Land use regression models for estimating individual NOx and NO₂ exposures in a metropolis with a high density of traffic roads and population.This study is conducted to characterize the intra-urban distribution of NOx and NO2; develop land use regression (LUR) models to assess outdoor NOx and NO2 concentrations, using the ESCAPE modeling approach with locally specific land use data; and compare NOx and NO2 exposures for children in the Taipei Metropolis by the LUR models, the nearest monitoring station, and kriging methods based on data collected at the measurement sites. 
Land use regression
Land use regression models for estimating individual NOx and NO₂ exposures in a metropolis with a high density of traffic roads and population.This study is conducted to characterize the intra-urban distribution of NOx and NO2; develop land use regression (LUR) models to assess outdoor NOx and NO2 concentrations, using the ESCAPE modeling approach with locally specific land use data; and compare NOx and NO2 exposures for children in the Taipei Metropolis by the LUR models, the nearest monitoring station, and kriging methods based on data collected at the measurement sites.  Land use data and traffic-related information in different buffer zones were combined with measured concentrations to derive LUR models using supervised forward stepwise multiple regressions.  The LUR models gave a wider variation in estimating NOx and NO2 exposures than either the ordinary kriging method or the nearest measurement site did for the children of Taiwan Birth Cohort Study (TBCS) in Taipei.
LUR models
Land use regression models for estimating individual NOx and NO₂ exposures in a metropolis with a high density of traffic roads and population.This study is conducted to characterize the intra-urban distribution of NOx and NO2; develop land use regression (LUR) models to assess outdoor NOx and NO2 concentrations, using the ESCAPE modeling approach with locally specific land use data; and compare NOx and NO2 exposures for children in the Taipei Metropolis by the LUR models, the nearest monitoring station, and kriging methods based on data collected at the measurement sites. 
ESCAPE modeling approach
Land use data and traffic-related information in different buffer zones were combined with measured concentrations to derive LUR models using supervised forward stepwise multiple regressions. 
supervised forward stepwise multiple regressions