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Article

Development and Performance Evaluation of an Adapted QuEChERS-Gas Chromatography–Mass Spectrometry Method for the Analysis of Cocaine in Surface Water Samples

by
Ana Rita da Conceição Figueira
and
Daniel Barbosa Alcântara
*
Integrated Science Center, Federal University of Northern Tocantins, Araguaína 77824-838, TO, Brazil
*
Author to whom correspondence should be addressed.
Spectrosc. J. 2025, 3(4), 23; https://doi.org/10.3390/spectroscj3040023
Submission received: 27 June 2025 / Revised: 26 August 2025 / Accepted: 12 September 2025 / Published: 24 September 2025
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Abstract

The consumption of illicit psychoactive substances, such as cocaine, poses significant public health and socioeconomic challenges due to its widespread use and impact on the central nervous system. This study aimed to develop and validate an analytical method for quantifying cocaine in surface water using an adapted QuEChERS extraction procedure and gas chromatography–mass spectrometry (GC-MS). The research included a bibliographic review of about 40 articles and laboratory analyses conducted at the Federal University of Northern Tocantins (UFNT). The results showed a matrix effect of −54.24%. This negative matrix effect impacted accuracy, as interference from other sample components can suppress the analyte signal, resulting in a smaller measured quantity. This indicates signal suppression, which can be corrected through matrix-matched calibration. Recovery values ranged from 61.3% to 107.7%, demonstrating satisfactory accuracy. The validated method proved suitable for monitoring cocaine in surface water and can serve as a biomarker for untreated sewage discharges.

1. Introduction

Psychoactive substances have been widely used for a variety of purposes, including medicinal, therapeutic, and recreational. However, the consumption of certain drugs generates significant social and health problems, leading to restrictions or bans due to their association with addiction, dependence, and disruption of social order [1,2]. The complexity of drug use and its consequences for society is evident, as frequent use causes social, biological, and psychological harm [3,4]. Consequently, drug abuse and dependence result in multiple socioeconomic impacts, such as increased healthcare costs, traffic accidents, urban violence, and youth mortality, among others [5,6].
With the advancement of globalization and the accelerated dissemination of psychoactive substances, it has become crucial to understand consumption patterns and their consequences. To address these challenges, effective strategies are required to control and monitor drugs, especially through Sewage-Based Epidemiology (SBE). This innovative tool enhances drug consumption monitoring compared to traditional approaches, offering greater accuracy and efficiency by analyzing chemical substances in sewage systems to estimate consumption within a population [7]. Furthermore, the data generated by SBE can support public authorities in developing targeted public safety and health strategies to mitigate drug-related harm.
For SBE to be successfully implemented, robust analytical methodologies are required, involving key steps such as extraction, cleanup, identification, and quantification of analytes in complex aqueous matrices. Among pretreatment approaches, Solid Phase Extraction (SPE) is widely employed; however, it is costly, time-consuming, and requires specialized equipment and consumables. These limitations restrict its use in many academic or regional laboratories. In contrast, the QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) method represents a more accessible alternative, as it is simple, inexpensive, and adaptable to different analytes. Although originally developed for pesticide analysis in food, QuEChERS has been successfully applied in studies involving drugs of abuse [8]. Its cost-effectiveness and operational simplicity make it particularly attractive for laboratories with limited resources, broadening the feasibility of drug monitoring studies in different contexts.
In the present study, surface water was used as the analytical matrix to adapt and validate the QuEChERS method for cocaine analysis, followed by gas chromatography–mass spectrometry (GC-MS). The choice of surface water, rather than sewage, was due to practical constraints such as regulatory requirements and logistical barriers for sewage sampling during the research timeframe. Nevertheless, validating the methodology in surface water provides a solid foundation for its future application to sewage samples. Since the method was tested in a complex aqueous matrix, its robustness and reliability support its adaptability to more challenging matrices such as sewage. Importantly, this approach illustrates how laboratories facing similar bureaucratic or infrastructural limitations can still advance in developing accessible methodologies to support SBE research.
Thus, this work was structured in two stages: (i) a literature review addressing the analysis of drugs of abuse and their metabolites in aqueous matrices, and (ii) the experimental development of an analytical method at the Central Laboratory of Analyses of the Federal University of Northern Tocantins (UFNT). The latter stage involved sample collection, extraction via QuEChERS, instrumental analysis using GC-MS, and validation of critical parameters such as matrix effect, precision, and recovery. Therefore, the main objective of this study is to demonstrate the applicability of an accessible and adaptable method for the determination of cocaine in water matrices, supporting broader perspectives for its use in future SBE applications.

