A national fine spatial scale land-use regression model for ozone.
Kerckhoffs, Jules ; Wang, Meng ; Meliefste, Kees ; Malmqvist, Ebba LU
; Fischer, Paul
; Janssen, Nicole A H
; Beelen, Rob
and Hoek, Gerard
(2015)
In Environmental Research
140.
p.440-448
- Abstract
- 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 of primary pollutants but very limited for ozone. Our objective was to assess the feasibility of developing a national LUR model for ozone at a fine spatial scale. Ozone concentrations were measured with passive samplers at 90 locations across the Netherlands (19 regional background, 36 urban background, 35 traffic). All sites were measured simultaneously during four 2-weekly campaigns spread over the seasons. LUR models were developed for the summer average as the primary exposure and annual average using predictor variables obtained with Geographic Information... (More)
- 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 of primary pollutants but very limited for ozone. Our objective was to assess the feasibility of developing a national LUR model for ozone at a fine spatial scale. Ozone concentrations were measured with passive samplers at 90 locations across the Netherlands (19 regional background, 36 urban background, 35 traffic). All sites were measured simultaneously during four 2-weekly campaigns spread over the seasons. LUR models were developed for the summer average as the primary exposure and annual average using predictor variables obtained with Geographic Information Systems. Summer average ozone concentrations varied between 32 and 61µg/m(3). Ozone concentrations at traffic sites were on average 9µg/m(3) lower compared to regional background sites. Ozone correlated highly negatively with nitrogen dioxide and moderately with fine particles. A LUR model including small-scale traffic, large-scale address density, urban green and a region indicator explained 71% of the spatial variation in summer average ozone concentrations. Land use regression modeling is a promising method to assess ozone spatial variation, but the high correlation with NO2 limits application in epidemiology. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/5453167
- author
- Kerckhoffs, Jules
; Wang, Meng
; Meliefste, Kees
; Malmqvist, Ebba
LU
; Fischer, Paul
; Janssen, Nicole A H
; Beelen, Rob
and Hoek, Gerard
- organization
- publishing date
- 2015
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Environmental Research
- volume
- 140
- pages
- 440 - 448
- publisher
- Elsevier
- external identifiers
-
- pmid:25978345
- wos:000357904100049
- scopus:84930941093
- pmid:25978345
- ISSN
- 1096-0953
- DOI
- 10.1016/j.envres.2015.04.014
- language
- English
- LU publication?
- yes
- id
- 9364139e-7b76-41d1-988d-438b15b26977 (old id 5453167)
- alternative location
- http://www.ncbi.nlm.nih.gov/pubmed/25978345?dopt=Abstract
- date added to LUP
- 2016-04-01 09:52:58
- date last changed
- 2022-03-27 01:42:07
@article{9364139e-7b76-41d1-988d-438b15b26977,
abstract = {{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 of primary pollutants but very limited for ozone. Our objective was to assess the feasibility of developing a national LUR model for ozone at a fine spatial scale. Ozone concentrations were measured with passive samplers at 90 locations across the Netherlands (19 regional background, 36 urban background, 35 traffic). All sites were measured simultaneously during four 2-weekly campaigns spread over the seasons. LUR models were developed for the summer average as the primary exposure and annual average using predictor variables obtained with Geographic Information Systems. Summer average ozone concentrations varied between 32 and 61µg/m(3). Ozone concentrations at traffic sites were on average 9µg/m(3) lower compared to regional background sites. Ozone correlated highly negatively with nitrogen dioxide and moderately with fine particles. A LUR model including small-scale traffic, large-scale address density, urban green and a region indicator explained 71% of the spatial variation in summer average ozone concentrations. Land use regression modeling is a promising method to assess ozone spatial variation, but the high correlation with NO2 limits application in epidemiology.}},
author = {{Kerckhoffs, Jules and Wang, Meng and Meliefste, Kees and Malmqvist, Ebba and Fischer, Paul and Janssen, Nicole A H and Beelen, Rob and Hoek, Gerard}},
issn = {{1096-0953}},
language = {{eng}},
pages = {{440--448}},
publisher = {{Elsevier}},
series = {{Environmental Research}},
title = {{A national fine spatial scale land-use regression model for ozone.}},
url = {{http://dx.doi.org/10.1016/j.envres.2015.04.014}},
doi = {{10.1016/j.envres.2015.04.014}},
volume = {{140}},
year = {{2015}},
}