A synchronized estimation of hourly surface concentrations of six criteria air pollutants with GEMS...
A synchronized estimation of hourly surface concentrations of six criteria air pollutants with GEMS data
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Publisher
London: Nature Publishing Group UK
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Language
English
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Publisher
London: Nature Publishing Group UK
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Contents
Machine learning is widely used to infer ground-level concentrations of air pollutants from satellite observations. However, a single pollutant is commonly targeted in previous explorations, which would lead to duplication of efforts and ignoration of interactions considering the interactive nature of air pollutants and their common influencing fac...
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Full title
A synchronized estimation of hourly surface concentrations of six criteria air pollutants with GEMS data
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TN_cdi_doaj_primary_oai_doaj_org_article_b816b65509014ad2a25dfce4df3d1449
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_b816b65509014ad2a25dfce4df3d1449
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ISSN
2397-3722
E-ISSN
2397-3722
DOI
10.1038/s41612-023-00407-1
