Abstract This paper reports the assessment of total ar-senic and six arsenic species (As(III), As(V), MMA, DMA,AsBet, AsCol) as contaminants of mussel samples collectedaround the island of Sardinia and in the Gulf of Venice.The samples were analysed using cation- and anion-ex-change HPLC-HG-AFS for speciation and ICP-AES forthe total As determination. To ensure the robustness of theroutine analytical method, the technique was validated us-ing a candidate reference material, BCR-710, and goodagreement was obtained. It was recognised that higher to-tal arsenic concentration in mussels does not necessarilyresult in higher toxicity of mussel samples.

Keywords Arsenic speciation · Routine analysis · Biological monitoring · Mussels

Introduction

Arsenic is ubiquitous throughout the biosphere due to itsnatural occurrence, in small concentrations, in all rock,soil, dust, water and air. It is also present due to anthropo-logical activity such as industrial processing and agricul-ture, with the latter being a significant source of contami-nation.

Determination of the total levels of arsenic is not suffi-cient to allow accurate evaluation of the element’s toxico-logical impact on the environment. This is because thetoxicity of arsenic can range from being very toxic tocompletely non-toxic, and is purely dependent on thechemical form in which it is present. Inorganic arsenic,

i.e. arsenite and arsenate, is considered carcinogenic [1],being more toxic than monomethylarsonic acid (MMA)and dimethylarsonic acid (DMA). The organic forms, ar-senobetaine (AsBet), arsenocholine (AsCol) and arseno-sugars, are considered either virtually or completely non-toxic.

The concentration of arsenic in seawater is generallyaround 2 µg L–1, and is mainly present in its inorganicforms [2]. However, the ability of marine animals and al-gae to biotransform the element to a less toxic form re-sults in the majority of their arsenic burden being presentas organo-arsenicals. An example of this is where phyto-plankton ingest arsenate from the aquatic environment, re-duce it to arsenite and then metabolise it further to pro-duce MMA and DMA. These compounds can then be eas-ily excreted, thereby protecting the organism from the el-ement’s toxic effect [2]. More highly developed marineanimals acquire most of their arsenic through the foodchain, rather than directly from water [3], and can producea wide range of organic arsenic compounds via the sorts ofmetabolic processes described above. Using traditional struc-tural organo-chemical methods, Edmonds and Francesconi[3] caused a major rethink regarding the toxicity of the ar-senic found in marine animals when they characterisedthe main non-toxic form of arsenic, arsenobetaine. Thiscompound is the major form of arsenic in such animals(>95%) and is thought to be the final metabolite [4].

Arsenic can be accumulated in marine animals, with itsconcentration ranging typically from 1 to 100 µg g–1 and isgenerally dependent on the levels of arsenic in the organ-isms’ immediate environment [2]. It might therefore beanticipated that the distribution of arsenic in aquatic eco-systems would be closely reflected in the amount found inthe body fluids and tissues of marine animals and thatthese matrices could then be used in biomonitoring exer-cises.

Biomonitoring plays an increasing role in modern en-vironmental observation programmes. According to theliterature, it is often not sufficient for assessment-orientedprogrammes like biomonitoring to determine only total el-ement concentrations in environmental samples. In the case

Csilla Sörös · Erzsébet Tünde Bodó · Péter Fodor ·Roberto Morabito

The potential of arsenic speciation in molluscs for environmental monitoring

Anal Bioanal Chem (2003) 377 : 25–31DOI 10.1007/s00216-003-1971-5

Received: 11 February 2003 / Revised: 31 March 2003 / Accepted: 8 April 2003 / Published online: 24 June 2003

SPECIAL ISSUE PAPER

C. Sörös (✉) · E. T. Bodó · P. FodorDepartment of Applied Chemistry, Faculty of Food Science,Szent István University, Villányi út 29–33, 1118 Budapest, Hungarye-mail: sori@omega.kee.hu

R. MorabitoENEA C.R. CASACCIA–TEIN/CHIM, Via Anguillarese, 301–00060 Rome, Italy

© Springer-Verlag 2003

of some trace elements, therefore, chemical speciation isindispensable without doubt [5, 6, 7, 8]. Mussels andclams have been widely used as biological monitoring or-ganisms [9, 10] in programmes such as the US Environ-mental Protection Agency’s (EPA) ‘Mussel Watch’. Inthis exercise, the blue mussel, Mytilus edulis, was suc-cessfully used as an indicator of marine pollution (Far-rington et al. 1983, Nelson et al. 1995). Molluscs have beenfavoured in the study of aquatic environments becausethey are particularly capable of bioaccumulating many in-organic compounds. Molluscs can transform the accumu-lated inorganic compounds to more toxic (MeHg) or non-toxic (AsBet) forms. This biotransformation capabilitydepends on (i) the intake and (ii) the transformation mech-anisms in animals. It is not clear in the literature whatkind of correlation exists between the total element andthe metabolised concentration in the biota.

