The 3D biogeochemical marine mercury cycling model MERCY v2.0 – linking atmospheric Hg to methyl mercury in fish

Abstract. Mercury (Hg) is a pollutant of global concern. Due to anthropogenic emissions, the global Hg burden has been ever increasing 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 under the UN Minamata Convention. 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 further 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 sea food.

Here, we present the governing equations and parameters implemented in the MERCY model and evaluate the model performance for two European shelf seas, the North-and Baltic Sea. With the presented 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 a rigid statistical framework developed for the quantitative evaluation of atmospheric chemistry transport models. Using the approach, we show that the MERCY model can reproduce observed average concentrations of individual Hg species (normalized mean bias: Hg_T 17 %, Hg⁰ 2 %, MeHg -28 %) in two complex coastal oceans. Moreover, it is able to reproduce the observed seasonality and spatial patterns. We find that the model error for Hg_T(aq) is mainly driven by the limitations of the physical model setup in the coastal zone and the poor quality of data on Hg in major rivers (i.e.: Schelde and Elbe). In addition, the model error in calculating vertical mixing and stratification contributes to the total Hg_T model error. For the vertical transport we find that the widely used particle partitioning coefficient for organic matter of log(k_d)=5.6 is too low for the coastal systems. For Hg⁰ the model performance is at a level where further model improvements will be difficult to detect. For MeHg, there is still a lack in the basic understanding of the processes governing methylation and demethylation. While the model can reproduce average MeHg concentrations this lack in understanding hampers our ability to reproduce the observed value range. Finally, we evaluate Hg and MeHg concentrations in biota and show, that modelled values are within the range of observed levels of accumulation in phytoplankton, zooplankton, and fish. The results of the model evaluation prove the feasibility of developing marine Hg models with similar predictive capability as 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.