Chemical Contamination Baseline in the Western Basinof the Mediterranean Sea Based on Transplanted Mussels
Bruno Andral • Francois Galgani • Corinne Tomasino • Marc Bouchoucha •
Charlotte Blottiere • Alfonso Scarpato • Jose Benedicto • Salud Deudero •
Monica Calvo • Alexandro Cento • Samir Benbrahim • Moustapha Boulahdid •
Cherif Sammari
Received: 19 March 2010 / Accepted: 23 August 2010 / Published online: 23 September 2010
� Springer Science+Business Media, LLC 2010
Abstract The MYTILOS project aimed at drawing up a
preliminary report on coastal chemical contamination at the
scale of the Western Mediterranean (continental coasts of the
Balearic Islands, Sicily, Sardinia, Corsica and Maghreb)
based on a transplanted mussels methodology validated
along the French coasts since 1996 by Ifremer and the Rhone
Mediterranee & Corsica water board. MYTILOS is backed
up by the INTERREG III B/MEDOC programme, the
PNUE/PAM-MEDPOL and Rhone Mediterranee & Corsica
water board. Three cruises (2004, 2005, 2006) have taken
place to assess the first state of chemical contamination along
the Western Mediterranean shores with the same method-
ology. Approximately 120 days were spent at sea deploying
and retrieving 123 mussel bags. The results obtained for all
studied contaminants were equivalent to those obtained
along the French coast according the RINBIO network.
These similarities relate to both the highest measured levels
and background levels throughout the 123 stations. The areas
of greatest impact were mainly urban and industrial centers
and the outlets of major rivers, with a far higher midsea
impact on the dilution of organic compounds than on metals.
Metal levels measured in midsea zones were found to be
similar to those in natural shellfish populations living along
the coast. On a global scale we can observe that the con-
taminants levels in the Mediterranean Sea are in the same
range as in other areas worldwide. Overall, the research
demonstrates the reliability of this methodology for marine
pollution monitoring, especially in the Mediterranean sea.
Marine mussels (Mytilus spp.) are known to be good can-
didates for quantitative biomonitoring of chemical
B. Andral (&) � F. Galgani � C. Tomasino � M. Bouchoucha
IFREMER, Laboratoire Environnement Ressource Provence
Azur Corse, BP 330-83507 La Seyne sur Mer Cedex, France
e-mail: [email protected]
C. Blottiere
TVT, Maison des Technologies, Place G. Pompidou,
83 000 Toulon, France
A. Scarpato
ISPRA, Via di Casalotti, 300 Rome, Italy
J. Benedicto
IEO/Murcia, Calle Varadero no. 1,
30740 San pedro de Pinatar, Spain
S. Deudero
Univ Balears/IMEDEA, Cra. de Valldemossa, Palma 07122,
Illes Balears
M. Calvo
CSIC-ACA, Jordi Girona 18-26, 08034 Barcelona, Spain
A. Cento
PSTS, Zona Industriale Blocco Palma 1,
S G. Agnelli Angolo, 95030 Catania, Sicily
S. Benbrahim
INRH, rue de Tiznit, Casablanca 01, Morocco
M. Boulahdid
ESSMAL, bois des cars, BP 19, 16320 Alger, Algeria
C. Sammari
INSTM, 28 rue du 02 mars 1934, 2025 Salammbo, Tunisia
123
Arch Environ Contam Toxicol (2011) 61:261–271
DOI 10.1007/s00244-010-9599-x
contaminants in coastal waters (Cossa 1989; Goldberg 1975;
Phillips and Rainbow 1993). They concentrate chemical
contaminants in their soft tissue up to 105 times more than the
concentration in water and they have a large geographical
distribution and a high tolerance to stress. They have already
been widely used in the so-called ‘‘passive’’ or ‘‘active’’
Mussel Watch Programmes (Honkoop et al. 2003; Kramer
1994; Martin et al. 1984; Sericano et al. 1995; Widdows et al.
1995). The previous studies such as the US Mussel Watch
and the French RNO (Claisse 1989) used indigenous mus-
sels. The latter studies used transplanted mollusks as in the
French RINBIO network (http://www.ifremer.fr/envlit/)
(Andral et al. 1998; Cossa 1989; De Kock and Van Het
Groenewoud 1985; Riget et al. 1997).
