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Local real-time forecasting of ozone exposure using temperature data

Publication ,  Journal Article
Lu, X; Gelfand, AE; Holland, DM
Published in: Environmetrics
November 1, 2018

Rigorous and rapid assessment of ambient ozone exposure is important for informing the public about ozone levels that may lead to adverse health effects. In this paper, we use hierarchical modeling to enable real-time forecasting of 8-hr average ozone exposure. This contrasts with customary retrospective analysis of exposure data. Specifically, our contribution is to show how incorporating temperature data in addition to the observed ozone can significantly improve forecast accuracy, as measured by predictive performance and empirical coverage. We adopt two-stage autoregressive models, also introducing periodicity and heterogeneity while still maintaining our objective of forecasting in real time. The entire effort is illustrated through modeling data collected at the Village Green monitoring station in Durham, North Carolina.

Duke Scholars

Published In

Environmetrics

DOI

EISSN

1099-095X

ISSN

1180-4009

Publication Date

November 1, 2018

Volume

29

Issue

7

Related Subject Headings

  • Statistics & Probability
  • 49 Mathematical sciences
  • 41 Environmental sciences
  • 05 Environmental Sciences
  • 01 Mathematical Sciences
 

Citation

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ICMJE
MLA
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Lu, X., Gelfand, A. E., & Holland, D. M. (2018). Local real-time forecasting of ozone exposure using temperature data. Environmetrics, 29(7). https://doi.org/10.1002/env.2509
Lu, X., A. E. Gelfand, and D. M. Holland. “Local real-time forecasting of ozone exposure using temperature data.” Environmetrics 29, no. 7 (November 1, 2018). https://doi.org/10.1002/env.2509.
Lu X, Gelfand AE, Holland DM. Local real-time forecasting of ozone exposure using temperature data. Environmetrics. 2018 Nov 1;29(7).
Lu, X., et al. “Local real-time forecasting of ozone exposure using temperature data.” Environmetrics, vol. 29, no. 7, Nov. 2018. Scopus, doi:10.1002/env.2509.
Lu X, Gelfand AE, Holland DM. Local real-time forecasting of ozone exposure using temperature data. Environmetrics. 2018 Nov 1;29(7).
Journal cover image

Published In

Environmetrics

DOI

EISSN

1099-095X

ISSN

1180-4009

Publication Date

November 1, 2018

Volume

29

Issue

7

Related Subject Headings

  • Statistics & Probability
  • 49 Mathematical sciences
  • 41 Environmental sciences
  • 05 Environmental Sciences
  • 01 Mathematical Sciences