For the analyst to be able to perform speciation analy-ses, some form of chromatographic separation followed bydetection using an element-specific detector is required.HPLC is the most frequently used separation technique,with GC [11] and capillary electrophoresis providing use-ful, complementary information [12]. Reversed-phaseion-pair chromatography [13], cation-exchange chromato-graphy, anion-exchange chromatography [14] as well assize-exclusion chromatography [15] have successfullybeen employed for separating the arsenic species in sea-food samples. Current thinking is that the complexity ofarsenic speciation requires the parallel use of at least twocomplementary separation techniques to provide the max-imum information regarding the various species [16].

With regard to element-specific detection, ICP-OES,AAS, ICP-MS and HG-AFS have played an importantrole in the development of suitable systems for arsenicspeciation investigations [17, 18].

As stated previously, one of the main problems facingspeciation analysis has been the lack of reference materi-als characterised specifically for chemical form ratherthan just the total amount of analyte. Without such mate-rials it is very difficult for analysts to gauge the accuracyof their data but, fortunately, there are an increasing num-ber of commercial species-characterised reference materi-als becoming available. However, some of these are syn-thetic, i.e. they have been made by adding the compoundsto the matrix, and may not truly reflect the behaviour ofthe analytes in their real environment. Therefore, suchmaterials should be used with great care.

For arsenic speciation there are several reference mate-rials available, but only BCR-710 (a ‘candidate’ referencematerial) is close to the analytical matrix described in thiswork [19, 20]. Hence, we have used this in our quality as-surance procedures.

This project was originally designed to monitor thedistribution of tributyltins (TBTs) in the marine environ-ment because they have been used as biocides in antifoul-ing paints and are known to produce a variety of malfor-mations in aquatic animals. Because the analysis of organo-tin compounds in environmental samples can be difficult,time consuming and expensive, a biomonitoring investi-

gation based on the accumulative properties of molluscswas proposed. Therefore, mussel and clam samples werecollected from the Mediterranean around the island ofSardinia and the coastal region next to Venice. Becausethe sampling is one of the most difficult and time con-suming (expensive) parts of environmental monitoring[21], effort was made to collect as much information aspossible from the results of the same sampling.

In this paper we intend to present: (i) the application of arobust analytical method for the quantification of As(III),As(V), DMA, MMA and AsBet; (ii) the definition of qual-ity assurance procedures sufficient to ensure that the methodis applicable to the routine biomonitoring of arsenic spe-cies in molluscs from contaminated areas; and (iii) thecontrol of correlation between the total and speciated ar-senic compounds in mussel samples. (From the samesamples, the total and methylated mercury were also de-termined and reported [22]).

Experimental

Sample collection

Mussels were cultivated in the low-arsenic waters ofSanta Gilla Pond and Olbia (Italy) and then transplantedat eight sampling sites along the coastline of Sardinia(signed with the name of marinas). All sized mussels wereset at depths between 3 and 5 m from the surface and be-tween 1.5 and 10 m from the bottom. Mussel collectionwas performed in autumn and winter, before the start ofthe animals’ reproductive cycle, i.e. 4 weeks after trans-plantation.

Samples from the Gulf of Venice were collected at 13sampling sites located in the vicinity of ports and marinas(signed with numbers). Both mussels (signed with ‘A’)and clams (signed with ‘B’) were collected.

Sample treatment

Sample preparation

After sampling, the molluscs were rinsed in millipore-grade water to remove any residual sand and then deep-frozen, homogenised in a blender, lyophilised and ho-mogenised again. Speciation of arsenic was carried out onthis dry material.

McSheehy et al. [23] compared the effects of three sol-vent systems (water, methanol and 1:1 methanol-water) onboth the species and the total amount of arsenic extracted.Because the reported data showed no difference betweenthe various solvent systems, water was used as the extrac-tant in this work.

