The use of positive matrix factorization with conditional probability functions in air quality studies: An application to hydrocarbon emissions in Houston, Texas

Atmospheric Environment

Volumn 40, Issue 17, 2006, Pages 3070-3091

  Xie, Yulong ^a   Berkowitz, Carl M ^a  

^a PACIFIC NORTHWEST NATIONAL LABORATORY   (United States)

Author keywords

Air quality; Conditional probability function (CPF); Houston; Positive matrix factorization (PMF); Receptor modeling; VOC

Indexed keywords

AIR QUALITY; HYDROCARBONS; INDUSTRIAL EMISSIONS; PHOTOCHEMICAL FORMING; STATISTICAL METHODS; VOLATILE ORGANIC COMPOUNDS;

CONDITIONAL PROBABILITY FUNCTION; MULTIVARIATE RECEPTOR MODEL; PHOTOCHEMICAL ASSESSMENT MONITORING STATIONS; POSITIVE MATRIX FACTORIZATION; RECEPTOR MODELING;

EARTH ATMOSPHERE;

HYDROCARBON; VOLATILE ORGANIC COMPOUND;

AIR QUALITY; CONCENTRATION (COMPOSITION); GEOGRAPHICAL REGION; INDUSTRIAL EMISSION; PHOTOCHEMISTRY; PROBABILITY; VOLATILE ORGANIC COMPOUND;

AIR POLLUTION; AIR QUALITY; ANALYTIC METHOD; ARTICLE; CONCENTRATION (PARAMETERS); ENVIRONMENTAL MONITORING; FACTORIAL ANALYSIS; INDUSTRIAL PRODUCTION; MEASUREMENT; NIGHT; PHOTOCHEMISTRY; PRIORITY JOURNAL; PROBABILITY; STATISTICAL MODEL; UNITED STATES;

HOUSTON; NORTH AMERICA; TEXAS; UNITED STATES;

EID: 33646092521     PISSN: 13522310     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.atmosenv.2005.12.065     Document Type: Article

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