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VAR model of PM2.5, weather and traffic in los angeles long beach area

  • Wang Weiqiang*
  • , Niu Zhendong
  • *Corresponding author for this work
  • University of California at Los Angeles

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The Los Angeles Long Beach Area has been the largest air polluter in LA regions. How to decrease the air pollution concentrations becomes a hot topic recently. A vector autoregressive model (VAR) was applied to modeling the time series of monthly maximum Particulate Matter (PM) 2.5 concentration in Los Angeles Long Beach Area. This paper explored the association among the current month PM2.5 concentrations and traffic and the meteorological covariates including wind speeds, temperatures, soil temperatures, dew points, for all the three datasets for LA long beach, 2001-2007, the VAR model appears to be supported by the datasets. This paper also provide parameter estimation, diagnostic checking procedures to model. Diagnostic tests have been applied to different VAR (p) models.

Original languageEnglish
Title of host publicationProceedings - 2009 International Conference on Environmental Science and Information Application Technology, ESIAT 2009
PublisherIEEE Computer Society
Pages66-69
Number of pages4
ISBN (Print)9780769536828, 9780769536828
DOIs
Publication statusPublished - 2009
Event2009 International Conference on Environmental Science and Information Application Technology, ESIAT 2009 - Wuhan, China
Duration: 4 Jul 20095 Jul 2009

Publication series

NameProceedings - 2009 International Conference on Environmental Science and Information Application Technology, ESIAT 2009
Volume3

Conference

Conference2009 International Conference on Environmental Science and Information Application Technology, ESIAT 2009
Country/TerritoryChina
CityWuhan
Period4/07/095/07/09

Keywords

  • Air pollution
  • Time series
  • Var model

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