A comparison of reanalysis techniques: Applying optimal interpolation and ensemble kalman filtering to improve air quality monitoring at mesoscale

Science of the Total Environment

Volumn 458-460, Issue , 2013, Pages 7-14

  Candiani, Gabriele ^a   Carnevale, Claudio ^a   Finzi, Giovanna ^a   Pisoni, Enrico ^a   Volta, Marialuisa ^a  

^a UNIVERSITY OF BRESCIA   (Italy)

Author keywords

Data assimilation; Ensemble Kalman Filter; Optimal interpolation; Particulate matter

Indexed keywords

AIR QUALITY MONITORING; DATA ASSIMILATION; ENSEMBLE KALMAN FILTER; ENSEMBLE KALMAN FILTERING; OPTIMAL INTERPOLATION; PARTICULATE MATTER; POLLUTION CONCENTRATION; REGIONAL AUTHORITIES;

AIR QUALITY; INTERPOLATION; KALMAN FILTERS;

OPTIMIZATION;

AIR QUALITY; ATMOSPHERIC POLLUTION; DATA ASSIMILATION; ENSEMBLE FORECASTING; EUROPEAN UNION; KALMAN FILTER; PARTICULATE MATTER;

ACCURACY; AIR ANALYSIS; AIR POLLUTION CONTROL; AIR QUALITY; ARTICLE; DATA ANALYSIS; ENSEMBLE KALMAN FILTER; ENSEMBLE KALMAN FILTERING; ENVIRONMENTAL MONITORING; FILTER; GEOGRAPHIC DISTRIBUTION; INVESTIGATIVE PROCEDURES; ITALY; MATHEMATICAL ANALYSIS; OPTIMAL INTERPOLATION; PARTICLE SIZE; PARTICULATE MATTER; PRIORITY JOURNAL; QUALITY CONTROL; TREND STUDY; VALIDATION PROCESS;

AIR POLLUTION; CHEMISTRY TECHNIQUES, ANALYTICAL; DATA COLLECTION; ENVIRONMENTAL MONITORING; GEOGRAPHY; ITALY; MODELS, THEORETICAL; PARTICULATE MATTER;

ITALY;

EID: 84877133118     PISSN: 00489697     EISSN: 18791026     Source Type: Journal    
DOI: 10.1016/j.scitotenv.2013.03.089     Document Type: Article

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