Extraction of arsenic species

An aliquot of homogenised mollusc tissue (0.3 g) wasweighed into a polycarbonate bottle and extracted into de-ionised water (3 ml). The bottle was then placed in a shak-

26

ing water bath for 60 min at 85 °C. In order to avoid thedeposition of solid material onto the side of the plastic bot-tles, the speed of the shaking water bath was programmed inthree steps. The samples were then centrifuged for 25 minat three different settings (3800, 3900 and 4000 g) and theresulting supernatant was collected in a volumetric flask(5 ml). The sample was made up to volume with deionisedwater and thoroughly mixed prior to fitration (Milliporemembrane filters, 0.45 µm HA). The extracts were thenanalysed immediately with the two different HPLC-HG-AFS systems described in the next section.

In order to obtain information on the efficiency of theextraction, a mass balance calculation was carried out us-ing ‘totals’ data for the levels of arsenic in the mollusc tis-sue, in the solid centrifuge pellet and in the supernatant.

All samples were subjected to a hydrogen peroxide/ni-tric acid digestion, where 2 ml of 30% H2O2 and 2 ml ofconcentrated HNO3 were added to 0.2 g of sample in aPTFE bomb and total digestion was carried out in a mi-crowave oven. The final volume was 10 ml. All sampleswere analysed in triplicate.

Instrumentation

The HPLC system comprised a Merck Model L-7100 qua-ternary pump (Merck) fitted with an on-line degassingsystem. Samples were introduced on to the column usinga Rheodyne 7125 injector (Rheodyne, Cotati, CA, USA)fitted with a 100-µl sample loop. The column was a Hamil-ton PRP-X-100 (250×4.1 mm, 10 µm) for anionic separa-tion and a SuperCosil LC-SCX (250×4.6 mm, 5 µm) forcationic separation. A guard cartridge containing the samestationary phase as the analytical column was used witheach system. Multichannel peristaltic pumps (Rainin In-struments, Woburn, MA, USA) were used to carry theHCl and NaBH4 solutions into the PEEK (polyether etherketone) mixing chambers of the separation system, allow-ing the eluent from the analytical columns to mix with thereagents for hydride generation (HG).

The anion-exchange separation was carried out using abinary gradient programme (A=10 mM NH4H2PO4 at pH 6.0and B=50 mM NH4H2PO4 at pH 6.0). The flow rate was1.6 ml min–1. Separation was completed within 15 min, giv-ing baseline resolution of As(III), DMA, MMA and As(V).

The cation-exchange separation was carried out usinga binary mobile phase gradient programme [A=deionisedwater (1–10 min) and B=300 mM ammonium formate ofpH 6 (10–25 min)]. The flow rate was 1.5 ml min–1. Sepa-ration was completed within 25 min, giving baseline reso-lution between AsBet and AsCol. In the HG-AFS system,AsBet and AsCol do not form volatile arsines by reduc-tion and can therefore not be detected directly. They there-fore have to be transformed into hydride-forming speciesby ultraviolet photolysis in the presence of 1.5 m/v% potas-sium persulfate, which can be performed on-line prior tothe determination by AFS[24].

The detection limits for AsBet, AsCol, As(III), As(V),DMA and MMA were 20, 40, 15, 30, 10 and 55 ng g–1, re-

spectively. For arsenical determination, the chromatographicsystems were connected to an AFS instrument (PSA10,033 Excalibur, Orpington, Kent, UK) equipped withboosted-discharge hollow cathode lamps (Photron, SuperLamp, Victoria, Australia). Hydrogen-argon diffusion flameswere employed. Constant gas flows were maintained byCole-Palmer rotameters (Niles, IL, USA). The arseno-hy-drides generated were transferred to the AFS detector bymeans of semi-permeable membrane dryer tubes (PermaPure). A Borwin Model digital-analogue converter was usedto acquire the AFS signal, which was then processed us-ing chromatographic software. Determination of total ar-senic in the digested samples, the filtrate and the supernatantwas performed using a Thermo Jarrel Ash ICAP-9000ICP-AES system (the instrument default parameters havebeen described elsewhere [25]).

