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Mathematical models are used for a wide range of toxicological problems such as the level predictions of the bioaccumulative chemicals in aquatic organisms. There are several types of mathematical models used for these problems such as equilibrium partitioning model (EQP), mechanistic mass balance models, fugacity models, compartment based kinetic models, physiologically and bioenergetics based models.

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Equilibrium partitioning model (EQP) is the simplest mathematical model for the prediction of accumulation levels. The model depends on the thermodynamic equilibrium of the exposed organism and exposure environment. Predictions of this model are independent from chemical properties, organism characteristics and environment conditions (Ryan, 2003).

Mechanistic mass balance models use mathematical descriptions of uptake and depuration phases of accumulation. These phases depend on organism characteristics and chemical properties, additional to EQP models. Early studies of bioaccumulation models were performed by Thomann (1989) and Gobas (1993). Rate constants were used for the development of these models. Fresh water food webs including sediment environment were set up in the models representing well the upper trophic level such as fish, but representing less accuracy of pollutant transfer for benthic invertebrates. Another mechanistic model study was developed by Morrison et.al. (1996) for benthic invertebrates. Pollutant uptake from water, sediment and plankton was considered in this model. Models developed by Morrison et al. (1996) and Gobas (1993) were combined for a new updated model of POP (Persistent Organic Pollutants) bioaccumulation in the food webs of Great Lakes ecosystem (Morrison et al, 1997; Morrison et al, 1999; Ryan, 2003).

Mechanistic models were mostly applied in freshwater ecosystems (e.g. Thomann, 1989; Gobas, 1993; Morrison et al, 1997). There have been few attempts of bioaccumulation modeling in marine ecosystems (e.g. Connolly, 1991; Linkov et al, 2002; Ryan, 2003). Ryan (2003) has been developed a food web bioaccumulation model to predict BSAF (biota sediment accumulation factor) for PCBs (Polychlorinated Biphenyls) (Log Kow greater than 5.24) in benthic marine

ecosystem. It has also been successfully applied for PAHs with log Kow greater than

4.6 (Ryan, 2003).

Furthermore, Campfens and Mackay (1997) were developed a food web bioaccumulation model in Great Lakes ecosystem. This model is based on fugacity principle which uses the same mathematical approach with rate constant principle additional to EQP principle for the model evaluation. They have also used a food web matrix in their model to represent the non-linearity of aquatic food webs (Ryan, 2003).

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Other models such as compartment based kinetic models, physiologically and bioenergetics based models are also usable for the determination of pollutant accumulation and distribution in aquatic organisms (Landrum et al, 1992)

Several toxicokinetic modeling studies were performed in order to predict the concentrations of organic chemicals especially in fish species. Advantages and disadvantages of both equilibrium and kinetic models were explained by comparing different model structures (Landrum et al, 1992). Mackay and Fraser (2000) were also compared empirical and mechanistic models in a review of bioaccumulation models (Stadnicka et al, 2012).

Toxicokinetic approaches like compartment and PBTK (physiologically based toxicokinetic modeling) models were also used to simulate the chemical concentrations in fish. A one-compartment model was developed by Arnot and Gobas (2004) to predict the bioaccumulation of organic chemicals in aquatic ecosystems. Additional to the predictions of bioaccumulation levels, acquiring site- specific toxicant concentrations, BCF (bioconcentration factor), BAF (bioaccumulation factor) and BSAF were amongst the objectives of the developed model. They also stated that the exchange of nonionic organic chemicals between the organisms and the surrounding environment can be represented using the same equation for different aquatic species. Another one compartment model was developed to represent the different accumulation levels between different species and organic chemicals (Hendriks et al, 2001). Kow (octanol-water partition

coefficient), lipid content, weight and trophic level of the species were the parameters used to predict the accumulation kinetics of selected chemicals. Besides one compartment models, multi compartment models were also used in toxicokinetic studies. Nichols et al. (1990; 1991; 1993) were developed and improved a physiologically based model for fish species using the relationship of the whole body lipid ratio with the volume of fat compartment. More physiological data were used for this model due to the number of compartments(Stadnicka et al, 2012).

