The speciation of arsenic in biological tissues and the certification of reference materials for quality control

Trends in Analytical Chemistry, Vol. 22, No. 4, 2003

Trends

The speciation of arsenic in biological tissues and the certification of reference materials for quality control Shona McSheehy, Joanna Szpunar, Roberto Morabito, Philippe Quevauviller

Shona McSheehy*,1 University of Pau, LCABIE, He´lioparc, 2 av. Pr. Angot, 64053 Pau, France Joanna Szpunar Group of Bio-Inorganic Analytical Chemistry, CNRS UMR 5034, He´lioparc, 2 av. Pr. Angot, 64053 Pau, France Roberto Morabito ENEA-PROT, Via Anguillarese 301, IT-00060, S. Maria de Galeria, Italy Philippe Quevauviller EC DG Environment, European Commission, Rue de la Loi 200, B-1049 Brussels, Belgium

1

Present address: Institute for National Measurement Standards, National Research Council of Canada, Ottawa, Ontario, Canada K1A 0R9 *Corresponding author. Tel.: +1 (613) 998 9849; Fax: +1 (613) 993 2451; E-mail: shona.mcsheehy@ nrc.ca

Arsenic is an ubiquitous element. Its toxicity, environmental mobility and accumulation in living organisms usually depend on the form in which the element is present. Information on the chemical forms is important for understanding the role of the element present as well as revealing its environmental cycle. This requirement stimulates the need for information on the speciation of arsenic and the development of suitable analytical methodology. It is well known that seafood can contain considerable quantities of naturally-acquired arsenic and developments in speciation have focused on seafood samples. It seems that the major arsenic species in fish, crustaceans and molluscs have the tetraalkylarsonium structure (R4As+) and the species in marine algae and bivalves have the trialkylarsine oxide structure (R3AsO). However, the concentrations are still low enough to require a sensitive analytical method based on the isolation, identification and quantification of the individual arsenic-containing species. This review will discuss the accepted techniques for the speciation of arsenic in biological tissues and the need for quality assurance of speciation analyses. Quality control will be discussed, focusing on the use of certified reference materials. As well as validation of methods, reference-material certification involves the participation of several laboratories, enabling the evaluation of state-of-the-art analytical techniques. The certification process of a candidate oyster-tissue reference material for different chemical species of elements (including arsenic species) is discussed. # 2003 Published by Elsevier Science B.V. Keywords: Analytical methods; Arsenic speciation; Biological tissues; Certified reference material; Oyster tissue; Quality control Abbreviations: AAS, Atomic absorption spectrometry; AE, Anion exchange; AES, Atomic emission spectrometry; AFS, Atomic fluorescence spectrometry; APCI, Atmospheric pressure chemical ionisation; API, Atmospheric pressure ionisation; CE, Cation exchange; CZE, Capillary zone electrophoresis; EI, Electron impact; ES, Electrospray; FAB, Fast atom bombardment; FD, Field desorption; FT, Fourier transform; GC, Gas chromatography; HG, Hydride generation; HPLC, High-performance liquid chromatography; ICP, Inductively coupled plasma; IS, Ionspray; LC, Liquid chromatography; MS, Mass spectrometry; NMR, Nuclear magnetic resonance; Q, Quadrupole; RP, Reversed phase; SE, Size exclusion; ToF, Time of flight

0165-9936/03/$ - see front matter # 2003 Published by Elsevier Science B.V. doi:10.1016/S0165-9936(03)00404-7

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1. Introduction Arsenic has the notoriety of being a toxic element but it is also widely established that its toxicity is critically dependent on the chemical form in which it is found [1]. There is concern over the level of toxic species in the environment and their exposure to living organisms. Sources of food and water are of particular interest because of the potential accumulation and the risk from human consumption. The majority of arsenic speciation studies have targeted both plants and fauna of marine origin, as they are known to accumulate arsenic to relatively high levels compared to other food sources. Fish and shell¢sh are known to contribute to the majority of ingested arsenic (75%) although it generally only constitutes a small percentage (2%) of the daily dietary intake [2]. However, in some countries, such as Japan, China and Korea, food from marine sources constitute an important part of the diet and a number of studies have been undertaken to determine the chemical form of arsenic in the organisms that contribute to the human diet. Arsenobetaine (AsB, trimethylarsonioacetate) is the most abundant arsenic species in marine fauna, whereas macro-algae contain a class of dimethylarsinoyl ribosides, known under the trivial name of arsenosugars [3]. Until recently, the development of analytical methodology for the determination of AsB and arsenosugars in edible resources might have seemed academic, since this class of compounds is generally believed to be innocuous to humans. Humans are able to convert arsenosugars to dimethyl arsinic acid (DMA) [4], while some recent studies indicate that DMA has the potential to be a human carcinogen [5]. As well as evaluations regarding risk to human health, the speciation of arsenic can also answer questions on the metabolic processes, which have been developed by marine organisms. The metabolic biotransformations of arsenic in marine life are known to lead to a wide range of organoarsenic compounds. The identi¢cation of these organoarsenicals can lead to the elucidation of metabolic and detoxi¢cation pathways, which can shed light on the way that living creatures are able to deal with this toxic element. Arsenic speciation could also help in the introduction of regulations for arsenic species in foodstu¡s and for environmental control. The increased concern for the speciation of elements has led to the development of new analytical techniques for their analysis. Careful selection of analytical techniques, development and optimisation of a suitable protocol are needed for each matrix speciated. The metabolism of arsenic in natural tissues has created a large number of endogenous species, some of which are still likely to remain unidenti¢ed. Therefore, a priority of the technique under development is that it allows for

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the identi¢cation of unknown species in a sample as well as quanti¢cation. The methods available for the speciation of natural tissues are generally a combination of separation techniques (high-performance liquid chromatography (HPLC) and capillary zone electrophoresis (CZE)) and modes of detection, which are speci¢c and o¡er high sensitivity - notably mass spectrometry (MS). Atomic MS allows low limits of detection speci¢c to elements (e.g. inductively coupled plasma (ICP)-MS) and molecular MS, often in tandem mode, allows for the characterization and identi¢cation of molecular species (electrospray (ES)-MS/MS). The techniques employed for the determination of elements in a biological sample should be accurate, precise and have limits of detection (LODs) su⁄ciently low for the study of trace species with a naturally low concentration. In addition, it is important that the analytical process does not in any way degrade the naturally-occurring analyte in the matrix. All this requires implementation of a controlled procedure that maintains the species in its original form. The series of steps involved in the analytical process (extraction, separation, and detection) are all liable to sources of error, which could distort the result from that of the real value. Sources of error should be kept under control; possible with quality-control (QC) procedures. The need to assure quality in modern analysis justi¢es interlaboratory studies, which also serve to develop and promote new analytical techniques. Comparison of techniques within a laboratory, with another laboratory and with the use of certi¢ed reference materials (CRMs) allows validation and control of newly developed analytical techniques and analytical protocols already in place. A CRM can allow for the validation of analytical quality by the accuracy and the precision of the measurement. The certi¢cation of speci¢c values allows the user to link his result with those of internationally-recognised standards [6]. International collaboration in a de¢ned ¢eld of speciation can improve analytical techniques. Unsatis¢ed with exchange of information via literature or conferences, many analysts exchange standards and samples to compare the techniques. Interlaboratory projects allow for the structuring of this approach in a manner where a candidate reference material can be certi¢ed [6].

2. Arsenic and organoarsenicals Arsenic is the 20th most abundant element in our environment and exists as one stable, natural isotope, 75 As. It is naturally present in the environment, usually as a component of inorganic compounds. For example, the terrestrial crust contains 3 mg/kg arsenic usually in the form of arsenopyrite (FeAsS) [7]. Volcanoes and

