
==== Front
MethodsX
MethodsX
MethodsX
2215-0161
Elsevier

S2215-0161(24)00348-0
10.1016/j.mex.2024.102896
102896
Environmental Science
A reliable method to prepare milligram size environmental samples to quantify metal(loid)s by high-resolution graphite furnace atomic absorption spectrometry
Costa Patrícia Gomes
Dal Pizzol Juliana Lemos
Zebral Yuri Dornelles
Bianchini Adalto adaltobianchini@furg.br
⁎
Instituto de Ciências Biológicas, Universidade Federal do Rio Grande - FURG, Avenida Itália km 8, Campus Carreiros, 96.203-900, Rio Grande, RS, Brazil
⁎ Corresponding author. adaltobianchini@furg.br
08 8 2024
12 2024
08 8 2024
13 1028966 6 2024
6 8 2024
© 2024 The Author(s)
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
We searched for an extraction method that would allow a precise quantification of metal(loid)s in milligram-size samples using high-resolution graphite furnace atomic absorption spectrometry (HR-GFAAS). We digested biological (DORM-4, DOLT-5 and TORT-3) and sediment (MESS-4) certified reference materials (CRMs) using nitric acid in a drying oven, aqua regia in a drying oven, or nitric acid in a microwave. In addition, we digested MESS-4 using a mixture of nitric and hydrofluoric acids in a drying oven. We also evaluated the effect of sample size (100 and 200 mg) on the extraction efficiency. Nitric acid extraction in a drying oven yielded the greatest recovery rates for all metal(loid)s in all tested CRMs (80.0 %–100.0 %) compared with the other extraction methods tested (67.3 %–99.2 %). In most cases, the sample size did not have a significant effect on the extraction efficiency. Therefore, we conclude that nitric acid digestion in a drying oven is a reliable extraction method for milligram-size samples to quantify metal(loid)s with HR-GFAAS. This validated method could provide substantial benefits to environmental quality monitoring programs by significantly reducing the time and costs required for sample collection, storage, transport and preparation, as well as the amount of hazardous chemicals used during sample extraction and analysis.

• Sample digestion with nitric acid in a drying oven yielded the greatest recovery rates of metal(loid)s from biological and sediment certified reference materials.

• The recovery rates of metal(loid)s from biological and sediment certified reference materials using nitric acid digestion in a drying oven ranged from 73 % to 100 %.

• Digestion with nitric acid in a drying oven is a simple and reliable method to extract small size environmental samples for metal(loid)s quantification by high-resolution graphite furnace atomic absorption spectrometry.

Graphical abstract

The images have been adapted from: https://i0.wp.com/jornal.usp.br/wp-content/uploads/2018/11/Imagem-a%C3%A9rea-da-%C3%A1rea-afetada-pelo-rompimento-da-Barragem-de-Fund%C3%A3o-em-Mariana-Minas-Gerais.-IBAMA-Flickr-CC.jpg?fit=768%2C510&ssl=1; https://i.em.com.br/xia23F4YBhXAVLI5cFETIxR_WtU=/675x/smart/imgsapp.em.com.br/app/foto_127989356258/2015/11/06/5440/20151107082147528055o.jpg; https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcTPjCPCrGwL31DLL9MwTLi2AgOdLGqxldJTqA&s; and https://br.freepik.com/Image, graphical abstract

Method name

A simple and reliable method for preparing milligram size environmental samples for the quantification of metal(loid)s by high-resolution graphite furnace atomic absorption spectrometry
Keywords

Aquatic contamination
Environmental monitoring
Method validation
Mining dam failure
Sample digestion
Sample extraction
==== Body
pmcSpecifications tableSubject area:	Chemistry	
More specific subject area:	Analytical chemistry of metal(loid)s	
Name of your method:	A simple and reliable method for preparing milligram size environmental samples for the quantification of metal(loid)s by high-resolution graphite furnace atomic absorption spectrometry.	
Name and reference of original method:	U.S. EPA. 1992. Method 3050A: Acid Digestion of Sediments, Sludges, and Soils, Revision 1. Washington, DC.
U.S. EPA. 1996. Method 3050B: Acid Digestion of Sediments, Sludges, and Soils, Revision 2. Washington, DC.
U.S. EPA. 2007. Method 3051A (SW-846): Microwave Assisted Acid Digestion of Sediments, Sludges, and Oils, Revision 1. Washington, DC.	
Resource availability:	Not applicable	

