Predicting hourly PM2.5 concentrations in wildfire-prone areas using a SpatioTemporal Transformer model.

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Bibliographic Details
Title: Predicting hourly PM2.5 concentrations in wildfire-prone areas using a SpatioTemporal Transformer model.
Authors: Yu M; Department of Geography, The Pennsylvania State University, United States of America. Electronic address: mqy5198@psu.edu., Masrur A; Environmental Systems Research Institute, United States of America., Blaszczak-Boxe C; Department of Geosciences, The Pennsylvania State University, United States of America; Department of Interdisciplinary Studies, Howard University, United States of America.
Source: The Science of the total environment [Sci Total Environ] 2023 Feb 20; Vol. 860, pp. 160446. Date of Electronic Publication: 2022 Nov 25.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 0330500 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-1026 (Electronic) Linking ISSN: 00489697 NLM ISO Abbreviation: Sci Total Environ Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1879-1026
DOI:10.1016/j.scitotenv.2022.160446