A Multi-Band Body-Worn Distributed Radio-Frequency Exposure Meter: Design, On-Body Calibration and Study of Body Morphology

A comprehensive review of 5G NR RF-EMF exposure assessment technologies: fundamentals, advancements, challenges, niches, and implications

This review offers a detailed examination of the current landscape of radio frequency (RF) electromagnetic field (EMF) assessment tools, ranging from spectrum analyzers and broadband field meters to area monitors and custom-built devices. The discussion encompasses both standardized and non-standardized measurement protocols, shedding light on the various methods employed in this domain. Furthermore, the review highlights the prevalent use of mobile apps for characterizing 5G NR radio network data. A growing need for low-cost measurement devices is observed, commonly referred to as "sensors" or "sensor nodes", that are capable of enduring diverse environmental conditions. These sensors play a crucial role in both microenvironmental surveys and individual exposures, enabling stationary, mobile, and personal exposure assessments based on body-worn sensors, across wider geographical areas. This review revealed a notable need for cost-effective and long-lasting sensors, whether for individual exposure assessments, mobile (vehicle-integrated) measurements, or incorporation into distributed sensor networks. However, there is a lack of comprehensive information on existing custom-developed RF-EMF measurement tools, especially in terms of measuring uncertainty. Additionally, there is a need for real-time, fast-sampling solutions to understand the highly irregular temporal variations EMF distribution in next-generation networks. Given the diversity of tools and methods, a comprehensive comparison is crucial to determine the necessary statistical tools for aggregating the available measurement data.

Instruments to measure environmental and personal radiofrequency-electromagnetic field exposures: an update

Modern human populations are exposed to anthropogenic sources of radiofrequency-electromagnetic fields (RF-EMFs), primarily to telecommunication and broadcasting technologies. As a result, ongoing concerns from some members of the public have arisen regarding potential health effects following RF-EMF exposures. In order to monitor human RF-EMF exposures and investigate potential health effects, an objective assessment of RF-EMF exposures is necessary. Accurate dosimetry is essential for any investigation of potential associations between RF-EMF exposure and health effects in human populations. This review updates state-of-the-art knowledge of currently available RF-EMF exposure assessment tools applicable in human epidemiological studies. These tools cater for assessing RF-EMF exposures in human environments; through mobile phone-based tools or other standalone tools. RF-EMF exposure assessment has been significantly improved through the application of some of these tools in recent years.

Lessons Learned from a Distributed RF-EMF Sensor Network

In an increasingly wireless world, spatiotemporal monitoring of the exposure to environmental radiofrequency (RF) electromagnetic fields (EMF) is crucial to appease public uncertainty and anxiety about RF-EMF. However, although the advent of smart city infrastructures allows for dense networks of distributed sensors, the costs of accurate RF sensors remain high, and dedicated RF monitoring networks remain rare. This paper describes a comprehensive study comprising the design of a low-cost RF-EMF sensor node capable of monitoring four frequency bands used by wireless telecommunications with an unparalleled temporal resolution, its application in a small-scale distributed sensor network consisting of both fixed (on building façades) and mobile sensor nodes (on postal vans), and the subsequent analysis of over a year of data between January 2019 and May 2020, during which slightly less than 10 million samples were collected. From the fixed nodes’ results, the potential errors were determined that are induced when sampling at lower speeds (e.g., one sample per 15 min) and measuring for shorter periods of time (e.g., a few weeks), as well as an adequate resolution (30 min) for diurnal and weekly temporal profiles which sufficiently preserves short-term variations. Furthermore, based on the correlation between the sensors, an adequate density of 100 sensor nodes per km² was deduced for future networks. Finally, the mobile sensor nodes were used to identify potential RF-EMF exposure hotspots in a previously unattainable area of more than 60 km². In summary, through the analysis of a small number of RF-EMF sensor nodes (both fixed and mobile) in an urban area, this study offers invaluable insights applicable to future designs and deployments of distributed RF-EMF sensor networks.

Exposure to radiofrequency electromagnetic fields: Comparison of exposimeters with a novel body-worn distributed meter

BACKGROUND

Exposure to radiofrequency electromagnetic fields (RF-EMF) is often measured with personal exposimeters, but the accuracy of measurements can be hampered as carrying the devices on-body may result in body shielding. Further, the compact design may compromise the frequency selectivity of the sensor. The aim of this study was to compare measurements obtained using a multi-band body-worn distributed-exposimeter (BWDM) with two commercially available personal exposimeters (ExpoM-RF and EmeSpy 200) under real-life conditions.

METHODS

The BWDM measured power density in 10 frequency bands (800, 900, 1800, 2100, 2600 MHz, DECT 1900 MHz, WiFi 2.4 GHz; with separate uplink/downlink bands for 900, 1800 and 2100 MHz); using 20 separate antennas integrated in a vest and placed on diametrically opposite locations on the body, to minimize body-shielding. RF-EMF exposure data were collected from several microenvironments (e.g. shopping areas, train stations, outdoor rural/ urban residential environments, etc.) by walking around pre-defined areas/routes in Belgium, Spain, France, the Netherlands and Switzerland. Measurements were taken every 1-4 s with the BWDM in parallel with an ExpoM-RF and an EmeSpy 200 exposimeter. We calculated medians and interquartile ranges (IQRs) and compared difference, ratios and correlations of geometric mean RF-EMF exposure levels per microenvironment as measured with the exposimeters and the BWDM.