Trends in Analytical Chemistry, Vol. 22, No. 4, 2003 groundwater are other natural sources of arsenic. Anthropogenic sources include non-ferrous smelters, burning of carbon, pesticides; the major current use is as a wood preservative [1]. Soils contain 0.05^0.2 mg/kg, but marine sediments can accumulate up to 40 mg/kg [8]. In seas and oceans, arsenic is present at a uniform concentration of 2mg/kg, usually as inorganic arsenic with low concentrations of monomethylarsonic acid (MMA) and DMA [9,10]. Marine organisms can contain hundreds of mg/kg of arsenic [8,11], accumulated from their surrounding water, sediments and food sources, especially in organisms which feed on the ocean £oor [8]. Arsenic falls into the category of elements with no physiological function, but its toxicity depends greatly on the species. In general, trivalent forms (reduced forms) are more toxic than pentavalent forms, and inorganic forms are more toxic than organic forms [11]. Indeed, for the inorganic form AsIII, the MLD50 (Maximum Lethal Dose: the dose that is fatal for half a population of experimental animals) is 14 mg/kg, whereas, for AsB, it is over 10 g/kg [12]. Based on evidence from studies concerning the inhalation or ingestion of arsenic, it has been classed as a human carcinogen [1]. However, it has previously been employed as a medicament (such as Fowler’s solution) and for centuries has been ingested, in the form of arsenic oxide, by Styrians because of its bene¢cial e¡ects and for ‘health reasons’ [13]. A provisional tolerable daily intake of inorganic arsenic via ingestion has been recommended at 2mg/kg body weight [14]. Because of the importance of the speci¢c form in which the arsenic is found, a large number of species have been characterized over the past few decades (Table 1). Inorganic forms can be found in small quantities in living organisms, but it is generally organoarsenic species that dominate. The presence of organoarsenicals in marine life has been speculated upon since the beginning of the century, but it was not until 1977 that this hypothesis was con¢rmed with the identi¢cation of AsB in a western rock lobster [15]. Since then, a large number of organoarsenic species have been identi¢ed in marine tissues. AsB is the major species in ¢sh and seafood, but they can also contain minor concentrations of inorganic arsenic, methylated compounds, arsenocholine (AsC +) or arsenosugars. However, marine organisms are known for their rich metabolism and presumably there are more organoarsenicals yet to be characterized. Although the focus has been directed at marine life, terrestrial tissues also contain arsenic, albeit to a lesser extent. More recent investigations into the presence of organoarsenicals in terrestrial samples have targeted food sources and fungi, where inorganic arsenic, methylated species and AsB have been found. A comprehensive list of species found in biological tissues by speciation techniques is presented in Table 2.

Trends 3. Analytical techniques for the speciation 3.1. Sampling and sample pre-treatment The ¢rst step in any analytical process is the sampling of the tissue to be analysed. Often, this is pre-empted by exposure or pollution and organisms are pre-selected, but there are many sampling strategies [16]. Factors, such as geographical situation, ecology (with respect to a speci¢c population of organisms or the ecosystem) and seasonal time periods, need to be taken into consideration when evaluating the representativeness of the sample. The sampling itself needs to be planned, designed for the speci¢c sample, documented and controlled to assure quality e¡ectively [16]. For a biological sample where bacteria will exist naturally, it is important to store tissue at low temperatures to prevent biological activity that could modify the nature of the sample. Another method of preservation, which also serves to concentrate the sample and improve sample handling, is removal of water by freezedrying. Careful mass measurement before and after freeze-drying will allow the percentage of moisture in the sample to be calculated. Once freeze-dried, the sample is dry and can be homogenised by grinding. A homogeneous sample is important to minimise variations in quanti¢cation that create uncertainty with respect to the real value [17]. The extraction of biological tissues has developed over the past decade with focus directed towards increased e⁄ciency with lower solvent volumes and reduced extraction times. In solid tissues, the analyte is often di⁄cult to extract; it is necessary to optimise the procedure for each matrix investigated. Tissues with high fat content, in particular some shell¢sh, may need to be defatted with a solvent, such as ether or acetone [18,19] before the extraction of arsenic. Most of the arsenic in biological tissues is in a water-soluble form, and, in general, can be extracted with water alone [20^22] or more commonly a mixture of water:methanol [23^30]. Other reagents, such as orthophosphoric acid [22] and tri£uoroacetic acid have also been used [31] to improve extraction e⁄ciency. Enzymatic extraction has been attempted with apples [32], ¢sh-based baby food [33] and ¢sh [34]. The enzymatic extraction of the ¢sh tissue was compared to a chloroform/methanol/water extraction and di¡erences between the arsenic species concentrations could indicate some speci¢city towards certain species when using di¡erent extraction solvents [34]. Extraction e⁄ciency also depends on the tissue extracted. In general, ¢sh tissues can give 90^100% extraction [18,19,22,35,36], whereas more complex matrices give a lower percentage. Shibata et al. found that a water:methanol extraction allowed 85^100% of the arsenic to be extracted in samples of oyster and red and brown algae [37,38]. However, the extraction was http://www.elsevier.com/locate/trac

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Table 1. List of arsenic species characterised from biological tissues No.

NAME (IUPAC or common)

Formula

Mr

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Arsenous acid (arsenite) Arsenic acid (arsenate) Monomethylarsenic acid Dimethylarsenic acid Trimethylarsenic oxide Tetramethylarsonium ion Arsenobetaine Trimethyl (2-carboxyethyl) arsonium inner salt Arsenocholine Dimethyloxarsylethanol Dimethylarsinylacetic acid N-[4-(dimethyl-arsinoyl) butanoyl] taurine 5-dimethylarsionyl 2,3,4-trihydroxy pentanoic acid 5-dimethyl arsionyl 2,3-dihydroxy pentanoic acid 4-dimethylarsinoyl-2,3-dihydroxy butanoic acid

OH-As(OH)2 O=As(OH)3 CH3AsO(OH)2 (CH3)2AsO(OH) (CH3)3AsO (CH3)4As+ (CH3)3As-CH2-COOH (CH3)3As-CH2-CH2-COOH (CH3)3As-CH2-CH2-OH (CH3)2AsO-CH2-CH2-OH (CH3)2AsO-CH2-CH2-COOH (CH3)2AsO(CH2)3CONH(CH2)2SO3H (CH3)2AsOCH2(CHOH)3COOH (CH3)2AsO(CH2)2(CHOH)2COOH (CH3)2AsOCH2(CHOH)2COOH

127 141 140 138 136 135 179 193 165 166 180 315 270 254 240

R= H OH OCH2CHOHCH2SO3H

238 254 392

OCH2CHOHCH2OH

328

OCH2CHOHCH2OSO3H

408

OCH2CHOHCH2OPO4CH2CHOHCH2OH

482

OCH2CHNH2CH2SO3H

391

OCH3 OCH2COOH

268 312 418 355 342

Dimethyl arsenoyl ribosides (Arseno-sugars):

16 17 18 19 20 21 22 23 24 25 26 27 28

5-dimethylarsinoyl-b-ribofuranose 5-dimethylarsinoyl-b-ribofuranosol A: 3-[50 -deoxy-50 -(dimethylarsinoyl)-b-ribofuranosyloxy]-2-hydroxypropane sulphonic acid B: 3-[50 -deoxy-50 -(dimethylarsinoyl)-b-ribofuranosyloxy]-2-hydroxypropylene glycol C: 3-[50 -deoxy-50 -(dimethylarsinoyl)-b-ribofuranosyloxy]-2-hydroxypropyl hydrogen sulfate D: 3-[50 -deoxy-50 -(dimethylarsinoyl)-b-ribofuranosyloxy]-2-hydroxypropyl 2, 3 hydroxypropyl phosphate E: 2-amino-3-[50 -deoxy50 -dimethylarsinoyl)-ribosyloxy] propane-1-sulphonic acid Methyl 5-deoxy-5-(dimethylarsinoyl)-b-D-ribose 3-[50 -deoxy-50 -(dimethylarsinoyl)-b-ribofuranosyloxy]-2-acetic acid 1-O-[50 -deoxy-50 -(dimethylarsinoyl)-b-D-ribosyl] mannitol N-[50 -deoxy-50 -dimethylarsinoyl-b-ribosyloxycarbonyl] glycine 3-[50 -deoxy-50 -(dimethylarsinoyl)-b-ribofuranosyloxy]-2-hydroxypropanoic acid Dimethylarsinyladenosine

OCONHCH2COOH OCH2CHOHCOOH

374

Trialkyl arsenio ribosides:

R= CH3 CH2CHCOOHCH2OCH2CHOHCH2OH

29 30

391 554

Trimethyl arsenio phosphate containing chains:

31 32

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Glyceryl phosphorylarsenocholine Phospatidylarsenocholine

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R= H CO(CH2)nMe

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Tissue

Extraction

Algae (brown)—phaeophyta (laminariales) Alaria marginata (ribbon kelp) Alaria marginata (ribbon kelp)

MeOH/H20, ASE (200 C, 1m static at 500psi) CE (ION 120)- AE (Hamilton PRP x-100) Prep. AE (Hamilton PRP x-100) MeOH/H20, shaking (1.5h)

Kelp powder Kelp powder

MeOH/H20, sonication (20m3) MeOH/H20, shaking (12h)

IP RP (Discovery C18 narrow-bore) CE cartridge (Hypersep SCX)

Ecklonia radiata

MeOH

Eisenia bicyclis (arame) Laminaria digitata Laminaria

MeOH/H20, sonication (10m5) H20, sonication probe MeOH/H20, sonication (3h2+20m3)

Laminaria japonica

MeOH/H20, sonication (15m)

Prep. SE (Sephadex LH-20) - AE (Sephadex DEAE) - HPLC and prep. TLC IP RP C18 (Inertsil ODS and Inertsil ODS-2) AE (Hamilton PRP x-100) Prep. SE (Sephadex G-15) -Prep. AE (DEAE) -IP RP (C18 Inertsil ODS-2) AE (Hamilton PRP x-100), CE (Ionpac Cs10)

Algae (brown)—phaeophyta (fucales) Fucus gardneri Fucus gardneri Fucus serratus Fucus serratus

MeOH/H20, sonication (10m5) MeOH/H20, sonication (10m5) MeOH (4h2) H20, sonication probe (1m2)

Fucus serratus Fucus vesiculosis Hizikia fusiforme Hizikia fusiforme Hizikia fusiforme http://www.elsevier.com/locate/trac

Sargassum lacerifolium Sargassum lacerifolium Sargassum lacerifolium Sargassum muticum Sargassum muticum

Separation

Detection

Species Identified

Ref.