Reagents and standards

All stock solutions and reagents used were of analyticalreagent grade and all dilutions were prepared using de-ionised water. Arsenite, monomethylarsonic acid and ca-codylic acid (DMA) stock solutions (1000 mg L–1) wereprepared by dissolving As2O3 (Reanal, Budapest, Hun-gary), CH3AsO3Na.6H2O (Carlo Erba, Milano, Italy) and(CH3)2AsO2Na.3H2O (Sigma-Aldrich, Steinheim, Ger-many). Arsenate stock solution (1000 mg L–1) was ob-tained from Merck, arsenobetaine stock solution was BCRCRM 626 and AsCol was a kind donation from K. A.Francesconi. For the procedures the following chemicalswere used: ammonium dihydrogen phosphate from Reanal(Budapest, Hungary), sodium borohydride from Sigma-Aldrich (Steinheim, Germany), sodium hydroxide, hydro-gen chloride and ammonium hydroxide from Merck(Darmstadt, Germany), potassium persulfate from Riedel(Germany). Calibration solution and reagents for hydridegeneration were prepared daily.

Quality assurance and quality control procedures

As has been stated previously, the range of available ref-erence materials for speciation-based quality assuranceprocedures is limited. In this study only a ‘candidate’ ref-erence material (BCR-710) was found as a similar matrix.This material contained several species of arsenic, there-fore it was used as the basis of the QA procedures. Thematerial was produced under the guidance of BCR, therebyallowing the analyst confidence in its homogeneity, and itwas used to assess the precision of the various analyticalstages.

Determined concentrations of total arsenic in musseltissues collected in Sardinia are summarised in Table 1.Three samples were taken from each sampling site andanalysed separately. The average of the three results is re-ported in the table with the calculated relatively low RSD(only in three cases does the RSD exceed 10%), showingthat arsenic distribution in the examined area is relatively

27

homogeneous. Mass balance (amount of extractable ar-senic+amount of non-extractable arsenic=total arsenic)was also determined by ICP-AES. One can conclude thatthe extraction process is under control, because summingextracted fractions and residues, 97±7% of the total ar-senic was measured. From 57% to 81% of the total arsenicin the mussels was found in the final aqueous extracts,which is in good agreement with data measured by McSheehy et al. [23]. On the other hand, the uncertainty ofthe extraction procedure presumably shows the differentchemical composition of the mussel species. From the as-pect of nutrition, mussels contain arsenic mainly in water-soluble form, but in small quantities the interaction withtissues is strong. Supposedly, in the stomach the rest ofthe arsenicals can also be released due to the acidic pH.

The developed method was applied to control the pre-cision of the mussel candidate reference material (BCR-710Oyster Tissue) (Table 2). For comparison with the certifi-cation report, the concentrations are reported as As speciesmolecular weight and not as As. The certification givesthe arsenobetaine concentration as 32.98±5.08 µg g–1 andin the indicative value only the DMA concentration as1.05±0.62 µg g–1. At the moment no reference material isavailable which is certified for all of the six species. Al-though peaks for inorganic arsenic and MMA were alsoobserved in our work, these species and AsCol were pre-sent at concentrations lower than the detection limit. Theextraction efficiency for total arsenic was 82.7% and the

measured concentrations of AsBet and DMA were withinthe certified and indicative concentration ranges. Themeasured AsBet was in the uncertainty range of the can-didate reference material. This indicates that no furthercorrection is needed in the extraction efficiency of analysedmussel samples.

28

Table 1 Material balance of Sardinian samples

Location of Total As RSD Water- Water- Measured Measured (a)+(b) the sample (µg g–1) (%) extractable extractable/total residue residue/total (%)

arsenic arsenicx100 (a) arsenic arsenicx100 (b)(µg g–1) (µg g–1)

Arbatax 11.1 11.2 8.6 77 1.8 16.2 94Villasimius 13.8 3.8 10.5 76 3.2 23.2 99Calasetta 9.6 2.6 7.3 76 2.2 22.9 99Caglari 7.5 2.2 5.3 71 1.6 14.7 92Oristano 7.5 11.1 4.5 60 3.0 40.0 100Alghero 10.3 8.9 8.3 81 2.2 21.4 102Asinara 7.6 15.9 4.3 57 3.6 47.4 104Olbia 9.7 7.0 5.7 59 3.0 30.9 90

average: 97±7

Table 2 Measured values of candidate RM

Arsenic species (µg g–1)

*AsBet 30.46±0.13*As (III) 0.31±0.01*DMA 1.05±0.04*MMA 0.94±0.04*As (V) 0.09±0.00Total amount of arsenicals 19.71±1.00Water-extractable arsenicals 16.32±0.92Non-extractable arsenicals 3.02±0.13

