A Neural Operator for Forecasting Carbon Monoxide Evolution in Cities

Journal: npj Clean Air

Abstract: This study introduces a neural operator, CoNOAir, developed to model carbon monoxide (CO) concentrations in urban environments. The performance of CoNOAir is evaluated against ground truth measurements, demonstrating its effectiveness in forecasting CO evolution in cities.

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Citation

If you found the GitHub codebase useful, please cit following work:

@article{tiwari2024cono,
  title={CoNO: Complex Neural Operator for Continous Dynamical Physical Systems},
  author={Tiwari, Karn and Krishnan, NM and Prathosh, AP},
  journal={arXiv preprint arXiv:2406.02597},
  year={2024}
}

@article{bedi2025neural,
  title={A Neural Operator for Forecasting Carbon Monoxide Evolution in Cities},
  author={Bedi, Sanchit and Tiwari, Karn and Kota, Sri Harsha and Krishnan, NM and others},
  journal={arXiv preprint arXiv:2501.06007},
  year={2025}
}