On-line ES MS On-line ES MS/(MS) ICP MS ICP MS ES QTOF MS/(MS) ES FT MS/(MS)

18, 19, 21 18, 19, 21

[30] [23]

4, 18, 19, 20, 21 19

[28] [29]

1

18, 19, 21 4, 18, 19, 21 18, 21 2, 4, 18, 19, 20, 21

[102, 103] [24] [20] [47]

2, 18, 19, 21

[62]

18, 19, 20 4, 18, 19, 20 2, 4, 18, 19, 20, 21 1, 2, 3, 4, 18, 19, 20, 21 18, 19, 20, 21 18, 20, 21 2, 18, 19, 20, 21

[25] [48] [60] [39]

2, 18, 20, 21

[68]

2, 4, 18, 19, 20, 21

[22]

2, 4, 18, 19, 20, 21, 22, 23 20 30 as a pair of isomers 2, 4, 18, 19, 20, 21

[105]

[43]

20

[23]

H NMR

13

C NMR IR

ICP MS On-line ES MS Off-line ES MS/(MS) ICP MS On-line ES MS/(MS) ICP MS

IP RP (C18 Inertsil ODS-2) ICP MS IP RP (C18 Inertsil ODS-2) ICP MS AE (Hamilton PRP x-100) On-line ES MS ICP MS AE (Hamilton PRP x-100) and CE (Zorbax 300 ICP MS On-line ES MS SCX) MeOH (4h2) RP (C8 Eclipse XDB), AE (Hamilton PRP x-100) On-line ES IT MSn AE (Hamilton PRP x-100) On-line ES MS H20, sonication probe 1 H NMR 13C NMR MeOH Prep. SE (Sephadex LH-20 or G-15) - AE (Sephadex DEAE) -prep. TLC MeOH/H2O, sonication (3h2+20m3) Prep. SE (Sephadex G-15) - Prep. AE (DEAE) AE Off-line ES MS/(MS) (Hamilton PRP -100), CE (Supelcosil SCX), RP ICP MS (Inertsil ODS-2), SE (Superdex peptide) ICP MS Orthophosphoric acid, MeOH/H2O or H2O, AE (Hamilton PRP x-100) and CE (Supelcosil rotation (14h) SCX) MeOH Prep SE (Sephadex G-15) - AE (Sephadex DEAE) - 1H NMR 13C NMR TLC (cellulose) MeOH SE - AE (DEAE) - SE (G15) Off-line FAB MS/(MS) Aqueous extract Inertsil ODS-2; Sephadex LH-20 ICP MS 1H NMR 13C NMR MeOH/H2O, ASE (1m) AE (Hamilton PRP x-100) ICP MS Off-line ES MS/(MS) MeOH/H2O, shaking (1.5h) Prep. AE (Hamilton PRP x-100) On-line ES MS/(MS) ICP MS

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Table 2. Arsenic species identified in biological samples and the analytical procedure employed. (The major species found is highlighted in bold)

[46] [20] [104]

[88,89] [49]

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196 Table 2 (continued) http://www.elsevier.com/locate/trac

Extraction

Separation

Detection

Species Identified

Ref.

Sargassum thunbergii

MeOH

Prep. SE (Sephadex LH-20) - Prep. AE (DEAE Sephadex a-25) - SEC (Sephadex G-15)- AE (DEAE Toyopearl 650M) - SEC (Sephadex G-10)

2-D 1H NMR (COSY)

29

[71]

Algae—rhodophyta Porphyra crispata

MeOH/H2O, sonication (15m)

AE (Hamilton PRP x-100), CE (Ionpac Cs10)

2, 18, 19, 21

[62]

MeOH/H2O, sonication (10m5)

IP RP (Inertsil ODS)

On-line ES MS/(MS) ICP MS ICP MS 1H NMR

1, 2, 4, 19, 21

[37]

MeOH/H2O, (3)

IP RP (Inertsil ODS)

ICP MS

19, 20, 21

[50]

AE (Hamilton PRP x-100)

On-line ES MS/(MS) ICP MS

17

[23]

MeOH/H2O, sonication (10m5) MeOH/H2O, sonication (10m5)

IP RP (Inertsil ODS), SE (Asahipak GS220) IP RP (Inertsil ODS), SE (Asahipak GS220) CE (Chrompak Ionspher C)

6, 7, 19, 21 19, 21 19

[38] [38] [55]

Mussel (hydrothermal vent) Mussel Mussel (digestive gland) Mytilus coruscum Oyster (CRM :NIST 1566a)

CHCl3/ MeOH/H2O MeOH/H2O, m-wave (2-8m) MeOH/H2O, sonication (10m5)

AE (ION-120) and CE (Ionspher C) AE (Hamilton PRP x-100) IP RP (Inertsil ODS), SE (Asahipak GS220) CE (Chrompak Ionspher C)

1, 2, 6, 4,

[65] [41] [38] [55]

Oyster (CRM :NIST 1566a) Oyster Oyster (candidate CRM)

MeOH/H2O, sonication (10m5) MeOH/H2O, sonication (20m) MeOH/H2O, sonication (1h2)

Tridacna maxima (kidney)

MeOH

C18 RP (Inertsil ODS and Inertsil ODS-2) AE (Hamilton PRP x-100) Prep SE (Sephadex G-15)- Prep. AE (DEAE)CE (Supelcosil SCX) Prep AE (Sephadex DEAE)

ICP MS ICP MS On-line (split) IS MS/(MS) ICP MS ICP MS ICP MS On-line (split) IS MS/(MS) ICP MS HG-AFS HG-ICP MS Off-line ES MS/(MS) ICP MS 1 H NMR 13C NMR

Tridacna derasa (kidney)

H2O, sonication

Tridacna derasa (kidney)

MeOH/H20, sonication (2h2+20m)

Marine Crustaceans Zooplankton Copepoda (tiny crustacean) Crab (Alaskan king crab) Crab Krill (Antartic) Euphausia superba Lobster pancreas (CRM : NRC TORT-1) Scallop (gonads) Shrimp Shrimp (hydrothermal vent) Marine Fish Cod

Porphyra tenera Algae—diatom Skeletonema costatum Algae—miscellaneous Arsenosugar degradation in simulated gastric juice Marine Bivalves Clam Meretrix lusoria Corbicula japonica (bivalve) Mussel

2, 4, 7, 18, 19 3, 4, 7 7, 19, 21 7, 19

4, 7, 19, 21 [24] 1, 2, 4, 7 [64] 4, 6, 7, 8, 9, 16, 19, 21 [27] 12, 18, 19, 20, 26, 27, 28, S29 13

[106]

SE (Sepkadex G-15)- AE (Hamilton PRP x-100) and CE (Chrompak Ionspher C) Prep. SE (Sephadex G-15) - Prep. AE (DEAE) AE (Hamilton PRP x-100), CE (Supelcosil SCX)

On-line ES MS Off-line ES Q-TOF MS/(MS) ICP MS

4, 7, 11, 13, 14, 15, 16, [69] 17, 18, 19, 20, 21, 24, 26, 27

MeOH/H2O, (3) MeOH, (24h) CHCl3/ MeOH/H2O, sonication (330m) MeOH MeOH/H2O, sonication (20m) MeOH/H2O, sonication (10m5) CHCl3/MeOH/H2O, sonication (330m) CHCl3/MeOH/H2O

IP RP (Inertsil ODS) RP (Hamilton PRP 1) CE (Ionospher C), AE (ION 120) SE (GS220 or GS220 HQ), RP (ODS) AE (Hamilton PRP x-100) C18 RP (Inertsil ODS-2) CE (Ionspher C), AE (ION 120) AE (ION-120) and CE (Ionspher C)

ICP MS ICP AES ICP MS ICP MS HG-AFS HG-ICP MS ICP MS ICP MS ICP MS

7, 3, 1, 4, 2, 4, 1, 1,

MeOH, m-wave (6m)

AE (Hamilton PRP x-100)

