The association between exposure determined by radiofrequency personal exposimeters and human exposure: A simulation study

The selection of an adequate exposure assessment approach is imperative for the quality of epidemiological studies. The use of personal exposimeters turned out to be a reasonable approach to determine exposure profiles, however, certain limitations regarding the absolute values delivered by the devices have to be considered. Apart from the limited dynamic range, it has to be taken into account that these devices give only an approximation of the exposure due to the influence of the body of the person carrying the exposimeter, the receiver characteristics of the exposimeter, as well as the dependence of the measured value on frequency band, channel, slot configuration, and communication traffic. In this study, the relationship between the field strength measured close to the human body at the location of the exposimeter and the exposure, that is, the field strength at the location of the human body without the human body present, is investigated by numerical means using the Visible Human model as an anatomical phantom. Two different scenarios were chosen: (1) For FM, GSM, and UMTS an urban outdoor scenario was examined that included a transmitting antenna mounted on the roof of one of four buildings at a street crossing, (2) For WLAN an indoor scenario was investigated. For GSM the average degree of underestimation by the exposimeter (relation of the average field levels at the location of the exposimeter to the field level averaged over the volume of the human body without the body present) was 0.76, and for UMTS 0.87; for FM no underestimation was found, the ratio was 1. In the case of WLAN the degree of underestimation was more pronounced, the ratio was 0.64. This study clearly suggests that a careful evaluation of correction factors for different scenarios is needed prior to the definition of the study protocol. It has to be noted that the reference scenario used in this study does not allow for final conclusions on general correction factors. Bioelectromagnetics 31:535–545, 2010. © 2010 Wiley‐Liss, Inc.     

Electromagnetic field measurements using personal exposimeters

The goal of this brief communication is to call the attention of researchers to possible pit falls when using personal exposimeters (PEM) in epidemiological field studies. One example of problematic handling of PEMs is presented in detail, whereas other possible error sources and other aspects to be considered using such devices are outlined only briefly.     

Exposure assessment of mobile phone base station radiation in an outdoor environment using sequential surrogate modeling

Human exposure to background radiofrequency electromagnetic fields (RF‐EMF) has been increasing with the introduction of new technologies. There is a definite need for the quantification of RF‐EMF exposure but a robust exposure assessment is not yet possible, mainly due to the lack of a fast and efficient measurement procedure. In this article, a new procedure is proposed for accurately mapping the exposure to base station radiation in an outdoor environment based on surrogate modeling and sequential design, an entirely new approach in the domain of dosimetry for human RF exposure. We tested our procedure in an urban area of about 0.04 km² for Global System for Mobile Communications (GSM) technology at 900 MHz (GSM900) using a personal exposimeter. Fifty measurement locations were sufficient to obtain a coarse street exposure map, locating regions of high and low exposure; 70 measurement locations were sufficient to characterize the electric field distribution in the area and build an accurate predictive interpolation model. Hence, accurate GSM900 downlink outdoor exposure maps (for use in, e.g., governmental risk communication and epidemiological studies) are developed by combining the proven efficiency of sequential design with the speed of exposimeter measurements and their ease of handling. Bioelectromagnetics 34:300–311, 2013. © 2012 Wiley Periodicals, Inc.     

Calibration and uncertainties in personal exposure measurements of radiofrequency electromagnetic fields

In the past 5 years radiofrequency personal exposure meters have been used to characterize the exposure during daily activities. We found from calibration tests for the 12 frequency bands of the EME Spy 121 exposimeter in a Gigahertz Transverse Electromagnetic cell and an Open Area Test Site, that these measurements tend to underestimate the actual exposure. Therefore, a maximum frequency‐dependent correction factor of 1.1–1.6 should be applied to the electric field. This correction factor consists of three multipliers correcting for calibration, elevation arrival angle, and influence of the body. The calibration correction factor should be determined per exposimeter, as the maximum range of response between exposimeters in a frequency band is 2.4 dB. Since the range of response for different elevation angles could reach 10.2 dB, a strict protocol for wearing the exposimeter during fieldwork should be followed to be able to compare and combine measurements made by different persons in the same microenvironments. Because the influence of the body depends on the azimuth angle of arrival, it may lead to an over‐ or underestimation. Thus, the body correction factor is an average over the angles and should only be applied in activities involving movement through the full 360° range of random angles of arrival. Bioelectromagnetics. Bioelectromagnetics 32:652–663, 2011. © 2011 Wiley Periodicals, Inc.     

