Lagrangian stochastic models are a largely used tool in the study of passive substances dispersion inside the Atmospheric Boundary Layer. Its application is related to the trajectory computation of thousands of particles, that numerically simulate the dispersion of suspense substances in the atmosphere. In this study, the basic concepts related to the Lagrangian stochastic modelling are presented and discussed together with its main characteristics and its computational implementation, to the study of particles dispersion in the atmosphere. In a computational experiment, the obtained results are compared with observational data from the TRACT experiment, that took place in Europe in 1992. The input data needed for the dispersion model are extracted from simulations with the numerical weather forecast model RAMS. Dispersion over Rio de Janeiro region is also tested in a second experiment. / Modelos Lagrangianos estocásticos constituem ferramenta muito utilizada no estudo da dispersão de substâncias passivas na Camada Limite Atmosférica. Sua aplicação consiste em calcular a trajetória de milhares de partículas, que simulam numericamente a dispersão de uma substância em suspensão na atmosfera. Nesta tese, são apresentados e discutidos os conceitos básicos relacionados à Modelagem Lagrangiana Estocástica de Partículas, bem como suas principais características e sua implementação computacional, para o estudo da dispersão de partículas na atmosfera. Numa experimentação computacional, comparam-se os resultados obtidos com dados observacionais provenientes do experimento TRACT, realizado na Europa em 1992. Os dados de entrada necessários ao modelo de dispersão são extraídos de simulações do modelo de previsão numérica do tempo RAMS. A dispersão sobre o Estado do Rio de Janeiro é também testada em um segundo experimento.

Aerosols are small, micrometer-sized particles, whose optical effects coupled with their impact on cloud properties is a source of large uncertainty in climate models. While their radiative forcing impact is largely of a cooling nature, there can be significant variations in the degree of their impact, depending on the size and the nature of the aerosols. The radiative and optical impact of aerosols are, first and foremost, dependent on their concentration or number density (an extensive parameter) and secondly on the size and nature of the aerosols (intensive, per particle, parameters). We employed passive (sunphotmetry) and active (backscatter lidar) measurements to retrieve extensive optical signals (aerosol optical depth or AOD and backscatter coefficient respectively) and semi-intensive optical signals (fine and coarse mode OD and fine and coarse mode backscatter coefficient respectively) and compared the optical coherency of these retrievals over a variety of aerosol and thin cloud events (pollution, dust, volcanic, smoke, thin cloud dominated). The retrievals were performed using an existing spectral deconvolution method applied to the sunphotometry data (SDA) and a new retrieval technique for the lidar based on a colour ratio thresholding technique. The validation of the lidar retrieval was accomplished by comparing the vertical integrations of the fine mode, coarse mode and total backscatter coefficients of the lidar with their sunphotometry analogues where lidar ratios (the intensive parameter required to transform backscatter coefficients into extinction coefficients) were (a) computed independently using the SDA retrievals for fine mode aerosols or prescribed for coarse mode aerosols and clouds or (b) computed by forcing the computed (fine, coarse and total) lidar ODs to be equal to their analog sunphotometry ODs. Comparisons between cases (a) and (b) as well as the semi-qualitative verification of the derived fine and coarse mode vertical profiles with the expected backscatter coefficient behavior of fine and coarse mode aerosols yielded satisfactory agreement (notably that the fine, coarse and total OD errors were <~ sunphotometry instrument errors). Comparisons between cases (a) and (b) also showed a degree of optical coherency between the fine mode lidar ratios.