1 Bioaccumulation Assessment

1.1 Introduction

This Annex presents the methodology utilised in the bioaccumulation assessment and the results. The product of this assessment is concentrations of contaminants of concern in seafood.

The objective of the bioaccumulation assessment is to predict the likely concentrations of Contaminants of Concern (COCs) in selected animals due to contaminant exposure through disposal operations at the proposed facilities at either South Brothers or East of Sha Chau.

1.3 Literature Review of Bioaccumulation of COC

Contamination in aquatic ecosystems has become one of the major environmental concerns worldwide. COCs are released from point sources to river/estuarine and coastal waters as a result of increased industrialization. Sediment is a potentially important source of COC for the overlying water, due to sediment resuspension (contributing to the particulate load) or sediment remobilization and diagenesis (contributing to the dissolved load). Once in the water column, COCs are then partitioned between the dissolved and particulate phases and this is controlled by adsorption/desorption and precipitation/dissolution. Many physico-chemical and biological factors (e.g., particle type/concentration, salinity, dissolved organic carbon concentration, and biological uptake) can influence the partitioning in the water column. Thus, COCs can become available to marine benthic invertebrates through uptake from the dissolved phase and ingestion of suspended particles and sediments.

The bioaccumulation of COC’s in aquatic organisms has received extensive attention over the last several decades because toxicity is dependent on their accumulation. The bioavailability is defined as the fraction of total COC in the environment that is available for accumulation in organisms. Many factors can control COC bioavailability, including the biological characteristics of the organisms (e.g., assimilation, feeding rate and pattern, size/age, and reproductive condition) and the geochemistry of the COC (e.g., contaminant partitioning in the water column and speciation). Further, these can be influenced by physico-chemical factors, such as temperature, salinity, dissolved organic carbon (DOC) concentration, and total suspended solids load (TSS).

Generally there are two approaches to predict pollutant concentrations in aquatic organisms (Landrum et al. 1992, Luoma and Fisher 1997):

1) partitioning equilibrium (EqP); and

2) kinetic modeling.

The approaches are well developed and have been used in the development of water quality criteria and sediment quality criteria in the US and elsewhere (i.e. using the equilibrium partitioning method and the bioconcentration factor to predict the concentrations in aquatic organisms) (Connell DW 1989; EPA 2000). The approach has been applied to the situation in southern China where marine organisms are exposed to contaminated sediment (Wang et al. 2002) and is thus applicable and relevant to the Hong Kong situation. Although there has been no experimental validation of these models in the Hong Kong context, the Trophic Trace model which is a comparable bioconcentration modelling tool, is endorsed by the USEPA and the US Army Corps of Engineers and is an internationally accepted standard for modelling bioconcentration in aquatic and marine environments (ERDC, 2003). The approach adopted here is therefore considered appropriate and scientifically valid.

The EqP approach assumes only one phase (waterborne) of uptake and a constant exposure. Mathematically, this can be expressed by:

BCF = C/C_w (1)

Where BCF is the COC bioconcentration factor (L g^-1); C is the COC concentration (mg g^-1) in the animals; and C_w is the COC concentration in the dissolved phase (mg L^-1). Thus, the likely concentration of COC in the animals due to uptake of desorbed COC can be directly calculated by:

C = BCF * C_w (2)

A more complicated EqP model has been developed for sediment quality criteria by assuming equilibrium partitioning of chemicals (mainly non-ionic organic) among the aqueous phase, sediment and organisms (Di Toro et al. 1991). Sediments in aquatic systems presently contain large amounts of contaminants and can be a potentially significant source for COC accumulation in benthic fauna. Correlations based on sediment concentration are now viewed as better predictors of tissue residues than predictions based on water (Di Toro et al. 1991). This approach is normally exploited by normalizing chemical concentrations based on the lipid content of organisms and the organic carbon content of sediments. Thus the biota-sediment accumulation factor (BSAF) can be calculated by:

BSAF = C_a(l)/C_s(c) (3)

where, C_a(l) is the chemical concentration in the animals normalized to their lipid content, C_s(c) is the chemical concentration in sediments normalized to organic carbon content. These BSAF values are considered to be independent of the type of sediments (Thomann et al. 1995).