Background

Sample preparation is the most laborious and sensitive stage of the process involved in the identification and quantification of chemical contaminants, including metal(loid)s, in environmental samples. Several techniques are available to prepare and quantify metal(loids) in biological and sediment samples. However, they show marked differences in cost, analyte loss, sensitivity, extraction efficiency, and residue generation. These differences are generally associated with the rigorous chemical (acid) and physical (heat) treatments to which the samples are subjected. Moreover, they are dependent on the nature (matrix) and mass of the sample, as well as the sensitivity of the equipment employed for metal(loid) identification and quantification. The analytical techniques used most frequently are atomic absorption spectroscopy (AAS), graphite furnace absorption atomic spectrometry (GFAAS), flame emission spectroscopy (FES), ultraviolet–visible (UV-Vis spectroscopy, inductively coupled plasma mass spectrometry (ICP-MS), inductively coupled plasma optical emission spectrometry (ICP-OES), and X-ray fluorescence spectrometry (XRF). Commercial certified laboratories often use > 1 and > 50 g of biological and sediment samples, respectively, for these analyses [[1], [2], [3], [4], [5], [6], [7], [8]]. In this context, comparative studies of different acid digestion methods for elemental analysis in traditional medicinale products [9] and plants [10] using AAS have been performed. Nonetheless, long-term programs devoted to monitor the impacts of environmental disasters of great intensity and spatial scope generally require the use of samples with a very small volume or mass due to the need to sample a diverse array of matrices and biological groups from different levels of the food web. This is the case for the Aquatic Biodiversity Monitoring Program (PMBA), which has been monitoring the impacts associated with the Fundão dam collapse that occurred in November 2015 (Mariana, Minas Gerais State, Southeastern Brazil). It is considered to be the world's largest disaster related to the collapse of a mining tailings dam. Since 2018, the PMBA has evaluated a wide variety of samples from very different environmental matrices (water, sediments, phytoplankton, zooplankton, insect larvae, shrimps, fishes, birds, turtles, and aquatic mammals). Samples are collected from freshwater (river, lakes and lagoons), coastal (beaches, mangroves and restinga) and marine (up to 50 m deep) ecosystems over a very wide geographical area [11,12]. With this background in mind, we tested three sample digestion methods to identify the simplest and most reliable method for preparing milligram-size samples to quantify metal(loid)s by high-resolution graphite furnace atomic absorption spectrometry (HR-GFASS) in a diverse array of environmental matrices.

Method details

Required reagents

• Ultrapure water (18.2 MΩ/cm resistivity)

• Ultrapure 65 % nitric acid (HNO3, Suprapur, Merck, Darmstadt, Germany)

• Ultrapure 35 % hydrochloric acid (HCl, Suprapur, Merck)

• Ultrapure 52 % hydrofluoric acid (HF, Suprapur, Merck)

• Certified Reference Material DORM-4 (National Research Council Canada [NRCC, Ottawa, Canada]), a certified reference material (CRM)

• DOLT-5 (NRCC), a CRM

• TORT-3 (NRCC), a CRM

• MESS-4 (NRCC), a CRM

Required equipment

• Micropipettes and micropipette tips

• Falcon tubes

• Glass Erlenmeyer flasks, measuring cylinders, and beakers

• Analytical balance (with 0.1-mg resolution)

• Drying oven with a digital temperature controller (50‒250 °C)

• Microwave sample preparation platform system (e.g., Multiwave 3000, Anton Paar, Graz, Austria)

• A high-resolution graphite furnace atomic absorption spectrometer (Control-A 700, Analytik Jena, Jena, Germany)

Procedures

We aimed to identify the simplest and most reliable method to digest milligram-size environmental samples for metal(loid) quantification using HR-GFAAS. We used four CRMs obtained from NRCC: DORM-4 (fish protein), DOLT-5 (fish liver), TORT-3 (lobster hepatopancreas) and MESS-4 (marine sediments). We prepared each CRM using different extraction methods (Fig. 1): digestion with HNO3 in a drying oven; digestion with aqua regia (HCl: HNO3, 3:1 [v/v]) in a drying oven; and digestion with HNO3 in a microwave sample preparation platform system. We also digested MESS-4 with a mixture of HNO3 and HF (3:1 [v/v]) (Fig. 1). For the procedure using a drying oven, we used a stainless-steel drying oven (60 × 60 × 70 cm; 252 L) with three shelves, a gravity convection system, and a digital temperature controller (50–250 °C) (De Leo, Porto Alegre, RS, Brazil). We performed the digestion at 60 °C for 24 h. For the procedure using a microwave, we used the Multiwave 3000 microwave sample preparation platform system with a rotor for eight 80-mL Teflon digestion chambers. We performed digestion in this microwave at 80 bar. To determine the possible influence of sample size (mass) on the metal(loid) extraction efficiency, we used two representative sample sizes (100 and 200 mg) of each CRM for each extraction method. We selected these sample sizes considering that environmental quality monitoring involves sampling small organisms (e.g., plankton and amphipods) and/or biological tissues (e.g., fish gills and liver). Prior to digestion, we dried the CRM sample in an oven (60 °C) until it reached its dry weight. Then, we digested each sample with the appropriate method (Fig. 1). After digestion, we diluted the samples with ultrapure MilliQ water (18.2 MΩ/cm resistivity) to a final volume of 10 mL using 15-mL plastic Falcon-type tubes.Fig. 1 This schematic shows the methods employed to digest certified reference materials (CRMs) for metal(loid) quantification using high-resolution graphite furnace atomic absorption spectrometry.