HG-AAS

2, 7, 9

18, 20 4, 7, 9 2, 3, 5, 6, 7, 9 7, 18, 19, 21 4, 7 7, 18, 19, 20, 21 2, 3, 5, 6, 7, 9 2, 4, 7

[21]

[50] [107] [56] [108] [64] [51] [56] [65] [36]

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Tissue

Tissue

Extraction

Abudefduf vaigiensis (coral reef fish tissue) Dogfish muscle (CRM : DORM-1)

Aqueous extract CH3COCH3 (3) then MeOH/H20, sonication (30m2)

Dogfish muscle (CRM : DORM-2) Dogfish muscle (CRM : DORM-2) Dogfish muscle (CRM : DORM-2) Mackrel Plaice Salmon

TLC - CE (Chrompak Ionspher C) 3-D LC, 4x, Prep C18 RP (Waters) - CE (Dowex 50W-x8) - CE (Amberlite IRC-50) C18 RP (Pierce) AE (Supelcosil SAX), CE (Supelcosil SCX) MeOH/H2O, shaking (14h) SPME-AE (Supelcosil SAX) MeOH/H2O, sonication (30m4) Orthophosphoric acid, MeOH/H2O or H2O, CE (Supelcosil SCX) rotation (14h+wash3) CHCl3/MeOH/H2O, sonication (1h2) Enzymatic digest (Trypsin, 4h)

CH3COCH3, then MeOH/H2O, ASE (35m) or sonication (10m) MeOH, m-wave (6m)

Sole Marine mammals Dugong liver Dugong dugong MeOH/H2O Porpoise (Dalls porpoise liver) Phocoenoides MeOH/H2O dalli Seal (ringed seal) Phoca hispida MeOH/H2O, shaken (20h+wash3) Seal (ringed seal liver) Phoca hispida Seal (harp seal liver) Phoca groenlandica Whale (short-fined pilot whale liver) Globicephala macrorhynchusfive

Separation

MeOH/H20 MeOH/H20 MeOH/H20

Marine Reptilia Turtle (green turtle liver) Chelonia mydas MeOH/H2O Turtle (loggerhead turtle liver) Caretta caretta MeOH/H2O

Detection

Species Identified

Ref.

On-line ES MS Off-line EI MS ICP MS

7, 8 4, 7, 9

[109] [18]

ICP MS On-line ES MS ICP MS

4, 6, 7, 9 7 4, 6, 7, 8, 9

[35] [63] [22] [34]

CE (Chrompak Ionspher C) AE (Hamilton PRP x-100)

AE (Benson SAX) 2, 4,7 ICP MS On-line (split) IS MS/(MS) 5, 6, 7, 9 ICP MS 2, 4, 7

AE (Hamilton PRP x-100)

HG-AAS

7, 9

[36]

AE (Hamilton PRP x-100), CE (Supelcosil SCX) AE (Hamilton PRP x-100), CE (Supelcosil SCX)

ICP MS ICP MS

3, 4, 7 3, 4, 7, 9

[54] [54]

AE (Hamilton PRP SCX) AE (Hamilton PRP AE (Hamilton PRP AE (Hamilton PRP

x-100) and CE (Supelcosil

ICP MS

3, 4, 6, 7, 9

[53]

x-100), CE (Supelcosil SCX) x-100), CE (Supelcosil SCX) x-100), CE (Supelcosil SCX)

ICP MS ICP MS ICP MS

3, 4, 7, 9 3, 4, 6, 7, 9 3, 4, 7, 9

[54] [54] [54]

AE (Hamilton PRP x-100), CE (Supelcosil SCX) AE (Hamilton PRP x-100), CE (Supelcosil SCX)

ICP MS ICP MS

3, 4, 7, 9 4, 7, 9

[54] [54]

[55] [19]

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CHCl3/MeOH/H20 CHCl3/MeOH

CE (Supelcosil SCX) 2-D CE (Dowex 50W-x8)- CE (Dowex 50W-x2) - TLC (cellulose)

ICP MS FAB MS

6, 7, 9 1, 2, 3, 4, 7, 9

[52] [70]

Terrestrial tissues Freshwater algae Nostoc sp. Ants Formica sp. Carrots Mushroom Amanita muscaria

MeOH/H2O, sonication (10m5) MeOH/H2O, shaking (14h+wash3) MeOH/H20/solvent, ASE MeOH/H2O, shaking (14h+wash3)

ICP MS ICP MS ICP MS ICP MS

4, 19 1, 2, 3, 4, 5, 7 1, 2, 3 1, 2, 4, 6, 7, 9

[24] [58] [42] [57]

Mushroom Calvatia exipuliformis Mushroom Collybia butyracea Rice, rice flour (CRM:1568a)

MeOH/H2O or H2O, shaking (12h) MeOH/H2O, shaking (14h+wash3) TFA, 100 C (6h), ASE investigated

IP RP (C18 Inertsil ODS and Inertsil ODS-2) AE (Supelcosil SAX), CE (Supelcosil SCX) AE (Waters IC-Pak Anion HR) AE (Supelcosil SAX), CE (Supelcosil SCX), RP (Hamilton PRP1) AE (Supelcosil SAX), CE (Supelcosil SCX) AE (Supelcosil SAX), RP (Hamilton PRP1) AE (Waters IC-Pak Anion HR, Dionex AS7 and AG7, Hamilton PRP x-100) AE (Hamilton PRP x-100) and CE (Supelcosil SCX)

ICP MS ICP MS ICP MS

1, 2, 4, 7 4, 7 1, 2, 4 (Rice flour also contains 3) 3, 4, 6, 18

[59] [66] [31]

Sheep urine after seaweed ingestion

ICP MS

[67]

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Marine fauna—miscellaneous Jellyfish Aurelia aurita Microorganisms (from marine sediment)

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Table 2 (continued)

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a little less successful for mussels, and only 34% arsenic could be extracted from a blue-green algae [24]. In a few cases, quantitative extraction can be achieved but a complete extraction of arsenic from seaweeds or fatty seafood can sometimes be di⁄cult. Extractions are aided by techniques, such as shaking, heating or soni¢cation. The latter is the most popular as the dispersion of tissue is thought to be maximised. The extraction is maximised in ultrasonic baths or with sonoprobes [20,39]. Some more modern extraction techniques include microwave-assisted extraction and accelerated solvent extraction (ASE). Low-power microwaves, employed to decrease extraction times while maintaining e⁄ciency, have been applied to oysters [40], mussels [41] and ¢sh tissues [36], allowing 97%, 85% and 95% extraction e⁄ciency, respectively. ASE employs heat and pressure, often as part of an automated system and has also been used for the extraction of arsenic species from carrots [42], rice [31], seaweed [30,43] and ¢sh tissues [19,44]. The extract itself may need further treatment prior to separation. As well as the analytes of interest, a good deal of matrix is often extracted. As this can cause interference, it may be good practice to remove the matrix from the extract and this can be achieved with cartridges. Solid particles, which could damage chromatographic columns, should also be removed by ¢ltering. 3.2. Separation mechanisms Liquid chromatography is the most popular technique for the separation of arsenic species, as they are, in general, readily soluble in aqueous solution. Gas chromatography (GC) of derivatised arsenic species is possible [45], but the extra step in the analytical procedure can lead to increased error. The most popular technique for the separation of species is HPLC because of the ease of coupling it with element-speci¢c detectors, as only a simple interface with element-speci¢c detectors, such as ICP-MS, is required. Reversed phase (RP) chromatography has been used for the separation of arsenic-containing species in seaweed extracts [46]. More than often than not, it is employed with the aid of ion-pairing (IP) reagents (IP RP), either cationic [18,47] or, more commonly, both cationic and anionic, such as tetraethyl ammonium hydroxide/ malonic acid mixture [24,38,48^51]. The speciation of arsenic by cation exchange (CE) is preferred for marine fauna in which AsB is often the major species. CE has been employed for jelly¢sh [52], seals [53,54], mussels [55], crab and shrimp [56] and ¢sh tissues [22,55]. It has also been employed for terrestrial tissues containing cationic organoarsenicals [57^59]. The preferred separation mechanism for marine £ora, which contain mostly arsenosugars, is anion exchange (AE) [20,22,23,26,30,39,43,46,60^62]. AE

