Modelling of street-scale pollutant dispersion by coupled simulation of chemical reaction, aerosol dynamics, and CFD

Abstract

Abstract. In the urban environment, gas such as nitrogen dioxide NO2, and particles impose adverse impacts on pedestrians’ health. The conventional computational fluid dynamics (CFD) methods that regard pollutant as passive scalar cannot reproduce the formation of secondary pollutants, such as NO2 and secondary inorganic and organic aerosols, leading to uncertain prediction. In this study, SSH-Aerosol, a modular box model that simulates the evolution of gas, primary and secondary aerosols, is coupled with the CFD software OpenFOAM and Code_Saturne. The transient dispersion of pollutants emitted from traffic in a street canyon is simulated using unsteady Reynolds-averaged Navier–Stokes equations (RANS) model. The simulated concentrations of NO2, PM10 and black carbon are compared with field measurements on a street of Greater Paris. The simulated NO2 and PM10 concentrations based on the coupled model achieved better agreement with measurement data than the conventional CFD simulation. Meanwhile, the black carbon concentration is underestimated, probably partly because of the underestimation of non-exhaust emissions (tyre and road wear). Vehicles are considered the main source of ammonia (NH3) in urban environments, which may condense with nitric acid (HNO3) to form ammonium nitrate. In the reference simulation with NH3 traffic emissions accounting for 1–2 % of NOx emissions, aerosol dynamics leads to an ammonium nitrate increase of 46 % on average over a 12-hour simulation period (5 a.m. to 5 p.m.) compared to the conventional CFD simulation. Furthermore, an increase in NH3 traffic emissions (to 10 % and 20 % of NOx emissions) may leads to a large increase in ammonium nitrate (35 % and 55 %) compared to the reference simulation. In addition, aerosol dynamics leads to a 52 % increase in 12-hour time-averaged organic matter concentrations compared to the conventional CFD simulation, because of the condensation of anthropogenic compounds from precursor-gas emissions and of background biogenic precursor-gases on the enhance inorganic concentrations.

Modelling concentration heterogeneities in streets using the street-network model MUNICH

“…The lower concentration difference for PM 10 than for the other compounds reflects that non-traffic sources are more important for PM 10 , and inversely they are small for BC. Despite the higher concentrations in MUNICH-hete-l1, BC concentrations remain strongly underestimated compared to observations, in agreement with the CFD simulations of Lin et al (2022). For PM 10 , NO 2 and NO x , the concentrations compare well to observations, e.g.…”