Prediction of 24-hour-average PM2.5 concentrations using a hidden Markov model with different emission distributions in Northern California

Science of the Total Environment

Volumn 443, Issue , 2013, Pages 93-103

  Sun, Wei ^a   Zhang, Hao ^a   Palazoglu, Ahmet ^b   Singh, Angadh ^b   Zhang, Weidong ^a   Liu, Shiwei ^a  

^a BEIJING UNIVERSITY OF CHEMICAL TECHNOLOGY   (China)

^b University of California   (United States)

Author keywords

Gamma; GEV distribution; Hidden Markov model; Lognormal; PM2.5

Indexed keywords

AIR POLLUTANTS; AIRBORNE POLLUTANTS; CALIFORNIA; DIFFERENT DISTRIBUTIONS; EMISSION DISTRIBUTION; FALSE ALARMS; FINE PARTICULATE MATTER; GAMMA; GENERALIZED EXTREME VALUE; GEV DISTRIBUTIONS; HIDDEN STATE; LOG-NORMAL; LOG-NORMAL DISTRIBUTION; METEOROLOGICAL FACTORS; MODEL PREDICTION; NON-GAUSSIAN; NON-GAUSSIAN DISTRIBUTION; PHOTOCHEMICAL AIR QUALITY MODELS; PREDICTION RATE; REGULATORY MANAGEMENT; ROUTINE PREDICTION; STATISTICAL MODELS;

AIR POLLUTION CONTROL; AIR QUALITY; ALARM SYSTEMS; ERRORS; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); HIDDEN MARKOV MODELS;

FORECASTING;

AIR QUALITY; ATMOSPHERIC POLLUTION; CONCENTRATION (COMPOSITION); EMISSION; MARKOV CHAIN; PARTICULATE MATTER; PHOTOCHEMISTRY; POLLUTION CONTROL; PREDICTION;

AIR ANALYSIS; AIR POLLUTANT; AIR POLLUTION; AIR QUALITY; ALGORITHM; ARTICLE; CONTROLLED STUDY; ENVIRONMENTAL MONITORING; GEOGRAPHIC DISTRIBUTION; HIDDEN MARKOV MODEL; MATHEMATICAL COMPUTING; NORMAL DISTRIBUTION; PARTICLE SIZE; PARTICULATE MATTER; PREDICTION; PRIORITY JOURNAL; PROBABILITY; PROCESS DEVELOPMENT; QUALITY CONTROL; UNITED STATES;

AIR POLLUTANTS; CALIFORNIA; MARKOV CHAINS; MODELS, THEORETICAL; PARTICLE SIZE; STOCHASTIC PROCESSES;

CALIFORNIA; UNITED STATES;

EID: 84869884924     PISSN: 00489697     EISSN: 18791026     Source Type: Journal    
DOI: 10.1016/j.scitotenv.2012.10.070     Document Type: Article

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