Fig 1

We quantified the metal(loid)s As, Cd, Cr, Cu, Fe, Mn, Pb and Zn in the digested samples was performed by using a high-resolution graphite furnace atomic absorption spectrometer. Metal(loid) quantification was based on a calibration curve generating using a serial dilution of a multi-element standard (1,000 mg/L) solution (Merck). The coefficients of determination (R2) of the calibration curves were 0.999989 for As, 0.999605 for Cd, 0.999940 for Cr, 0.999971 for Cu, 0.999870 for Fe, 0.999964 for Mn, 0.999984 for Pb, and 0.999967 for Zn. The results are expressed as mg/kg dry mass. Quality control and assurance procedures for metal(loid)s determination were based on analysis of blanks and spiked matrices.

Statistical analysis

The concentration of each metal(loid) measured in each experimental condition (CRM, sample digestion method, and sample size) is expressed as the mean ± standard error (SE). We also calculated the recovery percentage of each metal(loid) measured in each experimental condition based on the measured and expected concentrations for each respective CRM. The recovery percentage for each metal(loid) in each experimental condition is presented as the mean ± SE. The recovery percentage for each metal(loid) in each CRM sample subjected to each experimental condition was previously transformed [arc sin (√ percentage value/100)]. We checked the normality of the distribution and the homogeneity of variances by using the normal probability plot of raw residuals and the Cochran C test, respectively. We compared the mean for each metal(loid) in each experimental condition with one-way analysis of variance (ANOVA) followed by Tukey's honest significant difference (HSD) test. In all cases, we considered p < 0.05 to indicate a statistically significant difference.

Method validation

The concentrations of metal(loid)s measured in DORM-4, DOLT-5, TORT-3, and MESS-4 prepared following the three tested different sample extraction methods are shown in Tables 1, 2, 3, and 4, respectively. Based on the measured concentrations, we calculated the mean recovery percentage for each metal(loid) analyzed in each CRM; the means are shown in Fig. 2 for DORM-4, Fig. 3 for DOLT-5, Fig. 4 for TORT-3, and Fig. 5 for MESS-4. These four CRMs showed a wide range of mean concentrations for seven of the eight analyzed metal(loid)s (As: 6.87–59.5 mg/kg; Cd: 0.29–42.3 mg/kg; Cu: 15.70–497.0 mg/kg; Fe: 179–1070 mg/kg; Mn: 3.17–15.6 mg/kg; Pb: 0.16–0.40 mg/kg; and Zn: 51.6–136.0 mg/kg). The only exception was Cr, which showed a relatively narrow range (1.87–2.35 mg/kg). Additionally, it is interesting to note that general mean recovery percentages for all metal(loid)s analyzed in the biological CRMs (DORM-4, DOLT-5, and TORT-3) ranged from 71.0 to 100.0 %, regardless of the experimental conditions (sample digestion method and sample size; Fig. 2, Fig. 3, Fig. 4). Furthermore, they were very similar for the sediment CRM (MESS-4), ranging from 72.0 % to 96.7 % (Fig. 5).Table 1 The concentration of each metal(loid) measured in DORM-4 (fish protein) using the three sample preparation methods and the two sample masses.

Table 1	As	Cd	Cr	Cu	Fe	Mn	Pb	Zn	
Expected concentration (mg/kg) in DORM-4	
	6.87 ± 0.44	0.299 ± 0.018	1.87 ± 0.18	15.7 ± 0.46	343 ± 20	3.17 ± 0.26	0.404 ± 0.062	51.6 ± 2.8	
Method	Measured concentration (mg/kg) in DORM-4	
NO – 100 mg	6.26 ± 0.09	0.294 ± 0.001	1.87 ± 0.01	14.7 ± 0.07	312 ± 6	2.75 ± 0.07	0.389 ± 0.002	46.1 ± 0.6	
NO – 200 mg	6.37 ± 0.14	0.286 ± 0.004	1.82 ± 0.03	14.3 ± 0.20	293 ± 4	2.71 ± 0.06	0.378 ± 0.005	45.6 ± 0.6	
ARO – 100 mg	5.40 ± 0.12	0.247 ± 0.007	1.57 ± 0.04	12.4 ± 0.33	297 ± 3	2.26 ± 0.04	0.326 ± 0.008	39.2 ± 0.8	
ARO – 200 mg	5.92 ± 0.14	0.232 ± 0.003	1.48 ± 0.02	11.6 ± 0.16	316 ± 4	2.43 ± 0.04	0.306 ± 0.040	41.5 ± 0.6	
NM – 100 mg	5.02 ± 0.06	0.218 ± 0.003	1.85 ± 0.02	14.6 ± 0.13	258 ± 5	2.61 ± 0.05	0.312 ± 0.005	42.7 ± 0.3	
NM – 200 mg	5.44 ± 0.08	0.234 ± 0.003	1.81 ± 0.02	14.3 ± 0.18	265 ± 5	2.65 ± 0.06	0.325 ± 0.004	41.3 ± 0.7	
The “Method” column indicates the digestion method (NO, nitric acid in a drying oven; ARO, aqua regia in a drying oven; or NM, nitric acid in a microwave) and the sample size (100 or 200 mg). The data are expressed as the mean ± standard error. Each expected concentration is expressed as the value ± uncertainty.

