A MODEL FOR BIOACCUMULATION OF HEAVY
METAL IN THE AMERICAN OYSTER (Crassostrea
virginica) FROM APALACHICOLA BAY
Environmental Sciences Institute
Florida A&M University, Tallahassee, Florida
By
Dennis A. Apeti
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(NOAA ,2004)
APALACHICOLA, FL: Landings by Year
Year Millions of Pounds Millions of Dollars
2003 5.1 8.8
2002 5.6 9.2
2001 6.2 10.9
2000 10.3 11.4
1999 6.8 10.3
Background
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• Oyster Bioaccumulation Model (OBM)
• Adapted from FGETS (Barber et al. 1991)
• The main objective: determine long-term BAF factor for Cd and Zn using Crassostrea virginica in Apalachicola Bay.
The ModelThe ModelThe ModelThe Model
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IR
KowWater(overlying
water)
Food(phytoplankton,
detritus,
suspended
sediment)
Oyster
ERkg
Conceptual
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RERIRdt
dW−−=
W
BCi =
FGdt
dB+=
•The model is therefore composed of terms involving oyster weight, bioenergetics and
physiological parameters, metal physico-chemical characteristics
•Total body concentration
•Bioenergetics flux in C. virginica
•Total body burden of metal
Model Formulation
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Modeling uptake from water
G = Sgkg (Cw – Ct)
•Exchange across the gill G: Fick’s first law of diffusion
Eulamellibrach (C. virginica) gill showing parallel filaments (f).
(Medler & Silverman 2001)
•Metal transfer between filaments: can be modeled using the differential equation
0)1( 22
2
2
=−+ fXfX
fdλ
XY
FilamentGraetz classic problem in fluid mechanics Do n
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Modeling the uptake from food
•The net uptake from food can be represented by the mass balance equation
F = CpIR - CeER
•Assuming that a constant fraction of the ingested metal is eliminated in the feces
ER = (1 - αf)IR Where αfis the oyster’s assimilation efficiency for food.
F = αcCfIR Where αc
is the oyster’s assimilation efficiency for metal.
•The oyster assimilates a constant fraction of the ingested metals
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Modeling the bioenergetic flux
•The energy budget in C. virginica
growth = Feeding (energy) - respiration - excretion (Dame 1996).
•Parametization of physiological function•Allometric expression Y = Y0W
b is the “life’s universal scaling law”
(West and Brown 2004)
The behavior of complex biological processes:
•Feeding rate
•Oxygen consumption
•Total gill area
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Predicting the bioaccumulation factor (BAF)
• Definition: BAF is a coefficient constant that relates elemental concentrations in the oyster tissue to those in the in the
environmental water
pw
esteadyStat
CC
wholebodyBAF
+=
][
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Simulation
•FORTRAN
•Compiler: g77
•GNUPLOT: data processing & graphing
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Summer data input
Cadmium simulation
[Cd]field2.60±0.16 µg/g
0.5
1
1.5
2
2.5
3
0 100 200 300 400 500 600 700 800
ug/g
dry
-weig
ht)
Age (days)
Cd concentration
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Cadmium simulation
Winter data input [Cd]field 3.39±0.15 µg/g
0.5
1
1.5
2
2.5
3
3.5
0 100 200 300 400 500 600 700 800
ug/g
dry
-weig
ht)
Age (days)
Cd concentration
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Zinc simulation
Summer data input [Zn]field 431±58 µg/g
0
50
100
150
200
250
300
350
400
450
0 200 400 600 800 1000 1200 1400 1600
ug
/g d
ry-w
ieg
ht
Age (days)
Zn concentration
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Winter data input
Zinc simulation
[Zn]field 737±134 µg/g
0
100
200
300
400
500
600
700
800
0 100 200 300 400 500 600 700 800
ug
/g d
ry-w
ieg
ht
Age (days)
Zn concentration
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BAF determination
pw
esteadyStat
CC
bodywholeBAF
+
−=
][
2
310*5.5
10*)0.623.0(
4.3=
+=
−ppm
ppmBAFCd
4
310*0.3
10*)0.132.11(
730=
+=
−ppm
ppmBAFZn
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Model validationModel validationModel validationModel validation
Cd Zn
Cw 0.2 (DML-0.2) 1.0-12.0
Cp 9.0 (1.0-9.0) 40.0 (10-
40)
T (°°°°K) 297 (283-2003)
S (ppt) 5-40
Location Chesapeake Bay,
VA
Concentration in oyster
Simulation 3.0 2100
Reported values
0.9 - 4.2 700- 4000
The data were retrieved from the EPA Chesapeake Bay Program (2004) files VA106TOT and VATISSUE. Range of Cw
and Cp are given in (µg L-1) and elemental concentration in C.
virginica is in ((µg g-1 dry-weight).
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Cd simulation
Validation results
Reported: 1.0 - 4.2 µg/g
0.5
1
1.5
2
2.5
3
0 100 200 300 400 500 600 700 800
ug/g
(dry
-weig
ht)
Age (days)
Cd concentration
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Zn simulation
Validation results
Reported: 700 – 4000 µg/g
0
500
1000
1500
2000
2500
0 100 200 300 400 500 600 700 800
ug
/g (
dry
-wie
gh
t)
Age (days)
Zn concentration
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•OBM prediction are in agreement with field data.
