Atmospheric Chemistry and Physics (Mar 2021)

Turbulence-permitting air pollution simulation for the Stuttgart metropolitan area

  • T. Schwitalla,
  • H.-S. Bauer,
  • K. Warrach-Sagi,
  • T. Bönisch,
  • V. Wulfmeyer

DOI
https://doi.org/10.5194/acp-21-4575-2021
Journal volume & issue
Vol. 21
pp. 4575 – 4597

Abstract

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Air pollution is one of the major challenges in urban areas. It can have a major impact on human health and society and is currently a subject of several litigations in European courts. Information on the level of air pollution is based on near-surface measurements, which are often irregularly distributed along the main traffic roads and provide almost no information about the residential areas and office districts in the cities. To further enhance the process understanding and give scientific support to decision makers, we developed a prototype for an air quality forecasting system (AQFS) within the EU demonstration project “Open Forecast”. For AQFS, the Weather Research and Forecasting model together with its coupled chemistry component (WRF-Chem) is applied for the Stuttgart metropolitan area in Germany. Three model domains from 1.25 km down to a turbulence-permitting resolution of 50 m were used, and a single-layer urban canopy model was active in all domains. As a demonstration case study, 21 January 2019 was selected, which was a heavily polluted day with observed PM10 concentrations exceeding 50 µg m−3. Our results show that the model is able to reasonably simulate the diurnal cycle of surface fluxes and 2 m temperatures as well as evolution of the stable and shallow boundary layer typically occurring in wintertime in Stuttgart. The simulated fields of particulates with a diameter of less than 10 µm (PM10) and nitrogen dioxide (NO2) allow a clear statement about the most heavily polluted areas apart from the irregularly distributed measurement sites. Together with information about the vertical distribution of PM10 and NO2 from the model, AQFS will serve as a valuable tool for air quality forecasting and has the potential of being applied to other cities around the world.