Mollusks transplantation from a clean reference site to a
contaminated area can be an effective strategy for biomon-
itoring the effects of environmental changes in coastal zones
(Andral and Stanisiere 1999; Andral et al. 2001; Buestel
1997; De Kock 1983; De Kock and Van Het Groenewoud
1985; Odzac et al. 2000). The caging technique compensates
for the scarcity of natural shellfish stocks in many parts of the
coast. Bioaccumulation results from a pseudoequilibrium
between the concentration of the micropollutant in the
organism and levels in the environment (Borchard 1983;
Cossa 1989). It is based on the processes of absorption,
excretion, and accumulation. The amount of bioaccumulated
contaminants is closely linked to the mussel’s life cycle,
particularly the individual’s age and sexual maturity. Char-
acteristics of the immersion site, such as salinity and food
availability, influence pollutant bioavailability and specia-
tion as well as the metabolism and tissue growth of the
mussel, in which the pollutant is diluted (Cossa 1989; Kra-
mer 1994; NAS 1980; Phillips 1976). The transplantation
method makes it possible to control the source, age, and stage
of sexual maturity of the samples. However, implementing it
on a large geographic scale introduces factors such as vari-
ations in physiochemical characteristics and food availabil-
ity in the immersion zones. Although the concentrations
measured in the tissue are an indicator of bioavailable pol-
lutant levels, the bioaccumulation factor depends on mussel
growth in relation to the primary food production, or trophic
capacity, of the environment. Comparison of raw data on
tissue concentration between sectors of different trophic
potential might be misleading.
The Condition Index (CI), defined as the ratio of the soft
tissues dry weight over shell weight (Andral et al. 2004), is
a good indicator of the physiological state and growth
resulting from the environmental effect. The results
obtained by the RINBIO network show a strong correlation
between the CI and contaminant concentration in all geo-
graphical zones for certain contaminants, especially heavy
metals. It is therefore possible to define a correction model
for these contaminants and to obtain a concentration,
independent from the environmental effect, that can be
considered representative of bioavailable contaminant
concentration in the environment. On a large spatial scale,
this model enables the results to be adjusted for standard
mussels, and this makes result comparisons easier.
This original technique, validated along the French coast,
has been deployed in the West Mediterranean basin in our
studies in the context of the MYTILOS European project.
The purpose of MYTILOS is to obtain with the same
methodology the first map of coastal chemical contamina-
tion along the Western Mediterranean coast, including the
coast of Tunisia, Algeria, Morocco, Spain, France, Italy, the
Balearic Islands, Sicily, Sardinia, and Corsica.
MYTILOS is supported by the INTERREG III B/
MEDOC program, steered by Ifremer and backed by
Toulon Var Technologies, in cooperation with the ISPRA
(Italy), IEO (Spain), PSTS (Sicily), IMEDEA (Balearic
Islands), CSIC and the Agence Catalane de l’Eau (Cata-
lonia), INSTM (Tunisia), ISMAL (Algeria), INRH, DSPR,
and University of Agadir (Morocco). MYTILOS is also
backed by the PNUE/PAM–MEDPOL program and Rhone
Mediterranee & Corsica water board.
Materials and Methods
Transplantation
The species used was Mytilus galloprovincialis. The mus-
sels came from a firm in Languedoc-Roussillon that har-
vests contamination-free mussels from the open sea. The
batch was made up of adult mussels 18–24 months old, of
about 50 mm in dimension. The 3-kg samples were stored
in conchylicultural pouches mounted on PVC tubing and
reimmersed for 5 days so they could recluster prior to
transplantation.
Subsurface anchorages, consisting of a mussel bag
attached to a 30-kg weight, were kept in open water at a
depth of 15 m using an 11-l float. To compensate for
accidental trawl fishing losses, the subsurface anchorage
was doubled or even tripled at most stations to increase
chances of retrieval.
The stations were placed for 3 months at various depths
and distances from the coast. Generally, the depth was
20–50 m according to coastal configuration, and the bags
were attached at depths of 8–10 m. The aim was to locate
each station in an equivalent continental input dilution
volume to avoid being under the direct influence of one
contamination source.
A total of 149 stations were deployed during three
sample deployment periods. The deployment was con-
ducted using the R/V l0 Europe, which was able to carry the
3.5-m3 tanks used to transported the mussel bags plus all
262 Arch Environ Contam Toxicol (2011) 61:261–271
123
anchorage equipment. The deployments were conducted
during the mussels’ period of sexual dormancy. The
deployments dates and regions were as follows: Mytilos I
(March 20–April 15, 2004) extended from Cartagena
(Spain) to Orbelleto (Italy); Mytilos II (March 21–April 19,
2005) covered southern Italy and part of southern Spain as
well as the Balearic Islands, Sardinia, and Sicily; Mytilos
III (May 16–June 3, 2006) covered Corsica, the extreme
southern coasts of Spain, and the Maghreb coasts (Mor-
occo, Algeria, and Tunisia).
