When dealing with pollutants it is important to understand for a given compound its persistence (P) in the environment and its long range transport potential (LRTP). These two characteristics help in assessing its environmental fate as well as the spatial and temporal extents of environmental exposure (Leip and Lammel, 2004). Furthermore, it is also essential to identify the contamination sources and emissions. These have important implications for their fate as well as for the approach it should be followed to develop monitoring programs. For example, contaminants may be released in a pulse due to an accidental discharge; they may be periodically driven by human activities (application of pesticides in agriculture) or by environmental fluctuations (e.g. temperature dependence), or constantly during the year.
Even though the effects of contaminants are more pronounced in inland, transitional and coastal waters, the oceans play an important role in controlling the environmental transport, fate and sinks of organic pollutants, specifically persistent organic pollutants (POPs), at regional and global scales (Wania and Mackay, 1996; Dachs et al., 2002). It has been demonstrated that water-column processes have a strong impact on the air-sea exchange of organic contaminants, since their efficient removal from the mixed surface water layer reduces the volatilization rates and captures atmospheric pollutants (Dachs et al., 1999; Scheringer et al., 2004). Nevertheless, there is a complex interplay of processes controlling the vertical transport of contaminants in the water column the knowledge of which is limited due to the scarcity of measurements on the role of the ecosystems on the uptake, depuration and settling of POPs (Schulz-Bull et al., 1988; Dachs et al., 1997; Gustafsson et al., 1997; Dachs et al., 1999). On the other hand, coastal and marine sediments have been hypothesized to become a pool of contaminants available for mixing throughout the water column, especially during poorly stratified periods (Baker et al., 1991; Berlung et al., 2001; Bodgan et al., 2002; Ko et al., 2003; Jurado et al., 2007). Therefore, in order to be able to simulate properly the dynamics of organic pollutants in the water column, we need to consider all these aspects, in particular for shallow water bodies and the ocean shelf zone. The traditional approach to model contaminants in the water column is to consider two well-mixed boxes during stratification periods and one well-mixed the rest of the time (Schwarzenbach et al., 2003; Meijer et al., 2006). The extensive number of 0D models for these hydrophobic organic compounds (Wania and Mackay, 1996; Scheringer et al., 2000; Dalla Valle et al., 2003; Dueri et al., 2005) contrasts with the lack of spatially and temporally resolved models, with the exception of the recently developed coastal lagoon model for herbicides (Carafa et al., 2006), but its chemical behavior differs from those of POPs, and the lately one for HCH by Ilyina et al. (2006). In two previous works (Jurado et al., 2007; Marinov et al., 2007), we have developed a 1D dynamic hydrodynamic-contaminant model to analyze the influence of vertical mixing on the distribution of POPs in the water column. The effect of seasonal dynamics of phytoplankton on POPs fate has been also considered but as a forcing function. The selection of 1D model version followed two reasons – first, we planned to validate it using water column data for the selected chemicals and, second, the 1D version is adequate for opensea areas, where the atmospheric transport is the prevalent route for the introduction of contaminants (Tolosa et al, 1997). Furthermore, the 1D approach avoids the difficulties associated with providing time-series of boundary conditions; it reduces computation time and prepares a simpler model variant which after verification gives the option to easily extend it to 3D model version using the COHERENS framework as it has been foreseen in Stream 4 for the Thau lagoon case study. The model was applied to the organic contaminants families selected in Thresholds, i.e. PCBs, PAHs, and PBDEs, plus dioxins and furans, PCDD/Fs.
In this work, we have introduced a food-web ecological model that considers phytoplankton, zooplankton, bacteria and detritus. The model uses nutrient concentrations as forcings and it has been validated using chlorophyll a data at two different stations in the Mediterranean. The dynamics of the ecosystem has been coupled with the previous develop fate model in terms of organic matter and partitioning of the POPs. Environmental concentrations in all ecological compartments are simulated. In order to perform a first validation of the coupled model, experimental data on PAHs obtained at the Finokalia Station, Island of Crete, Greece. (Tsapakis et al., 2005 and 2006) have been used (the validation will continue by incorporating all available experimental data from Thresholds’ campaigns). The results show that the model is able to reproduce the experimental concentrations as well as the measured fluxes.