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Air quality forecasts with observation-based scaling of anthropogenic emissions for urban agglomerations
  • +10
  • Adrien Michel Deroubaix,
  • Guy P. Brasseur,
  • Maria de Fatima Andrade,
  • Alejandro Peralta,
  • Phiipp franke,
  • Mario Gavidia-Calderon,
  • Judith Johanna Hoelzemann,
  • Fei Jiang,
  • Inga Labuhn,
  • Laurent MENUT,
  • Nilton Rosário,
  • Guillaume Siour,
  • rita Yuri Ynoue
Adrien Michel Deroubaix
Max Planck Institute for Meteorology

Corresponding Author:[email protected]

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Guy P. Brasseur
Max Planck Institute for Meteorology
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Maria de Fatima Andrade
Instituto de Ciências Ambientais, Químicas e Farmacêuticas da Universidade Federal de São Paulo
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Alejandro Peralta
Instituto de Ciências Ambientais, Químicas e Farmacêuticas da Universidade Federal de São Paulo
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Phiipp franke
Forschungszentrum Jülich GmbH
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Mario Gavidia-Calderon
Instituto de Ciências Ambientais, Químicas e Farmacêuticas da Universidade Federal de São Paulo
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Judith Johanna Hoelzemann
Universidade Federal do Rio Grande do Norte
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Fei Jiang
International Institute for Earth System Science, Nanjing University
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Inga Labuhn
University of Bremen
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Laurent MENUT
Laboratoire de Meteorologie Dynamique
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Nilton Rosário
Federal University of Sao Paulo
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Guillaume Siour
CNRS/Universités Paris Est-Créteil et Paris Diderot, Institut Pierre Simon Laplace
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rita Yuri Ynoue
Instituto de Ciências Ambientais, Químicas e Farmacêuticas da Universidade Federal de São Paulo
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Abstract

Forecasting urban air quality is important for protecting public health, but current model forecasts are often limited by an inaccurate prescription of pollutant emissions from human activities. We developed a new approach that improves air quality forecasts by adjusting emission prescription based on observed concentrations in urban agglomerations for key pollutants such as nitrogen oxides, sulfur dioxide, carbon monoxide, particulate matter, and volatile organic compounds. Applying this new approach to the São Paulo metropolitan area, Brazil, we compared forecasted and observed pollutant concentrations (from 6 February to 17 April 2023). Using adjusted emission significantly improved air quality forecasts for São Paulo, especially for ozone levels after adjusting estimates of volatile organic compound emissions. However, the forecast of particulate matter concentrations remained challenging due to their links with gaseous pollutants. Our study demonstrates the potential of using observed concentrations in urban agglomerations to improve air quality forecasts. Extending this approach to other urban agglomerations can help refine emission estimates and improve regional air quality forecasts, enabling better decision making for health protection.
17 Apr 2024Submitted to ESS Open Archive
19 Apr 2024Published in ESS Open Archive