Kinetic models are required for non-steady state, non-equilibrium accumulation due to varying exposure in the field. Such an approach is not constrained by assuming constant exposure/thermodynamic equilibrium. Landrum et al. (1992) reviewed various kinetic models used in aquatic systems and hazard assessments, including the physiologically-based pharmacokinetic model (PBPK) and bioenergetic-based toxicokinetic model (BE). BE models describe toxicant accumulation and loss in terms of an animals’ energy requirements and usually treat the animal as a single compartment (Landrum et al. 1992).

Assuming that the COC is accumulated only from the water, the accumulation of COC can be described by a simple kinetic equation:

dC/dt = k_u*C_w - k_e*C (4)

where C is the COC concentration in the animals at time t; k_u is the uptake rate constant from the dissolved phase; k_e is the efflux rate constant (d^-1). Under steady-state condition, C can be directly calculated as:

C = k_u*C_w /k_e (5)

In this model, the BCF can similarly be calculated as:

BCF = k_u /k_e (6)

For sediment-ingesting animals, the accumulation of COC can be similarly modeled using the kinetic equation:

dC/dt = AE*IR*C_s - k_e*C (7)

Where AE is the COC assimilation efficiency from the ingested sediment, IR is the ingestion rate (g g^-1 d^-1); C_s is the COC concentration in the ingested sediment (mg g^-1). Under steady-state condition, C can be directly calculated as:

C = AE*IR*C_s /k_e (8)

Thus, to assess the possible COC accumulation (due to desorption from sediments) by the bivalves and fish, parameters required in the modeling calculation are the BCFs or the uptake rate constant k_u, efflux rate constant k_e, and COC concentrations in the water. To assess the possible COC accumulation by sediment- ingesting animals, parameters required in the modeling calculation are the assimilation efficiency (AE), ingestion rate (IR) of the animals, COC concentration in the sediment (C_s), and efflux rate constant k_e. If these parameters are not available for the animals, another approach will be to use the BSAF, as described in Eq. 3.

To further predict the COC concentration in the predators, the trophic transfer factor (TTF) needs to be introduced:

C_n = C_n-1 x TTF (9)

Where C_n is the COC concentration in the predator, and C_n-1 is the COC concentration in the prey.

1.4 Selection of Contaminants of Concern (COCs) and species for bioaccumulation assessment

The bioaccumulation assessment is based on the water quality modeling simulation of the release (i.e., desorption) of pollutants from the sediments disturbed during disposal. The COCs investigated are those used in the water quality modeling.

There are a lack of bioaccumulation and bioconcentration factors available in the literature for TBT and it is therefore not included in the Risk Assessment. This limitation does not limit the conservative nature of the assessment because background levels of TBT in sediment and dredged materials around the East of Sha Chau area are generally undetectable or very low. This statement is backed up by monitoring data collected at CMPIV since 1997 which has consistently recorded TBT in sediment and tissue samples below levels of concern.

There are two possible pathways for the accumulation of contaminants due to sediment resuspension: (1) desorption of contaminants into the water column following sediment resuspension followed by uptake from the water; and (2) ingestion of contaminated sediments. Thus, the selection of species for assessment is based on the availability of parameters to quantify the exposure pathways as well as the ecological significance. They can be separated into the following feeding groups:

1. 1. Pelagic fish – to assess the potential uptake of desorbed contaminants in the water column;

2. A filter-feeding bivalve – to assess the potential uptake of desorbed contaminants in overlying waters and from contaminated sediments;

3. A deposit-feeding worm (polychaete or sipunculan) - to assess the potential uptake of contaminants from sediment ingestion; and

4. Predatory fish, crab and shrimp that specifically prey on the above animals.

The selection of the species under these feeding groups is based on available literature and experience in bioaccumulation assessment. Where possible, local species are selected. There have been a number of studies on the bioaccumulation of COCs in local species such as green mussels, clams, sea bream and mangrove snapper (fish). However, there is a lack of information on the uptake of contaminants by local polychaete species, but studies on other deposit-feeding invertebrates such as the sipunculans are available. Where data gaps appear, information is supplemented with reference to international studies. It should be noted that, where no information is available on the uptake of the COCs in marine organisms within either local or international literature, an assessment of bioaccumulation potential of this parameter is not possible. In the later risk assessment work that has been conducted ambient values have been substituted where these data gaps occur.

1.5 Modeling of Contaminant Release

Concentrations of the COCs in water (dissolved phase) and in sediment are determined from the results of the water quality modeling.

