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dc.contributor.authorZhanqiong Heen_US
dc.contributor.authorSongsak Sriboonchitaen_US
dc.contributor.authorMin Heen_US
dc.date.accessioned2018-09-04T09:22:46Z-
dc.date.available2018-09-04T09:22:46Z-
dc.date.issued2013-04-03en_US
dc.identifier.issn1537744Xen_US
dc.identifier.issn1537744Xen_US
dc.identifier.other2-s2.0-84875524617en_US
dc.identifier.other10.1155/2013/381410en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84875524617&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/52258-
dc.description.abstractTo monitor and improve the urban air quality, the Chinese government has begun to make many efforts, and the interregional cooperation to cut and improve air quality has been required. In this paper, we focus on the seasonality of the first and second moments of the daily air pollution indexes (APIs) of 42 Chinese sample cities over 10 years, from June 5, 2000 to March 4, 2010, and investigate the dynamic correlation of air pollution indexes (APIs) between 42 Chinese cities and their corresponding regional and national levels; comparison with the model without seasonal consideration is made. By adopting a DCC-GARCH model that accounts for the seasonality, we found that (i) the transformed DCC-GARCH model including seasonality dummies improves the estimation result in this study; (ii) the seasonality feature of the second moment follows that of the first moment, with the condition mean and variance of the second and autumn significantly lower than spring, whereas that of winter is higher than spring; (iii) the correlation between local APIs and their corresponding regional and national levels is dynamic; (iv) comparing with the DCC-GARCH model estimation, the transformed model does not change the feature of the dynamic correlations very much. © 2013 Zhanqiong He et al.en_US
dc.subjectBiochemistry, Genetics and Molecular Biologyen_US
dc.subjectEnvironmental Scienceen_US
dc.subjectMedicineen_US
dc.titleSeasonality and dynamic spatial contagion of air pollution in 42 Chinese citiesen_US
dc.typeJournalen_US
article.title.sourcetitleThe Scientific World Journalen_US
article.volume2013en_US
article.stream.affiliationsKunming University of Science and Technologyen_US
article.stream.affiliationsChiang Mai Universityen_US
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