Intercomparison of Air Quality Models in a Megacity: Toward an Operational Ensemble Forecasting System for São Paulo
Adrien Deroubaix, Judith J. Hoelzemann, Rita Yuri Ynoue, Taciana Toledo de Almeida Albuquerque, Rafaela Cruz Alves Alberti, María de Fátima Andrade, Willian Lemker Andreão, Idir Bouarar, Ediclê de Souza Fernandes Duarte, Hendrik Elbern, Philipp Franke, Anne Caroline Lange, Pablo Lichtig, Lya Lugon, Leila Droprinchinski Martins, Gregori de Arruda Moreira, Rizzieri Pedruzzi, Nilton E. Rosário, Guy Brasseur
Abstract
Abstract An intercomparison of four regional air quality models is performed in the tropical megacity of São Paulo with the perspective of developing a forecasting system based on a model ensemble. Modeled concentrations of the main regulated pollutants are compared with combined observations in the megacity center, after analyzing the spatial scale of representativeness of air monitoring stations. During three contrasting periods characterized by different types of pollution events, the hourly concentrations of carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO 2 ), and particulate matter (PM 2.5 and PM 10 ) modeled by the ensemble are in moderate agreement with observations. The median of the ensemble provides the best performance ( R ≈ 0.7 for CO, 0.7 for NOx, 0.5 for SO 2 , 0.5 for PM 2.5 , and 0.4 for PM 10 ) because each model has periods and pollutants for which it has the best agreement. NOx concentration is modeled with a large inter‐model variability, highlighting potential for improvement of anthropogenic emissions. Pollutants transported by biomass burning events strongly affect the air quality in São Paulo and are associated with significant inter‐model variability. Modeled hourly concentration of ozone (O 3 ) is overestimated during the day (≈20 ppb) and underestimated at night (≈10 ppb), while nitrogen dioxide (NO 2 ) is overestimated at night (≈20 ppb). The observed O 3 concentration is best reproduced by the median of the ensemble ( R ≈ 0.8), taking advantage of the variable performance of the models. Therefore, an operational air quality forecast system based on a regional model ensemble is promising for São Paulo.