Thursday, November 20, 2014

Personal exposure meters underestimate the exposure of humans to non-ionizing radiation in indoor environmen

Assessment of human body influence on exposure measurements of electric field in indoor enclosures

de Miguel-Bilbao S, García J, Ramos V, Blas J. Assessment of human body influence on exposure measurements of electric field in indoor enclosures. Bioelectromagnetics. 2014 Nov 14. doi: 10.1002/BEM.21888. [Epub ahead of print]


Personal exposure meters (PEMs) used for measuring exposure to electromagnetic fields (EMF) are typically used in epidemiological studies. As is well known, these measurement devices cause a perturbation of real EMF exposure levels due to the presence of the human body in the immediate proximity. 

This paper aims to model the alteration caused by the body shadow effect (BSE) in motion conditions and in indoor enclosures at the Wi-Fi frequency of 2.4 GHz. For this purpose, simulation techniques based on ray-tracing have been carried out, and their results have been verified experimentally. 

A good agreement exists between simulation and experimental results in terms of electric field (E-field) levels, and taking into account the cumulative distribution function (CDF) of the spatial distribution of amplitude. The Kolmogorov-Smirnov (KS) test provides a P-value greater than 0.05, in fact close to 1. It has been found that the influence of the presence of the human body can be characterized as an angle of shadow that depends on the dimensions of the indoor enclosure. The CDFs show that the E-field levels in indoor conditions follow a lognormal distribution in the absence of the human body and under the influence of BSE. 

In conclusion, the perturbation caused by BSE in PEMs readings cannot be compensated for by correction factors. Although the mean value is well adjusted, BSE causes changes in CDF that would require improvements in measurement protocols and in the design of measuring devices to subsequently avoid systematic errors.

The motivation behind this paper is to study the potential errors that are associated with the exposure measurements to non-ionizing radiations due to the influence of the BSE in indoor environments, and the need for a quantification of this effect. Four indoor scenarios have been investigated to model the BSE in motion conditions.
This study compares the results of the simulation and the experimental measurements to model and analyze the attenuation of the E-field at the Wi-Fi frequency due to the effect of the human body in indoor enclosures.
Initial experimental measurements show that the BSE introduces an underestimation in the E-field levels of 2.8 (9 dB) considering the worst-case scenario, in which the PEM is situated in NLOS, and is therefore being affected by the BSE during the whole experiment. Attenuation depends on the AoA of the rays that impact the human body. A simulation technique has been proposed for the identification and quantification of the range of rays that are affected by the BSE. A shadow angle has been introduced as a model parameter to decide whether a particular ray is attenuated or not. This technique shows a good agreement with PEM measurements in respect to the obtained results and in terms of statistical accuracy.
The performed research in this study is motivated by previous works on the quantification of the shadow angle in open spaces. It demonstrates that it is possible to quantify the BSE in indoor enclosures as a shadow angle whose value is lower than in outdoor environments.
In addition, the conclusion drawn from the computation of the shadow angle has been contrasted with the carrying out of the experiment in three other indoor enclosures. It was concluded that the angle of shadow for indoor environments depends on the dimensions of the area being tested. The BSE is more significant in spacious enclosures than in small ones. In the case of small closed volumes, the rays that are scattered by the body arrive at the PEM of the shadow region after being reflected on the nearest walls without much attenuation. In contrast, in more spacious areas, those scattered rays travel longer paths and arrive at the PEM more attenuated.
This paper also provides a useful insight into the statistical features associated with the influence of the human body on the E-field levels that are measured by PEMs. The experimental and simulation results show that the EMF levels in the absence of the human body fit a Lognormal distribution, one of the most typical statistical distributions for indoor environments. The same distribution is followed by the results obtained when the PEM is affected by the BSE, and it is completely in NLOS. However, the underestimation caused by the BSE cannot be accurately corrected by an average correction factor, although that approach offers a roughly approximate solution.
This study demonstrates that ignoring the BSE is a systematic error that underestimates the real exposure of humans to non-ionizing radiation in indoor environments. This paper provides a useful methodology to understand the statistical consequences of the BSE.
Joel M. Moskowitz, Ph.D.
Director, Center for Family and Community Health
School of Public Health, University of California, Berkeley

Electromagnetic Radiation Safety

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