Work

Machine-learned modeling of PM2.5 exposures in rural Lao PDR

Year: 2019

Type: article

Source: The Science of The Total Environment

DOI: 10.1016/j.scitotenv.2019.04.258

Authors: L.D. Hill, A. Pillarisetti, S. Delapena, C. Garland, D. Pennise, A. Pelletreau, P. Koetting, T. Motmans, K. Vongnakhone, C. Khammavong, M.R. Boatman, J. Balmes, A. Hubbard, K.R. Smith

Institutions: University of California, Berkeley, Berkeley Air Monitoring Group (United States), University of California, San Francisco

Language: English

Topic: Energy and Environment Impacts

Subfield: Pollution

Field: Environmental Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: closed

Funders: National Science Foundation, Health Effects Institute, World Bank Group

Award: G8915973961

OpenAlex ID: W2936879261

FWCI: 0.405

Cites: 30

Cited by: 12

Related to: 10