Data integration model for air quality: a hierarchical approach to the global estimation of exposures to ambient air pollution-Reference-Cited by-同舟云学术

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Data integration model for air quality: a hierarchical approach to the global estimation of exposures to ambient air pollution

Published:2017-06-13 Issue:1 Volume:67 Page:231-253
ISSN:0035-9254
Container-title:Journal of the Royal Statistical Society: Series C (Applied Statistics)
language:en
Short-container-title:J. R. Stat. Soc. C

Author:

Shaddick Gavin¹²,Thomas Matthew L.²,Green Amelia²,Brauer Michael³,Donkelaar Aaron⁴,Burnett Rick⁵,Chang Howard H.⁶,Cohen Aaron⁷,Dingenen Rita Van⁸,Dora Carlos⁹,Gumy Sophie⁹,Liu Yang¹⁰,Martin Randall⁴,Waller Lance A.¹⁰,West Jason¹¹,Zidek James V.³,Prüss‐Ustün Annette⁹

Affiliation:

1. University of Exeter UK

2. University of Bath UK

3. University of British Columbia Vancouver Canada

4. Dalhousie University Halifax Canada

5. Health Canada Ottawa Canada

6. Emory University Atlanta Canada

7. Health Effects Institute Boston USA

8. European Commission Ispra Italy

9. World Health Organization Geneva Switzerland

10. Emory University Atlanta USA

11. University of North Carolina Chapel Hill USA

Funder

Engineering and Physical Sciences Research Council

World Health Organization

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/rssc.12227

Reference31 articles.

1. A Spatio-Temporal Downscaler for Output From Numerical Models

2. Spatial interaction and the statistical analysis of lattice systems (with discussion);Besag J.;J. R. Statist. Soc. B,1974

3. Global modeling of tropospheric chemistry with assimilated meteorology: Model description and evaluation

4. Exposure Assessment for Estimation of the Global Burden of Disease Attributable to Outdoor Air Pollution

5. Ambient Air Pollution Exposure Estimation for the Global Burden of Disease 2013

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