.45	0.0331	1.49	0.0326	2.98
Cr3+	0.0345	−2.53	0.0336	0.15	0.0341	−1.34
Zn2+	0.0335	0.30	0.0335	0.45	0.0329	2.08
Na+	0.0334	0.74	0.0325	3.42	0.0323	3.87
Co2+	0.0321	4.46	0.0316	6.10
Al3+	0.0326	2.98	0.0319	5.06
Cd2+	0.0325	3.42	0.0317	5.65
(SO4)2−	0.0320	4.91	0.0316	6.10
Mn2+	0.0327	2.83	0.0319	5.06
Ag+	0.0315	6.40
Cu2+	0.0318	5.51
Pd2+	0.0314	6.70
Co2+	0.0315	6.40

Measured Absorbance for 50 ug/L Au 0.0336 abs. Green: ±5% ≥ relative error. Red: ±5% < relative error.

. Recovery studies were conducted by introducing various ions into a 50 mL solution containing 50 µg/L of Au(III). The tolerance limit was defined as the concentration at which the introduced ion caused less than a ±5% relative error in the determination of gold. Upon reviewing the results, it is evident that the absorbance values remained high even in the presence of elevated ion concentrations. The ions that exhibited the most significant interference were Cu²⁺, Pd²⁺, Co²⁺, and Ag⁺, which had the greatest inhibitory effects. It is very unlikely that this level of silver, copper, palladium, or cobalt ions would be found in actual mine tailings. This enables the accurate determination of trace levels of gold in aqueous solutions without substantial interference from other ions.

3.10. Analytical Performance of Method

Calibration curves generated under the optimized SFODME conditions exhibited linearity within the range of 0.02–0.45 mg/L for gold. The regression equation for the gold determination was A = 6.26 × 10⁻¹C + 4.70 × 10⁻³, where A represents the absorbance and C is the concentration of metal ions in the solution (mg/L). The correlation coefficient for the calibration curve exceeded 0.99. When direct aspiration in FAAS without preconcentration was applied, the resulting equation was A = 1.47 × 10⁻²C + 5.06 × 10⁻⁴ (R² = 0.999), with a linear range of 1–20 mg/L. The enhancement factor, calculated as the ratio of the calibration curve slopes after and before preconcentration, was determined to be 42.57. The limit of detection (LOD), defined as the concentration corresponding to three times the standard deviation (3σ) of 10 blank measurements, was found to be 5.03 µg/L. The limit of quantification (LOQ), representing the lowest level of analyte that can be measured accurately and precisely, was defined as ten times the standard deviation (10σ) and was calculated as 16.76 µg/L. The relative standard deviation (RSD) for 20.0 µg/L of gold was ± 3.42% (n = 10). A summary of the method’s analytical features is provided in

Table 2. Analytical performance of the proposed method.

Analytical Figures
Regression Equation	A = xC + y	0.6258x + 0.0047
Correlation Coefficient		0.9988
Enhancement Factor		42.57
Linear Range	µg/L	20–450
LOD	3s (µg/L)	5.03
LOQ	10s (µg/L)	16.76
Precision	RSD (%) [20 µg/L] n = 10	3.42

.

3.11. Analysis of Certified Material

The proposed SFODME method was applied to the certified reference materials following the sample preparation procedure outlined in Section 2.3, “Preparation of Real Sample”. Recovery rates of 95–96% were achieved, and the results are detailed in

Table 3. Proposed method applied on the certified reference materials.

Reference Sample	Certified Au Concentration (mg/L)	Found Au Concentration by the Proposed Method (mg/L)	Recovery (%)
Rocklabs CRM SE114	0.626	0.599	95.69
OREAS CRM 61 f	4.752	4.521	95.14
OREAS CRM 231	0.504	0.486	96.43
OREAS CRM 235	1.486	1.419	95.49

.

3.12. Analysis of Real Samples

Real samples were collected from various mining facilities. These included mining waste samples from an open-pit gold–silver mine and tailing waste samples from an underground gold–silver mine, both located in the Aegean Region of Turkey. The proposed SFODME method was applied to the real samples following the sample preparation procedure. After the preconcentration step, the initial gold concentrations in the real samples were determined by correlating the absorbance values with the calibration curve (

Table 4. Proposed method applied on the real samples.