*are given in species moleculare weight

Table 3 Comparison between external and internal calibration ofthe BCR sample. Arsenic amount of the extractant calculated withinternal and external calibration processes

External Internal calibration calibration (ng As mL–1) (ng As mL–1)

As (III) 8.4±0.3 8.1±0.3DMA 26.6±1.0 25.1±1.0MMA 6.4±0.2 6.8±0.3As (V) 1.9±0.1 4.1±0.2AsBet 482±18 463±18AsCol <DL

Fig. 1 External (EX) and standard addition (IN) calibration plotsof DMA from candidate RM. In standard addition 50% of the orig-inal matrix was used

During the analytical process the matrix can influencenot only the separation, but the hydride generation as well.To investigate these phenomena, the anionic and cationicspecies in the candidate reference material (RM) werequantified using internal and external calibration processes(Table 3). The RSD of each concentration was in the 3.9–4.9% range (five replicates). From Table 3 one can see nosignificant difference between the results of the two cali-bration modes except in the case of As(V), where the bigdifference is due to the inaccuracy of standard addition atthis concentration, near to the detection limit. The curvesare practically the same (Fig. 1), showing that there are nointerfering effects of the mussel matrix during the analyt-ical process. Because of the excellent agreement for thecandidate RM analysis, the mussel samples were analysedonly by the less time consuming external calibration.

Results and discussion

For each sample, the concentrations of total arsenic, the fouranionic arsenic species (As(III), As(V), DMA and MMA)and AsBet were determined resulting in several hundredsof items of data. In data treatment, multivariate statisticscannot be used to investigate the relationship between lo-cality and the arsenic level in mussels, because the exam-ined parameters are not independent. It can be done onlyafter the data evaluation of independent parameters, such

as speciation of other elements (tin or mercury). For thestatistical evaluation of As speciation, graphical presenta-tion and plotting have been used to provide reasonable in-terpretation of the data. The mussel and clam sampleswere collected from sites around the island of Sardinia(the names of the sampling cities are cited in Table 4) andthe Gulf of Venice (west coast samples 1, 2, 6, 9, 12 andeast coast samples 3, 4, 5, 7, 8, 10, 11, 13). The total ar-senic concentration ranged from 7.4 to 30.8 µg g–1 dryweight. Focusing on mussel species, it becomes apparentthat samples collected from the east region of the Gulf ofVenice contain nearly twice as much arsenic as those fromalong the western coast sites. Similar results were foundfor the clam samples of Venice gulf. Data measured forSardinian samples are broadly distributed rather than dis-tinct, and only the As contamination in samples collectedfrom Villasimius harbour is relatively high.

It is important to estimate whether speciation providesextra information compared with data from total As deter-mination. For the speciation analysis two HPLC-HG-AFSsystems have been used, where the main tasks were to en-sure the appropriate separation, decrease the noise of thesystems and increase the signal/noise ratio. All the sam-ples were analysed with anion-exchange HPLC-HG-AFS,where NaH2PO4-containing eluent has been reported forarsenic separation. In our study, for anionic separation, theuse of different ionic forms of the eluent was investigatedto obtain an optimal signal/noise ratio. To the system

29

Table 4 Amount of anionicspecies and AsBet in musselsand clams

Samples Amount of Amount of anionic species (ng g–1) Amount Total total anions of AsBet As (ng g–1) As(III) DMA MMA As (V) (µg g–1) (µg g–1)

1A 605 203 137 136 129 5.4 7.42A 101 51 <DL <DL 49 6.3 9.63A 441 101 58 136 146 9.8 13.24B 587 127 71 288 101 11.1 12.85B 283 187 <DL <DL 96 8.9 12.96A 491 138 142 108 103 7.35 7.46B 545 476 <DL <DL 69 4.55 8.47A 367 80 162 125 <DL 24.9 30.88B 414 76 <DL 280 58 7.2 13.99A 314 97 130 <DL 87 5.7 8.39B 534 200 40 136 157 5.9 10.110A 534 173 172 98 90 12.2 12.311A 90 51 <DL <DL 39 12.8 13.311B 653 319 199 <DL 135 24.3 22.812A 296 120 105 <DL 71 7.75 7.812B 540 206 234 <DL 100 5.15 9.613A 468 76 89 207 97 11.6 13.313B 720 238 55 194 233 15.5 18.9Arbatax 48 34 14 <DL <DL 8.5 11.1Villasimius 221 61 160 <DL <DL 10.2 13.8Calasetta 97 53 44 <DL <DL 7.2 9.6Cagliari 131 29 101 <DL <DL 5.15 7.5Oristano 226 81 145 <DL <DL 4.2 7.5Algliero 229 46 183 <DL <DL 8 10.3Asinara 166 57 109 <DL <DL 4.1 7.6Olbia 261 37 224 <DL <DL 5.4 9.7

