1The 3D biogeochemical marine mercury cycling model MERCY – linking atmospheric Hg to methyl mercury in the marine food web.

<p>Mercury (Hg) is a pollutant of global concern. Due to anthropogenic emissions, the global Hg burden has been ever<br>increasing since preindustrial times. Hg emitted into the atmosphere gets transported on a global scale and ultimately<br>reaches the oceans where it is transformed into highly toxic methylmercury (MeHg) that effectively accumulates along<br>the food chain. The international community has recognized this serious threat to human health and in 2017 regulated<br>Hg under the UN Minamata Convention.<br>Currently, the first effectiveness evaluation of the Minamata Convention on mercury is being prepared and besides<br>observations, models play a major role in understanding environmental Hg pathways and to predict the impact of policy<br>decisions and external drivers (e.g. climate, emission, and land-use change) on Hg pollution. Yet, the available model<br>capabilities are mostly focused on atmospheric models covering the Hg cycle from emission to deposition. With the<br>presented model for marine mercury cycling (MERCY) we want to contribute to the currently ongoing effort to further<br>our understanding of Hg and MeHg transport, transformation, and bioaccumulation in the marine environment with the<br>ultimate goal of linking atmospheric Hg emissions to MeHg in sea food. MERCY is the first fully resolved 3dbiogeochemical<br>model linking atmospheric Hg to MeHg in higher trophic levels. Most importantly, the MERCY model<br>is prgrammed in a way that allows for the coupling of the Hg chemistry, ecosystem, and bioaccumulation models with<br>most established hydrodynamic ocean models. This is achieved using the Framework for Aquatic Biogeochemical<br>Models (FABM).<br>In this talk we present the MERCY model and its application using different hydrodynamic drivers. Moreover, we<br>discuss its capabilities and shortcomings in reproducing the key Hg species Hg0, Hg2+, and MeHg as well as Hg loads<br>in biota. The presented model evaluation is a first step in establishing quality criteria for marine Hg modelling. We show<br>that the model can reproduce observed average concentrations of individual Hg species (normalized mean bias: HgT<br>(aq) -17%, Hg0 2%, MeHg -28%). Moreover, it is able to reproduce the observed seasonality and spatial patterns. We<br>find that the model error for HgT (aq) is mainly driven by the limitations of the physical model setup in the coastal zone<br>and the poor quality of data on Hg in rivers. Morover, the model error in calculating vertical mixing and stratification<br>contributes to the total Hg model error.<br>skill is in a range where further model improvements will be difficult to detect. Finally, for MeHg, we find that we are<br>lacking the basic understanding of the actual processes governing methylation and demethylation. Here, the model can<br>reproduce average concentrations but falls short in reproducing the observed value range. The results prove the<br>feasibility of developing marine Hg models with similar predictive capability as established atmospheric chemistry<br>transport models. Yet, there are still major knowledge gaps in the dynamics governing methylation and<br>bioaccumulation. Based on our findings we discuss these knowledge gaps and identify the major uncertainties in our<br>current understanding of marine Hg cycling from a modeller&#8217;s perspective.</p>