Prediction of ultrafine particle number concentrations in urban environments by means of Gaussian process regression based on measurements of oxides of nitrogen

Environmental Modelling and Software

Volumn 61, Issue , 2014, Pages 135-150

  Reggente, Matteo ^a   Peters, Jan ^a   Theunis, Jan ^a   Van Poppel, Martine ^a   Rademaker, Michael ^b   Kumar, Prashant ^c   De Baets, Bernard ^b  

^a FLEMISH INSTITUTE FOR TECHNOLOGICAL RESEARCH VITO   (Belgium)

^b GHENT UNIVERSITY   (Belgium)

^c UNIVERSITY OF SURREY   (United Kingdom)

Author keywords

Gaussian process regression; Number distributions; Street canyon; Traffic emissions; Ultrafine particles; Urban air pollution

Indexed keywords

AIR POLLUTION; FOG; FORECASTING; GAUSSIAN NOISE (ELECTRONIC); NITROGEN; NITROGEN OXIDES;

GAUSSIAN PROCESS REGRESSION; NUMBER DISTRIBUTION; STREET CANYON; TRAFFIC EMISSIONS; ULTRAFINE PARTICLE; URBAN AIR POLLUTION;

GAUSSIAN DISTRIBUTION;

ATMOSPHERIC POLLUTION; CARBON MONOXIDE; CONCENTRATION (COMPOSITION); NITROGEN OXIDES; OZONE; PARTICLE SIZE; PREDICTION; REGRESSION ANALYSIS; STREET CANYON; TRAFFIC EMISSION; URBAN POLLUTION; GAUSSIAN METHOD; NUMERICAL MODEL; TYPOLOGY;

ANTWERP [ANTWERP (PRV)]; ANTWERP [BELGIUM]; BELGIUM;

EID: 84907354558     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2014.07.012     Document Type: Article

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