RESULTS

Across 267 microenvironments, medians and IQR of total BWDM measured RF-EMF exposure was 0.13 (0.05-0.33) mW/m². Difference: IQR of exposimeters minus BWDM exposure levels was -0.011 (-0.049 to 0.0095) mW/m² for the ExpoM-RF and -0.056 (-0.14 to -0.017) for the EmeSpy 200; ratios (exposimeter/BWDM) of total exposure had an IQR of 0.79 (0.55-1.1) for the ExpoM-RF and 0.29 (0.22-0.38) for the EmeSpy 200. Spearman correlations were 0.93 for the ExpoM-RF vs the BWDM and 0.96 for the EmeSpy 200 vs the BWDM.

DISCUSSION AND CONCLUSIONS

Results indicate that exposimeters worn on-body provide somewhat lower total RF-EMF exposure as compared to measurements conducted with the BWDM, in line with effects from body shielding. Ranking of exposure levels of microenvironments showed high correspondence between the different device types. Our results are informative for the interpretation of existing epidemiological research results.

Comparison of statistic methods for censored personal exposure to RF-EMF data

Several studies have characterized personal exposure to RF-EMF, which allows possible effects on health to be studied. All equipment has a detection limit, below which we obtain nondetects or censored data. This problem is a challenge for researchers as it makes the analysis of such data complex. We suggest reconsidering the statistical protocols of the nondetects analysis by comparing four different methods. Three of them substitute censored data using different approaches: regression on order of statistics (ROS) to simulate data below the detection limit (Method 1), substituting nondetect values by the detection limit divided by 2 (Method 2), a naïve calculation (Method 3) using the detection limit as a valid measurement. The fourth method consists of considering censored data to be missing values (Method 4). This article examines how these methods affect the quantification of personal exposure. We considered data from 14 frequency bands from FM to WiMax measured in Albacete (Spain) for 76 days every 10 s by a personal exposimeter (PEM) Satimo EME Spy 140.Methods 3 and 2 gave similar mean and median values to Method 1, but both underestimated the mean values when high nondetects records occurred, which conditioned the physical description of the real situation. The mean values calculated by Method 4 differed from those obtained by Method 1 but were similar when the percentage of nondetects was below 20%.Our comparison suggests that nondetects can be neglected when the percentage of censored data is low to provide a more realistic physical situation.

Public exposure to radiofrequency electromagnetic fields in everyday microenvironments: An updated systematic review for Europe

Communication technologies are rapidly changing and this may affect public exposure to radiofrequency electromagnetic fields (RF-EMF). This systematic review of literature aims to update a previous review on public everyday RF-EMF exposure in Europe, which covered publications until 2015. From 144 eligible records identified by means of a systematic search in PubMed, Embase and Web of Knowledge databases, published between May 2015 and 1 July 2018, 26 records met the inclusion criteria. We extracted quantitative data on public exposure in different indoors, outdoors and transport environments. The data was descriptively analyzed with respect to the exposure patterns between different types of environments. Mean RF-EMF exposure in homes, schools and offices were between 0.04 and 0.76 V/m. Mean outdoor exposure values ranged from 0.07 to 1.27 V/m with downlink signals from mobile phone base stations being the most relevant contributor. RF-EMF levels tended to increase with increasing urbanity. Levels in public transport (bus, train and tram) and cars were between 0.14 and 0.69 V/m. The highest levels, up to 1.97 V/m, were measured in public transport stations with downlink as the most relevant contributor. In line with previous studies, RF-EMF exposure levels were highest in the transportation systems followed by outdoor and private indoor environments. This review does not indicate a noticeable increase in everyday RF-EMF exposure since 2012 despite increasing use of wireless communication devices.

Characterisation of spatial and temporal variability of RF-EMF exposure levels in urban environments in Flanders, Belgium

Personal exposure to Radio-Frequency Electromagnetic Fields (RF-EMFs) was studied using personal measurements in five different microenvironments in each of five cities (Brussels, Antwerp, Ghent, Bruges and Hasselt) in Flanders, Belgium. These measurements were carried out by two researchers using on-body calibrated personal exposimeters. In three out of the five studied cities (Brussels, Ghent and Bruges), temporal aspects of personal exposure to RF-EMFs were studied as well. Measurements during and outside of rush hours (7:00-9:15 and 16:30-19:00) were compared. Likewise, measurements were executed during night time and compared to the ones measured during working hours. Representativeness and repeatability of the measurement method was studied as well. The highest mean total exposure was found in Brussels (2.63 mW/m²), the most densely populated city in this study. However, we measured higher downlink exposure in Antwerp than in Brussels, which might be an effect of the stronger legislation on base stations in Brussels. The measurements and used protocol were found to be both repeatable over time (r = 0.95 for median total exposure) and representative for the studied microenvironments in terms of path selection (r = 0.88 for median total exposure). Finally, in 10 out of the 13 on-body calibrated frequency bands we found that the measurement devices underestimate the intensity of the incident RF-EMFs with median underestimations up to 68%.

Radiofrequency Electromagnetic Radiation and Memory Performance: Sources of Uncertainty in Epidemiological Cohort Studies

Uncertainty in experimental studies of exposure to radiation from mobile phones has in the past only been framed within the context of statistical variability. It is now becoming more apparent to researchers that epistemic or reducible uncertainties can also affect the total error in results. These uncertainties are derived from a wide range of sources including human error, such as data transcription, model structure, measurement and linguistic errors in communication. The issue of epistemic uncertainty is reviewed and interpreted in the context of the MoRPhEUS, ExPOSURE and HERMES cohort studies which investigate the effect of radiofrequency electromagnetic radiation from mobile phones on memory performance. Research into this field has found inconsistent results due to limitations from a range of epistemic sources. Potential analytic approaches are suggested based on quantification of epistemic error using Monte Carlo simulation. It is recommended that future studies investigating the relationship between radiofrequency electromagnetic radiation and memory performance pay more attention to treatment of epistemic uncertainties as well as further research into improving exposure assessment. Use of directed acyclic graphs is also encouraged to display the assumed covariate relationship.