Abstract

The dispersion of cooking-generated aerosols from an urban street canyon is examined with building-resolving computational fluid dynamics (CFD). Using a comprehensive urban CFD model (PALM) with a sectional aerosol module (SALSA), emissions from deep frying and boiling are considered for near-ground and elevated sources. It is found that, with representative choices of the source flux, the inclusion of aerosol dynamic processes decreases the mean canyon-averaged number concentration by 15–40 % for cooking emissions, whereas the effect is significantly weaker for traffic-generated aerosols. The effects of deposition and coagulation are comparable for boiling, but coagulation dominates for deep frying. Deposition is maximised inside the leeward corner vortices, while coagulation increases away from the source. The characteristic timescales are invoked to explain the spatial structure of deposition and coagulation. In particular, the relative difference between number concentrations for simulations with and without coagulation are strongly correlated with the ageing of particles along fluid trajectories or the mean tracer age.

Highlights

  • Computational fluid dynamics (CFD) is a well-established tool for studying urban pollutant dispersion (e.g. Rivas et al, 2019)

  • To highlight the influence of the emission spectrum, we begin by comparing the aerosol number concentration fields generated by traffic and roadside restaurants, i.e. emission scenarios TR, NG-D and NG-B (Table 1)

  • For roadside cooking emissions from the windward side (Figs. 6b,c), pollutants recirculate around the corner before they can disperse through the rest of the canyon

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Summary

Introduction

Computational fluid dynamics (CFD) is a well-established tool for studying urban pollutant dispersion (e.g. Rivas et al, 2019). Most urban CFD studies assume neutral (uniform density) flow and passive scalar dynamics. To assess the effect of the background on the aerosol proceses, several cases with Nb > 0 are considered. Using a single emission scenario, NG-B, two cases are considered: (i) light pollution, Nb = 0.1N0; (ii) heavy pollution, Nb = 0.4N0, where N0 is the mean canyon-averaged number concentration for Nb = 0. These values are arbitrary; the increase in Nb is meant to capture the contrast between normal conditions and a severe pollution episode

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