Abstract

Abstract. Mercury is a global pollutant due to its long lifetime in the atmosphere. Its hemispheric transport patterns and eventual deposition are therefore of major concern. For the purpose of global atmospheric mercury chemistry and transport modelling the ECHMERIT model was developed. ECHMERIT, based on the global circulation model ECHAM5 differs from most global mercury models in that the emissions, chemistry (including general tropospheric chemistry and mercury chemistry), transport and deposition are coupled on-line to the GCM. The chemistry mechanism includes an online calculation of photolysis rate constants using the Fast-J photolysis mechanism, the CBM-Z tropospheric gas-phase mechanism and aqueous-phase chemistry based on the MECCA mechanism. Additionally, a mercury chemistry mechanism that incorporates gas and aqueous phase mercury chemistry is included. A detailed description of the model, including the wet and dry deposition modules, and the implemented emissions is given in this technical report. First model testing and evaluation show a satisfactory model performance for surface ozone and mercury mixing ratios (with a mean bias of 1.46 nmol/mol for ozone and a mean bias of 13.55 fmol/mol for TGM when compared with EMEP station data). Requirements regarding measurement data and emission inventories which could considerably improve model skill are discussed.

Highlights

  • While local and regional emission sources are the main cause of air pollution problems worldwide, there is increasing ev-idence that many air pollutants are transported on a hemispheric or global scale and are altering air quality even in remote areas (Stohl et al, 2002; Liang et al, 2004; Eckhardt et al, 2003; Lindberg et al, 2007)

  • Within ECHMERIT an approach similar to that described by Kerkweg et al (2006) is used, which applies the big leaf approach used in ECHAM3 and ECHAM4 (Ganzeveld and Lelieveld, 1995; Ganzeveld et al, 1998, 2006), taking into consideration bulk properties of the respective surfaces, without accounting for removal processes occuring in different layers of the canopy

  • With respect to Hg associated with aerosols, ECHMERIT distinguishes between Hg associated with particulate matter that is directly emitted to the atmosphere from anthropogenic sources, and the Hg associated with particulate matter that is left behind after the evaporation of fog, cloud www.geosci-model-dev.net/2/175/2009/

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Summary

Introduction

While local and regional emission sources are the main cause of air pollution problems worldwide, there is increasing ev-. Elemental Hg is in contrast, due to its long lifetime of 0.5–2 years (Hedgecock and Pirrone, 2004), transported over long distances This means that the relationship between emissions, atmospheric concentrations, and deposition is much less straightforward, than for shortlived chemical species, and interhemispheric transport plays a major role in mercury chemistry modelling. CTM-Hg (Global Chemical Transport Model for Mercury) developed by AER/EPRI (Atmospheric and Environmental Research, Inc./Electric Power Research Institute) (Seigneur et al, 2001, 2004) is another global scale offline model that runs with a resolution of 8×10◦ and nine vertical layers but has a rather complex chemistry included, that considers gasand aqueous-phase oxidation and aqueous-phase reduction of Hg species. The newly developed model ECHMERIT, that is presented in the following is designed to combine the advantages of an online-coupling approach for atmospheric chemistry and transport modelling with a rather complex tropospheric chemistry and mercury chemistry description, suitable for global scale issues and flexible enough to be run in low to high resolution

Atmospheric physics
Transport
Chemistry
Gaseous dry deposition
Particulate dry deposition and sedimentation
Wet deposition
Emissions
Model discretization
Technical implementation
Model setup
Model testing
Deposition velocities
OH concentrations
Hg mixing ratios
Statistical measures for mercury and ozone validation
Mercury deposition processes
Performance on a multiple-processor linux cluster
Findings
Conclusions and outlook
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