Performance of multi-city land use regression models for nitrogen dioxide and fine particles.
BACKGROUND
Land use regression (LUR) models have been developed mostly to explain intraurban variations in air pollution based on often small local monitoring campaigns. Transferability of LUR models from city to city has been investigated, but little is known about the performance of models based on large numbers of monitoring sites covering a large area.


OBJECTIVE
We aimed to develop European and regional LUR models and to examine their transferability to areas not used for model development.


METHODS
We evaluated LUR models for nitrogen dioxide (NO2) and particulate matter (PM; PM2.5, PM2.5 absorbance) by combining standardized measurement data from 17 (PM) and 23 (NO2) ESCAPE (European Study of Cohorts for Air Pollution Effects) study areas across 14 European countries for PM and NO2. Models were evaluated with cross-validation (CV) and hold-out validation (HV). We investigated the transferability of the models by successively excluding each study area from model building.


RESULTS
The European model explained 56% of the concentration variability across all sites for NO2, 86% for PM2.5, and 70% for PM2.5 absorbance. The HV R2s were only slightly lower than the model R2 (NO2, 54%; PM2.5, 80%; PM2.5 absorbance, 70%). The European NO2, PM2.5, and PM2.5 absorbance models explained a median of 59%, 48%, and 70% of within-area variability in individual areas. The transferred models predicted a modest-to-large fraction of variability in areas that were excluded from model building (median R2: NO2, 59%; PM2.5, 42%; PM2.5 absorbance, 67%).


CONCLUSIONS
Using a large data set from 23 European study areas, we were able to develop LUR models for NO2 and PM metrics that predicted measurements made at independent sites and areas reasonably well. This finding is useful for assessing exposure in health studies conducted in areas where no measurements were conducted.
Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands.
Meng
M
Wang
Rob
R
Beelen
Tom
T
Bellander
Matthias
M
Birk
Giulia
G
Cesaroni
Marta
M
Cirach
Josef
J
Cyrys
Kees
K
de Hoogh
Christophe
C
Declercq
Konstantina
K
Dimakopoulou
Marloes
M
Eeftens
Kirsten T
KT
Eriksen
Francesco
F
Forastiere
Claudia
C
Galassi
Georgios
G
Grivas
Joachim
J
Heinrich
Barbara
B
Hoffmann
Alex
A
Ineichen
Michal
M
Korek
Timo
T
Lanki
Sarah
S
Lindley
Lars
L
Modig
Anna
A
Mölter
Per
P
Nafstad
Mark J
MJ
Nieuwenhuijsen
Wenche
W
Nystad
David
D
Olsson
Ole
O
Raaschou-Nielsen
Martina
M
Ragettli
Andrea
A
Ranzi
Morgane
M
Stempfelet
Dorothea
D
Sugiri
Ming-Yi
MY
Tsai
Orsolya
O
Udvardy
Mihaly J
MJ
Varró
Danielle
D
Vienneau
Gudrun
G
Weinmayr
Kathrin
K
Wolf
Tarja
T
Yli-Tuomi
Gerard
G
Hoek
Bert
B
Brunekreef
D000393:Air Pollutants / Q000032:analysis*; D004784:Environmental Monitoring; D008962:Models, Theoretical; D009585:Nitrogen Dioxide / Q000032:analysis*; D052638:Particulate Matter / Q000032:analysis*
D000393:Air Pollutants; D052638:Particulate Matter; D009585:Nitrogen Dioxide