In a field of environmental protection there is a very important question about the options to determine impact of different pollution sources on air quality in areas more or less distant from those sources. For those predictions we can use physical or computer modelling. In this paper a computer model (Lagrangian Dispersion Model, or LDM) of air pollution propagation is developed and described. The LDM was created in order to work within the CLMM - Charles University Large-Eddy Microscale Model. In this paper we discuss theory of those models as well as technical solutions used to develop the LDM. The model is validated and subsequently applied on several cases with different degree of geometry complexity. Powered by TCPDF (www.tcpdf.org)

Dust aerosol emission is a critical topic in agriculture, occurring either by aeolian process from bare or sparsely vegetated cropland or as fugitive emission during tilling, harvest and many other farming activities. Aerosols, which are in the case of agriculture either mineral dust, organic particles or a mixture, are known for impacting human health, cloud formation and ultimately, the earth’s climate and ecosystem. Coupled atmosphere and aerosol transport models are commonly used to study aerosol dispersion in the atmosphere, but so far, agricultural sources are under-represented. Hence, estimations of these emissions’ actual impact are still somewhat uncertain regarding their seasonality, spatial distribution and the fraction of the global aerosol load. To fill this gap, this study aims at identifying suitable approaches for modelling aeolian emissions from sparsely vegetated cropland and fugitive emissions from tilling. Fugitive emissions are challenging since they mainly depend on human activity that is not predictable, but observed events can be used as case studies. For this, a Lagrangian particle dispersion model was chosen, which can trace the trajectory of individual particles in the emitted dust plume. So the particle model “Itpas” was developed to tackle fugitive emissions and to be capable of simulating the complex turbulent mixing of dust particles inside the atmospheric boundary layer. This model was used to simulate a case study based on measured tilling emissions, showing the particle dispersion for a stable and unstable stratified boundary layer. It was shown that within a stably stratified boundary layer, the dust plume is restricted to the near-source region. In contrast, emissions in unstable boundary layers go into long-range transport. This illustrates the spatial range a single tillage operation can have an impact. Aeolian dust emissions are controlled by the wind. For cropland, the emission variability is caused mainly by the frequently changing vegetation cover. Emissions can only occur in the time between tillage and newly grown crops or during drought periods. A parametrisation based on high-resolution satellite observations of the vegetation cover was created to include this process into a model. With this, a new dust emission scheme for cropland emission was developed for the model system COSMO-MUSCAT. In a case study of a dust outbreak from cropland in Poland in 2019, the model’s ability was tested extensively on multiple spatial resolutions. Validation against satellite-measured AOD, ground-measured PM10 and the vertical profile of the PollyNET lidar in Warsaw showed an overall good agreement of the model simulation with the observations. In the framework of this thesis, one dedicated model approach was developed for both the fugitive emissions and the aeolian emissions and validated upon case studies. These approaches could help better understand agricultural dust emissions, their spatial distribution, seasonality and, ultimately, global impact.