{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T13:32:30Z","timestamp":1781271150732,"version":"3.54.1"},"reference-count":23,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2017,3,2]],"date-time":"2017-03-02T00:00:00Z","timestamp":1488412800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/ijerph14030247","type":"journal-article","created":{"date-parts":[[2017,3,2]],"date-time":"2017-03-02T10:31:17Z","timestamp":1488450677000},"page":"247","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Google-Earth Based Visualizations for Environmental Flows and Pollutant Dispersion in Urban Areas"],"prefix":"10.3390","volume":"14","author":[{"given":"Daoming","family":"Liu","sequence":"first","affiliation":[{"name":"Safety and Emergency Laboratory, Shanghai Advanced Research Institute, Chinese Academy of Sciences, No.99 Haike Road, Pudong New District, Shanghai 201210, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sasa","family":"Kenjeres","sequence":"additional","affiliation":[{"name":"Transport Phenomena Section, Department of Chemical Engineering, Faculty of Applied Sciences and J. M. Burgerscentrum for Fluid Mechanics, Delft University of Technology, Van der Maasweg 9, 2629 HZ Delft, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2017,3,2]]},"reference":[{"key":"ref_1","first-page":"321","article-title":"The Built Environment Induced Urban Heat Island Effect in Rapidly Urbanizing Arid Regions\u2014A Sustainable Urban Engineering Complexity","volume":"1","author":"Golden","year":"2004","journal-title":"J. Integr. Environ. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1741","DOI":"10.1016\/j.envsoft.2005.09.003","article-title":"Wind flow and photochemical air pollution in Thessaloniki, Greece","volume":"21","author":"Moussiopoulos","year":"2006","journal-title":"Environ. Model. 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