Kalman filter based prediction system for wintertime PM10 concentrations in Macau
Hoi K.I.; Yuen K.V.; Mok K.M.
2008-07-01
Source PublicationGlobal Nest Journal
ISSN1790-7632
Volume10Issue:2Pages:140-150
Abstract

In the present study, the Kalman filter algorithm was applied to forecast the wintertime PM concentrations of Macau. The algorithm was implemented on an AR(2) model and an AREX model, respectively. The AR(2) model is essentially an autoregressive model of order 2, i.e., the daily averaged PM concentration tomorrow is predicted by a linear combination of the PM concentrations in the previous two days. The AREX model is built based on the AR(2) model. It is a combination of the autoregressive model and the exogenous inputs such as the wind speed and the wind direction on the day of prediction. Both models were tested by using the PM concentrations and the meteorological data between November of 2004 and February of 2005. It was found that the mean absolute prediction error percentage of the AR(2) model was 36.36%, with an RMS error of 34.94 μg m. The Pearson correlation coefficient between the predictions and the measurements is 0.59.Time-delay problem was associated with the AR(2) model, i.e., the trend of the predicted PM concentrations generally lagged behind the trend of the measurements. On the other hand, the error percentage of the AREX model was 32.45%, with an RMS error of 27.08 μg m. The Pearson correlation coefficient is 0.75. The time-delay problem was improved and the trend of the predictions was in good agreement with the measurements. The AREX model outperformed the AR(2) model since the meteorological conditions could reflect the dispersion condition and the nature of the replenishing air masses on the day of prediction. It was concluded that the Kalman filter was promising in the air quality prediction but caution should be made in the selection of the model classes. 

KeywordAir Quality Prediction Kalman Filter Macau Pm10
DOIhttps://doi.org/10.30955/gnj.000545
URLView the original
Indexed BySCI
Language英语
WOS Research AreaEnvironmental Sciences & Ecology
WOS SubjectEnvironmental Sciences
WOS IDWOS:000257936200003
PublisherGLOBAL NETWORK ENVIRONMENTAL SCIENCE & TECHNOLOGY, 30 VOULGAROKTONOU STR, ATHENS, GR 114 72, GREECE
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Citation statistics
Cited Times [WOS]:12   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF CIVIL AND ENVIRONMENTAL ENGINEERING
Corresponding AuthorMok K.M.
AffiliationDepartment of Civil and Environmental Engineering, University of Macau , Av. Padre Tomás Pereira S.J., Taipa, Macau SAR, China
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Hoi K.I.,Yuen K.V.,Mok K.M.. Kalman filter based prediction system for wintertime PM10 concentrations in Macau[J]. Global Nest Journal,2008,10(2):140-150.
APA Hoi K.I.,Yuen K.V.,&Mok K.M..(2008).Kalman filter based prediction system for wintertime PM10 concentrations in Macau.Global Nest Journal,10(2),140-150.
MLA Hoi K.I.,et al."Kalman filter based prediction system for wintertime PM10 concentrations in Macau".Global Nest Journal 10.2(2008):140-150.
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