Preprints
https://doi.org/10.5194/gmd-2020-282
https://doi.org/10.5194/gmd-2020-282

Submitted as: model evaluation paper 14 Nov 2020

Submitted as: model evaluation paper | 14 Nov 2020

Review status: a revised version of this preprint was accepted for the journal GMD and is expected to appear here in due course.

Simulation of O3 and NOX in Sao Paulo street urban canyons with VEIN (v0.2.2) and MUNICH (v1.0)

Mario E. Gavidia-Calderón1, Sergio Ibarra-Espinosa1, Youngseob Kim2, Yang Zhang3, and Maria de Fatima Andrade1 Mario E. Gavidia-Calderón et al.
  • 1Institute of Astronomy, Geophysics and Atmospheric Sciences, University of Sao Paulo, Sao Paulo, 05508-090, Brazil
  • 2CEREA, Joint Laboratory École des Ponts ParisTech/EDF R&D, Université Paris-Est, 77455 Champs-sur-Marne, France
  • 3Department of Civil and Environmental Engieneering, Northeastern University, Boston, MA 02115, USA

Abstract. We evaluate the performance of the Model of Urban Network of Intersecting Canyons and Highways (MUNICH) in simulating Ozone (O3) and Nitrogen Oxides (NOx) concentrations within the urban street canyons in the Sao Paulo Metropolitan Area (SPMA). The MUNICH simulations are performed inside Pinheiros neighborhood (a residential area) and Paulista Avenue (an economic hub), which are representative urban canyons in the SPMA. Both zones have air quality stations maintained by the Sao Paulo Environmental Agency (CETESB), providing data (both pollutants concentrations and meteorological) for model evaluation. Meteorological inputs for MUNICH are produced by a simulation with the Weather Research and Forecasting model (WRF) over triple-nested domains with the innermost domain centered over the SPMA at a spatial grid resolution of 1 km. Street links coordinates and emission flux rates are retrieved from the Vehicular Emission Inventory (VEIN) emission model, representing the real fleet of the region. The VEIN model has an advantage to spatially represent emissions and present compatibility with MUNICH. Building height is estimated from the World Urban Database and Access Portal Tools (WUDAPT) Local Climate Zone map for SPMA. Background concentrations are obtained from the Ibirapuera air quality station located in an urban park. Finally, volatile organic compounds (VOCs) speciation is approximated using information from Sao Paulo air quality forecast emission file and non-methane hydrocarbons concentration measurements. Results show an overprediction of O3 concentrations in both study cases. NOx concentrations are underpredicted in Pinheiros but are better simulated in Paulista Avenue. Compared to O3, NO2 is better simulated in both urban zones. The O3 prediction is highly dependent on the background concentration, which is the main cause for the model O3 overprediction. The MUNICH simulations satisfy the performance criteria when emissions are calibrated. The results show the great potential of MUNICH to represent the concentrations of pollutants emitted by the fleet close to the streets. The street-scale air pollutant predictions make it possible in the future to evaluate the impacts on public health due to human exposure to primary exhaust gases pollutants emitted by the vehicles.

Mario E. Gavidia-Calderón et al.

 
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Mario E. Gavidia-Calderón et al.

Data sets

MUNICH and VEIN input and output data for Sao Paulo Mario E. Gavidia-Calderón https://doi.org/10.5281/zenodo.4168056

Mario E. Gavidia-Calderón et al.

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Short summary
MUNICH model was used to calculate pollutant concentrations inside São Paulo streets. VEIN emission model provided the vehicular emissions and the coordinates of the streets. We used information from an air quality station to account for pollutant concentrations over the rooftop. Results showed that when emissions are calibrated, MUNICH satisfied the performance criteria. MUNICH can be used to evaluate the impact of traffic-related air pollution on public health.