Graph Machine Learning for Improved Imputation of Missing Tropospheric Ozone Data
Author:
Affiliation:
1. Jülich Supercomputing Centre, Forschungszentrum Jülich, 52425 Jülich, Germany
2. Max-Planck-Institut für Meteorologie, 20146 Hamburg, Germany
Funder
H2020 Industrial Leadership
H2020 European Research Council
Publisher
American Chemical Society (ACS)
Subject
Environmental Chemistry,General Chemistry
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.est.3c05104
Reference73 articles.
1. Tropospheric ozone and its precursors from the urban to the global scale from air quality to short-lived climate forcer
2. Tropospheric Ozone Assessment Report: Present-day distribution and trends of tropospheric ozone relevant to climate and global atmospheric chemistry model evaluation
3. Henschel, S.; Chan, G.; World Health Organization. Regional Office for Europe, Health risks of air pollution in Europe - HRAPIE project: New emerging risks to health from air pollution - results from the survey of experts; World Health Organization: 2013.
4. World Health Organization. Review of evidence on health aspects of air pollution: REVIHAAP project; World Health Organization: 2021.
5. Tropospheric Ozone Assessment Report: Present-day ozone distribution and trends relevant to human health
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