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has also been employed for marine fauna [19,35,36,41,53,54,63^65] and terrestrial organisms [31,42,58,59,66,67]. HPLC is suited to the direct coupling with most detectors. However, the volume of sample that can be injected is sometimes insu⁄cient to detect minor species. O¡line preparative work allows for the injection and separation of larger quantities of samples. The eluent can be monitored by analysis of eluting fractions. Preparative columns work under low pressure, from gravitational feed or a peristaltic pump. Collected fractions can be chromatographed for further isolation and puri¢cation of the analyte of interest. More often than not, this multidimensional protocol is applied for the isolation and puri¢cation of analytes prior to molecular detection [18,21,27,47,68^70] or NMR [71], which require purity and concentration higher than those of atomic detectors. More recently micro-scale separations have increased in popularity, as analysts try to improve separation e⁄ciency with reduced analysis time and reduced sample consumption [72]. Micro-bore and narrow-bore columns are popular for their compatibility with ionisation sources for MS [55,73], but have also been coupled with ICP-MS [18,28,74,75]. CZE boasts resolution much improved over that of chromatographic separations and has been applied to the separation of organoarsenic species [76,77], but, because of matrix interference, the analysis of real samples has proved to be more troublesome [78]. Stacking, an on-column pre-concentration method introduced to increase the detection sensitivity of CZE, has also been employed with respect to arsenic species [79]. 3.3. Detection/identi¢cation and coupling In modern analysis, there are two distinct modes of detectionOatomic and molecular. State-of-the-art instruments o¡er increased sensitivity and speci¢city with respect to trace analysis, together with advances in mass/charge resolution. Element-speci¢c (atomic) detectors are renowned for higher sensitivity, whereas molecular detectors o¡er information on the structural formula of a compound. Because of the low concentrations associated with trace analysis, importance is more often than not placed on the low LODs o¡ered by atomic detectors and the importance of identifying the species to be determined is often overlooked. Focus on the quality of an analysis should also extend to unambiguous identi¢cation of the species to be identi¢ed and assurance that the determined concentration, often quanti¢ed from a chromatographic peak, is attributable solely to the species in question. 3.3.1. Atomic detection. In atomic spectrometry, a high-energy excitation source is employed to atomise

Trends in Analytical Chemistry, Vol. 22, No. 4, 2003 and to ionise the analyte of interest. In this way, the compound itself is destroyed and only the elements contained within it are detected. These techniques o¡er sensitive and speci¢c detection of trace elements. Atomic absorption spectrometry (AAS) and atomic £uorescence spectrometry (AFS) su¡er from interference, and often hydrides are generated for the analysis of arsenic. However, there are limitations for the number of organoarsenic species that will generate hydrides with chemical reagents, so the chromatographic eluent is often irradiated with UV rays [40,64,80] or microwave digested [36] to degrade organoarsenicals before hydride generation (HG). Techniques such as MS and atomic emission spectroscopy (AES) are more popular because of the high dynamic range. Plasma excitation, ICP, is often used for liquid samples [11]. ICP-MS is an extremely sensitive element-speci¢c detector, which has the added advantage of high sensitivity in multi-elemental detection mode, and this is by far the most popular technique coupled with HPLC for the speciation of arsenic (Table 2). The problems encountered with HPLC-ICP-MS include limitations with respect to organic solvents and interference. Organic solvents present in the chromatographic eluent will cause carbon build-up in the plasma region. It is therefore necessary to keep organic solvent use to a minimum or to use oxygen to prevent carbon deposits. Interference from polyatomic ions, particularly ArCl+, is a problem overcome by the use of highresolution instruments or collision cells. For the determination of arsenic with a quadrupole instrument, the potential interference can be monitored, for example 37 Cl or 53Cr (37ClO). Any materials used in preparation of the sample for analysis are veri¢ed as containing no chlorinated compounds. HPLC-IC-MS is used for the identi¢cation of arsenic species by matching retention time of injected standards and spiking with the arsenic species of interest. However, one-dimensional HPLC has often proved to be insu⁄cient for the baseline speciation of all the arseniccontaining species in a sample, and problems can also occur when arsenic-containing standards are not available. Complex matrix can also contribute to the coelution of species, which would otherwise be separated as standards on a particular column. Orthogonal HPLC or bi-dimensional chromatography can reduce the chances of misidenti¢cation of arsenic species by HPLC- ICP- MS. 3.3.2. Molecular detection. With emphasis on the identi¢cation of organoarsenicals in tissues, molecular modes of detection with atmospheric pressure ionisation (API) sources and mass ¢lters are growing in popularity. A soft ionisation technique (ionspray (IS), electrospray (ES), atmospheric pressure chemical ionisation (APCI), fast atom bombardment (FAB), electron

Trends ionisation (EI), ¢eld desorption (FD)) is employed to create in the gas phase analyte ions, which are transmitted to the MS. Successful application of these techniques generally requires isolated and puri¢ed analytes because of their poor LODs and their sensitivity to matrix components compared with ICP-MS. The molecular ions are observed as the mass-to-charge ratio (m/z) and fragmentation of ions allows for further structural information. Arsenic is monoisotopic, so interpretation of mass spectra is not facilitated by a natural isotopic distribution, which can give characteristic patterns in ES-MS spectra. Thus, tandem MS can be employed where characteristic fragments can be observed for methylated species (e.g. m/z 105 and 120, which correspond to a dimethylated and trimethylated arsinoyl moieties, respectively) and arsenosugars (collision-induced dissociation (CID) spectra include ions at m/z 97, 195 and 237). MS has often been thought of as a technique o¡ering qualitative data rather than quantitative data, but recent articles concerning quanti¢cation with LC-MS have reported LODs below 30 pg/mL [81], which approach those of HPLC-ICP-MS. This is more evident when quanti¢cation is carried out in tandem-MS mode, as an important di¡erence between the molecular mode and the MS/MS mode is the absence of background noise in the latter. High-resolution instruments, such as QToF and Fourier transform (FT)-MS also provide a solution for the analysis of arsenic-containing species. The accurate m/z measurements can allow for the resolution of compounds, which have the same integral molecular mass but a di¡erent exact mass, and the elucidation of the exact empirical formula of the analyte, depending on the accuracy and precision of the instrument. Most modern instruments accommodate for analytical HPLC £ow rates employing techniques, such as high gas-£ow rates and higher temperatures, to promote desolvation. This allows for the direct coupling of the LC column to ES and APCI sources. For sources that require smaller £ow rates, typically 1^200 mL/min, either a split of the eluent from an analytical column or the use of narrow or micro-bore columns is necessary. The earliest speciation studies by molecular detection techniques were carried out not long after the initial characterization of AsB in lobster by X-ray crystallography [15]. AsB was characterized in several marine fauna tissues by FD-MS [82^86] or EI-MS [18,87]. However, these earlier studies employed large-scale extraction and separation procedures, often with several preparative, puri¢cation steps. As instruments available have increased in sensitivity and coupling has become the norm, extraction of 1g of tissue or even less is often su⁄cient for to identify species therein. One of the ¢rst demonstrations of hyphenation was LC-IS-MS/MS, which allowed the characterization of http://www.elsevier.com/locate/trac

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arsenosugars A, B, C, and D puri¢ed from alga sources as well as the speciation of several marine fauna [55]. The IS source requires low £ow rates and the eluent from the chromatographic column was split. ES ionisation with high gas-£ow rates as an interface for HPLCMS has been used on-line to characterize arsenosugars in the alga ribbon kelp [23,30,43], Laminaria and Porphyra [62] and Fucus [46]. Syringe infusion of puri¢ed analytes was employed with IS for the o¡-line speciation of organoarsenicals in brown algae [26,47,61,68], oyster [27] and the kidney of a giant clam [69]. Syringe infusion was also used for the speciation of a Sargassum extract with FAB-MS/MS in positive-ion mode and negative-ion mode [88], and, more recently, by nano-ES-QToF in negative-ion mode [89]. Characterization of orgaonoarsenicals using an instrument with only one mass ¢lter can be accomplished by comparing the selective ion monitoring (SIM) spectra of characteristic m/z after fragmentation in the source by varying fragmentation energies. This technique has been employed on-line for brown algae extracts of Fucus [20,60] and Laminaria [20] and the kidney of the giant clam, Tridacna derasa [21].

4. Quality assurance and quality control (QA/ QC) 4.1. QA Analytical QA is essential in all modern environmental, health and food-related studies. The demand is justi¢ed by the right of every individual to be able to trust certi¢ed values and to have con¢dence in analytical determinations that concern them, the most evident being clinical diagnosis, drug purity and food and water regulations. It is important that quality is assured, in order to minimise any consequences that can arise from decisions on contamination control or compliance with regulations that are based on analytical determinations. Laboratories involved in speciation studies are increasingly under pressure from the end user to assure the quality of their analyses. The quality of analytical work is characterised by sampling, speci¢city, sensitivity, throughput and precision of the technique and accuracy and representativeness of the result [90,91]. Furthermore, particular attention should be paid to intermediate steps, such as storage and sample treatment that often, especially in the case of speciation analysis, contribute to the total uncertainty in more directly than the ¢nal determination [92^94]. These factors should be improved, guaranteed and recorded by the analyst. Accuracy is based on the absence of systematic errors and uncertainty corresponds to the coe⁄cient of variation of a group of results, which re£ects random errors.