2. Methodology

This work focuses on analyzing and understanding the chemical analysis of illicit substances, such as cocaine. The study was conducted in two stages: the first consisted of a literature review covering the period from 2015 to 2023, using the SciSpace and ScienceDirect database platforms. In order to systematize the search process and have a more direct approach, the following descriptors were used: “Analysis of drugs of abuse in wastewater; chemical analysis of cannabis in wastewater and analysis of cocaine in wastewater”.
First, approximately 70 articles were found from various countries, such as Brazil, China and the United States. The following criteria were established for excluding the articles: (1) Articles that did not perform analyses of illicit substances in surface/waste water; (2) Articles that excluded experience reports; (3) Articles without abstracts or full texts available; (4) Articles focusing on other analyses, without a focus on illicit substances; and (5) Studies that were not in Portuguese, English or Spanish. Thus, after selecting the articles, 40 articles remained, which were selected to be included in the database (Table S1, see Supplementary Material).
The second stage of the research involved the experimental procedures, which were carried out at the Central Analytical Laboratory (LabCrom) of the Undergraduate Chemistry Program at the Federal University of Northern Tocantins (UFNT). To validate the method and serve as a blank for the validation study, a surface water sample (matrix) from Lago Azul was analyzed. This sample comes from the Lontra River basin, in the municipality of Araguaína, Tocantins, Brazil. The collection was conducted at this location because it attracts numerous visitors, provides ample space for family outings and cycling, and offers a bike path for motorcycles and cars. The location’s attractiveness, with beautiful views of the lake, allows for the installation of restaurants and bars along the route, facilitating increased traffic flow and the holding of various festive events. The water collected along the route comes from a sewage source.
The analyses were performed using gas chromatography coupled with mass spectrometry (GC-MS) which is a widely used analytical technique that combines the separation and quantification of chemical compounds by gas chromatography, with the identification of the substances present in the sample when coupled to a mass spectrometer [9]. Therefore, due to its effectiveness and sensitivity when it comes to compound separation, GC has become one of the most widely used equipment in chemistry and related fields [10]. Following the GC-MS analyses and the generation of chromatograms, calibration curves were constructed using the external standardization method and matrix-matched calibration (matrix superposition).

2.1. Standard Solutions Preparation

For the experimental analysis, the preparation of the standard solution is a priori necessary, as it is crucial for comparing results, optimizing errors and validating the analytical method. Therefore, deuterated commercial analytical standards of cocaine (COC-D3) was used, obtained by Merck, São Paulo, Brazil (purity > 99%) at a concentration of 100 µg mL−1 in acetonitrile (ACN), in which they were subsequently diluted to final concentrations of 300, 500, 800, 1000, 1300 and 1500 µg L−1, these being the working solutions.
For the working solutions, the following procedures were performed: An aliquot of the commercial solution of 100 µg mL−1 was transferred to a 10 mL volumetric flask and made up to volume with chromatographic grade acetonitrile (purity 99.9%) resulting in a final concentration of 10 mg L−1 (stock solution). Soon after, from the stock solution, the working solutions were prepared in acetonitrile for injection into the GC-MS. Then, the calibration curve was obtained, after analysis of the chromatographic data.

