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Boundary-Layer Meteorology

, Volume 164, Issue 2, pp 249–279 | Cite as

Effects of Roof-Edge Roughness on Air Temperature and Pollutant Concentration in Urban Canyons

  • Amir A. AliabadiEmail author
  • E. Scott Krayenhoff
  • Negin Nazarian
  • Lup Wai Chew
  • Peter R. Armstrong
  • Afshin Afshari
  • Leslie K. Norford
Research Article

Abstract

The influence of roof-edge roughness elements on airflow, heat transfer, and street-level pollutant transport inside and above a two-dimensional urban canyon is analyzed using an urban energy balance model coupled to a large-eddy simulation model. Simulations are performed for cold (early morning) and hot (mid afternoon) periods during the hottest month of the year (August) for the climate of Abu Dhabi, United Arab Emirates. The analysis suggests that early in the morning, and when the tallest roughness elements are implemented, the temperature above the street level increases on average by 0.5 K, while the pollutant concentration decreases by 2% of the street-level concentration. For the same conditions in mid afternoon, the temperature decreases conservatively by 1 K, while the pollutant concentration increases by 7% of the street-level concentration. As a passive or active architectural solution, the roof roughness element shows promise for improving thermal comfort and air quality in the canyon for specific times, but this should be further verified experimentally. The results also warrant a closer look at the effects of mid-range roughness elements in the urban morphology on atmospheric dynamics so as to improve parametrizations in mesoscale modelling.

Keywords

Energy balance model Large-eddy simulation Mid-range roughness element Urban canyon Urban micro-climatology 

Notes

Acknowledgements

Useful discussions with Leon Glicksman and Christoph Reinhart are acknowledged. We thank Kathleen Ross for assisting Amir A. Aliabadi and Leslie K. Norford with arrangements for travelling to United Arab Emirates for a relevant workshop in Masdar Institute of Science and Technology. Assistance of Ricky Leiserson and Philip Thompson with the setting up of the simulation platform is appreciated at Massachusetts Institute of Technology (MIT). We thank Matthew Kent and Joel Best with the setting up of the simulation platform at the University of Guelph. The help of Muhammad Tauha Ali in field installations and measurements is acknowledged. We thank the reviewers of the manuscript for their careful comments. E. Scott Krayenhoff was supported by NSF Sustainability Research Network (SRN) Cooperative Agreement 1444758 and NSF SES-1520803. This work was partially funded by a Cooperative Agreement between the Masdar Institute of Science and Technology, Abu Dhabi, United Arab Emirates and the Massachusetts Institute of Technology, Cambridge, MA, USA and by the National Research Foundation Singapore through the Singapore MIT Alliance for Research and Technology’s Centre for Environmental Sensing and Modelling interdisciplinary research program.

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Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  1. 1.Building Technology Program, Department of ArchitectureMassachusetts Institute of Technology (MIT)CambridgeUSA
  2. 2.School of Geographical Sciences and Urban PlanningArizona State UniversityTempeUSA
  3. 3.Singapore-MIT Alliance for Research and Technology CentreSingaporeSingapore
  4. 4.Masdar Institute of Science and TechnologyAbu DhabiUnited Arab Emirates

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