A national fine spatial scale land-use regression model for ozone.
作者： Jules Kerckhoffs , Meng Wang , Kees Meliefste , Ebba Malmqvist , Paul Fischer
DOI: 10.1016/J.ENVRES.2015.04.014
关键词: Nitrogen dioxide 、 Atmospheric sciences 、 Spatial ecology 、 Ozone 、 Geographic information system 、 Scale (map) 、 Pollutant 、 Environmental science 、 Meteorology 、 Land use regression 、 Spatial variability
摘要: Uncertainty about health effects of long-term ozone exposure remains. Land use regression (LUR) models have been used successfully for modeling fine scale spatial variation primary pollutants but very limited ozone. Our objective was to assess the feasibility developing a national LUR model at scale. Ozone concentrations were measured with passive samplers 90 locations across Netherlands (19 regional background, 36 urban 35 traffic). All sites simultaneously during four 2-weekly campaigns spread over seasons. developed summer average as and annual using predictor variables obtained Geographic Information Systems. Summer varied between 32 61µg/m(3). traffic on 9µg/m(3) lower compared background sites. correlated highly negatively nitrogen dioxide moderately particles. A including small-scale traffic, large-scale address density, green region indicator explained 71% in concentrations. is promising method variation, high correlation NO2 limits application epidemiology.
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