2.2. Extraction Procedure Using the Adapted QuEChERS Method

A surface water sample was collected from the Lontra River, located along Via Lago Avenue in the city of Araguaína, Tocantins, and used to obtain the matrix extract through an adapted QuEChERS method, as illustrated in Figure 1.
Initially, 10 mL of the sample was transferred to a 50 mL Teflon tube, followed by the addition of 5 mL of acetonitrile chromatographic grade (ACN, 99.9 %) using a volumetric pipette. The mixture was then vortexed (VM-370 Vortex Mixer, Intllab, Seri Kebangan, Malaysia) for 1 min. Next, 4 g of anhydrous magnesium sulfate (MgSO4, Merck, São Paulo, Brazil) and 1 g of sodium chloride (NaCl, NEON) were added. The mixture was vortexed again for 1 min and subsequently centrifuged for 5 min at 3000 rpm using an MTD Plus centrifuge (Rota-tion Technology Laboratory, São Paulo, Brazil).
After centrifugation, 1 mL of the supernatant, in ACN, was transferred to a 15 mL Teflon tube, to which 0.5 g of anhydrous MgSO4 was added. The mixture was vortexed for 1 min and centrifuged once more for 5 min. The final extract (supernatant) was then transferred to chromatographic vials for analysis by GC-MS.
The extract obtained by the adapted QuEChERS method was also used to prepare cocaine working solutions at concentrations of 300, 500, 800, 1000, and 1300 µg L−1, for the construction of a matrix-matched calibration curve. The matrix effect was evaluated by comparing the slopes of the calibration curves obtained in solvent (external calibration) and in matrix (matrix-matched calibration), according to Equation (1).
ME / % = ( b m − b s ) b s × 100
where
  • ME = matrix effect;
  • bm = angular coefficient of the curve in the matrix;
  • bs = angular coefficient of the curve in the solvent.
It is important to emphasize that the calculation results will allow us to determine whether or not the sample matrix is affecting the analyte signal response in the instrumentation (GC-MS). Therefore, if the result obtained after the EM calculation is negative, ion suppression occurs, the slope of the matrix curve will be lower than that of the solvent, demonstrating that the interferents in the sample reduce the analyte signal intensity.
However, if the result is positive, so-called ion enhancement occurs, and the slope of the matrix curve will be higher than that of the solvent. Unlike ion suppression, in this case, the matrix components would increase the analyte signal intensity.

2.3. Instrumental Parameters

The analyses were performed by the GC-MS/Agilent Technologies equipment (model 7890B of the GC and 5977B of the MS, California, United States). Using the helium carrier gas (99.999%) at a flow rate of 1.2 mL min−1, Agilent HP5-MS capillary column with dimensions of 30 m × 0.25 mm i.d. (internal diameter) and 0.25 µm film thickness of the stationary phase with composition (5% phenylmethylsiloxane). The injector operated in splitless mode (without sample division). The mass spectrometer operated in electron impact ionization (EI) mode at 70 eV, with an ion source at 230 °C and a transfer line temperature of 250 °C. 1.0 μL of the standard was injected with the Injector Temperature (IT) maintained at 260 °C. The quadrupole temperature was 150 °C. Analyses were performed in both Scan mode (m/z monitored: 40 to 500) and SIM mode (m/z monitored: 85 as confirmation ion and 185 as quantification ion for deuterated cocaine—COC-D3).
The working solutions were injected into the GC-MS, using the conditions described in Table 1. However, it is extremely important to emphasize that in order to obtain the chosen method, it was necessary to analyze methods in the literature and select the most appropriate one according to the interest of the present work, therefore the method was adapted from Alves (2010) [11].