Real Sample	Au Concentration (mg/L)
Mining Waste—1	Below Detection Limit
Mining Waste—2	0.036
Mining Waste—3	0.053
Tailings Sample—1	0.437
Tailings Sample—2	0.344

).

4. Discussion

This study illustrates the successful application of SFODME for the extraction of gold from real mining samples, with the quantification achieved through flow injection–flame atomic absorption spectrometry (FI-FAAS). The method demonstrates superior performance metrics, including the enhancement factor, limit of detection, linearity, and precision, when compared to the existing literature. A detailed comparison of the proposed method against other preconcentration techniques for gold is presented in

Table 5. Comparison of the proposed SFODME method with the literature for the determination of gold.

Preconcentration Technique	Detection Instrument	Enhancement Factor	Limit of Detection (LOD) (ug/L)	Linear Range (µg/L)	Precision (RSD) (%)	Reference
DLLME	FAAS	19.5	1.75	30–230	2.77	[23]
SsLLME	FAAS	51	1.5	-	4.20	[24]
USAE–SFODME	FAAS	34.8	0.45	1.5–400	1.68	[21]
CPE	FAAS	16	12.7	4–500	1.40	[25]
IL–DLLME	FAAS	23.7	0.13	0.9–400	-	[26]
IL–DLLME	ETAAS	50	0.0048	0.02–40	4.10	[13]
IP–DLLME	FAAS	40	1.8	8–100	3.20	[27]
DLLME	ICP–OES	149	0.09	0.3–100	6.00	[28]
SFODME	FAAS	42.6	5.03	20–450	3.42	This work

DLLME: dispersive liquid–liquid microextraction; SsLLME: supramolecular solvent microextraction; USAE–SFODME: using ultrasound-assisted emulsification of solidified floating organic drop; CPE: cloud point extraction; IL–DLLME: ionic liquid-dispersive liquid–liquid microextraction; IP–DLLME: ion pair-dispersive liquid–liquid microextraction; DLLME: dispersive liquid–liquid microextraction; SFODME: solidified floating drop microextraction; FAAS: flame atomic absorption spectrometry; ICP–OES: inductively coupled plasma–optical emission spectrometry.

. In addition to its analytical strengths, the developed procedure excels in the operational simplicity and cost efficiency, making it a practical solution.

5. Conclusions

Sample preparation is often time-intensive and vulnerable to contamination, underscoring the importance of adopting ecologically sustainable analytical techniques, especially for complex matrices. Green Analytical Chemistry (GAC) principles offer viable methods that minimize sample pretreatment, although this can be challenging with diverse samples. The aim is to streamline processes by reducing energy use, chemical consumption, and procedural steps. A challenge in evaluating analytical processes is obtaining comprehensive yet detailed assessments of environmental risks. To address this, the Analytical GREEnness (AGREE) metric system was developed, based on the 12 GAC principles [29]. This translates these criteria into a 0–1 scale, with the final score presented as a pictogram. In this study, the approach received an AGREE score of 0.53, indicating a low environmental impact for preconcentrating gold (Figure 10). This calculation was applied to the procedure prepared with the standard gold solution described in Section 2.4, not to the real mining sample or the certified reference material.

For future work, the developed solidified floating organic drop microextraction (SFODME) combined with FI-FAAS can be expanded to recover and quantify gold in various complex matrices beyond mining waste, such as electronic waste (e-waste), industrial effluents, and contaminated soil, where gold exists at trace and ultra-trace levels. Additionally, the method can be adapted to recover other valuable metals like silver, platinum, and palladium, which are often co-present with gold in similar matrices. To further enhance the method’s environmental sustainability, alternative green solvents and chelating agents could be explored, aligning with the principles of green chemistry. The present study successfully demonstrated a high sensitivity, accuracy, and reproducibility in preconcentrating and quantifying gold ions, validated through real mining samples and certified reference materials. Its application to real-world scenarios highlights its potential as a cost-effective and environmentally friendly technique for gold recovery, contributing to sustainable resource management and reducing the environmental burden of mining waste.