•OBM model can be used as a biomonitoring tool for a
long-term assessment of heavy metals in the Apalachicola Bay ecosystem.
•OBM model was effectively validated with data sets from Chesapeake Bay.
•C. virginica being ubiquitous and abundant in costal waters, the model can be considered sufficiently
flexible to be used in other estuarine environments.
Conclusion
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AcknowledgementsAcknowledgementsAcknowledgementsAcknowledgements
FAMU, Environmental Sciences Institute
Dr. Larry Robinson, Chair
Dr. Elijah Johnson
Dr. Michael Abazinge
Dr. Jennifer CherrierANERR:
Mr. Lee Edminston & staff
Funding:
•Title III grant to FAMU
•US DOE grant
•NOAA-ECSC grant
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ST1 ST2 ST3 ST4 ST5 ST60
1
2
3
4
5s u m m e r w in te r
S i te s
Cd
(u
g/g
dry
wt)
ST1 ST2 ST3 ST4 ST5 ST60
1
2
3
4
S i te s
Cr
(ug
/g d
ry w
t)ST1 ST2 ST3 ST4 ST5 ST6
0
5 0
1 0 0
1 5 0
S i te s
Cu
(u
g/g
dry
wt)
ST1 ST2 ST3 ST4 ST5 ST60 .0 0
0 .2 5
0 .5 0
0 .7 5
S i te s
Pb
(u
g/g
dry
wt)
ST1 ST2 ST3 ST4 ST5 ST60
5 0 0
1 0 0 0
1 5 0 0
S ite s
Zn
(u
g/g
dry
wt)
Seasonal variation in of metals in C. virginica
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Mean seasonal variation of metal in particulate phase (µµµµg kg-1)
Cd Cr Cu Pb Zn
summer winter Summer winter Summer winter summer winter summer winter
St 1 1.9±0.03 1.1±0.1 1.4±0.02 2.1±0.03 2.2±0.3 3.7±0.5 2.4±0.4 3.3±0.7 0.7±0.1 1.1±0.2
St2 1.4±0.1 1.8±0.2 2.8±0.02 3.7±0.1 4.0±0.5 5.8±1.0 3.9±0.6 6.0±1.0 1.2±0.3 2.4±0.4
St3 2.2±0.1 3.9±0.2 3.4±0.05 6.8±0.1 6.2±0.7 11±1.0 6.5±1.0 14±1.0 2.6±0.3 5.1±0.6
St4 1.5±0.1 2.1±0.1 2.1±0.02 3.4±0.1 4.3±0.6 6.8±1.0 4.0±0.4 8.4±1.0 1.7±0.2 2.8±0.4
St5 1.2±0.1 1.4±0.1 2.0±0.03 2.3±0.04 3.8±0.4 4.4±0.5 3.4±1.0 5.5±0.5 1.5±0.2 1.8±0.3
St6 3.8±0.03 1.3±0.2 0.8±0.6 6.3±1.0 0.6±0.10.4±0.1 2.1±0.2 0.7±0.01 1.2±0.1 3.0±0.4
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Correlation between metal content in oyster and particulate phase
0 1 2 3 40.000
0.001
0.002
r=0.63
Cr Oys2
Cr
in P
M
0 25 50 75 100 125 1500.0000
0.0005
0.0010
0.0015
r=0.72
Cu oys2
Cu
in
PM
0.00 0.25 0.50 0.75 1.000.0000
0.0005
0.0010
0.0015
r=0.30
Pb Oys2
Pb
in
PM
0 250 500 750 1000 1250 15000.0000
0.0005
0.0010
0.0015
r=0.50
Zn in OysZ
n in
PM
2.5 3.0 3.5 4.0 4.5 5.00.00000
0.00025
0.00050
0.00075
r=0.41
Cd Oys2
Cd
in
PM
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Modeling the bioenergetic flux
•The energy budget in C. virginica
growth = Feeding (energy) - respiration - excretion (Dame 1996).
•Parametization of physiological function•Allometric expression Y = Y0W
b is the “life’s universal scaling law” (West and Brown 2004)The behavior of complex biological processes such as metabolic, filtration, growth and
respiration rates
•Feeding rate:dT
WcbaY ∗∗+= )]([
•Oxygen consumption: 2
10 ))(exp(f
opt WfTTfY −=
Bougrier et al. (1995)
•Total gill area: baWS =
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Background
• Apalachicola Bay
– Geomorphology
• 260 km2
• Barrier islands
• 3 m depth
•Apalachicola River
•172 km southward
•752 m3/s flow
•Resident time 10
days
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Ecotoxicity of metal
Abnormal
larvae
15 (37 wks)Cd
Inhibition of
phagocytosis
1000Cd, Cu
Reduce shell thickness
elevatedCd, Cu & Zn
Increase
respiration, Damage gill
100
Cu
Gill damage Mortality
100-200Cd
EffectsCw (ug L-1)Metal
Toxic Effect of metals on oysters
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Potential human health effects
Metals and Health Effects
Metal Sources Exposure from Food
Dietary Allowance
Levels of Concern in
oyster
Health Effects
Cd
Industrial waste; AlloyingBatteries; electroplating
2 – 40 ppb 5 ppb in drinking water
TLC=3.7ug/g
CLC=28g/p/d
Damage to: Lung, Kidney, LiverHypertension; Prostate cancer
CrIndustrial process 60 ug/d 50 – 200
ug/dayTLC=13ug/g
CLC=500g/p/d
Mutagenic; TeratogenicDamage to: Liver and Kidney
CuIndustrial process; emission, miningfrom metal recovery
1 mg/d 340 – 900 ug/day
Hypertension; Haemolysis; Gastrointestinal
dysfunction
Pb
Industrial process; Computer chips 0.1 – 10 ppm TLC=1.7ug/g
CLC=83g/p/d
Neurotoxicity; Memory lossLearning deficit in children
ZnFossil fuel; Sewage; Dredging 2 – 29 ppm 8 – 11
mg/day
Metabolism disorder of mineralNausea and vomiting
TLC = total level of concern in tissue. CLC = consumption level of concern (FDA, 1993)Do n
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“Design and carry out a comprehensive
monitoring program to enable the reserve to
determine baseline changes in the status of
the lower Apalachicola River and Bay system
over long-term periods”.
