Land use regression model for ultrafine particles in Amsterdam

Hoek, G; Beelen, R; Kos, G; Dijkema, M; Zee, SC; Fischer, PH; Brunekreef, B

HERO ID

674679

Reference Type

Journal Article

Year

2011

Language

English

PMID

21158386

HERO ID 674679
In Press No
Year 2011
Title Land use regression model for ultrafine particles in Amsterdam
Authors Hoek, G; Beelen, R; Kos, G; Dijkema, M; Zee, SC; Fischer, PH; Brunekreef, B
Journal Environmental Science & Technology
Volume 45
Issue 2
Page Numbers 622-628
Abstract There are currently no epidemiological studies on health effects of long-term exposure to ultrafine particles (UFP), largely because data on spatial exposure contrasts for UFP is lacking. The objective of this study was to develop a land use regression (LUR) model for UFP in the city of Amsterdam. Total particle number concentrations (PNC), PM10, PM2.5, and its soot content were measured directly outside 50 homes spread over the city of Amsterdam. Each home was measured during one week. Continuous measurements at a central urban background site were used to adjust the average concentration for temporal variation. Predictor variables (traffic, address density, land use) were obtained using geographic information systems. A model including the product of traffic intensity and the inverse distance to the nearest road squared, address density, and location near the port explained 67% of the variability in measured PNC. LUR models for PM2.5, soot, and coarse particles (PM10, PM2.5) explained 57%, 76%, and 37% of the variability in measured concentrations. Predictions from the PNC model correlated highly with predictions from LUR models for PM2.5, soot, and coarse particles. A LUR model for PNC has been developed, with similar validity as previous models for more commonly measured pollutants.
Doi 10.1021/es1023042
Pmid 21158386
Wosid WOS:000286090500045
Is Certified Translation No
Dupe Override No
Is Public Yes
Language Text English
Is Qa No