1.5.1 Dissolved Phase

Contaminants adsorbed to sediment particles can be expected to either remain adsorbed to the sediment, settling or dispersing in direct proportion to suspended sediment concentrations, or desorb from the sediment particles and enter solution.

Values of the partition coefficients (Kd) have been determined. The majority of the Kd vales have been derived from the Chemical Database developed by the Dutch Ministry for Transport, Public Works and Water Management with the remainder taken from the Kellett Bank EIA and the East Sha Chau CMP IV EIA. For the organic compounds the P value is related to Total Organic Carbon (TOC) rather than Total Particulate Matter (TPM). In those cases a reference ratio TOC:TPM needs to be used. Since this ratio is highly variable both in space and in time, it is proposed to derive this value from the model output, rather than to prescribe a value. The selected P values are shown in Table 0.1~~Table 1.1Table 1.1Table 1.1~~.

Table 01.11.1 Partitioning Coefficients Utilised in the Bioaccumulation Assessment

Pollutant	Kd	Unit	UCEL Max. sediment conc.	Unit
Arsenic	130	l/g	42	mg/kg
Cadmium	100	l/g	4	mg/kg
Chromium	290	l/g	160	mg/kg
Copper	122	l/g	110	mg/kg
Lead	130	l/g	110	mg/kg
Mercury	700	l/g	1	mg/kg
Nickel	40	l/g	40	mg/kg
Silver ⁽¹⁾	200	l/g	2	mg/kg
Zinc	100	l/g	270	mg/kg
Total PCB's	1585	l/gOC	180	ug/kg
LMW PAH	0.075	l/g	3.16	mg/kg
HMW PAH	1.14	l/g	9.6	mg/kg
OC = 0.012 gOC/g ⁽¹⁾Wen LS, Santschi PH, Paternostro CL, Lehman RD, 1997. Colloidal and particulate silver in river and estuarine waters of Texas. Environ Sci Technol 31: 723-731.

The data on SS values have been taken from the modelling works. The input data for SS are determined as the depth averaged value within an area 400 m from the modelled pit boundary. The 400 m value is taken from the review of environmental monitoring data, which have indicated that the majority of the previous monitoring programmes regarded the “impact” area to be from 400m of the pit boundary. The SS data were taken from the worse case backfilling scenarios, those involving the use of trailer dredgers, which makes the assessment conservative. For South Brothers this value was 1.41 mg L^-1 and for East of Sha Chau 2.84 mg L^-1. Average values have been used in the assessment because the risk work, presented in Annex C, focuses on chronic risk and not acute. The use of maximum SS levels would bring an unwarranted level of conservativeness to this assessment, which would result in misleading results.

Application of the Kd values to the SS values results in the dissolved concentrations listed in Table 0.3~~Table 1.3Table 1.3Table 1.3~~.

Table 01.31.2 Dissolved Concentrations of COCs (µg L^-1)

Parameter	East of Sha Chau	South Brothers
Arsenic	0.016	0.008
Cadmium	0.00114	0.00056
Chromium	0.132	0.065
Copper	0.038	0.019
Lead	0.041	0.020
Mercury	0.00199	0.00099
Nickel	0.005	0.002
Silver ⁽¹⁾	0.00114	0.00056
Zinc	0.077	0.038
Total PCB's	0.00001	0.000005
LMW PAH	0.000001	0.0000003
HMW PAH	0.00003	0.00002

1.5.2 Sediment Ingestion

The water quality modeling provides estimates of sediment deposition in and around the pits. Although Kd values have been used to determine desorption for the purposes of the sediment ingestion assessment it was assumed that 0% of contaminants desorb. Such and assumption indicates that the bioaccumulation assessment is inherently conservative.

Following a similar approach to that for determining average SS values across the “impact area” adjacent to the pits the average rate of sediment deposition was determined. This value was then fed into a series of equations, which are detailed in Table 1.5. The end result of the calculations was a series of values for COC elevation in sediment in the South Brothers and East of Sha Chau areas..