ANERR Management Plan 1998 - 2003
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ChattahoocheeRiver
Flint River
Apalachicola
River
Tallahassee
Atlanta
Columbus
Albany
FLORIDAGULF OF
MEXICO
GEORGIA
ALABAMA
Apalachicola
Bay
Pollution Problems(Froelich & Lesley 2001, USGS
2000, Couch et al 1997)
Sources of metal
•Industrial activities
•Land & water use
•Urban/Suburban
•Agricultural
•Local commercial & sport boat activities
•Erosion
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Other Factors of Bioavailability
•Sediment resuspension:Boats
Dredging
Dredging material disposal
•Sediment oxidation
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Crassostrea virginica (Gmelin 1791) Metal sequestration
•Granular deposits
•Metallothionein
American oyster
•Bivalve (protandric hermaphrodism)
•Filter feeder (6-10 L h-1)
•Metals bioaccumulation (5 Cd, 18 Cr, 1100 Cu, 20 Pb, 13000 Zn) (Lin, 1999)
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ObjectivesObjectivesObjectivesObjectives
• Assess Cd, Cr, Cu, Pb and Zn concentrations in
Apalachicola Bay: water, sediment, C. virginica
• Assess seasonal fluctuations of heavy metals in bay
• Investigate the correlations between elemental
concentrations in the bivalve, in water column and in the sediment.
• Develop a computer model to simulate a long-term
bioaccumulation of metal in the oysterDo not
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Work Outline
•Assessment of metal concentrations in water, sediment and oyster tissue
•Modeling Heavy Metals (Cd, Zn) Bioaccumulation in C. virginica
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Materials And Methods
Sampling sites
– Summer collect
• Low flow (2002)
• June – Oct.
– Winter collection
• High flow (2003)
• Dec. - April
– Guidelines of US
FDA and NS&T.
Assessment of metal concentrations in Assessment of metal concentrations in Assessment of metal concentrations in Assessment of metal concentrations in
water, sediment and oyster tissuewater, sediment and oyster tissuewater, sediment and oyster tissuewater, sediment and oyster tissue
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Sample collections and preparations• Water
– Vertical water sampler at depth of 3 feet
– Water quality
•Sediment
–Gravity corer
–Sediments (top 10 cm)
–Homogenized and freeze dried
•Oyster
–Oyster tong.
–Composite of 10 animals
shell length
3”-3.5”
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Analysis
• Water/Particulate analysis
– Digestion: EPA Method 3020A
– Analysis GFAAS: EPA 200.12
– SRM: 3108 Cd, 3114 Cu, 3128 Pb and 3168 Zn
• Tissue/sediment analysis
– Digestion: EPA Method 3050B
– FAAS QC standards within 10%
– SRM: 1566b, 1646a
• Grain size analysis: Bouyoucos Hydrometer
• Organic Matter: Loss-On-Ignition (LOI)
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Statistical Analysis
Data processing
– Excel
– Prism statistical software
• One-way ANOVA with Tukey-Kramer post test,
analysis of variance (ANOVA) was conducted
• Student-t
• Regression analysis
• Correlation
• Error at the 95 % CL
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Results
Physical parametersAverage chemical and physical parameters in Apalachicola Bay
Summer season Winter season
Sites pH Sal.
ppt
DOmg/L
T oC pH Sal.