Table 2 The concentration of each metal(loid) measured in DOLT-5 (fish liver) using the three sample preparation methods and the two sample masses.

Table 2	As	Cd	Cr	Cu	Fe	Mn	Pb	Zn	
Exration (mg/kg) in DOLT-5	
	34.6 ± 2.4	14.5 ± 0.6	2.35 ± 0.58	35.0 ± 2.4	1070 ± 80	8.91 ± 0.70	0.162 ± 0.032	105.3 ± 5.4	
Method	Measured concentration (mg/kg) in DOLT-5	
NO – 100 mg	31.3 ± 0.9	13.5 ± 0.4	2.12 ± 0.05	33.6 ± 0.7	953 ± 16	7.75 ± 0.37	0.154 ± 0.019	96.9 ± 4.3	
NO – 200 mg	30.7 ± 0.2	13.3 ± 0.3	2.09 ± 0.05	32.8 ± 0.6	970 ± 17	7.24 ± 0.12	0.156 ± 0.019	84.3 ± 2.2	
ARO – 100 mg	25.7 ± 0.7	11.6 ± 0.3	1.82 ± 0.04	29.0 ± 0.7	858 ± 10	7.28 ± 0.19	0.139 ± 0.032	79.7 ± 1.6	
ARO – 200 mg	24.7 ± 0.3	11.4 ± 0.1	1.78 ± 0.02	28.5 ± 0.4	906 ± 11	6.75 ± 0.11	0.137 ± 0.016	87.3 ± 3.4	
NM – 200 mg	25.1 ± 0.4	10.7 ± 0.2	2.04 ± 0.07	32.3 ± 0.9	916 ± 30	6.70 ± 0.27	0.121 ± 0.030	77.4 ± 1.7	
NM – 200 mg	26.6 ± 0.6	10.3 ± 0.1	1.98 ± 0.05	31.6 ± 0.8	854 ± 19	6.32 ± 0.08	0.125 ± 0.005	85.0 ± 3.9	
The “Method” column indicates the digestion method (NO, nitric acid in a drying oven; ARO, aqua regia in a drying oven; or NM, nitric acid in a microwave) and the sample size (100 or 200 mg). The data are expressed as the mean ± standard error. Each expected concentration is expressed as the value ± uncertainty.

Table 3 The concentration of each metal(loid) measured in TORT-3 (lobster hepatopancreas) using the three sample preparation methods and the two sample masses.

Table 3	As	Cd	Cr	Cu	Fe	Mn	Pb	Zn	
Exration (mg/kg) in TORT-3	
	59.5 ± 3.8	42.3 ± 1.8	1.95 ± 0.24	497 ± 22	179 ± 8	15.6 ± 1.0	0.225 ± 0.018	136 ± 6	
Method	Measured concentration (mg/kg) in TORT-3	
NO – 100 mg	48.9 ± 0.8	38.0 ± 0.4	1.93 ± 0.02	482 ± 4	155 ± 3	14.0 ± 0.3	0.193 ± 0.010	99 ± 2	
NO – 200 mg	54.5 ± 0.8	38.6 ± 1.0	1.87 ± 0.03	479 ± 5	159 ± 2	12.7 ± 0.2	0.208 ± 0.008	106 ± 1	
ARO – 100 mg	46.8 ± 0.4	34.8 ± 1.4	1.79 ± 0.07	433 ± 8	137 ± 3	11.8 ± 0.1	0.177 ± 0.004	98 ± 1	
ARO – 200 mg	45.0 ± 0.5	33.9 ± 0.8	1.84 ± 0.05	441 ± 11	149 ± 2	10.9 ± 0.2	0.207 ± 0.009	112 ± 3	
NM – 100 mg	44.0 ± 1.1	32.4 ± 0.8	1.92 ± 0.01	462 ± 22	144 ± 3	13.3 ± 0.3	0.186 ± 0.010	107 ± 3	
NM – 200 mg	42.8 ± 0.4	33.3 ± 0.4	1.86 ± 0.06	467 ± 6	151 ± 1	11.7 ± 0.3	0.201 ± 0.007	106 ± 2	
The “Method” column indicates the digestion method (NO, nitric acid in a drying oven; ARO, aqua regia in a drying oven; or NM, nitric acid in a microwave) and the sample size (100 or 200 mg). The data are expressed as the mean ± standard error. Each expected concentration is expressed as the value ± uncertainty.

