Finite mixture models to characterize and refine air quality monitoring networks

Science of the Total Environment

Volumn 485-486, Issue 1, 2014, Pages 292-299

  Gómez Losada, Álvaro ^a,b   Lozano García, Antonio ^a   Pino Mejías, Rafael ^b   Contreras González, Juan ^c  

^a Environmental and Water Agency of Andalusia   (Spain)

^b UNIVERSITY OF SEVILLE   (Spain)

^c JUNTA DE ANDALUCÍA   (Spain)

Author keywords

Air quality monitoring networks; Finite mixture models; Imputation; Missing data; Random forests; Seville

Indexed keywords

AIR POLLUTION; AIR QUALITY; CARBON; CARBON MONOXIDE; DECISION TREES; MAXIMUM PRINCIPLE; MIXTURES; MONITORING; NITROGEN OXIDES; OPEN SOURCE SOFTWARE; OPEN SYSTEMS; POLLUTION; PRINCIPAL COMPONENT ANALYSIS; QUALITY MANAGEMENT; STATISTICS; SULFUR DIOXIDE;

AIR QUALITY MONITORING NETWORKS; FINITE MIXTURE MODELS; IMPUTATION; MISSING DATA; RANDOM FORESTS; SEVILLE;

POLLUTION DETECTION;

CARBON MONOXIDE; NITROGEN DIOXIDE; OZONE; SULFUR DIOXIDE;

AIR QUALITY; ATMOSPHERIC POLLUTION; CARBON MONOXIDE; COMPUTER SIMULATION; FINITE ELEMENT METHOD; NITROGEN DIOXIDE; NUMERICAL MODEL; OPTIMIZATION; PARTICULATE MATTER; SOFTWARE;

AIR MONITORING; AIR QUALITY; ARTICLE; CLUSTER ANALYSIS; MATHEMATICAL MODEL; NORMAL DISTRIBUTION; PARTICULATE MATTER; POLLUTION MONITORING; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; RANDOM FOREST; SPAIN;

ANDALUCIA; SEVILLA; SEVILLE; SPAIN;

AIR QUALITY MONITORING NETWORKS; FINITE MIXTURE MODELS; IMPUTATION; MISSING DATA; RANDOM FORESTS; SEVILLE;

AIR POLLUTANTS; AIR POLLUTION; CARBON MONOXIDE; ENVIRONMENTAL MONITORING; MODELS, CHEMICAL; MODELS, STATISTICAL; NITROGEN DIOXIDE; OZONE; PARTICULATE MATTER; PRINCIPAL COMPONENT ANALYSIS; SPAIN; SULFUR DIOXIDE; VEHICLE EMISSIONS;

EID: 84898434706     PISSN: 00489697     EISSN: 18791026     Source Type: Journal    
DOI: 10.1016/j.scitotenv.2014.03.091     Document Type: Article

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