Developing a novel hybrid model for the estimation of surface 8 h ozone (O 3 ) across the remote Tibetan Plateau during 2005–2018

We developed a two-stage model called the random-forest–generalised additive model (RF–GAM), based on satellite data, meteorological factors, and other geographical covariates, to predict the surface 8 h O3 concentrations across the remote Tibetan Plateau. The 10-fold cross-validation result suggest...

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Bibliographic Details
Published in:	Atmospheric chemistry and physics 2020-05, Vol.20 (10), p.6159-6175
Main Authors:	Li, Rui, Zhao, Yilong, Zhou, Wenhui, Meng, Ya, Zhang, Ziyu, Fu, Hongbo
Format:	Article
Language:	English
Subjects:	Additives Air pollution Air quality Cities Cities and towns Decision trees Health risks Learning algorithms Machine learning Model accuracy Novels Ozone Performance prediction Plateaus Pollutants Pollution Public health Remote monitoring Remote regions Root-mean-square errors Satellite data Spatial variations Studies Time VOCs Volatile organic compounds Weather Web sites (World Wide Web) Websites World health
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