Mercury (Hg) is a pollutant of global concern. Due to anthropogenic emissions, the atmospheric and surface ocean Hg burden has increased substantially since preindustrial times. Hg emitted into the atmosphere gets transported on a global scale and ultimately reaches the oceans. There it is transformed into highly toxic methylmercury (MeHg) that effectively accumulates in the food web. The international community has recognized this serious threat to human health and in 2017 regulated Hg use and emissions under the UN Minamata Convention on Mercury. Currently, the first effectiveness evaluation of the Minamata Convention is being prepared, and, in addition to observations, models play a major role in understanding environmental Hg pathways and in predicting the impact of policy decisions and external drivers (e.g., climate, emission, and land-use change) on Hg pollution. Yet, the available model capabilities are mainly limited to atmospheric models covering the Hg cycle from emission to deposition. With the presented model MERCY v2.0 we want to contribute to the currently ongoing effort to improve our understanding of Hg and MeHg transport, transformation, and bioaccumulation in the marine environment with the ultimate goal of linking anthropogenic Hg releases to MeHg in seafood.

Here, we present the equations and parameters implemented in the MERCY model and evaluate the model performance for two European shelf seas, the North and Baltic seas. With the model evaluation, we want to establish a set of general quality criteria that can be used for evaluation of marine Hg models. The evaluation is based on statistical criteria developed for the performance evaluation of atmospheric chemistry transport models. We show that the MERCY model can reproduce observed average concentrations of individual Hg species in water (normalized mean bias: HgT 17 %, Hg0 2 %, MeHg −28 %) in the two regions mentioned above. Moreover, it is able to reproduce the observed seasonality and spatial patterns. We find that the model error for HgT(aq) is mainly driven by the limitations of the physical model setup in the coastal zone and the availability of data on Hg loads in major rivers. In addition, the model error in calculating vertical mixing and stratification contributes to the total HgT model error. For the vertical transport we find that the widely used particle partitioning coefficient for organic matter of log(kd)=5.4 is too low for the coastal systems. For Hg0 the model performance is at a level where further model improvements will be difficult to achieve. For MeHg, our understanding of the processes controlling methylation and demethylation is still quite limited. While the model can reproduce average MeHg concentrations, this lack of understanding hampers our ability to reproduce the observed value range. Finally, we evaluate Hg and MeHg concentrations in biota and show that modeled values are within the range of observed levels of accumulation in phytoplankton, zooplankton, and fish. The model performance demonstrates the feasibility of developing marine Hg models with similar predictive capability to established atmospheric chemistry transport models. Our findings also highlight important knowledge gaps in the dynamics controlling methylation and bioaccumulation that, if closed, could lead to important improvements of the model performance.