Volatile halogenated organic compounds containing bromine and iodine, which are naturally produced in the ocean, are involved in ozone depletion in both the troposphere and stratosphere. Three prominent compounds transporting large amounts of marine halogens into the atmosphere are bromoform (CHBr3), dibromomethane (CH2Br2) and methyl iodide (CH3I). The input of marine halogens to the stratosphere has been estimated from observations and modelling studies using low-resolution oceanic emission scenarios derived from top-down approaches. In order to improve emission inventory estimates, we calculate data-based high resolution global sea-to-air flux estimates of these compounds from surface observations within the HalOcAt (Halocarbons in the Ocean and Atmosphere) database (https://halocat.geomar.de/). Global maps of marine and atmospheric surface concentrations are derived from the data which are divided into coastal, shelf and open ocean regions. Considering physical and biogeochemical characteristics of ocean and atmosphere, the open ocean water and atmosphere data are classified into 21 regions. The available data are interpolated onto a 1°×1° grid while missing grid values are interpolated with latitudinal and longitudinal dependent regression techniques reflecting the compounds' distributions. With the generated surface concentration climatologies for the ocean and atmosphere, global sea-to-air concentration gradients and sea-to-air fluxes are calculated. Based on these calculations we estimate a total global flux of 1.5/2.5 Gmol Br yr−1 for CHBr3, 0.78/0.98 Gmol Br yr−1 for CH2Br2 and 1.24/1.45 Gmol Br yr−1 for CH3I (robust fit/ordinary least squares regression techniques). Contrary to recent studies, negative fluxes occur in each sea-to-air flux climatology, mainly in the Arctic and Antarctic regions. "Hot spots" for global polybromomethane emissions are located in the equatorial region, whereas methyl iodide emissions are enhanced in the subtropical gyre regions. Inter-annual and seasonal variation is contained within our flux calculations for all three compounds. Compared to earlier studies, our global fluxes are at the lower end of estimates, especially for bromoform. An under-representation of coastal emissions and of extreme events in our estimate might explain the mismatch between our bottom-up emission estimate and top-down approaches
Abstract. Concern about the adverse effects of mercury on human health and ecosystems has led to tightening emission controls since the mid 1980s. But the resulting mercury emissions reductions in many parts of the world are believed to be offset or even surpassed by the increasing emissions in rapidly industrializing countries. Consequently, concentrations of atmospheric mercury are expected to remain roughly constant. Here we show that the worldwide atmospheric mercury concentrations have decreased by about 20 to 38 %
Mercury is a priority pollutant as its mobility between the hydrosphere and the atmosphere threatens the biosphere globally. The air-water gas transfer of elemental mercury (Hg0) is controlled by its diffusion through the water-side boundary layer and thus by its diffusion coefficient, D(Hg), the value of which, however, has not been established. Here, the diffusion of Hg0 in water was modeled by molecular dynamics (MD) simulation and the diffusion coefficient subsequently determined. Therefore the movement of either Hg(0) or xenon and 1000 model water molecules (TIP4P-Ew) were traced for time spans of 50 ns. The modeled D(Xe) of the monatomic noble gas agreed well with measured data; thus, MD simulation was assumed to be a reliable approach to determine D(Hg) for monatomic Hg(0) as well. Accordingly, Hg(0) diffusion was then simulated for freshwater and seawater, and the data were well-described by the equation of Eyring. The activation energies for the diffusion of Hg0 in freshwater was 17.0 kJ mol(-1) and in seawater 17.8 kJ mol(-1). The newly determined D(Hg) is clearly lower than the one previously used for an oceanic mercury budget. Thus, its incorporation into the model should lead to lower estimates of global ocean mercury emissions.
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