A novel model for hourly PM2.5 concentration prediction based on CART and EELM
- Submitting institution
-
University of Greenwich
- Unit of assessment
- 12 - Engineering
- Output identifier
- 22019
- Type
- D - Journal article
- DOI
-
10.1016/j.scitotenv.2018.10.193
- Title of journal
- Science of The Total Environment
- Article number
- -
- First page
- 3043
- Volume
- 651
- Issue
- 2
- ISSN
- 0048-9697
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work was an international collaboration between UK and China, focusing on dust spread and air pollution which is particularly important for China. A new computational algorithm for fine dusts spreading in atmosphere has been developed based on machine learning. This work had a wide impact on not only industrial users but also strategy makers. The research was partially funded by Key Laboratory for Advanced Technology in Environmental Protection of Jiangsu Province, China (Grant AE201121).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