ppt
DOmg/L
T oC
St-1 7.9
20.0 7.8 24.0 7.3 10.8 10.2 9.2
St-2 8.0 18.0 6.5 27.3 7.3 12.7 6.5 10.6
St-3 7.2 4.8 8.6 28.3 7.0 5.3 10.0 19.8
St-4 7.9 28.7 6.0 27.4 7.8 17.1 9.3 18.3
St-5 7.9 30 5.0 27.2 7.8 13.1 12.3 20.6
St-6 8.4 27.8 6.8 28.8 7.8 18.3 9.5 19.1
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Quality assurance with NIST SRM
SRM 1566a
Cd Cr Pb0
1
2
3Measured
Certified
Elements
ug
/g d
ry w
t
SRM 1566b
Cu Zn0
500
1000
1500
Measured
Certified
Elements
ug
/g d
ry w
t
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Liquid SRM
3114 Cu 3108 Cd 3128 Pb 3168 Zn0.0
0.5
1.0
1.5Measured
Certified
SRM
ug
/ml
SRM 1646a
Cd Cr Cu Pb Zn0
25
50
75Measured
Certified
Elements
ug
/g d
ry w
t
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Mean seasonal variation of metal in dissolved phase (µµµµg L-1)
*Reported values are MDL
Site
Cd Cr Cu Pb Zn
Summer winter summer winter summer winter summer winter summer winter
ST1 0.2* 0.2* 1* 1* 2.5* 2.5* 2.0* 2.0* 3.0* 3.0*
ST2 0.2* 0.2* 1.5 2 2.5 2.5* 2.0* 2.0* 11 11
ST3 0.22 0.23 2.2 2.6 4.1 11.4 2.0* 2.0* 11.2 12
ST4 0.22 0.2* 1.6 1.5 3.3 7.1 2.0* 2.0* 5.2 12
ST5 0.2* 0.2* 1* 1.5 2.5* 5.5 2.0* 2.0* 3.0* 10
ST6 0.22 0.22 1* 1.5 2.5* 5.3 2.0* 2.0* 0.4 3.0*
Assessment of metals in the water column
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Illustration of spatial variation: Sediment
ST1 ST2 ST3 ST4 ST5 ST60 .0 0
0 .0 5
0 .1 0
0 .1 5
S ite s
Cd
(u
g/g
dry
wt)
ST1 ST2 ST3 ST4 ST5 ST60
5 0
1 0 0
1 5 0
S ite s
Cr
(ug
/g d
ry w
t)
ST1 ST2 ST3 ST4 ST5 ST60
1 0
2 0
3 0
S ite s
Cu
(u
g/g
dry
wt)
ST1 ST2 ST3 ST4 ST5 ST60
1 0
2 0
3 0
4 0
S ite sP
b (
ug
/g d
ry w
t)
ST1 ST2 ST3 ST4 ST5 ST60
5 0
1 0 0
1 5 0
S ite s
Zn
(u
g/g
dry
wt)
Assessment of metals in the sediment
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Seasonal variation of metals in surficial sediments
ST1 ST2 ST3 ST4 ST5 ST60 .0
0 .1
0 .2S um m er W inter
S ite s
Cd
(u
g/g
dry
wt)
ST1 ST2 ST3 ST4 ST5 ST60
5 0
1 0 0
1 5 0
S ites
Cr
(ug
/g d
ry w
t)
ST1 ST2 ST3 ST4 ST5 ST60
1 0
2 0
3 0
S ite s
Cu
(u
g/g
dry
wt)
ST1 ST2 ST3 ST4 ST5 ST60
1 0
2 0
3 0
4 0
5 0
S ite s
Pb
(u
g/g
dry
wt)
ST1 ST2 ST3 ST4 ST5 ST60
5 0
1 0 0
1 5 0
S ite s
Zn
(u
g/g
dry
wt)
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Sediment standards
National water/sediment criteria
Metal Saltwater (µµµµgL-1)CMC CCC
Source Sediment (µµµµgg-1)NOEL PEL
Source
Cd 40 8.8 EPA 1 7.5 FDEP
Cr 1100 50 EPA 33 240 FDEP
Cu 4.8 3.1 EPA 28 170 FDEP
Pb 210 8.1 EPA 21 160 FDEP
Zn 90 81 EPA 68 300 FDEP
CMC: criteria maximum concentration. CC: criterion continuous concentration. NOEL: no effect level PEL: probable effect level. (EPA, 2002; FDEP, 1994))
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Illustration of spatial variation of metals in C. virginica
ST1 ST2 ST3 ST4 ST5 ST60
1
2
3
4
5
S i t e s
Cd
(u
g/g
dry
-wt)
ST1 ST2 ST3 ST4 ST5 ST60
1
2
3
4
S i t e s
Cr
(ug
/g d
ry-w
t)
ST1 ST2 ST3 ST4 ST5 ST60
5 0
1 0 0
1 5 0
S i t e s
Cu
(u
g/g
dry
-wt)
ST1 ST2 ST3 ST4 ST5 ST60 . 0 0
0 . 2 5
0 . 5 0
0 . 7 5
S i t e s
Pb
(u
g/g
dry
-wt)
ST1 ST2 ST3 ST4 ST5 ST60
5 0 0
1 0 0 0
1 5 0 0
S i te s
Zn
(u
g/g
dry
-wt)
Assessment of metals in C. virginica
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Correlation between metal content in oyster and sediment
0.0 0.5 1.0 1.5 2.0 2.50
25
50
75
100
r = 0.10
Cr in Oyst (ug g -1)
Cr
in S
ed
(u
g g
-1)
0 25 50 75 1000
10
20
30
r = 0.65
Cu in Oyst (ug g -1)
Cu
in
Sed
(u
g g
-1)
0.0 0.1 0.2 0.3 0.4 0.50
10
20
30
40
r = 0.20
Pb in Oyst (ug g -1)
Pb
in
Sed
(u
g g
-1)
0 100 200 300 400 500 600 7000
50
100
150
r = 0.10
Zn in Oyst (ug g -1)
Zn
in
Sed
(u
g g
-1)
0 1 2 3 40.0
0.1
0.2
0.3
r = - 0.04
Cd in Oyst (ug g -1)
Cd
in
Sed
(u
g g
-1)
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• Metal in surficial sediment lower than standard
criteria
• Elemental concentrations in the sediment did not
show true patterns of spatial and temporal
variations
• Concentrations of selected metals were
significantly greater in the oyster tissue than in the
water column
Partial conclusion
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•Metals in C. virginica correlate better with metals in
particulate phase.