Table 01.51.3 Methodology for Predicting Increase in Sediment Concentrations of COCs (example is Nickel)

Nickel			South Brothers	East of Sha Chau
Deposition Rate (SS)	kg/m²/day¹	A	0.0480	0.0735
Concentration in Disposal Material (UCEL)	mg/kg	B	40	40
Bioturbation Depth	M	C	0.1	0.1
Volume of Sediment	m³	D	0.1	0.1
Typical Density of Sediment	kg/m³	E	750	750
Ambient Sediment Concentration	mg/kg	F	18.27	18.27
In situ Sediment Mass (kg)		D x E = G	75	75
In situ Nickel Mass (mg)		G x F = H	1370.25	1370.25
Deposition of Nickel (mg m2 day)		A x B = I	2.7116	2.94
Day 1 In situ Nickel Mass mg		H + I = J	1372.962	1373.19
Day 1 In situ Nickel Concentration (mg/kg)		J/G = K	18.30615	18.3092
Total Disposal Days (14Mm3 = 26,700m3/d)		L	524	524
Deposition of Nickel over Facility Lifetime (mg/m2)		L x I = M	1006.92	1540.56
Lifetime in situ Nickel Mass (COC) mg		M + H = N	2377.17	2910.81
In situ Lifetime Sediment Mass (kg)	kg	(L*A)+G=P	100.173	113.514
Change in Volume	m³	P/E = Q	0.133564	0.151352
Change in Height	cm	Q/1m/1m=R	0.133564	0.151352
Overall Lifetime In situ Nickel Concentration (mg/kg)	mg/kg		23.73	25.64

2 Detailed assessment of bioaccumulation

2.1 Pelagic Fish

In assessing COC bioaccumulation by the marine fish, it is assumed that the COCs are predominantly accumulated from the dissolved phase and uptake from the sediment particles is negligible. COCs in the dissolved phase originate from desorption from the resuspended sediments (with 100% desorption). Two approaches are therefore used to predict the likely COC concentrations in marine fish, including the BCF approach and the kinetic approach. For the BCF approach, the COC concentration is directly calculated as the BCF times the desorbed COC concentration using Eq. 2. The mean BCFs of metals (Cr, Pb and Ni) are referred from International Atomic Energy Agency (IAEA, 2000). For other metals, the BCF is calculated by the kinetic equation (Eq. 6) with known uptake rate constant k_u and efflux rate constant k_e from the local fish species (mangrove snappers, sweetlips and seabreams) (Xu and Wang 2002, Wang and Wong 2003, Long and Wang submitted). The BCF of Cu is calculated from the field data of Gibbs and Miskowicz (1995).

Using these two approaches, the calculated COC concentrations in the fish as a result of uptake of desorbed metals are shown in Table 2.2, together with the BCFs used in the calculations. Ambient concentrations have been calculated from a review of biota data collected in reference areas between 1997 and 2000 as part of the biomonitoring programme under the CMPIV monitoring programmes (Table 2.1) (ERM 2004).

Table 2.1 Concentrations of Contaminants of Concern in Marine Biota Collected in Reference Areas Between 1997 and 2000

Parameter	*Charybdis* sp	*Cynoglossus* sp	*Trypauchen* *vagina*	*Leiognathus brevirostris*	Average Fish	*Metapenaeus affinis*	*Metapenaeus ensis*	*Oratosquilla oratoria*	*Turritella terebra*	Average Prawn
Arsenic (mg kg^-1)	4.11	2.83	5.15	1.18	3.05	2.82	3.32	4.34	3.30	3.49
Cadmium (mg kg^-1)	0.42	0.03	0.01	0.01	0.02	0.02	0.01	0.90	0.28	0.31
Chromium (mg kg^-1)	0.10	0.06	0.05	0.06	0.05	0.06	0.05	0.08	0.50	0.07
Copper (mg kg^-1)	15.24	2.63	2.07	2.25	2.32	8.72	7.81	29.09	33.59	15.21
Lead (mg kg^-1)	0.14	0.09	0.16	0.08	0.11	0.06	0.12	0.07	1.20	0.08
Mercury (mg kg^-1)	0.02	0.02	0.04	0.03	0.03	0.01	0.01	0.02	0.03	0.01
Nickel (mg kg^-1)	0.29	0.06	0.04	0.06	0.05	0.10	0.11	0.28	29.81	0.16
Silver (mg kg^-1)	0.29	0.03	0.03	0.03	0.03	0.05	0.03	0.57	1.55	0.22
Zinc (mg kg^-1)	21.30	4.90	7.52	14.58	9.00	13.49	14.13	23.46	77.40	17.02
Low M Wt PAHs	25.00	25.00	25.00	25.00	25.00	25.00	25.00	25.00	25.00	25.00
High M Wt PAHs	75.00	75.00	75.00	75.00	75.00	75.00	75.00	75.00	75.00	75.00
PCBs	4.22	5.50	2.64	16.94	8.36	2.35	1.23	11.18	4.48	4.92

Table 2.12.1 The predicted COC concentrations in the fish as a result of uptake of desorbed metals. The bioconcentration factor (BCF) used in the calculations is also shown.