without a column, 20 ng mL–1 arsenate was injected andthe baseline was monitored after applying three differenteluents and deionised water. A better signal/noise ratio wasobtained using an (NH4)H2PO4 buffer system; NaH2PO4and KH2PO4 produced less sensitivity and more noise(Fig. 2).

The effect can be explained as follows. In the cold hydrogen flame no spectral interference can be expected.On the other hand introducing large amounts of Na- andK-ions into the flame as easily excitable elements allowsthe flame to lose energy for the arsine dissociation, andthe measured signal/noise ratio decreases.

In Fig. 3, an anion-exchange chromatogram is shown.All the unretained arsenic species, which include arsenite

and cationic compounds, are eluted at approximately 2.0 minin the column void volume [26]. On the other hand, with-out photochemical oxidation, the cationic species are in-visible for AFS because they do not form volatile hy-drides, and the gas-liquid separator does the job. Inorganicarsenate was eluted at approximately 10.5 min. Baselineseparation of all four compounds was obtained. In Table 4,the quantities of the anionic species are presented. Theconcentrations of toxic anionic species were in the range48–720 ng g–1, three orders of magnitude less than theAsBet concentration. The anionic concentration of the mea-sured samples represents the natural toxic contamination.In the samples collected at the Venice coast, in manycases all four measured toxic As species were determined.In samples collected at the Sardinia coast, the concentra-tion of only two toxic species was higher than the detec-tion limit. No local distribution has been found after thestatistical analysis of data from Venice Gulf, but big dif-ferences in total arsenic distribution were observed be-tween two filter-feeding organisms originating from thesame place. Z. Slejkovec et al.agree that clams can accu-mulate more arsenic than mussels at the same locations[27].

All samples were also analysed by cation-exchangeHPLC-UV-HG-AFS, and the results showed that only onepeak was observed for each mussel sample. The retentiontime of AsBet was about 6 min and of AsCol was approx-imately 18 min for a standard solution. In all measuredsamples the AsCol concentration was less than the detec-tion limit. Z. Slejkovec et al. have also reported that AsBet is the most prominent form in mussels [26, 28, 29].The AsBet (Table 4) concentration in samples from theeastern coast of Venice was higher than that in western coastsamples, which agrees with the data for total arsenic con-centration. In the case of samples from the Sardinian coastone can see that, except for one sample (similar to the total concentration) collected at Villasimius where the AsBet concentration is significantly higher than the aver-age, the mean concentration of AsBet is less than that insamples collected at Venice. The contamination (industrialand civilisation) is higher at Venice than at the Sardiniancoast, and the total As and As species concentrations ofmussel samples reflect this.

As a general conclusion of monitoring we can deducethat, from the inorganic toxic arsenic concentration of sea-water in the tissue of mussels and clams, more than 90%of the determined arsenic was converted as a result of bio-detoxification into organic non-toxic AsBet. In Figs. 4aand b, the correlation between the total arsenic and an-ionic (a) and cationic (b) arsenic was investigated. On thebasis of Fig. 4a it appears that no correlation exists be-tween the total arsenic and the anionic species concentra-tion of mollusc samples, it is mainly accidental. On theother hand, the correlation between the total arsenic andAsBet concentration is unambiguous, as the AsBet con-centration in the samples increased with increasing totalAs concentration.

30

Fig. 2 Chromatograms presenting signal/noise ratio following dou-ble injection of arsenate without column. Four different mobile phaseshave been checked: (a) KH2PO4, (b) NaH2PO4, (c) (NH4)H2PO4,(d) H2O

Fig. 3 Determination of toxic arsenic anionic species in sample10A with anion-exchange HPLC-HG-AFS

Conclusions

It seems that there is no implicit need for arsenic specia-tion analysis for the environmental monitoring of As inthe sea, since there is a direct correlation between the to-tal As and AsBet concentration in the case of all samplestested. On the other hand, this is an attempt to show thatthe level of speciation analysis is high enough to help de-cision makers to set legislative standards. More samples,more species determination and higher levels of selectiv-ity and sensitivity will contribute to the deeper under-standing of the marine environment when applying allsorts of monitoring.