Table 4 The concentration of each metal(loid) measured in MESS-4 (marine sediments) using the four sample preparation methods and the two sample masses.

Table 4	As	Cd	Cr	Cu	Fe	Mn	Pb	Zn	
Extraction (mg/kg) in MESS-4	
	21.7 ± 2.8	0.28 ± 0.04	94.3 ± 1.8	32.9 ± 1.8	37900 ± 1600	298 ± 14	21.5 ± 1.2	147 ± 6	
Method	Measured concentration (mg/kg) in MESS-4	
NO – 100 mg	18.4 ± 0.2	0.25 ± 0.01	82.8 ± 3.3	30.3 ± 0.8	31909 ± 637	261 ± 4	20.6 ± 0.4	125 ± 3	
NO – 200 mg	19.7 ± 0.4	0.26 ± 0.00	85.3 ± 1.4	31.4 ± 1.0	30315 ± 476	264 ± 6	19.7 ± 0.5	123 ± 3	
ARO – 100 mg	16.6 ± 0.4	0.23 ± 0.01	82.6 ± 1.6	27.5 ± 1.5	28461 ± 515	233 ± 4	18.2 ± 1.0	112 ± 2	
ARO – 200 mg	16.1 ± 0.2	0.25 ± 0.01	83.9 ± 1.4	29.3 ± 2.7	28741 ± 507	231 ± 8	19.5 ± 0.6	115 ± 2	
NFO – 100 mg	17.7 ± 0.5	0.26 ± 0.01	88.2 ± 1.7	28.3 ± 1.3	25523 ± 691	226 ± 10	20.0 ± 0.3	115 ± 3	
NFO – 200 mg	16.5 ± 0.3	0.27 ± 0.01	85.1 ± 3.0	29.4 ± 0.9	26746 ± 568	219 ± 6	21.1 ± 0.5	109 ± 3	
NM – 100 mg	16.0 ± 0.4	0.21 ± 0.00	91.1 ± 0.4	29.7 ± 1.3	30429 ± 706	245 ± 8	15.6 ± 0.1	121 ± 2	
NM – 200 mg	16.0 ± 0.2	0.21 ± 0.00	90.9 ± 1.0	28.3 ± 0.7	30769 ± 362	222 ± 2	16.9 ± 0.3	112 ± 2	
The “Method” column indicates the digestion method (NO, nitric acid in a drying oven; ARO, aqua regia in a drying oven; NFO, nitric and hydrofluoric acids in a drying over; or NM, nitric acid in a microwave) and the sample size (100 or 200 mg). The data are expressed as the mean ± standard error. Each expected concentration is expressed as the value ± uncertainty.

Fig. 2 Metal(loid) recovery from 100 and 200 mg of the certified reference material DORM-4 (fish protein) using three extraction methods (NO, nitric acid in a drying oven; ARO, aqua regia in a drying oven; and NM, nitric acid in a microwave). The data are presented as the mean recovery rate for each metal(loid), represented as a circle: As, black; Cd, red; Cr, green; Cu, yellow; Fe, blue; Mn, pink; Pb, cyan; and Zn, dark red). The dotted lines indicate the 80 %–100 % recovery range.

Fig 2

Fig. 3 Metal(loid) recovery from 100 and 200 mg of the certified reference material DOLT-5 (fish liver) using three extraction methods (NO, nitric acid in a drying oven; ARO, aqua regia in a drying oven; and NM, nitric acid in a microwave). The data are presented as the mean recovery rate for each metal(loid), represented as a circle: As, black; Cd, red; Cr, green; Cu, yellow; Fe, blue; Mn, pink; Pb, cyan; and Zn, dark red). The dotted lines indicate the 80 %–100 % recovery range.

Fig 3

Fig. 4 Metal(loid) recovery from 100 and 200 mg of the certified reference material TORT-3 (lobster hepatopancreas) using three extraction methods (NO, nitric acid in a drying oven; ARO, aqua regia in a drying oven; and NM, nitric acid in a microwave). The data are presented as the mean recovery rate for each metal(loid), represented as a circle: As, black; Cd, red; Cr, green; Cu, yellow; Fe, blue; Mn, pink; Pb, cyan; and Zn, dark red). The dotted lines indicate the 80 %–100 % recovery range.

Fig 4

Fig. 5 Metal(loid) recovery from 100 and 200 mg of the certified reference material MESS-4 (marine sediments) using three extraction methods (NO, nitric acid in a drying oven; ARO, aqua regia in a drying oven; and NM, nitric acid in a microwave). The data are presented as the mean recovery rate for each metal(loid), represented as a circle: As, black; Cd, red; Cr, green; Cu, yellow; Fe, blue; Mn, pink; Pb, cyan; and Zn, dark red). The dotted lines indicate the 80 %–100 % recovery range.

