Importance of satellite observations for high-resolution mapping of near-surface NO2 by machine learning

Nitrogen dioxide (NO2) is an important air pollutant with negative health effects and a precursor of ozone and particulate matter responsible for photo-chemical smog and wintertime air pollution. To evaluate human exposure to NO2 for public health assessment, maps of near-surface NO2 concentrations...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Remote sensing of environment 2021-10, Vol.264, p.112573, Article 112573
Hauptverfasser:	Kim, Minsu, Brunner, Dominik, Kuhlmann, Gerrit
Format:	Artikel
Sprache:	eng
Schlagworte:	Air pollution Atmospheric models COVID-19 COVID-19 pandemic lockdown Domains Extreme gradient boosting (XGBoost) Ground level High resolution High resolution map of NO2 Land use Learning algorithms Machine learning Mathematical models Nitrogen dioxide Nitrogen dioxides (NO2) Outdoor air quality Ozone Pandemics Particulate matter Photochemical smog Pollutants Public health Satellite data Satellite observation Satellites Sentinel-5 precursor satellite Shapley additive exPlanations (SHAP) Smog Statistical analysis Statistical models Temporal variations TROPOspheric Monitoring Instrument (TROPOMI) Urban areas
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!