Air pollutant retention within a complex of urban street canyons

Epidemiological studies of health effects associated with ambient air pollution are subject to uncertainty in the effects estimates related to the spatial and temporal variability of ambient air pollution. This study examines meteorological and concentration decay data for an urban canopy in Oklahoma City, OK to develop a modeling approach that can be used to estimate spatiotemporal variability in contaminant retention that could add bias or uncertainty to epidemiological results. Concentration and microscale turbulent wind data from the Joint Urban 2003 study were reanalyzed to examine scaling relationships between contaminant residence time in urban street canyons, urban boundary layer winds, and urban topography. Street-level sulfur hexafluoride (SF6) concentration time series were reviewed to find time periods that included a peak and decay. Exponential decay curves were fitted to each period, and a characteristic residence time was derived from each model slope. That residence time was nondimensionalized by the ratio of mean urban boundary layer wind speed to height of the building just upwind of the street canyon in which the concentration was measured. Sonic detection and ranging (SODAR) data were used to assess atmospheric turbulence conditions at times concurrent with the concentration decay measurements. Reynolds number (Re) was calculated from the 15-min average wind velocity and ranged from 2.1 × 106 to 7.6 × 107. Nondimensional residence time (H) ranged from 3.7 to 996 with a median of 13.3. Inverse relationships were validated between H and Re and between H and the street canyon aspect ratio. These relationships provided a mechanism to understand time-varying ventilation within a street canyon. The results shown here were intended to demonstrate how scaling relationships derived from the transport equation can be used to provide rapid estimates of characteristic decay times for the purpose of estimating variability in the concentrations encountered in an urban environment. This could be a useful tool to reduce uncertainty in air pollution epidemiological study results related to spatial and temporal variability in urban concentrations.

Duke Scholars

Author Daniel Vallero Civil and Environmental Engineering