Acknowledgements The authors acknowledge the ideas, thesamples and the cooperation of the co-workers of ENEA/PROT(Italy). Prof. A. Contu from the University of Cagliari (Italy) andDr. A. Bortoli from ARPAV (Venice, Italy) are gratefully acknowl-edged for sampling at the Sardinia and Venice sites, respectively.Special thanks to Ms. Ildikó Ipolyi for practical help and to JohnLewis for scientific suggestions. Thanks for the financial help toOTKA (Hung. Sci. Fund) 32296 and 37216.

References

1. Sabbioni E, Fischbach M, Pozzi G, Pietra R, Gallirono M,Piette J (1991) Carcinogenesis 12:1287

2. Burguera M, Burguera JL (1997) Talanta 44:15813. Francesconi KA, Edmonds JS (1993) Oceanogr Mar Biol Annu

Rev 31:1114. Ackley KL, B’Hymer C, Sutton KL, Caruso JA (1999) Anal At

Spectrom 14:8455. Phillips JH, Rainbow PS (1993) Biomonitoring of trace aquatic

contaminants. Elsevier, London6. Markert B(ed) (1993) Plants as biomonitors. VCH, New York

7. Emons H, Schladot JD, Schwuger MJ (1997) Chemosphere 34:1875

8. Oehlmann J, Stroben E, Schulte-Oehlmann U, Bauer B, Fio-roni P, Markert B (1996) Fresenius J Anal Chem 354:540

9. Lohan MC, Statham PJ, Peck L (2001) Polar Biol 24:80810. Al-Aasm IS, Clarke JD, Fryer BJ (1998) Environ Geol 33:12211. Ebdon L, Hill S, Walton AP, Ward RW (1998) Analyst 3:115912. Wickenheiser EB, Michalke K, Drescher C, Hirner AV, Hensel

R (1998) Fresenius J Anal Chem 362:49813. Mester Z, Vitanyi G, Morabito R, Fodor P (1999) J Chro-

matogr A 832:18314. Prohaska T, Pfeffer M, Tulipan M, Stingeder G, Mentler A,

Wenzel WW (1999) Fresenius J Anal Chem 364:46715. Huang Y-M, Whang C-W (1998) Electrophoresis 19:214016. Van den Broeck K, Vandecasteele C (1998) Mikrochim Acta

128:7917. Van Holderbeke M, Zhao YN, Vanhaecke F, Moens L, Dams

R, Sandra P (1999) J Anal At Spectrom 14:22918. Gómez-Ariza JL, Sánchez-Rodas D, Beltran R, Corns W,

Stockwell P (1998) Appl Organomet Chem 12:43919. Morabito R, Kramer K, Donard OFX, Muntau H, Lobinske R,

French W, Bowadt S, Quevauviller P EUR report, Brussels (inpress)

20. McSheehy S, Spuznar J, Morabito R, Quevauviller P The spe-ciation of arsenic in biological tissues and the certification ofreference materials for quality control. Submitted to TrAC

21. Valdovinos C, Zuniga M (2002) Bull Environ Contam Toxicol69:393

22. Ipolyi I, Massanisso P, Sposato S, Fodor P, Morabito R Con-centration levels of total and methyl mercury in mussel sam-ples collected along the coasts of Sardinia Island. Anal ChimActa (in press)

23. McSheehy S, Pohl P, Lobinski R, Szpunar J (2001) Analyst126:1055

24. Sur R, Begeraw J, Dunemann L (1999) Fresenius J Anal Chem363:526

25. Müller J (1999) Fresenius J Anal Chem 363:57226. Slejkovec Z, van Elteren JT, Byrne AR (1997) Acta Chim Slov

44:22527. Slejkovec Z, Byrne AR, Smodis B, Rossbach M (1996) Frese-

nius J Anal Chem 354:59228. Shiomi K, Kakehashi Y, Yamanaka H, Kikuchi T (1987) Appl

Organomet Chem 1:17729. Cullen WR, Dodd M (1989) Appl Organomet Chem 3:79

31

Fig. 4 a Distribution of sum of anionic species versus total ar-senic. b Distribution of AsBet versus total arsenic