•This suggested that C. virginica preferably uptake
metals from the particulate phase.
•Tissue metal content showed patterns of temporal
and seasonal variations suggesting that C. virginica
could be a serious candidate for biomonitoring of
heavy metals in Apalachicola estuary.
Partial conclusions
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• In order to efficiently use C. virginica as
biological indicator one needs to be able to
quantify the time dependent metal
bioaccumulation in the bivalve.
• This is the object of the next study: the
computer modeling of metal accumulation in
C. virginica.
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Metal-Ligand complex formation (Manahan 2000):
Estuarine mixing: exchange of dissolved and particulate
Mn+ (sorbed) Mn+ (aq)
MLn+ (sorbed) MLn+ (aq)
L(sorbed) L(aq)
•Solubility controlled by:
•pH (solubility ~ to 1/pH)
•pE (solubility ~ to pE)
•Salinity (inorganic ligands Cl-1, SO4-2)
•DOC (chelation or complexation)
•Alkalinity (form insoluble complexes CO32- and OH-)
Chemical Form and Bioavailability
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•Solutions to the equation is reduced to the determination of λn and ƒn which are nth eigenvalue and
corresponding eigenfunction respectively. The
eigenvalues were determined (Johnson et al 2005) and using the first eigenvalue λ1 = 1 the mass conductance
can be expressed as follow
)
2
1
)3
2exp(99.01
(
z
z
G
G
g
N
N
h
Dk
−−=
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Model implementation
Cd Zn Source
Cw (µµµµg L-1) 0.23w / 02s 11.2w / 7.0s This study
Cp (µµµµg L-1) 6.0w / 6.0s 13.0w / 11.0w This study
kow 5*105 7*105 Ambrose 1999
Hlamel (cm) 0.05 0.05 Newell et al. 1996
Xlamel (cm) 1.50 1.50 This study
Vlamel (cm s-1) 0.60 0.60 Jones et al. 1992
AE (%) 60.0 73.0 Reinfelder et al. 1997
T (°°°°K) 298 298 This study
S (ppt) 25.0 25.0 This study
pH 7.8 7.8 This study
Cw = dissolved metal Cp = particulate metal S = salinity T = temperature (°°°°K)
Parameter used for model implementation
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Model implementation
Sites
Cd
Winter Summer
Zn
Winter Summer
ST-1 3.78±0.81 2.65±0.07 527±27.4 263±24
ST-2 3.81±0.26 1.86±0.14 837±38.0 593±38
ST-3 3.18±0.25 2.89±0.25 1296±45.0 619±28
ST-4 3.42±0.56 2.33±0.12 806±13.4 395±25
ST-5 3.24±0.52 2.85±0.21 614±18.3 374±26
ST-6 2.88±0.16 2.78±0.10 343±33.4 343±12
Average 3.39±0.15 2.56±0.16 737±134 431±58
Cd and Zn concentrations in C. virginica.
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• First time application of FGETS for bivalves
• First time modeling heavy metal bioaccumulation
in Apalachicola Bay
• Applicability of the model in other estuaries
Relevance Relevance Relevance Relevance
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RationalRationalRationalRational
Need to: preserve, protect this implies monitoring
“Design and carry out a comprehensive
monitoring program to enable the reserve to
determine baseline changes in the status of
the lower Apalachicola River and Bay system
over long-term periods”, (ANERR, 1998).
Effort to satisfy the primary research objective of
which is :
We propose :
•Crassostrea virginica as bioindicator of
heavy metal uptake in Apalachicola Bay
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Chemical Form and Bioavailability
Chemistry of metals in saline water (fergusson 1990)
Mn+ + xH2O [M(H2O)x]n+ [M(H2O)x-1 OH](n-1)+ + H+(aq)
Solvation hydrolysis
[M(H2O)x-1 OH](n-1)+ [M(H2O)x-2 (OH)2](n-2)+ + H+(aq)
hydrolysis
Metal-Ligand complex formation (Manahan 2000):
Estuarine mixing: exchange of dissolved and particulate
Mn+ (sorbed) Mn+ (aq)
MLn+ (sorbed) MLn+ (aq)
L(sorbed) L(aq)
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Sites
Cd
Oyst (µµµµg g-1) PP (µµµµg 1)
Cr
Oyst (µµµµg g-1) PP (µµµµg L1)
Cu
Oyst (µµµµg g-1) PP ( µµµµg 1)
Pb
Oyst (µµµµg g-1) PP ( µµµµg 1)
Zn
Oyst (µµµµg g-1) PP (µµµµg 1)
ST1 2.65±0.07 5.42±0.40 1.09±0.03 11.32±0.10 26.6±0.54 16.1±2.01 0.20±0.01 15.9±2.50 263±24.1 4.7±1.20
ST2 1.86±0.14 6.43±0.30 1.07±0.05 12.4±0.18 74.0±4.05 20.2±3.17 0.20±0.01 21.7±3.70 593±38.0 6.10±1.30
ST3 2.89±0.25 8.41±0.42 1.31±0.16 13.3±0.20 76.7±1.17 24.2±2.56 0.36±0.02 25.1±4.00 619±28.4 10.0±1.20
ST4 2.33±0.12 8.43±0.53 1.26±0.31 11.8±0.10 55.4±2.77 24.0±3.51 0.21±0.01 12.2±2.30 395±25.6 9.71±1.32
ST5 2.85±0.21 7.53±0.50 1.44±0.16 12.5±0.179 46.1±3.24 24.6±2.36 0.19±0.01 21.5±5.5 374±26.3 9.60±1.40
ST6 2.78±0.10 6.65±0.55 1.05±0.02 12.0±0.11 58.9±2.60 23.5±2.00 0.41±0.01 20.0±2.31 343±12.5 9.50±1.50
Comparison of elemental concentrations ((µg g-1 dry-weight) in tissue vs. particulate collected in the winter season
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Sit
e
Cd
Oyster
Sed
Cr
Oyster Sed
Cu
Oyster
Sed
Pb
Oyster Sed
Zn
Oyster Sed
ST
13.8±0.8
0.14±0.00
21.1±0.4 48.8±4.33 65.0±7.2 9.9±2 0.40±0.1 13.1±5.2 527±27 492±2
ST
2
3.81±0.2
6
0.14±0.00
11.1±0..6 89.36±6.0 84.2±12 19±2 0.36±0.1 28.7±3.4 837±38 97±7
ST
33.18±0.3
0.15±0.00
21.58±0.6 97.31±4.9
101±22.
