Análise da incorporação da direção do vento na modelagem de emissões atmosféricas de superfícies líquidas

Abstract

With the increasing impact of human activities on the environment, efficient sewage management and the minimization of its adverse effects become necessary. In this context, it is important to plan the minimization of environmental impacts that may arise from sewage treatment activities, including potential atmospheric emissions. For this purpose, emission models are important tools to estimate the emissions of compounds from the liquid phase and to plan management strategies. This study addresses the importance of including wind direction in the modeling of atmospheric emissions from liquid surfaces, an aspect often overlooked in conventional studies. Employing a methodology that utilizes the Python language and a combination of specialized libraries along with Google Earth for defining study surfaces, the central objective is to analyze the sensitivity in determining wind friction velocity (𝑢∗) and mass transfer coefficient in the liquid phase (𝑘𝐿) by including wind direction as an additional variable in modeling. This enhanced approach, considering wind streak variation depending on wind direction relative to the surface, was contrasted with simpler approaches (traditionally adopted), where wind streak is considered as a constant value. The analysis was conducted on six surfaces with different geometric configurations. In all cases, a difference between the 𝑢∗ and 𝑘𝐿 values obtained by the different approaches was demonstrated, highlighting notable discrepancies between conventional methods and the proposed method, especially on surfaces with complex geometries. The results underscore the need for revision and adaptation of conventional atmospheric emission models in sewage treatment facilities, where effective management of emissions is crucial to minimizing environmental and public health impacts. This study provides a useful tool for future research, encouraging further studies to explore other environmental variables that may interact with wind direction, expanding the scope of application of the proposed method.