Fig 5

The As recovery percentages were similar in the tested biological (71.4 %–92.7 %; Fig. 2, Fig. 3, Fig. 4) and sediment (73.5 %–92.4 %; Fig. 5) CRMs (Fig. S1). We observed higher means for sample digestion using HNO3 in a drying oven, regardless of the sample size (100 or 200 mg) and the CRM tested (Fig. 2, Fig. 3, Fig. 4, Fig. 5 and Fig. S1). We noted a similar finding for Cd, especially for the biological CRMs (Fig. 2, Fig. 3, Fig. 4 and Fig. S2). For the sediment CRM, there were no significant differences between the sample digestion methods we tested, except for HNO3 in a microwave. In that case, there was a lower Cd recovery percentage regardless of the sample size (Fig. 5 and Fig. S2). The general ranges of Cd recovery percentages were similar in the biological (71.0 %–98.5 %; Fig. 2, Fig. 3, Fig. 4) and sediment (77.4 %–93.8 %; Fig. 5) CRMs (Fig. S2).

For Cr, we observed a narrower range of recovery percentages was observed for the sediment CRM (89.7 %–96.7 %; Fig. 5) compared with the biological CRMs (75.9 %–100.0 %; Fig. 2, Fig. 3, Fig. 4). Again, the extraction methods using HNO3 yielded the highest mean recovery percentages (Fig. 2, Fig. 3, Fig. 4, Fig. 5 and Fig. S3). However, there were no significant differences in the extraction efficiency for the three biological CRMs when using HNO3 regardless the apparatus (drying oven or microwave) and the sample size (Fig. 2, Fig. 3, Fig. 4 and Fig. S3). On the other hand, we observed better Cr extraction efficiency for the sediment CRM when using HNO3 in a microwave (Fig. 5 and Fig. S3). Except for TORT-3, sample digestion with aqua regia in a drying oven yielded a lower Cr recovery percentage (Fig. 2, Fig. 3, Fig. 4, Fig. 5 and Fig. S3). This extraction method also yielded the lowest mean Cu recovery percentages for the three biological CRMs (Fig. 2, Fig. 3, Fig. 4 and Fig. S4). As observed for Cr, sample digestion with HNO3 in a drying oven or a microwave resulted in higher mean Cu recovery percentages for the three biological CRMs regardless of the sample size (Fig. 2, Fig. 3, Fig. 4 and Fig. S4). On the other hand, there was no significant difference among the digestion methods for the sediment CRM (Fig. 5 and Fig. S4). Considering all extraction methods (Fig. S4), the general range for the Cu recovery percentages was similar for the biological CRMs (74.0 %–97.0 %; Fig. 2, Fig. 3, Fig. 4) and sediment CRM (77.0 %–97.5 %; Fig. 5).

Regarding Fe, sample extraction with HNO3 in a drying oven yielded the highest mean recovery percentages, especially for the smaller sample size (100 mg) of the biological CRMs (Fig. 2, Fig. 3, Fig. 4, Fig. 5 and Fig. S5). When extracting with aqua regia in a drying oven and using a larger sample size (200 mg), the recovery percentages for DOLT-5 (Fig. 3) and TORT-3 (Fig. 4) were similar to those observed using HNO3 in a drying oven (Fig. S5). However, the Fe recovery percentage was increased when 200 mg of DORM-4 was extracted with aqua regia in a drying oven (Fig. 2 and Fig. S5). It is worth noting that the mean Fe recovery percentages were lower when DORM-4 (Fig. 2) and DOLT-5 (Fig. 3) were extracted with HNO3 in a microwave (Fig. S5). Considering all extraction methods together, the general Fe recovery percentages for Fe in biological CRMs (75.3 %–92.1 %) were similar to those observed for the other analyzed metal(loid)s (Fig. 2, Fig. 3, Fig. 4).

In the case of Mn, the general ranges of recovery percentages in the biological CRMs (71.3 %–89.7 %; Fig. 2, Fig. 3, Fig. 4) and the sediment CRM (72.4–89.0 %; Fig. 5) were quite similar (Fig. S6). As observed for most metal(loid)s, extraction of biological and sediment CRMs using aqua regia in a drying oven resulted in lower Mn recovery percentages regardless of the sample size (Fig. 2, Fig. 3, Fig. 4, Fig. 5 and Fig. S6). Moreover, extraction of the sediment CRM with HNO3 and HF in a drying oven resulted in a lower Mn recovery percentage (Fig. 5 and Fig. S6). We noted the best results when using the HNO3 in a drying oven, especially for 100 mg of sample (Fig. 2, Fig. 3, Fig. 4, Fig. 5 and Fig. S6).

