Orders-of-magnitude speedup in atmospheric chemistry modeling through neural network-based emulation

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Kelp, Makoto M.; Tessum, Christopher W.; Marshall, Julian D.;
  • Subject: Physics - Atmospheric and Oceanic Physics | Physics - Computational Physics | Statistics - Machine Learning

Chemical transport models (CTMs), which simulate air pollution transport, transformation, and removal, are computationally expensive, largely because of the computational intensity of the chemical mechanisms: systems of coupled differential equations representing atmosp... View more
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