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The errors encountered arise from aspects of the analytical process, which cannot be controlled. The analytical steps of extraction, derivatisation, separation and detection are all prone to errors, which may go unobserved by the analyst. Sources of contamination, loss or degradation of the analyte, errors in calibration and matrix interference can all contribute to a¡ect a result. Systematic errors, which occur continuously, will distort the true value of a determination, causing inaccuracy. The uncertainty of the result may be low, and, unless the result is veri¢ed with a QC procedure, it may go unobserved. Random errors will cause high uncertainty and will be observed by the analyst, who has responsibility to verify each stage of the procedure to try to eliminate or control the source of error. 4.2. QC Quality can be assured with QC measures applied to method validation, accuracy and precision [95]. The validation of an analytical method and precision can be carried out within the laboratory. According to the sample to be analysed, an appropriate method should be developed (bearing in mind that sources of interference should be eliminated or controlled), calibrated and monitored in a timely fashion using a CRM. The analytical technique can be kept under control by statistical control charts, which should help maintain reproducible results. However, the accuracy of an analytical determination can be validated with some kind of external corroboration: comparison of the result with a di¡erent analytical technique within the laboratory; comparison with a result from an analytical procedure carried out in another laboratory; or, use of CRMs, which enable calibration, traceability and accuracy to be determined, as well as validating a newly developed method [95]. 4.3. Interlaboratory studies The collaboration of several laboratories is one of the best methods to make progress in a speci¢c ¢eld of analysis. These studies prove useful in detecting systematic errors, which can occur in the analyses. The sources of errors encountered are: sampling; sample pre-treatment; ¢nal measurements; and, laboratory errors. Interlaboratory studies involve the analysis of a common material, so that sampling errors should be eliminated and only errors associated with the laboratory and the analytical procedure will be encountered. Intercomparison studies involve several laboratories determining one or more components in a common sample and comparing the results from the di¡erent methods applied in the di¡erent laboratories [95]. It is accepted that, if the intercomparison values of such a study are in good statistical agreement, it will be the best approximation of the truth [96].

Trends in Analytical Chemistry, Vol. 22, No. 4, 2003 For example, the certi¢cation of a candidate reference material requires the participation of several laboratories in the study. Laboratories with proven ability in the analysis required are invited to participate and are asked to analyse a common tissue, which is distributed by a central laboratory responsible for data collection and evaluation. Each laboratory will follow strict guidelines for storage and sampling of the sample, and the number and the timing of the analyses with respect to structured studies, but they are allowed to select the analytical technique used for the measurement. In this way, di¡erent sample pre-treatment methods, separation techniques and techniques of ¢nal determination can be compared and discussed, as well as the overall performance of the individual laboratories. 4.4. CRMs CRMs serve the analyst in validating a method and demonstrating the accuracy of a determination. A CRM is de¢ned as ‘a reference material, accompanied by a certi¢cate, where one or more property values are certi¢ed by procedures, which establish traceability to an accurate realisation of the unit in which the property values are expressed, and where each certi¢ed value is accompanied by an uncertainty at a stated level of con¢dence’ [97]. The use of CRMs has been reviewed extensively with respect to QC [6,96,98,99]. The CRMs, determined by interlaboratory studies, allow the analyst to compare his result to a certi¢ed value. CRMs of a particular matrix can be used to monitor and to control the level of contamination in environmental samples. CRMs can be used for calibrating an analytical instrument and traceability. The accuracy of a method (especially when developing a new method) can be checked and working standards and statistical control charts can be evaluated with CRMs. 4.4.1. Arsenic-containing CRMs. There are a large number of arsenic-containing CRMs [98] but most of them are limited to the certi¢cation of the total-element concentration. Speciated CRMs are important, as the ¢eld of trace-element analysis has expanded from totalelement measurements to that of trace-element species. As a response to the increase and need for improvement of speciation studies, several CRMs have been developed. Table 3 gives a comprehensive list of the CRMs speciated for arsenic that exist for environmental studies.

Trends Seafood plays an important role here as the tissues are regularly found to be of interest because of the number of species accumulated. The ultimate validation of an analytical procedure is carried out by analysis of a CRM having the same (or very similar) matrix as the analysed sample. In addition, there is a large range of arsenic-containing species and for research purposes it would be bene¢cial to have a choice of CRMs, which incorporate a whole range of chemical forms. Because of this and the limited number of CRMs available, there is a need to develop more speciated CRMs. Until very recently, only two CRMs existed on the market (from the BCR, European Commission, Belgium) concerned with arsenic speciation: BCR-626, an AsB solution; and, BCR-627 made from tuna ¢sh, certi¢ed for total arsenic, AsB and DMA. The certi¢cation procedure of the speciated tuna-¢sh tissue, BCR 627, has been reviewed [100] and outlines the analytical and validation procedures used. A third CRM, DORM-2 produced by the US Nuclear Regulatory Commission (NRC), has a certi¢ed total-element concentration, but only gives indicative values for the species. The recent MULSPOT (Multi-species Oyster Tissue Reference Material) project will allow for the production of a new CRM with oyster matrix.

5. Certi¢cation of candidate reference materials A special ISO guide describes the rules that should be followed for the certi¢cation of reference materials. It states: ‘‘a certi¢ed value should be an accurate estimate of the true value with a reliable estimate of the uncertainty compatible with the end use requirements’’ [101]. Because of the complicated matrix associated with real samples, the determination or certi¢cation cannot be carried out by direct gravimetric methods. The species to be determined need to be removed from the matrix before the certi¢cation by interlaboratory studies [6]. The certi¢cation relies on the use of several di¡erent methods and the certi¢cation procedure involves each laboratory carrying out a minimum of ¢ve independent, replicate determinations on at least two di¡erent bottles on di¡erent days. The measurements from each laboratory are grouped and statistically analysed to determine whether the species concentrations can be certi¢ed.

Table 3. List of arsenic-speciated CRMs available on the market today CRM

Matrix tissue

Total [element]

Species 1

Species 2

BCR 626 BCR 627 DORM-2 (NRC)

AsB solution Tuna fish Dogfish muscle

As 4.8  0.3 mg/kg As 18 1.1 mg/kg

AsB 1031  6 mg/kg AsB 52  3 mmol/kg AsB 16.4  1.1 mg As /kg

DMA 2  0.3 mmol/kg TMAs+ 0.248  0.054 mg As/kg

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5.1. The MULSPOT project The MULSPOT Project was funded by the Standards, Measurements and Testing Programme (SM&TOformerly BCR) of the European Union under Contract N.SMT4-CT98-2232 in 1998. The aim was the certi¢cation of an oyster matrix reference material for species of Sn, Hg and As. The main partners are ENEA (ItalyO Co-ordinator), University of Madrid (Spain), University of Umea (Sweden), JRC of Ispra (Italy). Mermayde (The Netherlands) and University of Pau (France). Started in October 1998 and ended in June 2002, the MULSPOT Project carried out two intercomparison and one certi¢cation exercises. Three oyster tissues (T34, T37 and T38) were prepared by the JRC of Ispra for the exercises and a fourth reference material (T36) was prepared for recovery evaluation. 22 laboratories from European countries and 1 laboratory from Canada participated in the certi¢cation. The laboratories asked to participate were required to demonstrate their quality in the speci¢c task required [6]. They were allowed to use the analytical methods of their choice with respect to extraction, separation and detection, but there were speci¢c guidelines for stability, homogeneity, recovery, moisture and intercomparison, which had to be followed by all participating laboratories. 5.2. Selection of the candidate CRM The selection of an appropriate material is a critical step in the production process of a CRM. Not only is the initial selection based on the commercial interest of the matrix, but the material must also have su⁄cient quantities of the species of interest. The CRM must be representative of samples analysed in laboratories. The similarity of analytes and their binding properties, the possible interference and the physical status of the material, as well as matrix composition, must be taken into consideration [96]. In addition, it must be a common tissue for speciation to interest the scienti¢c community. The levels of analytes must be compatible with current analytical techniques and the stability of the species present should be long term (the product will not be useful if the certi¢ed levels change after a few weeks). The selection for the candidate CRM in the MULSPOT Project was oyster, which is a tissue of particular interest, as it is widely consumed and is capable of containing interesting species of the above-mentioned elements. 5.2.1. Preliminary assays using a spiked oyster material. Even though previous studies have shown that an oyster can contain several species of arsenic and the total concentration expected could be 15 mg/kg dry weight, there was still a fear that inadequate levels of species of interest would be present in the sample and

