Quantifying wintertime O3 and NOx formation with relevance vector machines
Description
Underlying data associated with figures in publication. Portions of this dataset are inaccessible because: Data is now available for public access. They can be accessed through the following means: Data available through Data.gov and EDG. Format: Excel spreadsheet.
This dataset is associated with the following publication:
Olson, D., T. Riedel, J. Offenberg, M. Lewandowski, R. Long, and T. Kleindienst. Quantifying wintertime O3 and NOx formation with relevance vector machines. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 259: 118538, (2021).
Resources
| Name |
Format |
Description |
Link |
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53 |
ScienceHub%20entry%20for%20RVM%20Utah%20%28Olson%20et%20al.%2C%202021%29.xlsx |
https://pasteur.epa.gov/uploads/10.23719/1520921/ScienceHub%20entry%20for%20RVM%20Utah%20%28Olson%20et%20al.%2C%202021%29.xlsx |
Tags
- ozone
- air-quality
- fine-particulate-matter-pm2-5
- secondary-organic-aerosol
- machine-learning