Random forest meteorological normalisation models for Swiss PM 10 trend analysis

@article{Grange2018RandomFM,
  title={Random forest meteorological normalisation models for Swiss PM 10 trend analysis},
  author={S. Grange and D. Carslaw and A. Lewis and E. Boleti and C. Hueglin},
  journal={Atmospheric Chemistry and Physics},
  year={2018},
  volume={18},
  pages={6223-6239}
}
  • S. Grange, S. Grange, +4 authors C. Hueglin
  • Published 2018
  • Atmospheric Chemistry and Physics
  • Abstract. Meteorological normalisation is a technique which accounts for changes in meteorology over time in an air quality time series. Controlling for such changes helps support robust trend analysis because there is more certainty that the observed trends are due to changes in emissions or chemistry, not changes in meteorology. Predictive random forest models (RF; a decision tree machine learning technique) were grown for 31 air quality monitoring sites in Switzerland using surface… CONTINUE READING
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