title: Accounting for spatial effects in land use regression for urban air pollution modeling.
abstract: In order to accurately assess air pollution risks, health studies require spatially resolved pollution concentrations. Land-use regression (LUR) models estimate ambient concentrations at a fine spatial scale. However, spatial effects such as spatial non-stationarity and spatial autocorrelation can reduce the accuracy of LUR estimates by increasing regression errors and uncertainty; and statistical methods for resolving these effects--e.g., spatially autoregressive (SAR) and geographically weighted regression (GWR) models--may be difficult to apply simultaneously. We used an alternate approach to address spatial non-stationarity and spatial autocorrelation in LUR models for nitrogen dioxide. Traditional models were re-specified to include a variable capturing wind speed and direction, and re-fit as GWR models. Mean R(2) values for the resulting GWR-wind models (summer: 0.86, winter: 0.73) showed a 10-20% improvement over traditional LUR models. GWR-wind models effectively addressed both spatial effects and produced meaningful predictive models. These results suggest a useful method for improving spatially explicit models.
authors.affiliation: Department of Geography, University of Calgary, Calgary Alberta, Canada. Electronic address: bertazzs@ucalgary.ca.
authors.forename: Stefania
authors.initials: S
authors.lastname: Bertazzon
authors.affiliation: Air Health Science Division, Health Canada, 269 Laurier Avenue West, Ottawa, Ontario, Canada. Electronic address: markey.johnson@hc-sc.gc.ca.
authors.forename: Markey
authors.initials: M
authors.lastname: Johnson
authors.affiliation: Department of Biology, University of Ottawa, Ottawa, Ontario, Canada. Electronic address: kristin.eccles@uottawa.ca.
authors.forename: Kristin
authors.initials: K
authors.lastname: Eccles
authors.affiliation: Department of Medicine, University of Calgary, Calgary Alberta, Canada; Department of Community Health Sciences, University of Calgary, Calgary Alberta, Canada. Electronic address: ggkaplan@ucalgary.ca.
authors.forename: Gilaad G
authors.initials: GG
authors.lastname: Kaplan
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000032:analysis* / Q000191:economics / Q000706:statistics & numerical data; D000465:Algorithms; D002170:Canada; D004784:Environmental Monitoring / Q000379:methods; D040362:Geographic Information Systems; D006801:Humans; D008962:Models, Theoretical; D009585:Nitrogen Dioxide / Q000032:analysis; D052638:Particulate Matter / Q000032:analysis; D058998:Remote Sensing Technology / Q000379:methods; D062206:Spatial Analysis; D000068916:Spatial Regression; D014919:Wind
chemical_list: D000393:Air Pollutants; D052638:Particulate Matter; D009585:Nitrogen Dioxide
keywords: Air pollution; Environmental modeling; Land use regression; Nitrogen dioxide; Spatial analysis; Wind