Metals	Elevated concentration	BCF (L kg^-1)	Elevated Concentration in fish (mg kg^-1)	Ambient Concentration in fish (mg kg^-1)	Total Concentration in Fish (mg kg^-1)
*East of Sha Chau*
As	0.0155064	350	0.00543	1.18235	1.188
Cd	0.001136	200	0.00023	0.00941	0.010
Cr	0.131776	200	0.02636	0.06294	0.089
Cu	0.0381128	2200	0.08385	2.25471	2.339
Pb	0.040612	200	0.00812	0.08382	0.092
Hg	0.001988	6800	0.01352	0.03471	0.048
Ni	0.004544	1000	0.00454	0.06059	0.065
Ag	0.00548	500	0.00274	0.02500	0.028
Zn	0.07668	700	0.05368	14.57647	14.630
LMW PAH	0.00000067	1000	0.00000	0.02500	0.025
HMW PAH	0.00003108	10000	0.00031	0.07500	0.075
PCBs	0.00000972	100000	0.00097	0.01694	0.018
*South Brothers*
As	0.00768768	350	0.00269	1.18235	1.185
Cd	0.0005632	200	0.00011	0.00941	0.010
Cr	0.0653312	200	0.01307	0.06294	0.076
Cu	0.01889536	2200	0.04157	2.25471	2.296
Pb	0.0201344	200	0.00403	0.08382	0.088
Hg	0.0009856	6800	0.00670	0.03471	0.041
Ni	0.0022528	1000	0.00225	0.06059	0.063
Ag	0.0005632	500	0.00028	0.02500	0.025
Zn	0.038016	700	0.02661	14.57647	14.603
LMW PAH	0.00000033	1000	0.00000	0.02500	0.025
HMW PAH	0.00001541	10000	0.00015	0.07500	0.075
PCBs	0.00000482	100000	0.00048	0.01694	0.017
Note: BCF of Arsenic is from EPA 1980. BCFs of Cd and Zn from Xu and Wang (2002) and are calculated from the kinetic equation. BCF of Hg from Wang and Wong (2003) and is calculated from the kinetic equation. BCF of Ag from Long and Wang (submitted, Environmental Toxicology and Chemistry) and is calculated from the kinetic equation. BCFs of Cu from Gibbs and Miskowicz (1995). BCFs of Cr, Pb and Ni from IAEA (2000). BCFs of PAHs and PCBs from Veith & Kosian (1983).

2.2 Marine bivalves (mussels and clams)

In assessing the bioaccumulation by the bivalves, uptake from the dissolved uptake and sediment ingestion are separately modelled. The kinetic equation of Eq. 6 is used to predict the accumulation from the dissolved phase as a result of COC desorption from the sediment. The k_u and k_e measured in the local green mussels (Perna viridis) are used to calculate the likely BCF. Alternatively, the BCF is directly referred from IAEA (2000). The predicted COC concentrations in these animals due to uptake of desorbed COCs are shown in Table 2.3.

Table 2.32.2 The predicted COC concentrations in the bivalves (mussels/clams) as a result of uptake of desorbed metals. The bioconcentration factor (BCF) used in the calculations is also shown.

