Spatiotemporal Modeling of Ozone Levels in Quebec (Canada): A Comparison of Kriging, Land-Use Regression (LUR), and Combined Bayesian Maximum Entropy–LUR Approaches | Zendy

Ariane Adam-Poupart | Zendy; Allan Brand | Zendy; Michel Fournier | Zendy; Michael Jerrett | Zendy; Audrey Smargiassi | Zendy

Open Access

Spatiotemporal Modeling of Ozone Levels in Quebec (Canada): A Comparison of Kriging, Land-Use Regression (LUR), and Combined Bayesian Maximum Entropy–LUR Approaches

Author(s) -

Ariane Adam-Poupart,

Allan Brand,

Michel Fournier,

Michael Jerrett,

Audrey Smargiassi

Publication year - 2014

Publication title -

environmental health perspectives

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.257

H-Index - 282

eISSN - 1552-9924

pISSN - 0091-6765

DOI - 10.1289/ehp.1306566

Subject(s) - kriging , mean squared error , environmental science , air quality index , regression analysis , regression , statistics , bayesian probability , atmospheric sciences , mathematics , meteorology , geography , geology

Ambient air ozone (O3) is a pulmonary irritant that has been associated with respiratory health effects including increased lung inflammation and permeability, airway hyperreactivity, respiratory symptoms, and decreased lung function. Estimation of O3 exposure is a complex task because the pollutant exhibits complex spatiotemporal patterns. To refine the quality of exposure estimation, various spatiotemporal methods have been developed worldwide.

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