418.0±1 0.50±0.1 32.5±7.6 129±45 103±1
ST
43.42±0.6
0.15±0.00
11.68±0.4 91.96±6.5
108±21.
016.0±2 0.40±0.1 33.3±2.5 806±13 97±4
ST
53.24±0.5
0.15±0.00
12.1±0.3 84.92±7.3 73.1±12 17.7±1 0.5±0.03 30.1±3.5 614±18 85±5
ST
62.9±0.2
0.15±0.00
11.7±0.3 85.0±5.0 57.5±2.3 21.0±1 0.3±0.04 29.9±1.1 343±33 87±3
Comparison elemental concentrations ((µg g-1 dry-weight) in tissue vs. sediments collected in the winter season
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Cr-Correlation
0 25 50 75 100 1250
1
2
3
r = 0.46
Cr in sediment (ug/g)
Cr
in o
yste
r (u
g/g
)
Cu-Correlation
0 10 20 300
50
100
150Cu Oyst
Cu in sediment (ug/g)
Cu
in
oyste
r (u
g/g
)
r = 0.53
Pb-Correlation
0 10 20 30 400.3
0.4
0.5
0.6Pb-Oyst
Pb in sediment (ug/g)
Pb
in
oyste
r (u
g/g
)
r = -0.18
Zn-Correlation
0 25 50 75 100 1250
500
1000
1500Zn-Oyst
r = 0.65
Zn in sediment (ug/g)
Zn
in
oyste
r (u
g/g
)
Cd-Correlation
0.135 0.140 0.145 0.150 0.1552.5
3.0
3.5
4.0
4.5Cd-Oyst
Cd in sediment (ug/g)
Cd
in
oyste
r (u
g/g
)
r = -0.97
Fig : Oyster vs Sediment colleted in the winter seasonDo n
ot dis
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te with
out a
uthor
autho
rizati
on
0 2 5 5 0 7 5 1 0 0 1 2 5
0 .1 4
0 .1 5
0 .1 6
r = 0 .4 5 6
C r ( u g /g )
Cd
(u
g/g
)
0 2 5 5 0 7 5 1 0 0 1 2 50
5 0
1 0 0
1 5 0
r = 0 .9 9 4
C r (u g /g )
Zn
(u
g/g
)
0 2 5 5 0 7 5 1 0 0 1 2 50
1 0
2 0
3 0
4 0
r = 0 .8 3 0
C r (u g /g )
Pb
(u
g/g
)
0 .1 3 5 0 .1 4 0 0 .1 4 5 0 .1 5 0 0 .1 5 50
1 0
2 0
3 0
4 0
r = 0 .5 4 1
C d ( u g /g )
Pb
(u
g/g
)
0 .1 3 5 0 .1 4 0 0 .1 4 5 0 .1 5 0 0 .1 5 50
5 0
1 0 0
1 5 0
r = 0 .3 8 0
C d (u g /g )
Zn
(u
g/g
)
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ST-1 St-2 ST-3 ST-4 ST-5 ST-60
10
20% OM-1
% OM-2
Site
Org
an
ic m
att
er
(%)
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0 10 20 30 4 0
0 .12
0 .13
0 .14
0 .15
0 .16
r = 0.737
% Fine fract ion
Cd
in
sed
imen
t (u
g/g
)
C r-% F P
0 1 0 2 0 3 0 400
2 5
5 0
7 5
1 0 0
r = 0.931
% Fine fraction
Cr
in s
ed
imen
t (u
g/g
)
C u -% F P
0 1 0 2 0 3 0 4 00
1 0
2 0
3 0
r = 0 .738
% Fine fraction
Cu
in
sed
imen
t (u
g/g
)
P b-% FP
0 10 20 30 400
10
20
30
40
r = 0 .900
% Fine fract ion
Pb
in
sed
imen
t (u
g/g
)
Zn-% F P
0 1 0 2 0 3 0 4 00
5 0
1 0 0
1 5 0
r = 0.851
% Fine fraction
Zn
in
sed
imen
t (u
g/g
)
F ig ...: C o rre latio n be twe en m e tals co nce ntratio ns and % f ine f rac tions ed im ents c o lle c ted in the low f lo w se as on. P ears on c o rre latio nc oe f f ic ient values (r) are rep o rted .