Metals	Elevated concentration	BCF (L kg^-1)	Elevated Concentration in Bivalve (mg kg^-1)	Ambient Concentration in Bivalve (mg kg^-1)	Total Concentration in Bivalve (mg kg^-1)
*East of Sha Chau*
As	0.0155064	350	0.00543	3.30	3.305
Cd	0.001136	10000	0.01136	0.28	0.296
Cr	0.131776	1000	0.13178	0.50	0.636
Cu	0.0381128	2000	0.07623	33.59	33.665
Pb	0.040612	2570	0.10437	1.20	1.300
Hg	0.001988	2000	0.00398	0.03	0.032
Ni	0.004544	2000	0.00909	29.81	29.822
Ag	0.00548	60000	0.32880	1.55	1.884
Zn	0.07668	22000	1.68696	77.40	79.091
LMW PAH	0.00000067	1000	0.00000	0.03	0.025
HMW PAH	0.00003108	10000	0.00031	0.08	0.075
PCBs	0.00000972	100000	0.00097	0.00	0.005
*South Brothers*
As	0.00768768	350	0.00269	3.30	3.303
Cd	0.0005632	10000	0.00563	0.28	0.290
Cr	0.0653312	1000	0.06533	0.50	0.569
Cu	0.01889536	2000	0.03779	33.59	33.627
Pb	0.0201344	2570	0.05175	1.20	1.247
Hg	0.0009856	2000	0.00197	0.03	0.030
Ni	0.0022528	2000	0.00451	29.81	29.818
Ag	0.0005632	60000	0.03379	1.55	1.589
Zn	0.038016	22000	0.83635	77.40	78.240
LMW PAH	0.00000033	1000	0.00000	0.03	0.025
HMW PAH	0.00001541	10000	0.00015	0.08	0.075
PCBs	0.00000482	100000	0.00048	0.00	0.005
Note: BCF of Arsenic is from EPA 1980. BCFs of Cd, Cr(VI), and Zn from Wang (2003), calculated from the kinetic equation (Eq. 6). To convert the BCF of Cr(VI) to Cr(III), it is assumed that the uptake of Cr(III) is 3 times lower than the uptake of Cr(VI) (Wang et al. 1997). BCF of Ag from Wang et al. (1996) calculated from the kinetic equation (Eq. 6). BCFs of other metals (Cu, Pb, Hg, Ni) from IAEA (2000). BCFs of PAHs and PCBs from Pruell et al. (1987).

2.3 Polychaete and Other Deposit-Feeding Worms (Sipunculans).

Similar to marine bivalves ingesting sediments, the accumulation of COCs by the deposit-feeding polychaetes and other worms such as sipunculans is also predicted using the kinetic equation (Eq. 8). However, the AE of COCs has been measured only for a few metals with good techniques (e.g., Cd, Cr, Zn). The extraction of metals from the sediments by the gut juices has been measured in a few polychaete species (e.g., Cu, Pb, Ni, Hg). In order to predict the likely accumulation of these metals in the polychaetes, it is inherently assumed that the AE of these metals is comparable to the extraction efficiency. Such assumption is based that all the extracted metals are assimilated by the animals, and extraction represents the maximum rate of uptake. Thus, prediction of metal accumulation based on the extraction efficiency can be considered as a conservative estimate of the metal accumulation in the deposit-feeding animals. For these animals, the maximum ingestion rate is assumed to be 200% of the tissue dry weight each day (Cammen 1980, Wang et al. 1999). The influx rate of the metals from ingested sediments is then calculated using Eq. 7.

To predict the accumulation of organic contaminants such as PAH and PCBs, again the approach of BSAF is used. In these calculations, the lipid content of the animals and the organic carbon content of the sediments are also considered. The BSAFs of PAHs (0.2) and PCBs (0.68) have been quantified in marine polychaetes in several previous studies (Maruya et al. 1997, Kaag et al. 1997), and these measurements were based on the lipid content and the sediment organic carbon content. To convert these values for the total sediments and the whole individual animal, it is assumed that the organic carbon content in the sediment is 2% and the lipid content of the polychaetes is 1.6% (Maruya et al. 1997). These predictions are shown in Table 2.4.

Table 2.42.3 The predicted COC concentrations in the polychaetes as a result of uptake from sediments. AE: assimilation efficiency, IR: ingestion rate, k_e: efflux rate constant, BSAF: Biota-sediment bioaccumulation factor.