Recovery
The samples were hauled with two vessels (‘‘Tethys II’’
and ‘‘Europe’’) on different occasions. Oceanographic
vessels provided vital logistical support (diving logistics,
sample processing, preparation), including a zodiac
equipped with detection instruments (sweep sonar, vertical
echo sounder) for station retrieval operations. Retrieval
was mainly done by diving. Operations were fast and safe
and because the bags resided at depths of 8–10 m, no
decompression was needed.
The retrieval dates were July 2–21, 2004, June 17–26,
2005, and August 10–27, 2006. After retrieval, the mussels
were separated and rinsed in seawater. At each station, the
length of the shell was recorded, the mussels were opened
raw, and the flesh was scraped out of the shell with a
stainless-steel scalpel. For each sample, pooled shells were
dried at 60�C in an oven for 48 h and then weighed. Pooled
flesh was weighed after freeze-drying. The ratio of dry
flesh weight to dry shell weight (FW/SW) was used to
determine the CI for each sample.
Analysis
Before the chemical analysis, mussel tissues were dried and
homogenized. The quality of analytical data was checked
by the analysis of certified reference material. Analyses
were performed under the Quasimeme assurance quality
program. The following techniques were used to test for
contaminants.
For heavy metals, 0.5 g of freeze-dried sample was
mineralized by an HNO3 solution at 90�C.
Quantification of lead, cadmium, and nickel was
performed by atomic adsorption spectrometry with a
Zeeman-effect graphite furnace [detection limit: 0.1 mg/
kg dry weight (dw)].
Mercury was determined by atomic fluorescence after
reduction with an SnCl2 solution (detection limit:
0.01 mg/kg dw).
DORM2 certified mussel reference materials was used to
control analytical reliability.
For dichlorodiphenyltrichlorethane and its metabolites
(DDT ? DDD ? DDE), hexachlorocyclohexane (aHCH,
cHCH), and polychlorobiphenyls (PCBs), 5 g of freeze-
dried sample were extracted by hexane/acetone solution
and cleaned up with sulfuric acid.
PCB 205 and PCB 207 as internal standards were added
for recovery estimates. Analyses were performed by
capillary gas chromatography coupled with an electron
capture detector (detection limit: 1 lg/kg dw).
For polycyclic aromatic hydrocarbons (PAHs), 5 g of
freeze-dried sample were extracted by hexane/acetone
solution and cleaned up with a silica gel cartridge.
Fluorene D10 and Perylene D12 as internal standards
were added for recovery estimates. Analyses were
performed by capillary gas chromatography coupled with
mass spectrometry (detection limit: 1–10 lg/kg dw).
For dioxins, 5 g of freeze-dried sample were extracted by
dichloromethane/acetone solution and cleaned up with a
silica gel cartridge, an alumin column, a florisil column,
active carbon, and sulfuric acid. The 16 congener of
dioxins and furans marked by 13C as the internal standard
was added for recovery estimates. Analyses were per-
formed by high-performance chromatography combined
with mass spectrometry (detection limit: 1 lg/kg dw).
For nonionic detergents such as nonylphenols [4-(para)-
nonylphenol] and octylphenols (para-tert-octylphenol),
5 g of freeze-dried sample were extracted by hexane/
acetone solution and cleaned up with a fluorisil column.
Phenanthrene D10 as the internal standard was added for
recovery estimates. Analyses were performed by gas
chromatography coupled with mass spectrometry (detec-
tion limit: 10 lg/kg dw).
For brominated diphenyl ethers, 5 g of freeze-dried
sample were extracted by hexane/acetone solution and
cleaned up with a fluorisil column. PCB 209 as the
internal standard was added for recovery estimates.
Analyses were performed by gas chromatography com-
bined with mass spectrometry–CI negative (detection
limit: 1 lg/kg dw).
All of the above compounds were analyzed for each
station, except dioxins, brominated diphenyl ethers, and
nonionic detergents, which were measured at around one
out of five stations. Considering the cost of analysis, these
compounds were measured on a reduced number of sam-
ples that were situated in front of urban and industrial
centers and in front of major rivers.
All results are expressed in micrograms, nanograms, or
picograms of contaminants per gram of dry mussel flesh.
For dioxins, results are expressed according to the potential
toxicity of the measured elements compared to the most
toxic compound: 2,3,7,8-TCDD (tetrachloro-dibenzo-p-
dioxin). The potential quantity of associated dioxins and
Arch Environ Contam Toxicol (2011) 61:261–271 263
123
furans is described using the toxic equivalent quantity
(TEQ), expressed in equivalent dioxin (Van den Berg et al.
1998). It corresponds to the sum, for all measured toxic
congeners, of concentrations weighted by the TEF (toxic
equivalent factor).
