TY - JOUR
T1 - Land use regression models for Ultrafine Particles in six European areas
AU - van Nunen, Erik
AU - Vermeulen, Roel
AU - Tsai, Ming-Yi
AU - Probst-Hensch, Nicole
AU - Ineichen, Alex
AU - Davey, Mark E
AU - Imboden, Medea
AU - Ducret-Stich, Regina
AU - Naccarati, Alessio
AU - Raffaele, Daniela
AU - Ranzi, Andrea
AU - Ivaldi, Cristiana
AU - Galassi, Claudia
AU - Nieuwenhuijsen, Mark J
AU - Curto, Ariadna
AU - Donaire-Gonzalez, David
AU - Cirach, Marta
AU - Chatzi, Leda
AU - Kampouri, Mariza
AU - Vlaanderen, Jelle
AU - Meliefste, Kees
AU - Buijtenhuijs, Daan
AU - Brunekreef, Bert
AU - Morley, David
AU - Vineis, Paolo
AU - Gulliver, John
AU - Hoek, Gerard
PY - 2017/2/28
Y1 - 2017/2/28
N2 - Long-term Ultrafine Particle (UFP) exposure estimates at a fine spatial scale are needed for epidemiological studies. Land Use Regression (LUR) models were developed and evaluated for six European areas based on repeated 30-minute monitoring following standardized protocols. In each area; Basel (Switzerland), Heraklion (Greece), Amsterdam, Maastricht and Utrecht ('the Netherlands'), Norwich (United Kingdom), Sabadell (Spain), and Turin (Italy), 160-240 sites were monitored to develop LUR models by supervised stepwise selection of GIS predictors. For each area and all areas combined, ten models were developed in stratified random selections of 90% of sites. UFP prediction robustness was evaluated with the Intraclass Correlation Coefficient (ICC) at 31-50 external sites per area. Models from Basel and the Netherlands were validated against repeated 24-hour outdoor measurements. Structure and Model R2 of local models were similar within, but varied between areas (e.g. 38-43% Turin; 25-31% Sabadell). Robustness of predictions within areas was high (ICC 0.73-0.98). External validation R2 was 53% in Basel and 50% in the Netherlands. Combined area models were robust (ICC 0.93-1.00) and explained UFP variation almost equally well as local models. In conclusion, robust UFP LUR models could be developed on short-term monitoring, explaining around 50% of spatial variance in longer-term measurements.
AB - Long-term Ultrafine Particle (UFP) exposure estimates at a fine spatial scale are needed for epidemiological studies. Land Use Regression (LUR) models were developed and evaluated for six European areas based on repeated 30-minute monitoring following standardized protocols. In each area; Basel (Switzerland), Heraklion (Greece), Amsterdam, Maastricht and Utrecht ('the Netherlands'), Norwich (United Kingdom), Sabadell (Spain), and Turin (Italy), 160-240 sites were monitored to develop LUR models by supervised stepwise selection of GIS predictors. For each area and all areas combined, ten models were developed in stratified random selections of 90% of sites. UFP prediction robustness was evaluated with the Intraclass Correlation Coefficient (ICC) at 31-50 external sites per area. Models from Basel and the Netherlands were validated against repeated 24-hour outdoor measurements. Structure and Model R2 of local models were similar within, but varied between areas (e.g. 38-43% Turin; 25-31% Sabadell). Robustness of predictions within areas was high (ICC 0.73-0.98). External validation R2 was 53% in Basel and 50% in the Netherlands. Combined area models were robust (ICC 0.93-1.00) and explained UFP variation almost equally well as local models. In conclusion, robust UFP LUR models could be developed on short-term monitoring, explaining around 50% of spatial variance in longer-term measurements.
U2 - 10.1021/acs.est.6b05920
DO - 10.1021/acs.est.6b05920
M3 - Article
C2 - 28244744
SN - 0013-936X
VL - 51
SP - 3336
EP - 3334
JO - Environmental Science and Technology
JF - Environmental Science and Technology
IS - 6
ER -
