Predicting submicron air pollution indicators: A machine learning approach
The regulation of air pollutant levels is rapidly becoming one of the most important tasks for the governments of developing countries, especially China. Submicron particles, such as ultrafine particles (UFP, aerodynamic diameter ≤ 100 nm) and particulate matter ≤ 1.0 micrometers (PM1.0), are an unr...
| Main Authors: | , , |
|---|---|
| Format: | Journal Article |
| Published: |
Royal Society of Chemistry
2013
|
| Online Access: | http://hdl.handle.net/20.500.11937/5665 |