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May 2010

Volume 22, Issue 5, Articles (05xxxx)

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Phys. Fluids 22, 051301 (2010); http://dx.doi.org/10.1063/1.3407662 (20 pages)

H. J. S. Fernando, D. Zajic, S. Di Sabatino, R. Dimitrova, B. Hedquist, and A. Dallman
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Flow, turbulence, and pollutant dispersion in urban atmospheres

H. J. S. Fernando, D. Zajic, S. Di Sabatino, R. Dimitrova, B. Hedquist, and A. Dallman

Phys. Fluids 22, 051301 (2010); http://dx.doi.org/10.1063/1.3407662 (20 pages) | Cited 16 times

Online Publication Date: 13 May 2010

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The past half century has seen an unprecedented growth of the world’s urban population. While urban areas proffer the highest quality of life, they also inflict environmental degradation that pervades a multitude of space-time scales. In the atmospheric context, stressors of human (anthropogenic) origin are mainly imparted on the lower urban atmosphere and communicated to regional, global, and smaller scales via transport and turbulence processes. Conversely, changes in all scales are transmitted to urban regions through the atmosphere. The fluid dynamics of the urban atmospheric boundary layer and its prediction is the theme of this overview paper, where it is advocated that decision and policymaking in urban atmospheric management must be based on integrated models that incorporate cumulative effects of anthropogenic forcing, atmospheric dynamics, and social implications (e.g., health outcomes). An integrated modeling system juxtaposes a suite of submodels, each covering a particular range of scales while communicating with models of neighboring scales. Unresolved scales of these models need to be parametrized based on flow physics, for which developments in fluid dynamics play an indispensible role. Illustrations of how controlled laboratory, outdoor (field), and numerical experiments can be used to understand and parametrize urban atmospheric processes are presented, and the utility of predictive models is exemplified. Field experiments in real urban areas are central to urban atmospheric research, as validation of predictive models requires data that encapsulate four-dimensional complexities of nature.
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92.60.Sz Air quality and air pollution
92.60.Fm Boundary layer structure and processes
47.27.-i Turbulent flows
89.60.-k Environmental studies
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