Abstract
In the present study, we address the development and application of an efficient tool for conversion of results obtained by an integrated computational fluid dynamics (CFD) and computational reaction dynamics (CRD) approach and their visualization in the Google Earth. We focus on results typical for environmental fluid mechanics studies at a city scale that include characteristic wind flow patterns and dispersion of reactive scalars. This is achieved by developing a code based on the Java language, which converts the typical four-dimensional structure (spatial and temporal dependency) of data results in the Keyhole Markup Language (KML) format. The visualization techniques most often used are revisited and implemented into the conversion tool. The potential of the tool is demonstrated in a case study of smog formation due to an intense traffic emission in Rotterdam (The Netherlands). It is shown that the Google Earth can provide a computationally efficient and user-friendly means of data representation. This feature can be very useful for visualization of pollution at street levels, which is of great importance for the city residents. Various meteorological and traffic emissions can be easily visualized and analyzed, providing a powerful, user-friendly tool for traffic regulations and urban climate adaptations.
Highlights
The continuous degradation of urban air quality is closely related to intensive worldwide urbanization
This increase in source emissions in combination with extreme climate or weather events requires the development and application of state-of-the-art numerical simulation tools, which will be able to better understand local environmental conditions to support the development of sustainable environmental solutions for urban areas [2,3]
To provide detailed information of air pollution in urban areas generated by traffic emissions, we apply our recently
Summary
The continuous degradation of urban air quality is closely related to intensive worldwide urbanization. A rapid pace of urbanization is associated with an increase of pollutant concentrations, originating from industrial and traffic emissions. This increase in source emissions in combination with extreme climate or weather events requires the development and application of state-of-the-art numerical simulation tools, which will be able to better understand local environmental conditions to support the development of sustainable environmental solutions for urban areas [2,3]. Sustainable solutions for urban areas usually include a minimization of air and water pollution, as well as a reduction of energy and water use. To achieve the required reductions in air and water pollution, various scenarios including local meteorological, climate, geographical and emission conditions need to be taken into account in numerical simulations. To provide detailed information of air pollution in urban areas generated by traffic emissions, we apply our recently
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