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Modelling indoor electromagnetic fields (EMF)
Bron: www.ncbi.nlm.nih.gov/pubmed/?term=24632329 .
13 maart 2014
Environ Int. 2014 Mar 13;67C:22-26. doi: 10.1016/j.envint.2014.02.008. (Epub ahead of print)
Modelling indoor electromagnetic fields (EMF) from mobile phone base stations for epidemiological studies.
Beekhuizen J1, Vermeulen R1, van Eijsden M2, van Strien R3, Bürgi A4, Loomans E2, Guxens M1, Kromhout H1, Huss A5.
1Institute for Risk Assessment Sciences (IRAS), Division Environmental Epidemiology, Utrecht University, Yalelaan 2, 3584 CM, Utrecht, The Netherlands.
2Department of Epidemiology and Health Promotion, Public Health Service of Amsterdam (GGD), 1018 WT, Amsterdam, The Netherlands.
3Department of Environmental Health, Public Health Service of Amsterdam (GGD), 1018 WT, Amsterdam, The Netherlands.
4ARIAS umwelt.forschung.beratung, CH-3011, Bern, Switzerland.
5Institute for Risk Assessment Sciences (IRAS), Division Environmental Epidemiology, Utrecht University, Yalelaan 2, 3584 CM, Utrecht, The Netherlands. Electronic address: email@example.com.
Radio frequency electromagnetic fields (RF-EMF) from mobile phone base stations can be reliably modelled for outdoor locations, using 3D radio wave propagation models that consider antenna characteristics and building geometry. For exposure assessment in epidemiological studies, however, it is especially important to determine indoor exposure levels as people spend most of their time indoors. We assessed the accuracy of indoor RF-EMF model predictions, and whether information on building characteristics could increase model accuracy. We performed 15-minute spot measurements in 263 rooms in 101 primary schools and 30 private homes in Amsterdam, the Netherlands. At each measurement location, we collected information on building characteristics that can affect indoor exposure to RF-EMF, namely glazing and wall and window frame materials. Next, we modelled RF-EMF at the measurement locations with the 3D radio wave propagation model NISMap. We compared model predictions with measured values to evaluate model performance, and explored if building characteristics modified the association between modelled and measured RF-EMF using a mixed effect model. We found a Spearman correlation of 0.73 between modelled and measured total downlink RF-EMF from base stations. The average modelled and measured RF-EMF were 0.053 and 0.041mW/m2, respectively, and the precision (standard deviation of the differences between predicted and measured values) was 0.184mW/m2. Incorporating information on building characteristics did not improve model predictions. Although there is exposure misclassification, we conclude that it is feasible to reliably rank indoor RF-EMF from mobile phone base stations for epidemiological studies.
Copyright © 2014 Elsevier Ltd. All rights reserved.
Base station, Electromagnetic fields, Exposure, Indoor, Modelling, Radio wave propagation
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