Between‐country comparison of whole‐body SAR from personal exposure data in Urban areas

In five countries (Belgium, Switzerland, Slovenia, Hungary, and the Netherlands), personal radio frequency electromagnetic field measurements were performed in different microenvironments such as homes, public transports, or outdoors using the same exposure meters. From the mean personal field exposure levels (excluding mobile phone exposure), whole‐body absorption values in a 1‐year‐old child and adult male model were calculated using a statistical multipath exposure method and compared for the five countries. All mean absorptions (maximal total absorption of 3.4 µW/kg for the child and 1.8 µW/kg for the adult) were well below the International Commission on Non‐Ionizing Radiation Protection (ICNIRP) basic restriction of 0.08 W/kg for the general public. Generally, incident field exposure levels were well correlated with whole‐body absorptions (SAR_wb), although the type of microenvironment, frequency of the signals, and dimensions of the considered phantom modify the relationship between these exposure measures. Exposure to the television and Digital Audio Broadcasting band caused relatively higher SAR_wb values (up to 65%) for the 1‐year‐old child than signals at higher frequencies due to the body size‐dependent absorption rates. Frequency Modulation (FM) caused relatively higher absorptions (up to 80%) in the adult male. Bioelectromagnetics 33:682–694, 2012. © 2012 Wiley Periodicals, Inc.     

Statistical analysis of personal radiofrequency electromagnetic field measurements with nondetects

Exposimeters are increasingly applied in bioelectromagnetic research to determine personal radiofrequency electromagnetic field (RF‐EMF) exposure. The main advantages of exposimeter measurements are their convenient handling for study participants and the large amount of personal exposure data, which can be obtained for several RF‐EMF sources. However, the large proportion of measurements below the detection limit is a challenge for data analysis. With the robust ROS (regression on order statistics) method, summary statistics can be calculated by fitting an assumed distribution to the observed data. We used a preliminary sample of 109 weekly exposimeter measurements from the QUALIFEX study to compare summary statistics computed by robust ROS with a naïve approach, where values below the detection limit were replaced by the value of the detection limit. For the total RF‐EMF exposure, differences between the naïve approach and the robust ROS were moderate for the 90th percentile and the arithmetic mean. However, exposure contributions from minor RF‐EMF sources were considerably overestimated with the naïve approach. This results in an underestimation of the exposure range in the population, which may bias the evaluation of potential exposure‐response associations. We conclude from our analyses that summary statistics of exposimeter data calculated by robust ROS are more reliable and more informative than estimates based on a naïve approach. Nevertheless, estimates of source‐specific medians or even lower percentiles depend on the assumed data distribution and should be considered with caution. Bioelectromagnetics. Bioelectromagnetics 29:471–478, 2008. © 2008 Wiley‐Liss, Inc.     

Statistical perturbations in personal exposure meters caused by the human body in dynamic outdoor environments

Personal exposure meters (PEM) are routinely used for the exposure assessment to radio frequency electric or magnetic fields. However, their readings are subject to errors associated with perturbations of the fields caused by the presence of the human body. This paper presents a novel analysis method for the characterization of this effect. Using ray‐tracing techniques, PEM measurements have been emulated, with and without an approximation of this shadowing effect. In particular, the Global System for Mobile Communication mobile phone frequency band was chosen for its ubiquity and, specifically, we considered the case where the subject is walking outdoors in a relatively open area. These simulations have been contrasted with real PEM measurements in a 35‐min walk. Results show a good agreement in terms of root mean square error and E‐field cumulative distribution function (CDF), with a significant improvement when the shadowing effect is taken into account. In particular, the Kolmogorov–Smirnov (KS) test provides a P‐value of 0.05 when considering the shadowing effect, versus a P‐value of 10⁻¹⁴ when this effect is ignored. In addition, although the E‐field levels in the absence of a human body have been found to follow a Nakagami distribution, a lognormal distribution fits the statistics of the PEM values better than the Nakagami distribution. As a conclusion, although the mean could be adjusted by using correction factors, there are also other changes in the CDF that require particular attention due to the shadowing effect because they might lead to a systematic error. Bioelectromagnetics 32:209–217, 2011. © 2010 Wiley‐Liss, Inc.