Data Standardization
The use of linear regression analysis for each contaminant
statistically infers that tissue concentration under steady-
state conditions can be a function of the CI. Depending on
the contaminant, a few stations that were apparently located
in contaminated areas did not obey this rule: They stand out
from linear models due to their consistently higher results.
For each contaminant, these outlying values were
removed and the parameters of the model describing the
effect of mussel physiology bioaccumulation were calcu-
lated. These regression lines allow one to normalize the
measured concentrations to a reference CI, and the con-
taminant levels are then comparable at a large spatial scale,
independently of the trophic conditions prevailing around
the sampling sites (Andral et al. 2004).
Data were regrouped for each of the regional subbasins
proposed by the MEDPOL program (UNEP/MAR/WMO
2001): Alboran (Alb), North Western (NW), South Wes-
tern (SW), and Tyrrhenian (Tyr) and descriptive statistics
were calculated. Significant differences between each
subbasin or country were calculated and analyzed in more
detail by the family of contaminants in published (Galgani
et al. 2010; Scarpato et al. 2009) or submitted (Benedicto
et al. 2010) articles.
Results
A total of 123 stations was retrieved from the 149 stations
originally deployed (82.5%) (Fig. 1).
Biometric Parameters
The analysis of shell height distribution showed that the
collected samples were well calibrated (Table 1). How-
ever, the analysis of flesh dry weight showed very marked
trophic variations between study sites. Growth conditions
in Alb (1.282 ? 0.343 g) and NW (1.049 ? 0.432 g) were
generally better than the SW (0.735 ? 0.223 g) and Tyr
(0.724 ? 0.222 g) basins. We also observed more favor-
able growing conditions in southern Spain, in the Ebre and
Rhone rivers input zones, and, generally speaking, in areas
adjacent to major cities and ports (Palma, Barcelona, and
Marseille). This observation was confirmed by the distri-
bution of individual flesh dry weight and by the condition
index.
Raw Contaminant Concentrations
The raw concentration results show that growth has a major
impact on result distribution, especially with regard to
heavy metals. Some trace metals (Cd, Hg, and Ni) showed
systematically higher levels in the most oligotrophic zones,
in relation to the distribution of the mussel condition index.
For example, the raw values of Cd measured in the Balearic
Islands were two to three times higher than those measured
at the mouth of the Ebre and on the Spanish coast (Fig. 2).
Concentrations of the vast majority of PCB congeners
were lower than the detection limits for the study. PCB 153
and PCB138 were the most reliable markers and were
present in all samples; their distribution is similar to that of
the sum of the 10 congeners.
Regarding PAHs, out of the 16 compounds analyzed, a
large majority did not exceed the analytical limit of
detection. At the scale of the three cruises, no compound
showed a distribution profile identical to that of the sum of
the 16 compounds. Compound distribution between sta-
tions was widely heterogeneous in comparison, for exam-
ple, to that of PCBs. aHCH, bHCH, and cHCH did not in
any case exceed the limit of detection in coastal zones.
Finally, metabolites of DDT were the most commonly
found elements.
Analysis of brominated diphenyl ethers and nonionic
detergents all showed results below the analytical limit of
detection. Regarding values that were lower than the ana-
lytical limit of detection, half of the detection limit value
was retained for data processing purposes for the other
contaminants.
Models
For each contaminant, adjustment parameters calculated on
the basis of the raw data from this campaign are presented
in Table 2. Models were significant (p values \ 0.05) for
most contaminants, with the exception of PAHs, which
showed no correlation between CI and tissue concentration.
The highest growth effect was observed for Cd, Hg, and
Nil, with a variation of more than 50% in results explained
by sample growth.
Adjusted Data
The value of the reference condition index is 0.11, which
corresponds to the mean of the CIs obtained from each
sample. Raw data were adjusted using this value and the
parameters for each model. However, data on PAH were
not processed according to this method.
For each contaminant, descriptive data statistics from
this campaign are presented in Table 3 by regional subba-
sin. At the scale of the studies, the distribution adjusted data
264 Arch Environ Contam Toxicol (2011) 61:261–271
123
for Pb was relatively homogenous, with an average value of
1.41 lg/g and a median of 1.17 lg/g. However, two sites
were pinpointed as being particularly impacted by lead: the
Portoscuso industrial site (subbasin SW), with a maximum
of 8.25 lg/g and the zone extending from Portman to El
Portus (Alb subbasin) from 5.3 to 6.25 lg/g, which was
home to a thriving mining industry with the dumping of
50 9 106 tons of waste-mining during the intensive
extractive activities carried out during the 1960–1990 per-
iod. The maximum levels observed in the NW subbasin are
in the area of Barcelona (2.79 lg/g) and in the Tyr subbasin
in Porto Ferrario on Elba Island (3.05 lg/g).