3. Results and Discussion

3.1. Literature Review Analysis

The articles selected for the literature review were analyzed using a sampling approach. A summary table was created to organize key information, including the year of publication, the countries where the analyses were conducted, the analytical methods employed, and other relevant details, as shown in Table S1 (see Supplementary Material). Based on the data compiled, a series of graphs was developed to visually summarize the findings. For instance, Figure 2 presents the main drugs of abuse and their metabolites, along with the frequency with which they were reported in the reviewed studies by year of publication.
From this perspective, is observed higher numbers of studies related to the analysis of drugs in surface water and wastewater between 2018 and 2021. Notably, in 2019, benzoylecgonine—a primary metabolite of cocaine—stood out as one of the most frequently investigated substances. This compound is a key biomarker of crack cocaine intake, a drug widely consumed among certain populations [12].
According to data from the Second National Survey on Cocaine and Crack Consumption in Brazil, approximately two million people had used cocaine in its smoked form (crack, merla, or oxi). In 2011, the highest prevalence was observed among males aged 25 to 34 years [13].
Figure 3 shows the percentage of articles found by concentration range. It is evident that THC-COOH and benzoylecgonine, metabolites of cannabis and cocaine, respectively, are detected at the highest concentrations (ng/L). Cocaine is known to be one of the most widely consumed stimulant drugs in Europe, with an estimated 14.1 million adults having used it at least once [14,15].

3.2. Chromatographic Analysis by GC-MS

Deuterated cocaine (COC-D3) was used as an internal standard in the GC-MS analysis, as it is structurally analogous to the analyte of interest and therefore suitable for mass spectrometric detection. The use of an isotopically labeled internal standard helps improve accuracy and precision in quantitative analysis.
Following the adaptation of the method proposed by Alves (2010) [11], the first chromatogram was obtained using a pure COC-D3 standard solution (10 mg L−1) in full scan (SCAN) mode, which allows for the detection of all fragmented ions (Figure 4A). This chromatogram showed a relatively long run time and an asymmetric peak for cocaine at a retention time of approximately 17.8 min.
To enhance sensitivity and improve peak symmetry for the target analyte, the Selected Ion Monitoring (SIM) mode was subsequently applied (Figure 4B). By focusing only on the specific ions of interest, the SIM mode provided improved detection. Additionally, an optimization of the oven temperature program enabled a reduction in the total run time. Specifically, the final temperature step at 280 °C, which was initially held for 3 min, was reduced to 1 min, resulting in a shorter total runtime of 18.85 min, as shown in Figure 4C, which also displays a well-defined peak for the 800 µg L−1 standard solution.

3.3. Sensitivity and Instrumental Precision

Based on the chromatographic data, a calibration curve was constructed for the analyte using six different concentrations: 300, 500, 800, 1000, 1300, and 1500 µg L−1 (Figure 5). From this curve, the limits of detection (LOD) and quantification (LOQ) were estimated. The LOD corresponds to the lowest amount of analyte that can be detected, though not necessarily quantified accurately, while the LOQ refers to the lowest concentration that can be quantified with acceptable precision and accuracy [16,17].
It is important to note that LOD and LOQ were only estimated for the calibration curve prepared in solvent, with values of 90 µg L−1 and 300 µg L−1, respectively. In the matrix-matched curve, however, the 300 µg L−1 concentration exceeded the LOQ, indicating the need for further dilutions to accurately determine the LOD and LOQ in the matrix.
Thus, LOD and LOQ are critical parameters in chemical analysis, as they define the method’s sensitivity for detecting and quantifying analytes in various sample types. Another essential parameter is the coefficient of determination (R2), which indicates how well the calibration curve fits the experimental data. An R2 value close to 1 suggests a good fit and, consequently, greater reliability of the analytical results.
Additionally, instrumental precision was evaluated through triplicate analyses, based on the calculation of the relative standard deviation (RSD), which ranged from 0.5% to 2%. These values demonstrate good repeatability, indicating that the results were consistent and close to the mean.