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0 5 1 0 1 5 2 0
0 .1 2
0 .1 3
0 .1 4
0 .1 5
0 .1 6
% O M -1
Cd
in
sed
imen
t u
gg
-10 5 1 0 1 5 2 0
0
2 5
5 0
7 5
1 0 0
% O M -1
Cr
in s
ed
imen
t u
gg
-1
0 5 1 0 1 5 2 00
1 0
2 0
3 0
% O M -1
Cu
in
sed
imen
t u
gg
-1
0 5 1 0 1 5 2 00
1 0
2 0
3 0
4 0
% O M -1
Pb
in
sed
imen
t u
gg
-1
0 5 1 0 1 5 2 00
5 0
1 0 0
1 5 0
% O M -1
Zn
in
sed
imen
t u
gg
-1
F ig: C o r r e lat io n be twe e n m e tal in s e d im e n t and % O M c o l le c te d in the s um m e r
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ST-1 ST-2 ST-3 ST-4 ST-5 ST-60
1
2
3
Sites
Cd
(u
g/g
dry
wt)
ST-1 ST-2 ST-3 ST-4 ST-5 ST-60
1
2
Sites
CR
(u
g/g
dry
wt)
ST-1 ST-2 ST-3 ST-4 ST-5 ST-60
25
50
75
100
Sites
Cu
(u
g/g
dry
wt)
ST-1 ST-2 ST-3 ST-4 ST-5 ST-60 .0
0 .1
0 .2
0 .3
0 .4
0 .5
Site s
Pb
(u
g/g
dry
wt)
ST-1 ST-2 ST-3 ST-4 ST-5 ST-60
250
500
750
Sites
Zn
(u
g/g
dry
wt)
Fig. X: Metal conc entrations in C . virginic a collec ted in s um m er form differentsam pling s ites in Apalachic ola Bay. Values are m ean ± SDE at 95 % CL (n = 5) .
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0 .9 1 .0 1 .1 1 .2 1 .3 1 .4 1 .5 1 .60
2 5
5 0
7 5
1 0 0
r = 0 .1 2P < 0 .0 5
C r in o ys t u g /g d r y w t
Cr
in s
ed
imen
t (u
g/g
)
0 2 5 5 0 7 5 1 0 00
1 0
2 0
3 0
r = 0 .7 5P < 0 .0 5
C d in o ys t u g /g d r y w t
Cu
in
sed
imen
t (u
g/g
)
0 .0 0 .1 0 .2 0 .3 0 .4 0 .50
1 0
2 0
3 0
4 0
r = 0 .4 4P < 0 .0 5
Pb in o ys t u g /g d r y w t
Pb
in
sed
imen
t (u
g/g
)
0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 6 0 0 7 0 00
2 5
5 0
7 5
1 0 0
1 2 5
r = 0 .1 0P < 0 .0 5
Zn in o ys t u g /g d r y w t
Zn
in
sed
imen
t (u
g/g
)
Fig: C o r re lat io n be twe e n m e tal in o ys te r and s e dim e nt c o lle c te d in the s um m e r
1 .7 5 2 .0 0 2 .2 5 2 .5 0 2 .7 5 3 .0 0 3 .2 50 .0
0 .1
0 .2
r = -0 .2 1P < 0 .0 5
C d in o ys t u g /g d r y w t
Cd
in
sed
imen
t (u
g/g
)
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ation
0 .1 2 0 .13 0 .14 0 .1 5 0 .1 60 .0
0 .5
1 .0
1 .5
2 .0
2 .5
3 .0
3 .5
r = 0 .2 6 9
C d in o y s t e r (u g /g )
Cd
in
sed
imen
t (u
g/g
)
0 25 5 0 75 1 0 00 .00
0 .25
0 .50
0 .75
1 .00
1 .25
1 .50
1 .75
r = 0 .1 1 3
C r in o y s te r (u g /g )
Cr
in s
ed
imen
t (u
g/g
)
0 1 0 2 0 3 00
2 5
5 0
7 5
1 0 0
r = 0 . 7 5 4
C u in o y s te r ( u g /g )
Cu
in
sed
imen
t (u
g/g
)
0 1 0 2 0 30 4 00 .0
0 .1
0 .2
0 .3
0 .4
0 .5
r = 0 . 4 3 7
P b in o y s te r (u g /g )
Pb
in
sed
imen
t (u
g/g
)
0 1 0 2 0 3 0 4 0 5 0 6 0 7 0 80 9 0 10 01 1 012 00
25 0
50 0
75 0
r = 0 . 5 6 5
Zn in o y s t er (u g /g )
Zn
in
sed
imen
t (u
g/g
)
F ig : C o r r e lat io n be tw e e n m e ta l in o y s te r an d s e d im e n t c o l le c te d in th e w i n te r
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C d
St-1 St-2 St-3 St-4 St-5 St-60 .0
0 .1
0 .2
F ig . X : C ad m ium c o nc e n tra tion in s e d im e n t c o lle c te d fo rm d iffe ren ts am p ling s ite s in A pa la c h ic o la B a yVa lu es a re m ea n ± S E M a t 9 5 % C L (n = 5 ). P > 0 .0 5
S a m p lin g s t a t io n s[C
d]
ug
/g d
ry w
t
C r
SS-1 SS-2 SS-3 SS-4 SS-5 SS-60
2 5
5 0
7 5
1 0 0
F ig . X: C h rom iu m c o nc en tra tio n in s ed im en t c o llec ted fo rm d iffe ren ts am p lin g s ites in Ap a lac h ic o la B ay .Va lue s a re m ea n ± S E M a t 9 5 % C L (n = 5 ). P > 0 .0 5
S am p lin g s ta t io n s
[Cr]
ug
/g d
ry w
t
C u
SS-1 SS-2 SS-3 SS-4 SS-5 SS-60
1 0
2 0
3 0
S a m p lin g s t a t io n s
[Cu
] u
g/g
dry
wt
F ig . X: C o pp e r c on c en tra tio n in s ed im e n t c o lle c te d fo rm d iffe ren ts a m p lin g s ite s in Apa la c h ic o la B ayVa lue s a re m ea n ± S E M a t 9 5 % C L (n = 5 ). P > 0 . 0 5