COCs	Elevated concentration in sediment (mg kg^-1)	AExIR/k_e	BSAF	Concentration in Polychaetes (mg kg^-1)
*East of Sha Chau*
As	10.335	0.25		2.58375
Cd	1.32	1		1.32000
Cr	43.633	0.5		21.81650
Cu	27.007	1		27.00700
Pb	24.666	0.5		12.33300
Hg	0.309	2		0.61800
Ni	7.373	0.5		3.68650
Ag	0.339	0.5		0.16950
Zn	60.936	1		60.93600
LMW PAH	1.047		0.2	0.20940
HMW PAH	3.248		0.2	0.64960
PCBs	0.059		0.68	0.04012
*South Brothers*
As	7.654	0.25		1.91361
Cd	0.978	1		0.97754
Cr	32.316	0.5		16.15823
Cu	20.003	1		20.00304
Pb	18.269	0.5		9.13455
Hg	0.229	2		0.45736
Ni	5.461	0.5		2.73031
Ag	0.251	0.5		0.12565
Zn	45.132	1		45.13248
LMW PAH	0.775		0.2	0.15505
HMW PAH	2.406		0.2	0.48118
PCBs	0.044		0.68	0.02969
Note: AEs of Cd, Cr, Zn: Wang et al. (2002). Extraction of Cu, Pb, and Ni: Peng et al. (submitted, Chemosphere). Extraction of Hg: Lawrence et al. 1999. Assuming that extraction=assimilation, k_e=0.02 d^-1, and IR=2 g g^-1 d^-1. BSAF of PAHs from Maruya et al. (1997). BSAF of PCBs from Kaag et al. (1997).

2.4 Predatory Fish, Crabs and Shrimps

To predict the likely COC concentrations in the predatory fish, crabs, and shrimps, the trophic transfer factor is used (Eq. 9). Specifically, the TTF is the ratio of COC concentrations in the predator to those in the preys. The TTF has been measured in a few specific predator-prey systems, but the data are relatively scattered. Suedel et al. (1994) have summarized the TTF of COCs in aquatic ecosystems; these values are then used in the model calculation. To predict the concentration in the predatory fish, the prey fish is assumed. To predict the COC concentrations in the crabs and shrimps, the prey polychaetes are assumed. The COC concentrations in the prey fish and in the polychaetes are referred from the model calculations, again assuming that the COCs are accumulation in the prey fish from the dissolved phase (due to desorption), and in the prey polychaetes from the ingested sediments (due to contaminated sediment deposition). Table 2.5 shows the model predictions.

Table 2.52.4 The predicted COC concentrations in the predators as a result of trophic transfer from the[prey species. TTF = Trophic Transfer Factor. Empty Cells are when no data are present

COCs	TTF in fish	TTF in crabs	TTF in shrimps	Elevation in fish	Elevation in crabs	Elevation in shrimps	Ambient in fish	Ambient in crabs	Ambient in shrimps	Total in fish	Total in crabs	Total in shrimps
COCs	TTF in fish	TTF in crabs	TTF in shrimps	(mg kg^-1)	(mg kg^-1)	(mg kg^-1)	(mg kg^-1)	(mg kg^-1)	(mg kg^-1)	(mg kg^-1)	(mg kg^-1)	(mg kg^-1)
*East of Sha Chau*
As	0.25	0.25	0.25	0.00135681	0.645938	0.645938	3.053377	4.11	3.493084	3.054734	4.757049	4.139022
Cd	0.1	0.01	2.4	0.00002272	0.0132	3.168	0.017039	0.42	0.312122	0.017062	0.432089	3.480122
Cr	0.7			0.01844864			0.054525	0.10	0.065421	0.072974	0.098889	0.065421
Cu	0.5			0.04192408			2.318844	15.24	15.20836	2.360768	15.24444	15.20836
Pb	0.7			0.00568568			0.110494	0.14	0.081132	0.11618	0.143889	0.081132
Hg	0.4	0.8	0.8	0.00540736	0.4944	0.4944	0.031622	0.02	0.01463	0.037029	0.511067	0.50903
Ni	0.7			0.0031808			0.053939	0.29	0.162308	0.05712	0.29	0.162308
Ag	0.5			0.00137			0.026389	0.29	0.217999	0.027759	0.287778	0.217999
Zn	1	1.2	0.7	0.053676	73.1232	42.6552	8.9993	21.30	17.02486	9.052976	94.4232	59.68006
LMW PAH	0.2	0.2	0.2	0.0000001	0.04188	0.04188	0.025	0.025	0.025	0.025	0.06688	0.06688
HMW PAH	0.2	0.2	0.2	0.0000622	0.12992	0.12992	0.075	0.075	0.075	0.075062	0.20492	0.20492
PCBs	4	1.2	1.2	0.00388895	0.048144	0.048144	0.008361	0.00	0.004919	0.01225	0.052366	0.053063
*South Brothers*
As							3.053377	4.11	3.493084	3.053377	4.111111	3.493084
Cd	0.1	0.01	2.4	0.0000113	0.00977535	2.34608483	0.017039	0.42	0.312122	0.017051	0.428664	2.658207
Cr	0.7			0.009146368			0.054525	0.10	0.065421	0.063672	0.098889	0.065421
Cu	0.5			0.020784896			2.318844	15.24	15.20836	2.339629	15.24444	15.20836
Pb	0.7			0.002818816			0.110494	0.14	0.081132	0.113313	0.143889	0.081132
Hg	0.4	0.8	0.8	0.002680832	0.36588469	0.36588469	0.031622	0.02	0.01463	0.034302	0.382551	0.380515
Ni	0.7			0.00157696			0.053939	0.29	0.162308	0.055516	0.29	0.162308
Ag	0.5			0.0001408			0.026389	0.29	0.217999	0.02653	0.287778	0.217999
Zn	1	1.2	0.7	0.0266112	54.1589763	31.5927362	8.9993	21.30	17.02486	9.025911	75.45898	48.6176
LMW PAH	0.2	0.2	0.2	0.0000001	0.0310097	0.0310097	0.025	0.025	0.025	0.025	0.05601	0.05601
HMW PAH	0.2	0.2	0.2	0.0000308	0.0962357	0.0962357	0.075	0.075	0.075	0.075031	0.171236	0.171236
PCBs	4	1.2	1.2	0.001928042	0.0356326	0.0356326	0.008361	0.00	0.004919	0.010289	0.039855	0.040552
Note: TTFs from Suedel et al. (1994) and USEPA (2000).

