Statistical Analyses of Ozone Temporal Trends: An Application of Multivariate Geostatistics
Space-time modeling of atmospheric pollutants has been actively attempted by many workers, including Kyriakidis (1999) who successfully integrated the deterministic trend m(t) and the probabilistic residual R(t) components of a random variable RV Z(t) through a stochastic simulation approach. Howeve...
| Main Authors: | , |
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| Format: | Book |
| Language: | English |
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VDM Verlag Dr. Müller
2008
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| Subjects: | |
| Online Access: | http://scholars.utp.edu.my/id/eprint/3007/ http://scholars.utp.edu.my/id/eprint/3007/1/Publication_Record_%28Books%29.docx |
| _version_ | 1848659338927800320 |
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| author | Yusoff, Nooryusmiza Srinivasan, Sanjay |
| author_facet | Yusoff, Nooryusmiza Srinivasan, Sanjay |
| author_sort | Yusoff, Nooryusmiza |
| building | UTP Institutional Repository |
| collection | Online Access |
| description | Space-time modeling of atmospheric pollutants has been actively attempted by many workers, including Kyriakidis (1999) who successfully integrated the deterministic trend m(t) and the probabilistic residual R(t) components of a random variable RV Z(t) through a stochastic simulation approach. However, many of the spatiotemporal studies carried a major assumption that the temporal aspect is fully understood and thus focused primarily on spatial modeling. The main objective of this work is concerned with evaluating the accuracy and suitability of the techniques used for modeling the temporal phenomena. Various statistical methodologies, i.e., linear regression, kriging and stochastic simulation, were performed in the case of predicting tropospheric ozone concentrations in Calgary, Alberta for 1998-2000. It should be emphasized that the more accurate the temporal modeling is performed at various environmental monitoring stations, the higher the probability of success in estimating ozone values at unknown locations. Therefore, exhaustive studies of ozone phenomena must be carried out at as many cities in Canada as possible. |
| first_indexed | 2025-11-13T07:28:51Z |
| format | Book |
| id | oai:scholars.utp.edu.my:3007 |
| institution | Universiti Teknologi Petronas |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-13T07:28:51Z |
| publishDate | 2008 |
| publisher | VDM Verlag Dr. Müller |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | oai:scholars.utp.edu.my:30072013-07-16T01:17:02Z http://scholars.utp.edu.my/id/eprint/3007/ Statistical Analyses of Ozone Temporal Trends: An Application of Multivariate Geostatistics Yusoff, Nooryusmiza Srinivasan, Sanjay TA Engineering (General). Civil engineering (General) Space-time modeling of atmospheric pollutants has been actively attempted by many workers, including Kyriakidis (1999) who successfully integrated the deterministic trend m(t) and the probabilistic residual R(t) components of a random variable RV Z(t) through a stochastic simulation approach. However, many of the spatiotemporal studies carried a major assumption that the temporal aspect is fully understood and thus focused primarily on spatial modeling. The main objective of this work is concerned with evaluating the accuracy and suitability of the techniques used for modeling the temporal phenomena. Various statistical methodologies, i.e., linear regression, kriging and stochastic simulation, were performed in the case of predicting tropospheric ozone concentrations in Calgary, Alberta for 1998-2000. It should be emphasized that the more accurate the temporal modeling is performed at various environmental monitoring stations, the higher the probability of success in estimating ozone values at unknown locations. Therefore, exhaustive studies of ozone phenomena must be carried out at as many cities in Canada as possible. VDM Verlag Dr. Müller 2008-05-22 Book PeerReviewed application/msword en http://scholars.utp.edu.my/id/eprint/3007/1/Publication_Record_%28Books%29.docx Yusoff, Nooryusmiza and Srinivasan, Sanjay (2008) Statistical Analyses of Ozone Temporal Trends: An Application of Multivariate Geostatistics. VDM Verlag Dr. Müller. |
| spellingShingle | TA Engineering (General). Civil engineering (General) Yusoff, Nooryusmiza Srinivasan, Sanjay Statistical Analyses of Ozone Temporal Trends: An Application of Multivariate Geostatistics |
| title | Statistical Analyses of Ozone Temporal Trends: An Application of Multivariate Geostatistics |
| title_full | Statistical Analyses of Ozone Temporal Trends: An Application of Multivariate Geostatistics |
| title_fullStr | Statistical Analyses of Ozone Temporal Trends: An Application of Multivariate Geostatistics |
| title_full_unstemmed | Statistical Analyses of Ozone Temporal Trends: An Application of Multivariate Geostatistics |
| title_short | Statistical Analyses of Ozone Temporal Trends: An Application of Multivariate Geostatistics |
| title_sort | statistical analyses of ozone temporal trends: an application of multivariate geostatistics |
| topic | TA Engineering (General). Civil engineering (General) |
| url | http://scholars.utp.edu.my/id/eprint/3007/ http://scholars.utp.edu.my/id/eprint/3007/1/Publication_Record_%28Books%29.docx |