P b
SS-1 SS-2 SS-3 SS-4 SS-5 SS-60
1 0
2 0
3 0
4 0
S a m p lin g s t a t io n s
[Pb
] u
g/g
dry
wt
F ig . X: Lead c onc en tra tion in s ed im ent c o llec ted fo rm d iffe ren ts am p ling s ites in Apa lac h ic o la B ayVa lues are m ean ± S E M a t 9 5 % C L (n = 5 ). P > 0 .0 5
Zn
SS-1 SS-2 SS-3 SS-4 SS-5 SS-60
5 0
1 0 0
1 5 0
S a m p lin g s ta t io n s
[Zn
] u
g/g
dry
wt
F ig . X: Zinc c o nc en tra t ion in s e d im e n t c o lle c ted fo rm d iffe re n ts a m p ling s ite s in Apa la c h ic o la B a yVa lu es a re m e an ± S E M a t 9 5 % C L (n = 5 ). P > 0 . 0 5
F ig : M e a n c o n c e n tr a tio n ( ± u n c e r ta in ty a t 9 5 % c o n f id e n c e le ve l) o f tr a c e m e ta l in r e c e n tse d im e n ts f r o m A p a la c h ic o la B a y
U
SS-1 SS-2 SS-3 SS-4 SS-5 SS-60 .0
2 .5
5 .0
7 .5
S a m p lin g s ite s
[U]
ug
/g d
ry w
t
F ig . X : U ra n ium c on c e n tra tio n in s ed im en t c o lle c ted fo rm d iffe ren ts am p lin g s ite s in Apa la c h ic o la B ayVa lue s a re m ea n ± S E M a t 9 5 % C L (n = 5 ). P > 0 .0 5Do not
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ation
Assuming a laminar flow, chemical transport between filaments can be modeled as
2
22 )1(
2
3
XYX
∂
Θ∂=
∂
Θ∂−
where is the chemical dimensionless concentration, X is the dimensionless distance normal to the surface of the filament such that X=0 denote the centerline, and Y is the dimensionless distance along the length of the filament.
Θ
wC
yxC ),(=Θ
h
xX =
Vh
yDY
2=
where C(x,y) is the chemical concentration between the filament at the distance x from the filament surface and y along the length of the filament and D (cm2 /s) is the diffusivity of the chemical.
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The dimensionless length or Graetz number NGz of the filament is defined by Ywhen y = l. Using this definition and the functional notation (X, NGz) to designate the dimensionless chemical concentration of the interfilament water at the position X between adjacent filaments, the normalized bulk concentration, CB/Cw, can be defined as the weighted average
Θ
∫
∫−
−Θ==Θ
1
0
2
1
0
2
)1(
)1)(,(
dXX
dXXNX
C
C Gz
w
BB
Using the Graetz-Nusselt solutions reported by Colton et al. (1971), this equation can be evaluated as
)3
2(exp 2
0
Gzm
m
mB NB λ−=Θ ∑∞
=
where the coefficient Bm is determined by the mth eigenvalue, , and corresponding eigenfunction, fm of the differential equation.
mλ
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Boundary conditions:Assuming steady-state diffusion 00 =
Θ=x
dX
d
Θ−=Θ
= wshx NdX
d1
Where is the channel wall Sherwood number, which is defined as wshN
D
hkN w
shw=
where is the permeability or conductance of the wall.
wk
Using the first eigenvalue ( , the bulk concentration of chemical can be estimated by
)11 =λ
)3
2exp(99.0 Gz
w
BB N
C
C−==Θ
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ation
Overall Conclusion
•Metal in surficial sediment lower than standard criteria
•Elemental concentrations in the sediment did not show true patterns of spatial and temporal variations.
•Concentrations of selected metals were greater in the
oyster tissue than in the water column
•Metals in C. virginica correlate better with metals in
particulate phase.
•In addition, differences in tissue metal content showed
patterns of temporal and seasonal variations suggesting that C. virginica could be a serious candidate for biomonitoring of
heavy metals in Apalachicola estuary.
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minate
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t auth
or au
thoriz
ation