3 Summary

A summary of determined body burden concentrations from the above exercise is presented below in

Table 3.1~~Table 3.1Table 3.1Table 3.1~~.

Table 3.13.1 Summary of Body Burden Concentration of Contaminants in the Target Species

Mg kg^-1	Pelagic Fish	Bivalve	Predatory Fish	Crab	Shrimp
*East of Sha Chau*
As	1.18778	3.305427	3.054734	4.757049	4.139022
Cd	0.009639	0.29576	0.017062	0.432089	3.480122
Cr	0.089296	0.635576	0.072974	0.098889	0.065421
Cu	2.338554	33.66503	2.360768	15.24444	15.20836
Pb	0.091946	1.299973	0.11618	0.143889	0.081132
Hg	0.048224	0.031976	0.037029	0.511067	0.50903
Ni	0.065132	29.82229	0.05712	0.29	0.162308
Ag	0.02774	1.8836	0.027759	0.287778	0.217999
Zn	14.63015	79.09096	9.052976	94.4232	59.68006
LMW PAH	0.025001	0.025001	0.025	0.06688	0.06688
HMW PAH	0.075311	0.075311	0.075062	0.20492	0.20492
PCBs	0.017913	0.005452	0.01225	0.052366	0.053063
*South Brothers*
As	1.18504	3.30269	3.05338	4.11111	3.49308
Cd	0.00952	0.29003	0.01705	0.42866	2.65821
Cr	0.07601	0.56913	0.06367	0.09889	0.06542
Cu	2.29628	33.6266	2.33963	15.2444	15.2084
Pb	0.08785	1.24735	0.11331	0.14389	0.08113
Hg	0.04141	0.02997	0.0343	0.38255	0.38052
Ni	0.06284	29.8177	0.05552	0.29	0.16231
Ag	0.02528	1.58859	0.02653	0.28778	0.218
Zn	14.6031	78.2404	9.02591	75.459	48.6176
LMW PAH	0.025	0.025	0.025	0.05601	0.05601
HMW PAH	0.07515	0.07515	0.07503	0.17124	0.17124
PCBs	0.01742	0.00496	0.01029	0.03985	0.04055
*Ambient*
As	1.182353	3.3	3.053377	4.111111	3.493084
Cd	0.009412	0.2844	0.017039	0.418889	0.312122
Cr	0.062941	0.5038	0.054525	0.098889	0.065421
Cu	2.254706	33.5888	2.318844	15.24444	15.20836
Pb	0.083824	1.1956	0.110494	0.143889	0.081132
Hg	0.034706	0.028	0.031622	0.016667	0.01463
Ni	0.060588	29.8132	0.053939	0.29	0.162308
Ag	0.025	1.5548	0.026389	0.287778	0.217999
Zn	14.57647	77.404	8.9993	21.3	17.02486
LMW PAH	0.025	0.025	0.025	0.025	0.025
HMW PAH	0.075	0.075	0.075	0.075	0.075
PCBs	0.016941	0.00448	0.008361	0.004222	0.004919

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