Adjusted levels of Cd were globally homogenous
throughout the stations, with an average of 1.32 lg/g and a
median of 1.28 lg/g. A few stations showed relative peaks
of around 2 lg/g: Filicudi and Ustica stations in the
Tyr subbasin (Sicily) and Aguilas and Adra in Spain
(Alb subbasin).
Several sites impacted by Hg were recorded: first and
foremost the Portoscuso site in Sardinia (SW subbasin),
with a maximum level of 0.31 lg/g, witnessing significant
contamination generated by a large industrial complex. To
a slightly lesser degree, high levels are recorded in the SW
subbasin in Skida (0.19 lg/g) and in the Tyr subbasin,
especially in Palermo (0.22 lg/g).
Average adjusted concentrations of Ni were around
1.1 lg/g, with a median of 0.94 lg/g. Extreme values were
found in some sampling sites in SW subbasin, especially in
Tunisia (Tabarka, 3.18 lg/g), Algeria (Oued Zhor,2.89 lg/g;
Oran,2.47 lg/g), Morocco (Nador, 2.72 lg/g), and the south
of Spain (Fuengirola, 2.44 lg/g). Median values between
each subbasin are homogeneous.
The average value of the sum of DDT compounds was
3.93 ng/g, with a median of 3 ng/g at the scale of the study.
For this compound, median values between each subbasin are
also similar. Significant peaks were recorded in the NW and
Tyr subbasins, especially in front of Marseille (15.47 ng/g),
Barcelone (15.17 ng/g), and Napoli (15.34 ng/g). In the SW
subbasin, Algiers also showed a high level (10.23 ng/g). The
level recorded at the Algiers station was equivalent to the
overall levels recorded at stations off the coast of the
following rivers and streams: Ebre, Rhone, and, to slightly
lesser levels, Tet, Aude, Herault (NW subbasin), and Tevere
(Tyr subbasin).
Fig. 1 Location of the artificial mussel stations deployed for the MYTILOS project
Arch Environ Contam Toxicol (2011) 61:261–271 265
123
Regarding the sum of the 10 congeners of PCBs and the
PCB153, the distribution showed a similar profile. The
average value of the sum of PCBs compounds was
14.58 ng/g, with a median of 8.98 ng/g at the scale of the
studies. The results indicate the presence of sites impacted
by PCBs, in the NW sub basin(Barcelona, 63.87 ng/g;
Marseille, 103.52 ng/g), the Tyr subbasin (Naples.
91.48 ng/g), and SW subbasin (Algiers, 51.13 ng/g).
This characteristic presence of PCBs in front of major
urban centers is further confirmed by values obtained in the
Tyr subbasin at La Maddalena (58.49 ng/g), adjacent to a
major naval base. To a lesser degree, inputs by the Ebre
(20.37 ng/g) and Rhone rivers (37.80 ng/g) can also be
pinpointed.
Results concerning the sum of the 16 dosed molecules
for PAHs are expressed in raw values. Large data hetero-
geneity was observed at the scale of the study, with an
average value of 46.51 ng/g and a median of 44.4 ng/g.
Two peaks were identified in the NW and Tyr subbasins
situated in Marseille (105.5 ng/g) in France and Piombino
in Italy (80.8 ng/g), adjacent to a large industrial complex.
Regarding fluoranthene—considered by the RINBIO
and RNO networks as the best representative of PAHs—we
also observed large data heterogeneity, with the highest
levels at the Bagnoli station (15.93 ng/g) in the Naples bay.
However, the peaks identified using the sum of 16 PAHs at
Cortiou and Piombino were not found for this compound.
Table 1 Statistical distribution of biometric parameters
N SH SW FW FW/N CI Fat
Alboran
Mean 11.7 237.000 102.867 14.457 1.282 0.143 6.266
Standard
dev.
1.7 15.152 9.900 2.350 0.343 0.032 1.735
SW
Mean 16.9 237.737 138.282 11.919 0.735 0.091 7.350
Standard
dev.
2.7 19.119 26.881 1.895 0.223 0.027 2.824
TYR
Mean 18.8 236.717 149.215 13.263 0.724 0.089 5.971
Standard
dev.
6.4 19.314 39.544 5.696 0.220 0.024 2.822
NW
Mean 24.3 243.420 197.857 25.810 1.049 0.126 5.881
Standard
dev.
