AI RESEARCH
End-to-end data-driven prediction of urban airflow and pollutant dispersion
arXiv CS.LG
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ArXi:2603.17606v1 Announce Type: new Climate change and the rapid growth of urban populations are intensifying environmental stresses within cities, making the behavior of urban atmospheric flows a critical factor in public health, energy use, and overall livability. This study targets to develop fast and accurate models of urban pollutant dispersion to decision-makers, enabling them to implement mitigation measures in a timely and cost-effective manner.