Kees de Hoogh
Audrey de Nazelle
Helgah M. Akhlaghi
Kirsten T. Eriksen
Ingeborg M. Kooter
Jedynska, A., Hoek, G., Wang, M., Yang, A., Eeftens, M., Cyrys, J., Keuken, M., Ampe, C., Beelen, R., Cesaroni, G., Forastiere, F., Cirach, M., de Hoogh, K., de Nazelle, A., Nystad, W., Akhlaghi, H. M, Declercq, C., Stempfelet, M., Eriksen, K. T, Dimakopoulou, K., Lanki, T., Meliefste, K., Nieuwenhuijsen, M., Yli-Tuomi, T., Raaschou-Nielsen, O., Janssen, N., Brunekreef, B. & Kooter, IM. (2017). Spatial variations and development of land use regression models of oxidative potential in ten European study areas. Atmospheric Environment,150C. K. Chan, H. Singh, A. Wiedensohler. 24-32. United Kingdom: Pergamon Press. Retrieved from https://doi.org/10.1016/j.atmosenv.2016.11.029
Oxidative potential (OP) has been suggested as a health-relevant measure of air pollution. Little information is available about OP spatial variation and the possibility to model its spatial variability. Our aim was to measure the spatial variation of OP within and between 10 European study areas. The second aim was to develop land use regression (LUR) models to explain the measured spatial variation. OP was determined with the dithiothreitol (DTT) assay in ten European study areas. DTT of PM2.5 was measured at 16–40 sites per study area, divided over street, urban and regional background sites. Three two-week samples were taken per site in a one-year period in three different seasons. We developed study-area specific LUR models and a LUR model for all study areas combined to explain the spatial variation of OP. Significant contrasts between study areas in OP were found. OP DTT levels were highest in southern Europe. DTT levels at street sites were on average 1.10 times higher than at urban background locations. In 5 of the 10 study areas LUR models could be developed with a median R2 of 33%. A combined study area model explained 30% of the measured spatial variability. Overall, LUR models did not explain spatial variation well, possibly due to low levels of OP DTT and a lack of specific predictor variables.
Mary MacKillop Institute for Health Research