Application of Improved CFD Modeling for Prediction and Mitigation of Traffic-Related Air Pollution Hotspots in a Realistic Urban Street

The correct prediction of air pollutants dispersed in urban areas is of paramount importance to safety, public health and a sustainable environment. Vehicular traffic is one of the main sources of nitrogen oxides (NO x) and particulate matter (PM), strongly related to human morbidity and mortality. In this study, the pollutant level and distribution in a section of one of the main road arteries of Antwerp (Belgium, Europe) are analyzed. The assessment is performed through computational fluid dynamics (CFD), acknowledged as a powerful tool to predict and study dispersion phenomena in complex atmospheric environments. The two main traffic lanes are modeled as emitting sources and the surrounding area is explicitly depicted. A Reynolds-averaged Navier- Stokes (RANS) approach specific for Atmospheric Boundary Layer (ABL) simulations is employed. After a validation on a wind tunnel urban canyon test case, the dispersion within the canopy of two relevant urban pollutants, nitrogen dioxide (NO2) and particulate matter with an aerodynamic diameter smaller than 10 mu m (PM10), is studied. An experimental field campaign led to the availability of wind velocity and direction data, as well as PM10 concentrations in some key locations within the urban canyon. To accurately predict the concentration field, a relevant dispersion parameter, the turbulent Schmidt number, Sc is prescribed as a locally variable quantity. The pollutant distributions in the area of interest - exhibiting strong heterogeneity - are finally demonstrated, considering one of the most frequent and concerning wind directions. Possible local remedial measures are conceptualized, investigated and implemented and their outcomes are directly compared. A major goal is, by realistically reproducing the district of interest, to identify the locations inside this intricate urban canyon where the pollutants are stagnating and to analyze which solution acts as best mitigation measure. It is demonstrated that removal by electrostatic precipitation (ESP), an active measure, and by enhancing the dilution process through wind catchers, a passive measure, are effective for local pollutant removal in a realistic urban canyon. It is also demonstrated that the applied ABL methodology resolves some well known problems in ABL dispersion modeling.

Automated summary

Accurate prediction of urban air pollutant dispersion is crucial for safety, public health, and environment. This study in Antwerp, Belgium analyzes pollutants using computational fluid dynamics, models traffic emissions, and suggests local mitigation measures. Results show effective pollutant removal methods and improvements in atmospheric boundary layer dispersion modeling.