Using Land Use Regression Models to Estimate Individual Exposure to NOx and NO2 in Taipei Metropolis
Date Issued
2012
Date
2012
Author(s)
Chu, Yu-Hsiu
Abstract
Background－This study developed land use regression models to assess NOx and NO2 ambient concentrations in order to minimize the exposure misclassification and achieve better individual exposure assessment for the future epidemiology studies.
Method－A population density based sampling strategy was used to select 40 locations as NOx and NO2 monitoring sites in the central region of Taipei Metropolis, including 18 traffic sites and 22 urban sites. One additional background site was selected for annual average adjustment. NOx and NO2 concentrations were monitored simultaneously by using Ogawa passive samplers for 2-week period in three seasons during 2009 and 2010. With collected land use information containing land-cover and traffic related data, a series of potential predictor variables in concentric circle buffers with several radii ranging from 25 to 5000m of each monitoring site were obtained by using GIS system. Based on stochastic modeling techniques, we combined the average concentrations and values of predictor variables in stepwise procedure to develop the final LUR models for NOx and NO2.
Results－The adjusted annual mean concentrations were 46.6±14.5 ppb for NOx and 26.0±6.5 ppb for NO2. Vertical variation (High/Low ratio =0.74) was discovered for the modification of LUR models. There were 6 variables for the final model of NOx (adjusted R2=0.77), including the major road length within 25m, urban green area within 300m, urban green area in 300-5000m buffer, major road length in 50-500m buffer, major road length in 25-50m buffer, and natural area within 500m. And there were 4 predictors for the NO2 model (adjusted R2=0.70), including the natural area within 500m, major road length within 25m, industry-residential area within 500m, and urban green area within 100m. One birth cohort was indentified for exposure assessment by three approaches including Ordinary Kriging, nearest station method, and developed LUR models. LUR models showed moderate spatial variation and higher resolution than other methods.
Conclusion－This study indicates that the ambient concentration of NOx and NO2 can be well estimated by LUR models with 4-6 variables in Taipei Metropolis, and LUR approach provides better spatial resolutions than interpolation method or regulatory stations.
Subjects
Land use regression
Exposure assessment
Geographic information system (GIS)
traffic emission
vertical distribution
Nitrogen oxides (NOx)
nitrogen dioxide (NO2)
SDGs
Type
thesis
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