For Pb (Fig. S7), the general recovery percentage ranges for each extraction method were similar for the biological CRMs (74.5 %–96.3 %; Fig. 2, Fig. 3, Fig. 4) and the sediment CRM (72.0 %–97.0 %; Fig. 5). For Zn (Fig. S8), the general recovery percentage ranges were similar for the biological CRMs (72.3 %–91.8 %; Fig. 2, Fig. 3, Fig. 4) and the sediment CRM (72.8 %–85.7 %; Fig. 5). For TORT-3 (Fig. 4), there was no significant difference among the sample extraction methods for either Pb or Zn. However, DORM-4 (Fig. 2) and DOLT-5 (Fig. 3) extraction with HNO3 in a drying oven resulted in higher Pb recovery percentages regardless of the sample size (Figs. S7 and S8). Extraction of the sediment CRM (Fig. 5) with HNO3 in a microwave resulted in lower Pb recovery percentages compared with the other sample extraction methods, regardless of the sample size (Fig. S7). For Zn, there were no marked differences among the different extraction methods used for the sediment CRM (Fig. S8).

We tested two methods employing HNO3 with a drying oven or a microwave. The mean recovery percentages were higher when using a drying oven for most of all analyzed metal(loid)s, except for Cr and Cu from the biological and sediment CRMs (Fig. 2, Fig. 3, Fig. 4, Fig. 5) and Pb and Zn from TORT-3 (Fig. 4). These findings can be explained, at least in part, by considering that the metal(loid) concentrations after sample digestion in a microwave may not reflect the total content of these analytes in the sample [13]. Indeed, the microwave-assisted acid extraction method is designed to mimic sample extraction using conventional heating with HNO3 [[13], [14], [15]].

We also assessed the possible influence of two sample sizes (100 and 200 mg) on the metal(loid) extraction efficiency (Fig. 2, Fig. 3, Fig. 4). The sample size did not affect the quantification of most analyzed metal(loid)s (Fig. 2, Fig. 3, Fig. 4, Fig. 5), except for As and Mn in TORT-3 (Fig. 4). There was a higher As recovery percentage when using 200 mg of TORT-3 sample digested in a drying oven. On the other hand, digestion of 200 mg of TORT-3 with HNO3 in a drying oven resulted in a lower Mn recovery percentage (Fig. 4).

Based on our findings, we conclude that the conventional sample extraction method – digestion with HNO3 in a drying oven – is the most reliable method to extract and quantify metal(loid)s using HR-GFAAS in small environmental samples (biota and sediment weighing 100–200 mg). In previous studies, researchers have reported that the efficiency of metal(loid) quantification by AAS depends on the digestion procedure, the element that is analyzed, and the biological matrix. For example, researchers have tested HNO3 alone as well as mixtures of HNO3 with other strong acids (HNO3–HCl, HNO3–perchloric acid [HClO4], HNO3– H2SO4, HNO3–HCl–HClO4, HNO3–HCl–H2SO4, and HNO3–H2SO4– HClO4) in traditional medicinale products [9] and plants [10]. Those studies also used AAS to quantify the same metal(loid)s evaluated in the present study. According to the authors certain acid mixtures could extract Al, As, Cd, Fe, Mg, Mn, Pb, Ni, and Zn more efficiently than HNO3 alone. However, the extraction efficiency was strongly dependent on the element and the biological matrix analyzed. In fact, none of the tested mixtures was the most efficient for all analyzed metal(loid)s and matrices. Conversely, in the present study, we found that digestion with HNO3 alone was the most efficient extraction method for the same metal(loid)s evaluated in those studies. Indeed, the recovery rates were 80–100 % for all metal(loid)s and matrices (sediment and biota) tested, except for Zn in TORT-3. In the present study, the only acid mixtures we tested were aqua regia for biological CRMs and HNO3 and HF (3:1 [v/v]) for the sediment CRM. However, neither mixture showed better extraction efficiency for all metal(loid)s and matrices tested, as observed for the digestion with HNO3 alone. Finally, it is worth noting that extraction with HNO3 uses less toxic and dangerous reagents, making it safer to perform and more environmentally friendly than the other extraction methods involving mixtures of strong acids. Moreover, this conventional method requires simple equipment that is commonly found in research facilities, making it relatively easy to perform.

In conclusion, our data demonstrated that the conventional method of sample digestion using HNO3 alone can be applied reliably for small size environmental samples. This is especially advantageous in the scope of long-term research programs focused on evaluating and monitoring the impacts of environmental disasters of large intensity and extension. In this case, collecting samples from a diverse array of environments, matrices, and organisms from different trophic levels with great frequency is often necessary.

Limitations

None.

Ethics statements

No ethical considerations were required.

CRediT authorship contribution statement

Patrícia Gomes Costa: Conceptualization, Methodology, Investigation, Formal analysis, Resources, Data curation, Validation, Visualization. Juliana Lemos Dal Pizzol: Investigation, Resources, Data curation, Visualization. Yuri Dornelles Zebral: Formal analysis, Validation, Writing – original draft. Adalto Bianchini: Conceptualization, Methodology, Resources, Validation, Writing – review & editing, Supervision, Project administration, Funding acquisition.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix Supplementary materials

Image, application 1

Data availability

Data will be made available on request.