3.4. Suppression Signal

In addition to the validation parameters, the matrix effect (ME) was evaluated. This effect refers to the interference caused by co-extracted compounds present in the sample, which can significantly affect the precision and accuracy of analytical results [16].
Figure 5 presents the calibration curves obtained using two approaches: external calibration and matrix-matched calibration. According to the literature, ME values within the range of –20% to +20% are considered acceptable and indicate no significant matrix effect. Values outside this range suggest the presence of a matrix effect, in which case the matrix-matched calibration curve should be used for quantitative analysis [17].
As shown in Figure 5, the calibration curve prepared in solvent had a determination coefficient (R2) of 0.9998, while the matrix-matched curve presented an R2 of 0.9833. The linear equations obtained were: y = 2546.3x − 581202 for the solvent and y = 1165x − 284750 for the matrix. Based on the calculation in Equation (1), the matrix effect was estimated at −54.25%.
This negative ME value indicates that components of the matrix reduced the analyte signal. Studies suggest that such interference may be attributed to coexisting compounds that compete with the analytes during analysis, resulting in signal suppression [17].
Factors such as the physicochemical properties of the analyte and the composition of the sample matrix can directly influence the ME [18]. Although a negative matrix effect poses a challenge for quantification, it can be considered acceptable if matrix-matched calibration is used to correct for such interference.

3.5. Accuracy and Intra-Assay Precision

Based on the recovery data, both intra-assay precision and accuracy were assessed. The recovery results were organized into two main parameters: the recovered concentration of cocaine (µg L−1) and the recovery percentage (Rec/%), as presented in Table 2.
According to the guidelines of the Commission Implementing Regulation (UE) 2021/808 of March 2021 and INMETRO (2020) for the validation of chromatographic methods, the maximum allowable relative standard deviation (RSD%) is 20% and 15%, respectively [16,17].
As shown in Table 2, the cocaine recovery percentages ranged from 61.3% to 107.7%, indicating that the results fall within acceptable limits. These values demonstrate good analytical accuracy, particularly when considering the complexity of the matrix and the low concentration levels of the analyte. In such cases, recovery values between 50% and 120%, with an RSD of up to ±15%, are considered acceptable [18,19].

4. Conclusions

The data obtained from the literature review indicate that research employing the Wastewater-Based Epidemiology (WBE) approach remains limited, underscoring the need for further studies that provide actionable results for public health and policy-making, given the complexity of illicit drug use as a societal problem.
The experimental results demonstrate that the developed method yields a robust analytical performance. The calibration curves exhibited strong linearity, with determination coefficients (R2) indicating good linearity, while the relative standard deviation (RSD) values confirmed that the data are precise and repeatable. Although the matrix effect (ME) showed a negative influence on analyte detection, this interference can be effectively compensated by applying matrix-matched calibration curves, thereby ensuring the method’s accuracy, precision, and reliability.
Furthermore, the recovery rates, ranging from 61.3% to 107.7%, fall within acceptable limits and confirm the method’s effectiveness in extracting and quantifying the target analyte in complex aqueous matrices.
Given these results, the performance of the evaluated validation parameters demonstrates that the method is suitable for monitoring cocaine residues in surface waters. Moreover, the data obtained through this approach can provide reliable estimates of drug consumption in the monitored populations, thereby supporting scientific research and informing public health interventions.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/spectroscj3040023/s1, Table S1: Summary of Studies on Illicit Drug Analysis in Wastewater by WBE [2,4,6,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55].

Author Contributions

Conceptualization, A.R.d.C.F. and D.B.A.; methodology, A.R.d.C.F. and D.B.A.; validation, A.R.d.C.F. and D.B.A.; formal analysis, A.R.d.C.F. and D.B.A.; investigation, A.R.d.C.F. and D.B.A.; resources, A.R.d.C.F. and D.B.A.; data curation, A.R.d.C.F. and D.B.A.; writing—original draft preparation, A.R.d.C.F.; writing—review and editing, A.R.d.C.F.; supervision, D.B.A.; project administration, D.B.A.; funding acquisition, D.B.A. All authors have read and agreed to the published version of the manuscript.

Funding

This study was financially supported by the UFNT Research Office (PROPESQ/UFNT), under Call for Proposals No. 012/2025.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author at daniel.alcantara@ufnt.edu.br.

Acknowledgments

The authors thank the Central Analytical Laboratory (LabCrom) at the Federal University of Northern Tocantins (UFNT) for providing the necessary infrastructure to carry out this research. The authors thank the Tocantins Research Support Foundation (FAPT, Tocantins, Brazil) for providing Ana Rita with a scientific initiation scholarship during the period of this work.

