Author:
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Nunen, Erik van; Vermeulen, Roel; Tsai, Ming-Yi; Probst-Hensch, Nicole M.; Ineichen, Alex; Davey, Mark; Imboden, Medea; Ducret Stich, Regina; Naccarati, Alessio; Raffaele, Daniela; Ranzi, Andrea; Ivaldi, Cristiana; Galassi, Claudia; Nieuwenhuijsen, Mark J.; Curto, Ariadna; Donaire González, David; Cirach, Marta; Chatzi, Leda; Kampouri, Mariza; Vlaanderen, Jelle; Meliefste, Kees; Buijtenhuijs, Daan; Brunekreef, Bert; Morley, David; Vineis, Paolo; Gulliver, John; Hoek, Gerard
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Abstract:
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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 min 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, 10 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 h
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. |