Evaluation of the Impact of Air-Sea Exchange on Atmospheric Mercury Concentrations

  • Johannes BieserEmail author
  • Corinna Schrum
Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)


Mercury is a toxic substance that is ubiquitous in the environment. In the atmosphere mercury exists mainly in the form of gaseous elemental mercury (GEM). Deposition is dominated by oxidized mercury species although they make up for only 1% of the total mercury in the atmosphere. The situation in the aquatic environment is inverse. Here, mercury exists mainly in its oxidized state HgII. Due to photolysis and biological activity mercury in the Ocean is reduced to dissolved elemental mercury (DEM). As mercury is constantly cycling between the ocean and the atmosphere it is important to include both compartments into a chemistry transport model in order to understand it’s environmental fate. For this study, we coupled the atmospheric chemistry transport system CMAQ to the three dimensional Eulerian ocean-ecosystem model ECOSMO. We implemented photolysis, chemical reactions, and biologically induced transformation for elemental, oxidized, and methylated mercury species into the ocean model. Based on wind speed and temperature elemental mercury is exchanged between the ocean and the atmosphere. The model was set up for a regional domain covering the North- and Baltic Sea region and was run for a period of 14 years from 1993 to 2005. The ocean model was evaluated using DEM observations from a series of six cruises (MNB = 0.21 MNE = 0.53). Furthermore, we compared model results with and without ocean coupling to GEM observations at 5 EMEP stations. We found, that the coupled model system is able to reproduce GEM peaks which the uncoupled CTM was missing. However, the effect was limited to stations in a vicinity of 100 km to the coast (e.g. at the EMEP station DE09 in Zingst the model bias was reduced from −0.11 to 0.02 for the year 2000 and from −0.10 to −0.03 for 2005). On average, atmospheric GEM concentrations were increased by 5% in the North and Baltic Sea region.


  1. Barthel K, Daewel U, Pushpadas D, Schrum C, Arthun M et al (2012) Resolving frontal structures: on the computational costs and pay-off using a less diffusive but computational more expensive advection scheme. Ocean Dyn. doi: 10.1007/s10236-012-0578-9
  2. Bieser J, Aulinger A, Matthias V, Quante M, Builtjes P (2011a) SMOKE for Europe—adaptation, modification and evaluation of a comprehensive emission model for Europe. Geosci Model Dev 4:47–68. doi: 10.5194/gmd-4-47-2011 CrossRefGoogle Scholar
  3. Bieser J, Aulinger A, Matthias V, Quante M, Denier van der Gon HAC (2011b) Vertical emission profiles for Europe based on plume rise calculations. Environ Pollut 159:2935–2946. doi: 10.1016/j.envpol.2011.04.030 CrossRefGoogle Scholar
  4. Bieser J, Matthias V, Travnikov O, Hedgecock MI, Gencarelli CN, De Simone F, Weigelt A, Zhu J (2014a) A diagnostic evaluation of modeled mercury wet deposition in Europe using atmospheric speciated high-resolution observations. Environ Sci Pollut Res 21(16)Google Scholar
  5. Bieser J, Matthias V, Travnikov O, Hedgecock MI, Gencarelli CN, De Simone F, Weigelt A, Zhu J (2014b) Impact of mercury chemistry on regional concentration and deposition patterns. In: Gyring S-E, Batchvarova E (eds) Air pollution modeling and its application XXIII, pp 189–195Google Scholar
  6. Bieser J, Schrum C (2016) Impact of marine mercury cycling on coastal atmospheric mercury concentrations in the North- and Baltic Sea region, ELEMENTA 111. doi: 10.12952/journal.elementa.000111
  7. Bullock OR, Brehme KA (2002) Atmospheric mercury simulations using the CMAQ model: formulation description and analysis of wet deposition results. Atmos Environ 36:2135–2146CrossRefGoogle Scholar
  8. Daewel U, Schrum C (2013) Simulating long-term dynamics of the coupled North Sea and Baltic Sea ecosystem with ECOSMO II. Model description and validation. J Mar Sys 119–120:30–49Google Scholar
  9. Gencarelli CN, Bieser J, Carbone F, DeSimone F, Hedgecock IM, Matthias V, Travnikov O, Yang X, Pirrone N (2016) Sensitivity study of regional mercury dispersion in the atmosphereGoogle Scholar
  10. Kuss J, Schneider B (2007) Variability of the gaseous elemental mercury Sea-Air flux of the Baltic Sea. Environ Sci Technol 41:8018–8023CrossRefGoogle Scholar
  11. Kuss J (2014) Water-air gas exchange of elemental mercury: an experimentally determined mercury diffusion coefficient for Hg0 water-air flux calculations. Limnol Oceanogr 59(5):1461–146Google Scholar
  12. Nightingale PD, Malin G, Law CS, Watson AJ, Liss P et al (2000) In-situ evaluation of air-sea gas exchange parameterizations using novel conservative and volatile tracers. Glob Biogl Cyc 14:373–387CrossRefGoogle Scholar
  13. Qureshi A (2011) Quantifying and reducing uncertainties in global mercury cycling. Disseration ETH No. 19709. Zürich, SwitzerlandGoogle Scholar
  14. Schrum C, Backhaus JO (1999) Sensitivity of atmosphere-ocean heat exchange and heat content in the North Sea and the Baltic Sea. Tellus A 51(4):526–549. doi: 10.1034/j.1600-0870.1992.00006.x CrossRefGoogle Scholar
  15. Travnikov O, Ilyin I (2009) The EMEP/MSC-E mercury modeling system. In: Pirrone N, Mason RP (eds) Mercury fate and transport in the global atmosphere. Springer, Dordecht, pp 571–587Google Scholar
  16. UNEP (United Nations Environmental Program) (2013) Minamata Convention on MercuryGoogle Scholar
  17. Wängberg I, Schmolke S, Schager P, Munthe J, Ebinghaus R et al (2001) Estimates of air-sea exchange of mercury in the Baltic Sea. Atmos Environ 35(2001):5477–5484CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Helmholtz-Zentrum GeesthachtInstitute of Coastal ResearchGeesthachtGermany

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