Crossmark

Spatiotemporal prediction of continuous daily PM2.5 concentrations across China using a spatially explicit machine learning algorithm

Crossref DOI link: https://doi.org/10.1016/j.atmosenv.2017.02.023

Published Print: 2017-04

Update policy: https://doi.org/10.1016/elsevier_cm_policy

Authors

Zhan, Yu

Luo, Yuzhou

Deng, Xunfei

Chen, Huajin

Grieneisen, Michael L.

Shen, Xueyou

Zhu, Lizhong

Zhang, Minghua
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (21607127)

Key Research and Development Program of Ministry of Science and Technology of China (2016YFC020710)
License Information

Text and Data Mining valid from 2017-04-01
More Information

This article is maintained by: Elsevier

Article Title: Spatiotemporal prediction of continuous daily PM2.5 concentrations across China using a spatially explicit machine learning algorithm

Journal Title: Atmospheric Environment

CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.atmosenv.2017.02.023

Content Type: article

Copyright: © 2017 Elsevier Ltd. All rights reserved.