Modelling of mercury emissions from background soils.

Emissions of volatile mercury species from natural soils are believed to be a significant contributor to the atmospheric burden of mercury, but only order-of-magnitude estimates of emissions from these sources are available. The scaling-up of mercury flux measurements to regional or global scales is confounded by a limited understanding of the physical, chemical and biochemical processes that occur in the soil, a complex environmental matrix. This study is a first step toward the development of an air-surface exchange model for mercury (known as the mercury emission model (MEM)). The objective of the study is to model the partitioning and movement of inorganic Hg(II) and Hg(0) in open field soils, and to use MEM to interpret published data on mercury emissions to the atmosphere. MEM is a multi-layered, dynamic finite-element soil and atmospheric surface-layer model that simulates the exchange of heat, moisture and mercury between soils and the atmosphere. The model includes a simple formulation of the reduction of inorganic Hg(II) to Hg(0). Good agreement was found between the meteorological dependence of observed mercury emission fluxes, and hourly modelled fluxes, and it is concluded that MEM is able to simulate well the soil and atmospheric processes influencing the emission of Hg(0) to the atmosphere. The heretofore unexplained close correlation between soil temperature and mercury emission flux is fully modelled by MEM and is attributed to the temperature dependence of the Hg(0) Henry's Law coefficient and the control of the volumetric soil-air fraction on the diffusion of Hg(0) near the surface. The observed correlation between solar radiation intensity and mercury flux, appears in part to be due to the surface-energy balance between radiation, and sensible and latent heat fluxes which determines the soil temperature. The modelled results imply that empirical correlations that are based only on flux chamber data, may not extend to the open atmosphere for all weather scenarios.