Global-scale environmental transport of persistent organic pollutants

In order to realistically simulate both chemistry and transport of atmospheric organic pollutants, it is indispensable that the applied models explicitly include coupling between different components of the global environment such as atmosphere, hydrosphere, cryosphere and soil system. A model with such properties is presented.

The atmospheric part of the model is based on the equations in a general contravariant form which permits easy changes of the coordinate system by redefining the metric tensor of a specifically employed coordinate system. Considering a need to include explicitly the terrain effects, the terrain following spherical coordinate system is chosen from among many possible coordinate systems. This particular system is a combination of the Gal-Chen coordinates, commonly employed in mesoscale meteorological models, and the spherical coordinates, typical for global atmospheric models.

In addition to atmospheric transport, the model also simulates the exchange between air and different types of underlying surfaces such as water, soil, snow, and ice. This approach permits a realistic representation of absorption and delayed re-emission of pollutants from the surface to the atmosphere and, consequently, allows to capture hysteresis-like effects of the exchange between the atmosphere and the other components of the system. In this model, the most comprehensive numerical representation of the exchange is that for soil. In particular, the model includes a realistic soil module which simulates both diffusion and convection of a tracer driven by evaporation from the soil, precipitation, and gravity.

The model is applied to a long-term simulation of the transport of pesticides (hexachlorocyclohexanes in particular). Emission fluxes from the soil are rigorously computed on the basis of the realistic data of the agricultural application. All four modelled systems, i.e. atmosphere, soil, hydrosphere and cryosphere, are driven by objectively analysed meteorological data supplemented, when necessary, by climatological information. Therefore, the verification against the observed data is possible. The comparison of the model results and the observations taken at remote stations in the Arctic indicates that the presented global modelling system is able to capture both trends and short-term components in the observed time series of the concentrations, and therefore, provides a useful tool for the evaluation of the source–receptor relationships.