6.4 13.528 50.827 11.721 0.432 0.045 2.728
N number of individuals per batch, SH shell height (mm), SW shell
weight (g), FW flesh weight (g), FW/N individual flesh weight (g), CIcondition index (FW/SW), fat content (%)
Fig. 2 Raw levels of cadmium
in lg/gof dry flesh (filled circle)
along the Spanish
Mediterranean coast and the
Balearic Islands against the CI
(open triangle)
Table 2 CI/contaminant level regression models
Contaminant Model R2 Cp
Cadmium Cd = 0.124[1/CI] ? 0.01 84.65 \0.0001
Lead Pb = 0.021[1/CI ] ? 0.932 6.57 0.01
Mercury Hg = 0.008 [1/CI ] ? 0.007 81.71 \0.0001
Nickel Ni = 0.049[1/CI ] ? 0.41 50.25 \0.0001
Sum of DDTs DDTs = 15.398CI ? 1.328 19.44 \0.0001
Sum of PCBs PCBs = 39.236CI ? 5.174 14.78 \0.0001
Sum of 16 PAHs PAHs = –36.277CI ? 43.223 1.41 0.21
Dioxins DEF = 3.069CI ? 0.145 47.47 \0.0001
R2: regression coefficient; Cp: critical probability
266 Arch Environ Contam Toxicol (2011) 61:261–271
123
Regarding the results for the dioxines compounds, the
median distribution is situated at *0.7 pg/g (TEQ).
Medians for the Tyr and the NW subbasins are higher. One
peak recorded in the Marseille area reveals the existence of
significant inputs of these compounds (2.66 pg/g). It also
confirms the peak measured for PCBs, which belong to the
same compound family. On the project scale, we observed a
similar distribution to that of PCB congeners, with highest
values at Barcelona, La Maddalena, Napoli, and Algiers.
Discussion
The MYTILOS project confirmed the operational viability
of the RINBIO methodology. The project’s logistics,
anchorage structures, and deployment/retrieval techniques
allowed cost minimization, plus a highly satisfactory
retrieval rate taking into account the shape and diversity of
the studied coasts.
The CI distribution is indicative of the trophic hetero-
geneity of the Mediterranean coastal waters. Overall, the
waters are richer in the NW subbasin, due to the nutrients
contributed by the Rhone (Minas and Monas 1989) and the
Ebre rivers. In the Alb subbasin, this high productivity is
due to a nutriment enrichment, which has an Atlantic or a
Mediterranean origin in relation with upwelling activities
(Minas et al. 1984).
The CI distribution also provides clues as to the levels of
chemical contamination (except PAH), especially in the
case of trace metals. These findings can be explained by
greater tissue growth in areas where concentrations in the
waters are the highest and thus require adjustment with
reference to a standard CI. Tissue growth is especially
likely to mask or dilute the levels measured in the case of
metals like Cd, which is essentially present in seawater in a
dissolved form. Its uptake and bioaccumulation via feeding
(filtered particles) is negligible (Borchardt 1985; Riisgaard
et al. 1987).
In a more general way, the most highly impacted zones
were mainly situated adjacent to urban and industrial
centers and the outlets of major rivers.
During this study, all measured contaminants showed
equivalent levels to those recorded by the RINBIO network
(Andral and Tomasino 2004, 2007). This similarity related
to both highest levels and the background noise recorded at
the 123 study stations.
This method is also valuable in that it makes it pos-
sible to confront the adjusted data to those available on
