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\begin{document}

\title{Air quality forecasts with observation-based scaling of anthropogenic
emissions for urban agglomerations}



\author[1]{Adrien Michel Deroubaix}%
\author[1]{Guy P. Brasseur}%
\author[2]{Maria de Fatima Andrade}%
\author[2]{Alejandro Peralta}%
\author[3]{Phiipp franke}%
\author[2]{Mario Gavidia-Calderon}%
\author[4]{Judith Johanna Hoelzemann}%
\author[5]{Fei Jiang}%
\author[6]{Inga Labuhn}%
\author[7]{Laurent MENUT}%
\author[8]{Nilton Rosário}%
\author[9]{Guillaume Siour}%
\author[2]{rita Yuri Ynoue}%
\affil[1]{Max Planck Institute for Meteorology}%
\affil[2]{Instituto de Ciências Ambientais, Químicas e Farmacêuticas da Universidade Federal de São Paulo}%
\affil[3]{Forschungszentrum Jülich GmbH}%
\affil[4]{Universidade Federal do Rio Grande do Norte}%
\affil[5]{International Institute for Earth System Science, Nanjing University}%
\affil[6]{University of Bremen}%
\affil[7]{Laboratoire de Meteorologie Dynamique}%
\affil[8]{Federal University of Sao Paulo}%
\affil[9]{CNRS/Universités Paris Est-Créteil et Paris Diderot, Institut Pierre Simon Laplace}%


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  \date{May 25, 2024}


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\begin{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 S\selectlanguage{ngerman}ão 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.%
\end{abstract}\selectlanguage{ngerman}%



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