Stochastic flow switching in street intersections

Klippel, K., Auerswald, T. ORCID: https://orcid.org/0009-0007-5827-5487, Goulart, E. V., Reis Jr., N. C., Carpentieri, M., Barlow, J. F. ORCID: https://orcid.org/0000-0002-9022-6833, Soulhac, L. and Coceal, O. ORCID: https://orcid.org/0000-0003-0705-6755 (2026) Stochastic flow switching in street intersections. Sustainable Cities and Society, 149. 107791. ISSN 2210-6715 doi: 10.1016/j.scs.2026.107791

Abstract/Summary

This study investigates the stochastic nature of turbulent flow switching at street intersections in urban canopies. Direct numerical simulations of turbulent flow over a uniform array of rectangular buildings of height h with a 45° inflow direction reveal bistable switching of horizontal wind direction at heights z = 0.125h and z = 0.25h, where the flow alternates between alignment with the short-street (0°) and long-street (90°) axes. The characteristic switching time scale is approximately 10.5T (where T = h/uτ is the eddy turnover time), with a standard deviation of 3.7T and a longer residence time in the long-street-aligned state. Wind-tunnel experiments for different idealized urban configurations confirm that this bistable switching is a generic process, with time scales that depend on building geometry and incident wind direction. Analysis of field measurements at a real intersection in London (UK) also shows intermittent bistable switching, indicating that the phenomenon is robust but sensitive to external forcing and building heterogeneity. Flow switching at intersections influences scalar transport, particularly in the near field, where the strongest correlations between wind direction and concentration are found in the adjacent short street. In the far field, these correlations are weakened by increased mixing and street network- scale interactions. Overall, the findings show that stochastic flow switching is an intrinsic mechanism that shapes urban ventilation pathways and modifies pollutant dispersion patterns, highlighting its relevance for both dispersion modelling and real-world air-quality assessments. With these applications in mind, simple approaches for including this process in street network dispersion models are outlined.

Item Type	Article
URI	https://centaur.reading.ac.uk/id/eprint/131339
Identification Number/DOI	10.1016/j.scs.2026.107791
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	Elsevier
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