Table 3 Statistical distribution of adjusted data (Pb, Cd, Hg, Ni, DDTs, CB 153, PCBs, dioxins) and raw data (fluoranthene, PAHs) in dry
weight
Pb
(lg g-1)
Cd
(lg g-1)
Hg
(lg g-1)
Ni
(lg g-1)
Sum of DDTs
(ng g-1)
CB 153
(ng g-1)
Sum of PCBs
(ng g-1)
Fluo
(ng g-1)
Sum of PAHs
(ng g-1)
Sum of dioxins
(pg g-1)
Alboran
Median 1.097 1.542 0.087 0.837 3.145 2.114 7.870 1.568 38.400 0.386
Mean 1.498 1.554 0.087 1.099 3.688 2.445 8.826 1.691 43.067 0.386
Standard Dev. 1.379 0.278 0.021 0.627 2.073 1.948 4.423 0.845 17.087 0.003
Max 6.254 2.114 0.152 2.722 7.514 6.821 18.749 4.080 84.600 0.388
SW
Median 1.260 1.399 0.101 0.900 2.411 1.837 7.859 1.683 42.800 0.403
Mean 2.184 1.386 0.113 1.072 3.188 3.212 11.436 2.244 46.774 0.534
Standard dev. 2.125 0.180 0.057 0.300 1.957 4.627 10.448 1.782 14.434 0.276
Max 8.249 1.684 0.309 2.908 10.215 19.555 51.135 7.426 79.600 1.022
TYR
Median 1.020 1.224 0.098 0.962 3.242 2.316 9.438 1.988 47.700 0.530
Mean 1.106 1.262 0.102 1.127 3.951 4.668 15.221 2.931 48.310 0.653
Standard dev. 0.405 0.231 0.026 0.519 2.584 6.257 16.072 3.016 14.138 0.306
Max 3.057 2.045 0.216 3.198 15.333 28.046 91.486 15.934 80.400 1.493
NW
Median 1.297 1.273 0.084 0.926 3.060 2.552 9.997 1.553 41.900 0.494
Mean 1.357 1.292 0.087 0.979 4.429 4.965 17.122 1.827 45.900 0.668
Standard dev. 0.416 0.214 0.012 0.275 3.509 7.914 19.232 1.794 18.351 0.540
Max 2.790 1.968 0.123 1.845 15.445 40.707 103.524 10.819 105.500 2.667
Arch Environ Contam Toxicol (2011) 61:261–271 267
123
Ta
ble
4B
asel
ine
for
the
MY
TIL
OS
pro
ject
,R
INB
IO,
RN
On
etw
ork
and
wo
rld
wid
ed
ata
(in
mg
orl
g/k
gd
ryw
eig
ht)
Loca
tion
Yea
rS
pec
ies
Dat
aP
b
(lg
g-
1)
Cd
(lg
g-
1)
Hg
(lg
g-
1)
Ni
(lg
g-
1)
DD
T
(ng
g-
1)
DD
Ts
(ng
g-
1)
CB
15
3
(ng
g-
1)
PC
Bs
(ng
g-
1)
Flu
o
(ng
g-
1)
PA
Hs
(ng
g-
1)
Ref
eren
ces
Wes
tM
edit
erra
nea
nco
ast
2004–2006
Tra
nsp
lante
d
Mu
ssel
Med
ian
1.1
71
.29
0.0
90
.94
0.5
32
.28
.98
1.7
54
4.4
Th
isst
ud
y
Min
0.6
0.8
60
.05
0.6
20
.51
.50
.51
.83
0.5
21
.9
Max
8.2
52
.11
0.3
3.1
86
15
.54
1.3
10
3.5
16
10
5.5
Fre
nch
Med
iter
ranea
nco
ast
2006
Tra
nsp
lante
d
Mu
ssel
Med
ian
1.0
70
.88
0.0
70
.93
0.5
06
.60
4.0
41
2.4
62
.10
33
.05
An
dra
lan
d
To
mas
ino
(20
07)
Min
0.2
80
.40
.02
0.4
70
.50
1.5
00
.50
1.4
70
.50
18
.50
Max
8.4
42
.67
0.2
32
.48
5.4
07
0.8
b4
4.3
01
36
.74
12
.30
82
.30
Fre
nch
Med
iter
ranea
nco
ast
1995–1999
Muss
elM
ean
1.8
0.7
20.1
21.4
815.1
18.7
13.2
RN
O(2
00
6)
Min
0.1
0.2
0.0
40
.47
1.8
71
.57
2.1
9
Max
10
0.6
88
.41
83
.2b
59
32
43
Fre
nch
atla
nti
c/ch
anel
coas
t1995–1999
Muss
elM
ean
1.4
0.6
0.1
21.5
55.3
19.4
21.4
RN
O(2
00
6)
Min
0.4
0.1
70
.03
0.4
50
.63
0.1
64
Max
9.6
3.0
30
.53
63
6.6
49
52
45
No
rth
Sea
19
93
Mu
ssel
Med
ian
2.5
50
.66
0.2
14
48
56
Ber
gm
an(1
99
3)
Min
1.8
0.3
0.1
31
22
0
Max
6.3
7.6
90
.39
10
19
9.1
57
4
Cel
tic
Sea
a1
99
8M
uss
elM
ean
0.7
50
.75
0.1
10
–70
\1
35
0O
SP
AR
(20
00)
Bal
tic
Sea
19
97
Mu
ssel
Mea
n2
2.1
30
.13
11
.8S
zefe
r(2
00
2)
US
A2
00
3M
uss
els
and
Oy
ster
Med
ian
0.9
35
3.3
70
.08
22
.16
0.4
99
3.0
28
10
.35
NO
AA
Nat
ion
al
stat
us
Lo
wle
vel
\0
.58
\2
.156
\0
.055
\1
.39
\0
.14
\0
.88
\1
.775
Hig
hle
vel
[1
.903
5[
6.3
36
[0
.166
[4
.70
[7
.18
[3
5.3
0[
19
0.6
9
Was
hin
gto
n2
00
4–
200
5M
uss
elM
in0
.55
2.1
0.0
70
.88
1.6
12
13
4K
imb
roug
het
al.