Acknowledgments

This work was supported by the “Fundo Brasileiro para a Biodiversidade - Funbio” (Brasília, DF, Brazil; grant number 105/2016 ), “Fundação Renova” (Belo Horizonte, MG, Brazil; grant number 809/2018 ) and “Fundação Espírito-santense de Tecnologia – Fest” (Vitória, ES, Brazil; grant number 01/2018 ). A. Bianchini is a research fellow of the Brazilian “Conselho Nacional de Desenvolvimento Científico e Tecnológico – CNPq” (Brasília, DF, Brazil; grant number 311410/2021-9 ).

Related research article: P.G. Costa, L.C. Marube, V. Artifon, A.L. Escarrone, J.C. Hernandes, Y.D. Zebral, A. Bianchini, Temporal and spatial variations in metals and arsenic contamination in water, sediment and biota of freshwater, marine and coastal environments after the Fundão dam failure, Sci. Total Environ. 806 (2022) 151340, doi:10.1016/j.scitotenv.2021.151340.

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.mex.2024.102896.
==== Refs
References

1 Draghici C. Jelescu C. Dima C. Coman G. Chirila E. Heavy metals determination in environmental and biological samples Simeonov L. Kochubovski M. Simeonova B. Environmental Heavy Metal Pollution and Effects on Child Mental Development, NATO Science for Peace and Security Series C: Environmental Security 1 2011 Springer Dordrecht 145 158 10.1007/978-94-007-0253-0_9
2 Soylak M. Aydin A. Determination of some heavy metals in food and environmental samples by flame atomic absorption spectrometry after coprecipitation Food Chem. Toxicol. 49 2011 1242 1248 10.1016/j.fct.2011.03.002 21419188
3 Davidson C.M. Methods for the determination of heavy metals and metalloids in soils Alloway B.J. Heavy Metals in Soils: Trace Metals and Metalloids in Soils and their Bioavailability 3rd ed. 2013 Springer New York 97 140 10.1007/978-94-007-4470-7_4
4 Lima E. Sobrinho N. Pérez D. Coutinho I. Comparing methods for extracting heavy metals from histosols for establishing quality reference values Rev. Bras. Cienc Solo 40 2016 e0150097 10.1590/18069657rbcs20150097
5 Methods for the Determination of Metals in Environmental Samples, Supplement 1 2013 U.S. EPA Bibliogov, U.S. EPA, Washington, D.C.
6 Arjomandi M. Shirkhanloo H. A review: analytical methods for heavy metals determination in environment and human samples Anal. Methods Environ. Chem. J. 2 2019 97 126 10.24200/amecj.v2.i03.73
7 Madjar R.M. Mot A. Vasile Scăețeanu G. Mihalache M. Methods used for heavy metal determination in agricultural inputs Res. J. Agric. Sci. 52 2020 148 158
8 APHA Standard Methods for the Examination of Water and Wastewater 24th ed. 2022 American Public Health Association Washington, D.C
9 Uddin A.H. Khalid R.S. Alaama M. Abdualkader A.M. Kasmuri A. Abbas S.A. Comparative study of three digestion methods for elemental analysis in traditional medicine products using atomic absorption spectrometry J. Anal. Sci. Technol. 7 2016 6 10.1186/s40543-016-0085-6
10 Bankaji I. Kouki R. Dridi N. Ferreira R. Hidouri S. Duarte B. Sleimi N. Caçador I. Comparison of digestion methods using atomic absorption spectrometry for the determination of metal levels in plants Separations 10 2023 40 10.3390/separations10010040
11 Costa P.G. Marube L.C. Artifon V. Escarrone A.L. Hernandes J.C. Zebral Y.D. Bianchini A. Temporal and spatial variations in metals and arsenic contamination in water, sediment and biota of freshwater, marine and coastal environments after the Fundão dam failure Sci. Total Environ. 806 2022 151340 10.1016/j.scitotenv.2021.151340
12 Franco T. Zorzal-Almeida S. Sá F. Bianchini A. Dergam J.A. Eskinazi-Sant'Anna E.M. Albino J. Vieira L.S. Santos L.G.M. Ribeiro A.P.L. Bastos A.C. Ex-post impact assessment on a large environmental disaster Environ. Chall. 15 2024 100889 10.1016/j.envc.2024.100889
13 Method 3051A (SW-846): Microwave Assisted Acid Digestion of Sediments, Sludges, and Oils, Revision 1 2007 U.S. EPA U.S. EPA, Washington, D.C.
14 Method 3050A: Acid Digestion of Sediments, Sludges, and Soils, Revision 1 1992 U.S. EPA Washington, D.C.
15 Method 3050B: Acid Digestion of Sediments, Sludges, and Soils, Revision 2 1996 U.S. EPA Washington, D.C.
