| Summary: | The global atmospheric cycling of persistent organic pollutants is complex because of partitioning among phases of the aerosol and revolatilization. Many of the substances are detrimental to human health and the environment. Global dynamical multicompartmental chemistry and transport models are needed to investigate their fate and distributions. The first study investigates climate change influences on the meridional transports of dichlorodiphenyltrichloroethane (DDT) and polychlorinated biphenyls (PCBs) to and from the Arctic by application of the MPI-MCTM model. The objectives are to determine major transport gates along the Arctic Circle, the trends in import and export fluxes, and the relationships between transports and two selected patterns of climate variability, the Arctic Oscillation (AO) and the North Atlantic Oscillation (NAO), under present-day (1970−1999) and future (2070−2099) climate. The pollutants enter the Arctic by passing through the Alaska−Northwest Territories regions, Greenland, the Norwegian Sea−Northwestern Russia, and the Urals−Siberian; whereas they leave the Arctic via the Canadian Arctic and Eastern Russia. DDT import fluxes to the Arctic show a decreasing trend during the present climate, but the trend is expected to change to increasing import fluxes. In contrast, PCB153 export from the Arctic is expected to be increasing in the future climate. The zonal mean meridional fluxes across the Arctic Circle are positively correlated with AO/NAO in winter, corresponding to high net imports when the frequency of positive AO/NAO increases. Under the future climate, there will be an increasing significance of the correlations for DDT while the correlations for PCB153 are expected to weaken. It is concluded that the long-term accumulation trends of other persistent pollutants in the Arctic need to be studied specifically. In the second study, the new module SVOC was developed and coupled to the ECHAM/MESSy Atmospheric Chemistry (EMAC) model to facilitate a continuous development of modeling ...
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