Conflicts of Interest

The authors declare that they have no conflict of interest.

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Figure 1. Illustration of the sample extraction procedure using the adapted QuEChERS method. Created using BioRender Software.
Figure 1. Illustration of the sample extraction procedure using the adapted QuEChERS method. Created using BioRender Software.
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Figure 2. Number of studies investigating each substance in water samples by year of publication.
Figure 2. Number of studies investigating each substance in water samples by year of publication.
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Figure 3. Distribution of studies by concentration range (ng/L) of detected drug metabolites in water samples.
Figure 3. Distribution of studies by concentration range (ng/L) of detected drug metabolites in water samples.
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Figure 4. (A) Chromatogram of cocaine (10 mg L−1 in ACN) obtained in SCAN mode with mass spectrum in the m/z range of 40–500; (B) chromatogram of cocaine (10 mg L−1 in ACN) obtained in SIM mode; (C) chromatogram obtained in SIM mode after injection of 800 µg L−1 of cocaine in ACN, following modification of the column oven temperature program.
Figure 4. (A) Chromatogram of cocaine (10 mg L−1 in ACN) obtained in SCAN mode with mass spectrum in the m/z range of 40–500; (B) chromatogram of cocaine (10 mg L−1 in ACN) obtained in SIM mode; (C) chromatogram obtained in SIM mode after injection of 800 µg L−1 of cocaine in ACN, following modification of the column oven temperature program.
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Figure 5. Calibration curves in solvent and matrix, including correlation coefficients, linear equations.
Figure 5. Calibration curves in solvent and matrix, including correlation coefficients, linear equations.
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Table 1. Oven temperature programming.
Table 1. Oven temperature programming.
Rate (°C/min)Temperature (°C)Hold Time/min
600
151805
352002
352801
Note: Total running time: 18.85 min.
Table 2. Cocaine recovery percentages at two spiking levels with respective intra-assay precision expressed as relative standard deviation (RSD%) (n = 3).
Table 2. Cocaine recovery percentages at two spiking levels with respective intra-assay precision expressed as relative standard deviation (RSD%) (n = 3).
Spiked Concentration
(µg L−1)		Measured Concentration
(µg L−1)		Mean Concentration
(µg L−1)		RSD (%)Recovery (%)Mean Recovery (%)RSD (%)
350377.19349.886.76107.7699.966.76
350337.5996.45
350334.8895.68
933572.53612.036.6661.3665.596.66
933654.0570.10
933609.5165.32
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MDPI and ACS Style

da Conceição Figueira, A.R.; Alcântara, D.B. Development and Performance Evaluation of an Adapted QuEChERS-Gas Chromatography–Mass Spectrometry Method for the Analysis of Cocaine in Surface Water Samples. Spectrosc. J. 2025, 3, 23. https://doi.org/10.3390/spectroscj3040023

AMA Style

da Conceição Figueira AR, Alcântara DB. Development and Performance Evaluation of an Adapted QuEChERS-Gas Chromatography–Mass Spectrometry Method for the Analysis of Cocaine in Surface Water Samples. Spectroscopy Journal. 2025; 3(4):23. https://doi.org/10.3390/spectroscj3040023

Chicago/Turabian Style

da Conceição Figueira, Ana Rita, and Daniel Barbosa Alcântara. 2025. "Development and Performance Evaluation of an Adapted QuEChERS-Gas Chromatography–Mass Spectrometry Method for the Analysis of Cocaine in Surface Water Samples" Spectroscopy Journal 3, no. 4: 23. https://doi.org/10.3390/spectroscj3040023

APA Style

da Conceição Figueira, A. R., & Alcântara, D. B. (2025). Development and Performance Evaluation of an Adapted QuEChERS-Gas Chromatography–Mass Spectrometry Method for the Analysis of Cocaine in Surface Water Samples. Spectroscopy Journal, 3(4), 23. https://doi.org/10.3390/spectroscj3040023

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