(20
08)
Max
7.6
11
1.3
44
29
14
46
96
2
Cal
iforn
ia2004–2005
Muss
elM
in0.4
60.5
90.0
40.5
42
4.4
63
Kim
bro
ugh
etal
.
(20
08)
Max
5.5
8.4
0.3
49
.25
20
64
24
43
4
Ven
ezuel
a1991
Oyst
erM
in0.4
0.3
311
0.5
20.4
0.8
7Ja
ffe
etal
.(1
99
8)
Max
0.7
10
.91
18
1.1
1.4
2.6
Gulf
of
Aden
2005
Per
nap
erna
Min
2.6
0.1
0.5
Most
afa
etal
.(2
00
9)
Max
22
.63
.62
.5
India
2002
Per
nap
ernaa
Mea
n1
.25
6.3
1.2
Sas
iku
mar
etal
.(2
00
6)
Chin
a2
00
1M
uss
elM
in0
.46
0.4
81
.35
.77
14
1.3
41
0.3
Fu
ng
etal
.(2
00
4)
Max
2.9
35
.31
4.7
83
30
64
01
33
52
.4
268 Arch Environ Contam Toxicol (2011) 61:261–271
123
M. galloprovincialis and M. edulis while respecting
equivalent biometric criteria. Comparison of these is also
possible with data from the National Observation Network
of the water quality on French coasts (RNO 2006).
As for the RINBIO network, the tendency for shellfish to
uptake metals in dissolved form (Andral et al. 2004;
Borchardt 1985; Riisgaard et al. 1987; Wang et al. 1997)
and homogeneous levels in the water column seem to have
little impact on variations in levels between marine stations
(Table 4). Under these conditions, levels of metals mea-
sured in natural populations sampled on the coast are
nearly identical to those obtained from transplants of
mussels immersed in the open sea.
However, the open-sea dilution effect is greater with
organic compounds. Levels measured in mussels in artifi-
cial stations are much lower than values observed in
organisms sampled directly on the coast. This phenomenon
might be related to the uptake kinetics of these molecules,
which are ingested as food, adsorbed on suspended parti-
cles (Herbes 1977). In an oligotrophic sector, or at great
distances from the shoreline, the scarcity of particulate
matter from watersheds results in low concentrations in the
mussels.
Concerning dioxin compounds, the distribution median
for MYTILOS samples is situated around 0.7 pg/g (TEQ),
which is relatively low in comparison to the data obtained
by an RNO study (RNO 2002). RNO average concentra-
tions measured throughout the French coasts were of
8.8 pg/g (TEQ), with lower concentrations on the Medi-
terranean coast than on other coasts.
Results from different studies involving bivalve samples
from various marine environments worldwide are also
summarized in Table 4. The comparison of data from
different studies, however, is generally complicated by
substantial changes that have been made in the analytical
methods, the seasonality of sampling, and the number of
congener for the organic compounds and must be exercised
with caution.
At the global scale, we can observe that the levels in the
Mediterranean Sea are in the same range as in other areas
worldwide. The main differences concern the maximum
values that are related to local high contaminations like for
Pb in the Gulf of Aden or Ni in Washington state. As for
French coasts, natural populations are more affected by
organic compounds than transplanted organisms.
Acknowledgments The authors wish to underline the great expe-
rience-sharing through which all project partners were able to judge
the easy implementation of this methodology and familiarize them-
selves with its main concepts through active participation in all
operations. The authors also wish to acknowledge the support by EEC
(Interreg /Medocc IIIC) and the Rhone-Mediterranean-Corsica Water
Agency and the support of UNEP MEDPOL for Morocco Algeria and
Tunisia.
Ta
ble
4co
nti
nu
ed
Loca
tion
Yea
rS
pec
ies
Dat
aP
b
(lg
g-
1)
Cd
(lg
g-
1)
Hg
(lg
g-
1)
Ni
(lg
g-
1)
DD
T
(ng
g-
1)
DD
Ts
(ng
g-
1)
CB
15
3
(ng
g-
1)
PC
Bs
(ng
g-
1)
Flu
o
(ng
g-
1)
PA
Hs
(ng
g-
1)
Ref
eren
ces
Au
stra
lia
19
93
Mu
ssel
Mea
n1
.13
0.0
7H
ayn
esan
d
To
ohey
(19
95)
Min
0.7
0.0
2
Max
1.6
20
.18
Arc
tic
Oce
an1
99
3B
ival
ves
Mea
n1
.42
.70
.08
6.4
26
21
57
0S
eric
ano
etal
.(2
00
1)
aD
ata
tran
sform
edin
dry
wet
(fac
tor
5)
bD
ata
ob
tain
edw
ith
lag
oo
nst
atio
n
Arch Environ Contam Toxicol (2011) 61:261–271 269
123
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