A dependent Bayesian Dirichlet process model for source apportionment of particle number size distribution-Reference-Cited by-同舟云学术

A dependent Bayesian Dirichlet process model for source apportionment of particle number size distribution

Published:2022-09-22 Issue:1 Volume:34 Page:
ISSN:1180-4009
Container-title:Environmetrics
language:en
Short-container-title:Environmetrics

Author:

Baerenbold Oliver¹^ORCID,Meis Melanie²^ORCID,Martínez‐Hernández Israel³,Euán Carolina³^ORCID,Burr Wesley S.⁴^ORCID,Tremper Anja¹^ORCID,Fuller Gary¹,Pirani Monica¹,Blangiardo Marta¹

Affiliation:

1. Department of Epidemiology and Biostatistics, MRC Centre for Environment and Health Imperial College London UK

2. Department of Atmospheric and Oceanic Sciences Consejo Nacional de Investigaciones Cientinficas y Tecnologicas (CONICET), Centro del Mar y la Atmósfera y los Océanos (CIMA‐UBA‐CONICET), Universidad de Buenos Aires Buenos Aires Argentina

3. Department of Mathematics and Statistics Lancaster University Lancaster UK

4. Department of Mathematics Trent University Peterborough Ontario Canada

Funder

Medical Research Council Canada

National Institute for Health Research

Publisher

Wiley

Subject

Ecological Modeling,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/env.2763

Reference46 articles.

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3. Assessment of microscale spatio-temporal variation of air pollution at an urban hotspot in Madrid (Spain) through an extensive field campaign

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