Simulating building downwash of heavy metals by using virtual sources: Methodology and results

Abstract

There is a discrepancy in data quality between the highly detailed concentration measurements in the surroundings of industrial plants emitting heavy metals and the registered emission data at these sites. When simulating the concentration fields in the direct vicinity of the emitting plants by using the bi-gaussian model IFDM and the reported emissions, the simulated concentrations were much lower than the measured concentrations. Originally, this was thought to be due to diffuse, wind-fugitive emissions not reported in the official inventories. Therefore, inverse modeling was performed to get the emission data and wind dependency of these emissions. It was expected that the emissions coming out of the inverse modeling would follow a power law of the wind speed except for very low and very high wind speeds. In the latter case, a constant emission was expected, while in the former case, no emissions were expected to be found. However, this lower threshold did not seem to exist in the modeled emissions. Furthermore, these emissions seemed to have their source in spots not used for storage of heavy metals such as parking lots. Detailed analysis of these results showed that another effect, known as building downwash, is responsible for this behavior. Thereafter, it was shown that it is possible for a bi-gaussian model that lacks a building downwash module, to simulate correct concentration levels by putting in virtual sources just behind the buildings causing the building downwash phenomenon. By using half of the available concentration data for the inverse modeling and half for the validation, it was shown that this technique can be used to produce detailed and validated concentration maps of the surroundings of the industrial site. Finally, it was shown that in this case studying building downwash has an important effect on local concentrations and that a better representation of building downwash is needed in bi-gaussian models to describe the complex dispersion patterns in the wake of industrial sites.