Hourly land-use regression modeling for NO2 and PM2.5 in the Netherlands.

Annual average land-use regression (LUR) models have been widely used to assess spatial patterns of air pollution exposures. However, they fail to capture diurnal variability in air pollution and consequently might result in biased dynamic exposure assessments. In this study we aimed to model average hourly concentrations for two major pollutants, NO2 and PM2.5, for the Netherlands using the LUR algorithm. We modelled the spatial variation of average hourly concentrations for the years 2016–2019 combined, for two seasons, and for two weekday types. Two modelling approaches were used, supervise... Mehr ...

Verfasser: Ndiaye, Aisha
Shen, Youchen
Kyriakou, Kalliopi
Karssenberg, Derek
Schmitz, Oliver
Flückiger, Benjamin
Hoogh, Kees de
Hoek, Gerard
Dokumenttyp: Artikel
Erscheinungsdatum: 2024
Schlagwörter: Air pollution hourly models / Land-use regression / Random forest / Temporal adjustment / Temporal variation / Biochemistry / General Environmental Science
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-28791046
Datenquelle: BASE; Originalkatalog
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Link(s) : https://dspace.library.uu.nl/handle/1874/452880