Modeling studies of the transport and transformation of pollutants in the lower troposphere

The utilization of mathematical models to represent the fates and transformations of atmospheric pollutants constitutes a fundamental practice that has contributed to the conceptual understanding of a variety of phenomena. These models provide the necessary framework for incorporating diverse atmospheric processes into a coherent system for studying their interactions. Consequently, we use several increasingly complex simulation tools to comprehend different aspects of pollution phenomena, such as the dispersion of non-reacting pollutants emitted from a smokestack, the forecast of tropospheric ozone formation over a regional scale, and the sensitivity of sulfate aerosol to changes on nitrogen oxides and hydrocarbon source strengths.; Starting with the simplest approach for simulating the dispersion of a chemically non-reactive contaminant, we explore the comparability of Gaussian-type model predictions to atmospheric measurements. This work investigates the differences between finite-time averaged observations and ensemble mean concentrations as predicted by Gaussian models in laboratory and atmospheric boundary layer (ABL) flows. For a given averaging time it is shown that this difference is smaller in laboratory flows than in the ABL under the same stability and statistical conditions. Furthermore, with data from the Willis-Deardorff convection tank experiments, it is shown that the values of the normalized differences between observations and model predicted concentrations in the ABL exceed 50% for an averaging time of the order of 1 hour. These findings give a clear indication of the need for development of more accurate and sophisticated modeling tools to depict the atmospheric dispersion of non-reactive pollutants.; In view of the fact that Gaussian models show high discrepancies between modeled and observed concentrations and that this approach is unable to simulate the formation of secondary pollutants, it is necessary to increase the level of complexity to model phenomena such as photochemical smog. Thus, a three-dimensional model, the Hybrid Single-Particle Lagrangian Integrated Trajectories model with a generalized non-linear Chemistry Module (HY-SPLIT CheM), has been utilized to forecast summertime ozone concentrations over the northeastern United States. (Abstract shortened by UMI.)...