Modeling airborne benzene in space and time with self-organizing maps and Bayesian techniques

Environmental Modelling and Software

Volumn 41, Issue , 2013, Pages 151-162

  Strebel, Kathrin ^a   Espinosa, Gabriela ^b   Giralt, Francesc ^b   Kindler, Annegret ^a   Rallo, Robert ^b   Richter, Matthias ^a   Schlink, Uwe ^a  

^a HELMHOLTZ CENTRE FOR ENVIRONMENTAL RESEARCH UFZ   (Germany)

^b UNIVERSITAT ROVIRA I VIRGILI   (Spain)

Author keywords

Bayesian inference; Benzene; Self organizing maps; Spatial and temporal prediction; Spatial variation; Volatile organic compounds

Indexed keywords

AIRBORNE CHEMICAL CONTAMINANTS; ALTERNATIVE APPROACH; BAYESIAN HIERARCHICAL MODEL; BAYESIAN INFERENCE; BAYESIAN TECHNIQUES; BENZENE CONCENTRATION; COEFFICIENT OF DETERMINATION; ENVIRONMENTAL PARAMETER; HIGH CONCENTRATION; HIGH RESOLUTION; INPUT FACTORS; LEIPZIG; MEAN ABSOLUTE ERROR; MODELING TECHNIQUE; PERFORMANCE MEASURE; PERSONAL EXPOSURES; SPACE AND TIME; SPATIAL CONCENTRATION; SPATIAL VARIATIONS; SPATIOTEMPORAL MODELING; TEMPORAL PREDICTION; TRAFFIC ROUTES; URBAN AREAS;

BAYESIAN NETWORKS; CONFORMAL MAPPING; FILLING; HIERARCHICAL SYSTEMS; INFERENCE ENGINES; VOLATILE ORGANIC COMPOUNDS;

BENZENE;

ATMOSPHERIC MODELING; ATMOSPHERIC POLLUTION; BAYESIAN ANALYSIS; BENZENE; CHEMICAL POLLUTANT; POLLUTION EXPOSURE; SELF ORGANIZATION; SPATIAL VARIATION; SPATIOTEMPORAL ANALYSIS; TRAFFIC EMISSION; URBAN ATMOSPHERE; VOLATILE ORGANIC COMPOUND;

GERMANY; LEIPZIG; SAXONY;

EID: 84872029196     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2012.12.001     Document Type: Article

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