Generally, fish species were used as target organisms of bioaccumulation modeling studies. BAF-QSAR (Quantitative Structure Activity Relationship) is a food web bioaccumulation model developed for fish species in upper, middle and lower trophic levels of aquatic food webs. It is based on the article of Arnot and Gobas (2003). The

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code is written in Microsoft Excel workbook. Non-ionic organic chemicals can be classified with this model according to their bioaccumulative potential in the aquatic food web. FISH bioaccumulation model contains both bioconcentration and biomagnification processes. This model code is written in BASIC programming language and describes the uptake and depuration of organic chemicals by fish. MICHTOX is a coupled mass balance and bioaccumulation model developed by U.S. EPA for toxic chemicals in Lake Michigan (Rossmann, 2005). Accumulation of chemicals, especially PCBs in lake trout and bloater was predicted using MICHTOX model. Another bioaccumulation model, OMEGA, represents four trophic levels (phytoplankton, zooplankton, small and large fish) in marine and fresh water food chain. In OMEGA model, accumulation kinetics of the target organic chemicals are predicted with fugacity theory using both chemicals' and organisms' properties such as octanol–water partition ratio (Kow) of the chemical, weight and lipid content of the

organism additional to the trophic level.

Except the models mentioned above, there are also other computer models which can also be used for bioaccumulation studies besides their other properties like chemical fate modeling, toxicity and risk assessment. AQUATOX is a general ecological risk assessment model. Environmental fate and effects of pollutants can be represented with AQUATOX model. In this model, bioaccumulation process and its potential toxic effects are included. This model is used for streams, small rivers, ponds and reservoirs. BASS is another model used to predict the population and bioaccumulation dynamics of fish assemblages exposed to both hydrophobic organic pollutants and borderline metal complex with sulfhydryl groups like cadmium, copper, lead and mercury. Bioaccumulation algorithms of this model are based on diffusion kinetics. Also, the model is coupled to a process-based model for growth of individual fish. Biotic Ligand Model predicts the bioavailability, bioaccumulation and toxicity of metals. EcoFate is a time-dependent model used to predict the concentrations of organic chemicals in water, sediment, fish and fish eating birds. Predicted concentrations in lakes, rivers and marine inlets can be simulated with this model. E-MCM simulates the transfer of mercury in a linear food chain through dietary and direct uptakes. This model is executed both in steady state and dynamic modes. QEAFDCHN is a dynamic bioaccumulation model. This model assumes that the chemicals are uptake through the respiration and ingestion process and lost by

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diffusion across the respiratory surfaces. These uptake and loss processes of toxic chemicals by forage and predatory fish are mechanistically simulated with this model. RAMAS Ecosystem models the bioaccumulation process in food chains. There are several options to select for the execution of this model such as specifying the nature and parametric description of uptake kinetics, survival and fecundity, density dependence, appropriate dose-response models. Additionally, 2nd order Monte-Carlo analysis is used for the natural and temporal variability and measurement errors of the model. TRIM.FaTE is a multimedia compartment model developed to represent the fate and transfer of chemicals in both aquatic and terrestrial environments. Bioaccumulation of organic chemicals and metals can be modeled with this compartment based model. Equations and compartments can be edited and linked together due to its flexible interface.

All kinds of mentioned bioaccumulation models (equilibrium partitioning model, mechanistic mass balance models, fugacity models, compartment based kinetic models, physiologically and bioenergetics based models) are mainly aimed to predict the bioaccumulation levels of pollutants in aquatic ecosystems. This literature review revealed that the bioaccumulation modeling studies were mostly performed for fresh water food webs, especially for the upper trophic levels such as fish species. Bioaccumulation predictions are also focused on the levels of organic chemicals such as PCBs and metals in food webs. Beside these studies, there are also modeling studies including sediment environment and lower trophic levels such as planktons, zooplanktons and invertebrates.

In this study, PAH bioaccumulation and depuration in mussel tissues were investigated by using two model PAHs having different Kow values and number of

rings. The study also aimed to investigate the toxic effects of those PAHs along with their accumulation and depuration from the mussel tissues. Theoretical modeling part of the study was supported with the experimental study. Depuration periods followed immediately the uptake period in the performed experiments.The difference of this study comes from the combination of model and toxicity investigations, thus it is observed how the bioaccumulation affect the toxicity in mussels.

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Modeling of PAH bioaccumulation studies were generally performed with fish species due to their high mobility and ecological role in the food webs. Energy transfer between lower and upper trophic levels of the food chain makes fish species ecologically important (Beyer, 1996; Oost, 2003). Mussel species are also important elements of the food chain besides fish species. Even in some food cultures, they can directly reach to the upper level of the trophic level due to directly consumption by humans. Mussels accumulate and transfer PAHs to the higher levels of the food chain due to their low enzyme activity and low PAH metabolization. Thus, modeling studies with mussel species can highlight the concentration levels and transfer routes of PAHs in the food chain. If PAH concentration levels in mussels can be determined during or after the periods of PAH exposures, needed durations to depure the mussels can also be determined with modeling studies. Furthermore, if the routes of PAH transfer in the mussels can be determined with modeling studies, then the control mechanisms to prevent PAH bioaccumulation in mussels can be searched and applied.