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Original article
Stability of measured and modelled spatial contrasts in NO2 over time
  1. Marloes Eeftens1,
  2. Rob Beelen1,
  3. Paul Fischer2,
  4. Bert Brunekreef1,3,
  5. Kees Meliefste1,
  6. Gerard Hoek1
  1. 1Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
  2. 2Center for Environmental Health Research, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
  3. 3Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
  1. Correspondence to Marloes Eeftens, Institute for Risk Assessment Sciences (IRAS), Utrecht University, PO Box 80178, 3508 TD Utrecht, The Netherlands; m.r.eeftens{at}


Objectives Land use regression (LUR) modelling is a popular method to estimate outdoor air pollution concentrations at the home and/or work addresses of individual subjects in epidemiological studies. Typically, such models are constructed using measurements from dedicated monitoring campaigns lasting up to 1 year. It is unknown to what extent such models can adequately predict concentrations in earlier or later time periods. We tested the stability of measured and modelled spatial contrasts in outdoor nitrogen dioxide (NO2) pollution across the Netherlands over 8 years.

Methods NO2 measurements were conducted at 40 locations in the Netherlands in 1999–2000. In 2007, NO2 was again measured at 144 locations, of which 35 were the same as in 1999–2000. This enabled us to compare measurements as well as model predictions between the two time periods.

Results NO2 measurements conducted in 2007 agreed well with NO2 measurements taken in 1999–2000 at the same locations (R2=0.86). LUR models from 1999–2000 and 2007 explained 85% and 86% of observed spatial variance, respectively. The 2007 LUR model explained 77% of spatial variability in the 1999–2000 measurements and the 1999–2000 model explained 81% of variability in the 2007 measurements.

Conclusion We found good agreement between measured spatial contrasts in outdoor NO2 in 1999–2000 and 2007. LUR models predicted spatial contrast 8 years in the past (2007 model) and 8 years in the future (1999–2000 model) well. This supports the use of LUR models in epidemiological studies with health data available for a later or earlier timepoint.

  • Land use regression
  • air pollution
  • long term
  • geographic information systems
  • traffic
  • nitrogen oxides
  • exposure assessment
  • exposure monitoring
  • retrospective exposure assessment
  • pollution

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  • Competing interests None.

  • Provenance and peer review Not commissioned; externally peer reviewed.