title: Development and back-extrapolation of NO2 land use regression models for historic exposure assessment in Great Britain.
abstract: Modeling historic air pollution exposures is often restricted by availability of monitored concentration data. We evaluated back-extrapolation of land use regression (LUR) models for annual mean NO2 concentrations in Great Britain for up to 18 years earlier. LUR variables were created in a geographic information system (GIS) using land cover and road network data summarized within buffers, site coordinates, and altitude. Four models were developed for 2009 and 2001 using 75% of monitoring sites (in different groupings) and evaluated on the remaining 25%. Variables selected were generally stable between models. Within year, hold-out validation yielded mean-squared-error-based R(2) (MSE-R(2)) (i.e., fit around the 1:1 line) values of 0.25-0.63 and 0.51-0.65 for 2001 and 2009, respectively. Back-extrapolation was conducted for 2009 and 2001 models to 1991 and for 2009 models to 2001, adjusting to the year using two background NO2 monitoring sites. Evaluation of back-extrapolated predictions used 100% of sites from an historic national NO2 diffusion tube network (n = 451) for 1991 and 70 independent sites from automatic monitoring in 2001. Values of MSE-R(2) for back-extrapolation to 1991 were 0.42-0.45 and 0.52-0.55 for 2001 and 2009 models, respectively, but model performance varied by region. Back-extrapolation of LUR models appears valid for exposure assessment for NO2 back to 1991 for Great Britain.
authors.affiliation: Small Area Health Statistics Unit, MRC-PHE, School of Public Health, Imperial College London , St. Mary's Campus, London W2 1PG, United Kingdom. j.gulliver@imperial.ac.uk
authors.forename: John
authors.initials: J
authors.lastname: Gulliver
authors.forename: Kees
authors.initials: K
authors.lastname: de Hoogh
authors.forename: Anna
authors.initials: A
authors.lastname: Hansell
authors.forename: Danielle
authors.initials: D
authors.lastname: Vienneau
mesh_terms: D004784:Environmental Monitoring; D008962:Models, Theoretical; D009569:Nitric Oxide / Q000032:analysis*; D006113:United Kingdom
chemical_list: D009569:Nitric Oxide