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spiking was suggested. The ¢rst test material, T36, was spiked with species AsIII, AsV and DMA during the initial preparation step. However, overspiking of some species caused unusually high levels which were not representative of a real tissue. It was decided to use this material for method development and recovery tests and to prepare a new material by dilution with unspiked oyster, T37, to be used in the ¢rst intercomparison exercise. However, the species concentrations still remained too high, and, furthermore, subsequent stability and homogeneity tests suggested that the spiked species were not as stable as species present naturally. The stability study indicated the analyses were not controlled, as some species concentrations were erratic. As a result, a second intercomparison of an unspiked oyster material was envisaged. 5.2.2. Selection of unspiked test materials. Two materials, T34 and T38, from waters suspected of being polluted, but with naturally accumulated levels of species, were collected to investigate their suitability as RMs. T34 was collected from the Bay of Arcachon on the West Coast of France and T38 was collected from Venice Lagoon, Italy. The two unspiked samples were investigated for the relative amounts of the elements and the species of interest. The sample that was deemed to be the most interesting to the commercial market, based on intercomparison studies, was selected. T34 from Arcachon was found to be the tissue with the most potential commercial interest because it had the higher concentrations of species. This material was selected as candidate material BCR-710 to be certi¢ed whereas T38 was used as test material for the second intercomparison prior to certi¢cation. 5.3. Preparation of the candidate CRM Initial sample preparation involves the collection of a large amount of material from one pre-selected site. This could be several hundred kilograms of solid material for the production of a new CRM. The tissue should be homogeneous so that each independent subsampling from the CRM bottle gives an identical portion of tissue. The analytes should also be stabilized so that the CRM has a long shelf-life. For solids, this is often achieved by drying (less than 5% moisture) to avoid chemical or microbiological activity. Drying also improves the ease of handling of the tissue. To process the volume of fresh tissue, special industrial-size machines are necessary. The following is a summary of the preparation protocol for the oysters collected for the MULSPOT project. The oysters were de-purated near the outlet of the bay to eliminate sedimentary particulate. The fresh oyster

Trends in Analytical Chemistry, Vol. 22, No. 4, 2003 was kept at 15 C until it was processed to inhibit any bacterial activity or degradation of the tissue. The oysters were de-shelled and transported in cold condition to the JRC of Ispra, Italy, for further processing. The frozen tissue (70 kg) was minced and homogenised (Ultraturrax). The tissue was then freeze-dried, giving 13kg of dry tissue that was ground and sieved (125mm) to achieve the ¢nal product. This material was further homogenised in a rotating drum before bottling. Amber glass vials were used for bottling to reduce the risk of harm by UV irradiation. During bottling, an adequate number of bottles were randomly selected and put aside for homogeneity and stability tests. Homogeneity was evaluated by analysing the contents of: one bottle by taking 10 replicates (for within-bottle homogeneity); and, 20 bottles by taking one sample from each bottle (for between-bottle homogeneity). Stability was evaluated by storing samples at 20 C, 4 C and 20 C and analysing them after 1, 3, 6, 12 and 18 months of storage. The analyses were performed in triplicate. A sample stored at +40 C was also determined in triplicate after 1 month. 5.4. Certi¢cation guidelines 5.4.1. Storage. The received samples were stored in the freezer at 20 C. 5.4.2. Sampling. Before sampling from the bottle, the candidate CRM needs to be allowed to come to room temperature, so is left to stand for 1 h. The bottle is then shaken manually for 5 minutes to re-homogenise the material and left to stand for another 10 minutes before sampling the tissue. An adequate sample amount, representative of the material is 250^300 mg. 5.4.3. Recovery. The calculation of recovery was based on the determination of an elemental species in the tissue after the standard addition of the species to give two and four times the natural concentration. The series of determinations was carried out in duplicate. The spike, in an appropriate solvent, was added dropwise to the tissue while shaking continuously. The spike was left to interact with the tissue for at least 16 h. The tissue was then dried under a gentle stream of nitrogen before treatment for analysis.

Trends each bottle was sub-sampled three times. The samples were analysed on at least two di¡erent days. 5.5. Choice of analytical procedure and sources of error The choice of analytical techniques is often governed by what techniques are available to the analyst as well as the techniques most suited to the analytical problem. There is a large range of analytical techniques and steps that can be involved when speciating a sample, most notably extraction, derivatisation, separation and detection. Sources of error, such as poor extraction recovery, incomplete derivatisation, unresolved species and detection interference, should be controlled. Other sources of error can arise from the inaccurate quanti¢cation of a species because of inappropriate standards. 5.5.1. Calibration standards. The control of the quality of measurements implies that suitable calibrants are available. In the case of arsenic, there are a limited number of organoarsenic species commercially available. Often a laboratory will synthesise its own standards or prepare them from isolation and puri¢cation of a real sample. The standards that are commercially available include AsIII, AsV and DMA. MMA and several cationic organoarsenic species are not yet commercially available. The major organoarsenic species expected in the oyster is AsB. Only in the last two years has this species been available commercially as a CRM from the BCR and more recently in the form of a solid (Fluka). Matrix e¡ects can cause problems when quantifying by external calibration, and standard addition is the preferred technique. It is therefore essential that the correct analytes are used for the process of spiking and standard addition.

5.4.4. Moisture. The moisture content of the tissue was based on the loss of weight from the tissue when dried in an oven at 85 C during at least 24 h. Mass measurements were taken every hour and the ¢nal weight determination was noted as the value that di¡ered by less than 0.1% of the previous weight determination.

5.5.2. Extraction of arsenic species from an oyster tissue. Extraction is an important part of the analytical protocol. Quanti¢cation of a species from a poorly extracted tissue will result in a quanti¢ed value lower than the true value. The extraction procedure therefore needs to be optimised and the extraction e⁄ciency veri¢ed by determining a mass balance for a sequential extraction or the total-element concentration. The arsenic species present in the tissue are expected to have ionic character (anionic and cationic) and should, in theory, be soluble in an aqueous extractant. Table 4 includes a list of the extraction procedures employed by each laboratory involved in the intercomparison exercise for the speciation of arsenic. As expected, the most popular method of extraction comprises a water/methanol mixture aided by sonication or microwaves.

5.4.5. Analysis. A total of six completely independent determinations were carried out using both bottles, i.e.

5.5.3. Separation of the arsenic species. HPLC was the preferred technique of all the laboratories involved in http://www.elsevier.com/locate/trac

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Table 4. List of analytical protocols used by the participating laboratories in the MULSPOT intercomparison exercise Extraction

Laboratory

Determination

Laboratory

Water MeOH/water

9, 11, 15 14, 20, 24, 26, 29, 32

HPLC UV HG AFS HPLC ICP MS

9, 11, 20, 32 8, 14, 15, 24, 26, 29, 32

the interlaboratory study. The quanti¢cation of arsenic species depended on ¢nding separation conditions allowing the baseline separation of the species present. AE was found to be the most appropriate mechanism, although RP has also been employed (Table 4). Even when employing the same separation mechanism the choice of packing has a tremendous e¡ect on the separation. For example most AE columns do not allow the separation of AsB from AsIII, arsenosugar B or other cationic species. As AsB is the most important species in our tissue it was necessary to ¢nd a suitable technique for the baseline resolution of this species. 5.5.4. Detection of arsenic. The ease of coupling to HPLC and the high sensitivity o¡ered by ICP-MS makes it the preferred choice of mode of detection for arsenic (Table 3). Of the 10 laboratories involved, four employed HGAFS, the hydrides being formed by ultraviolet (UV) irradiation. With this technique, inorganic species, methylated species and AsB [40] can be detected, but it is possible that arsenosugars will not be observed. 5.6. Homogeneity The determination of species concentration in a CRM tissue often involves the destruction of the sub-sample by the analytical procedure. It is therefore necessary to take a sub-sample each time the tissue is analysed. There should be a su⁄cient quantity of tissue for several determinations and each sub-sample should be equal. The homogeneity of the tissue within a bottle needs to be assured. Many bottles of the same tissue are made in producing a CRM, and each bottle should be identical, so the homogeneity of the tissue between bottles also needs to be assured. The homogeneity study was carried out shortly after receipt of the bottles to minimise any degradation of species caused by instability. The bottles were stored at 20 C until sampling. For the homogeneity study, a bottle was selected at random. The sampling of the bottle was carried out 10 times, according to the guidelines. Simultaneously, two replicates of CRM 627 were determined. Within the same working week, the study of between-bottle homogeneity was carried out. According to guidelines, either 10 or 20 bottles were selected for sampling. One sample was taken from each bottle. For both studies, two replicates of CRM 627 were simultaneously sampled, extracted and determined to validate the method and to control reproducibility.

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Homogeneity is evaluated by the coe⁄cient of variation  the uncertainty. 5.6.1. Test of candidate oyster-tissue CRM. T34 has naturally-accumulated levels of arsenic species. The homogeneity determinations provided by laboratory 15 showed good agreement between the mean concentration of AsB from the within-bottle and betweenbottle studies (Table 5). The results for T34 showed a coe⁄cient of variation and uncertainty that overlapped so no inhomogeneity could be demonstrated. T34 was adequately homogeneous for certi¢cation. 5.7. Stability The tissue supplied as a CRM should have long-term stability for it to be reliable. Stability of the tissue implies the analytes should remain unchanged over the period of use of the material. This can be estimated with an accelerated aging procedure, such as heating. The stability of AsB and DMA was tested over a 12month period (December 2000^December 2001). Of the bottles received for the stability study, four were stored at 20 C, four at 4 C, four at 20 C, and one in an oven at 40 C. The determinations were carried out in triplicate from one bottle at each temperature. The same bottle at each temperature was used throughout the study. The bottle at 40 C was analysed at t=0 and 1month. The other bottles were analysed at t=0, 1 month, and 3, 6 and 12 months. Stability is evaluated by the result, RT, where result obtained after storage at

 Ugt guideline temperature RT ¼ result obtained after storage at  Ust safe temperature

The safe storage temperature is 20 C. In an ideal situation, RT should be 1.00. If RT  UT encompasses 1.00, no instability can be demonstrated.

Table 5. Homogeneity results for the tissue T34 from laboratory 15 AsB Conc. /mg kg1 Homogeneity within (n=10 ) Homogeneity between (n=20)

33.59 3.18 (CV 9.47%) 32.95 2.29 (CV 6.96%)

Trends in Analytical Chemistry, Vol. 22, No. 4, 2003 5.7.1. Test of candidate oyster-tissue CRM. This unspiked oyster was quanti¢ed for AsB. The average determinations from three replicates for each temperature and time are shown in Table 6. The results show a set of measurements that has changed very little over time, regardless of the temperature. The sample was thought to be su⁄ciently stable to qualify for the certi¢cation. 5.8. Technical discussion An interlaboratory meeting was arranged to assess the quality of the measurements from an interlaboratory study. Each participating laboratory reported at least six determinations of elemental species in the oyster tissues. The mean value with uncertainty was plotted on a bar chart for each laboratory and the results were compared. The accuracy and uncertainty need to be considered. To obtain the accuracy required for certi¢cation, it is necessary to ensure that no substantial systematic error is left undetected. Random errors or variations in the procedure cause uncertainty in the result and need to be minimised if the result is to be useful. Attention Table 6. Stability results of AsB in mg/kg for tissue T34 from laboratory 15 Time/months

+40 C

+20 C

+4 C

20 C

1 3 6 12

33.22

33.15 32.80 33.22 31.42

31.33 33.13 30.10 33.92

32.65 33.01 32.49 34.67

Trends should be paid in particular to errors during calibration and sources of contamination and interference. Any data set deemed unreliable because of a known or unknown source of error was omitted from the overall set of results. For the MULSPOT Project, a minimum of six determinations for each species was requested. Data sets were collected from 10 laboratories for the determination of AsB. The results of lab 8 were about double the mean values from the other laboratories, but a reason for this could not be identi¢ed. The data set of lab 11 was lower than the statistical mean, and this was caused by an incomplete photo-oxidation step in the analytical process. The omission of these two data sets as statistical outliers, resulted in the much-improved CV demonstrated in Barchart 1. Barchart 2 shows the data sets reported for the quanti¢cation of DMA minus statistical outliers. Seven laboratories reported values for DMA, one of which was omitted because of a high standard CV and a higher mean than that reported by the other laboratories. The explanation for this was incomplete baseline separation of DMA from AsB. The DMA-species concentration was low, and this could explain the lack of reported data sets from the other three laboratories that reported for AsB. Another explanation given by laboratory 15 is the close elution to an unknown species in the sample, demonstrated in Fig. 1a. Any attempt by lab 15 to add a standard addition of the species resulted in the co-elution of these species or non-linear standard addition gradients.

Barchart 1. Intercomparison determinations of AsB in T34 tissue omitting the statistical outlier data sets (laboratories 8 and 11).

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Barchart 2. Intercomparison determinations of DMA in T34 tissue omitting the statistical outlier data set (laboratory 29).

Figure 1. Comparison of elution profiles for an aqueous oyster extract on two anion exchange columns — (a) Supelcosil SAX and (b) Hamilton PRP x-100 — using the same elution conditions. Figure adapted from [110].

Several laboratories reported data sets for the quanti¢cation of other species in the oyster tissue. Three laboratories reported data sets for MMA, but the results were not in agreement. Data sets were also given for AsIII, AsV, AsC+ and arsenosugars. However, these species were not certi¢able for various reasons, including the limited number of reported data sets, concentrations approaching the LODs and unde¢ned species in the case of arsenosugars. 5.8.1. Certi¢cation. Strictly following the guidelines, a moisture determination was made each time a bottle was sampled. The mean moisture content for T34 was 4.7  1.3%. The data set for the total arsenic content ‘‘compared reasonably well’’, but the presence of two distinct clusters could prevent a certi¢ed value. An indicative value will be proposed. The major species in the tissue, AsB, will be certi¢ed and an indicative value

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will be reported for DMA. No other reported values were deemed reliable enough for certi¢cation or indication. 5.8.2. Problems encountered in the certi¢cation process. In addition to the discussed sources of error caused by interference or badly quanti¢ed standards, lack of peak purity was a common problem arising in the quanti¢cation of a species. To reduce loss of time with long speciation protocols or loss of the species through over-treatment of the sample, it is preferable if the baseline resolution of naturally-present species can be achieved using one separation mechanism. The co-elution or insu⁄cient baseline separation of AsB with cationic species is often unavoidable on most AE columns. Often, a high degree of matrix worsens the e¡ect by preventing the resolution of species present in a sample, although this would

Trends in Analytical Chemistry, Vol. 22, No. 4, 2003 normally be resolved with standards. Because of the unavailability of many organoarsenic standards, it may not be possible for the analyst to check for co-elution of species, and, without bi-dimensional chromatography, the co-eluting species may go undiscovered. Time should be taken to estimate the number and the ratio of species present in the sample by a multi-dimensional protocol before quanti¢cation, preferably with a mode of molecular detection for the con¢rmation of species identi¢cation [27]. Care should also be given to selection of the column as well as optimisation of the separation conditions, a point presented by lab 15, and reiterated by lab 14, in the certi¢cation meeting. Fig. 1 demonstrates the di¡erence in resolution of the same aqueous oyster extract on two AE columns. The large peak eluting close to the void volume on the Hamilton PRP x-100 column (Fig. 1b) is resolved on the Supelcosil SAX column (Fig. 1a) indicating at least four species are present. The ¢rst peak eluting from the Supelcosil SAX column is also caused by more than one species, cations eluting in the void volume. As a result of possible co-elution, it was proposed to include the following sentence in the certi¢cation report: ‘‘According to the present state of the art, it cannot be excluded that a small interference of other As compounds is included in the AsB results; this interference is below the con¢dence limit reported’’.

6. Conclusions The state-of-the-art analytical techniques available have allowed the detection and identi¢cation of many organoarsenic compounds in natural tissues. However, the complexities of metabolic pathways leave possible unidenti¢ed compounds, which complicate the analytical process. Often, a simple extraction-separationdetection protocol is insu⁄cient for the full characterisation of arsenic species in a living organism. Problems arise because of: retention time irreproducibility; the co-elution of species; the unavailability of standards; and, the presence of unidenti¢ed species. The issue of the chromatographic purity of peaks from extracts of natural samples needs to be tackled, and newly developed analytical protocols based on multiple separations and molecular detection techniques could aid the analyst in con¢rming the identi¢cation of ambiguous species. The analytical protocols in place and being developed need to be quality assured. QC measures need to be implemented for the control of each step of the analytical protocol so that accuracy is assured and uncertainty is reduced. Within a laboratory, reproducibility can be kept constant with the use of statistical control charts. However, control charts are unable to detect

Trends systematic errors, so data sets need to be veri¢ed with other methods, such as result comparison and CRMs. This demand for a QA/QC protocol has highlighted the need for more CRMs compatible with arsenic speciation and the need for the co-operation of RM producers and users for the certi¢cation of suitable materials. The CRMs required are very time-consuming and costly to produce. This limitation means that there needs to be greater emphasis on planning for candidate CRMs to ensure a tissue that will be successful. The recent MULSPOT Project will create an oysterbased CRM certi¢ed for multi-elemental species. The fact that this tissue will be suitable for analysts working on di¡erent elemental species should ensure a larger market. The tissue certi¢ed has naturally accumulated the elemental species. Spiked tissue investigated was rejected as species concentrations did not re£ect natural levels and the stability of species or homogeneity could be harder to control. The international collaboration of over 20 laboratories provided su⁄cient statistical data sets for there to be con¢dence in the certi¢ed values.

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