Impact of Radiofrequency Exposure From Mobile Phones on the Risk of Developing Brain Tumors in Korean and Japanese Adolescents: A MOBI-Kids Case-control Study.

BACKGROUND: This study aimed to examine the association between risk of brain tumors and radiofrequency (RF) exposure from mobile phones among young people in Korea and Japan. METHODS: This case-control study of brain tumors in young people was conducted in Korea and Japan under the framework of the international MOBI-Kids study. We included 118 patients diagnosed with brain tumors between 2011 and 2015 and 236 matched appendicitis controls aged 10-24 years. Information on mobile phone use was collected through face-to-face interviews. A detailed RF exposure algorithm, based on the MOBI-Kids algorithm and modified to account for the specificities of Japanese and Korean phones and networks, was used to calculate the odds ratios (ORs) for total cumulative specific energy using conditional logistic regression. RESULTS: The adjusted ORs in the highest tertile of cumulative call time at 1 year before the reference date were 1.61 (95% confidence interval [CI], 0.72-3.60) for all brain tumors and 0.70 (95% CI, 0.16-3.03) for gliomas, with no indication of a trend with exposure. The ORs for glioma specifically, were below 1 in the lowest exposure category. CONCLUSION: This study provided no evidence of a causal association between mobile phone use and risk of brain tumors as a whole or of glioma specifically. Further research will be required to evaluate the impact of newer technologies of communication in the future.

The association between real-life markers of phone use and cognitive performance, health-related quality of life and sleep.

INTRODUCTION: The real-life short-term implications of electromagnetic fields (RF-EMF) on cognitive performance and health-related quality of life have not been well studied. The SPUTNIC study (Study Panel on Upcoming Technologies to study Non-Ionizing radiation and Cognition) aimed to investigate possible correlations between mobile phone radiation and human health, including cognition, health-related quality of life and sleep. METHODS: Adult participants tracked various daily markers of RF-EMF exposures (cordless calls, mobile calls, and mobile screen time 4 h prior to each assessment) as well as three health outcomes over ten study days: 1) cognitive performance, 2) health-related quality of life (HRQoL), and 3) sleep duration and quality. Cognitive performance was measured through six "game-like" tests, assessing verbal and visuo-spatial performance repeatedly. HRQoL was assessed as fatigue, mood and stress on a Likert-scale (1-10). Sleep duration and efficiency was measured using activity trackers. We fitted mixed models with random intercepts per participant on cognitive, HRQoL and sleep scores. Possible time-varying confounders were assessed at daily intervals by questionnaire and used for model adjustment. RESULTS: A total of 121 participants ultimately took part in the SPUTNIC study, including 63 from Besancon and 58 from Basel. Self-reported wireless phone use and screen time were sporadically associated with visuo-spatial and verbal cognitive performance, compatible with chance findings. We found a small but robust significant increase in stress 0.03 (0.00-0.06; on a 1-10 Likert-scale) in relation to a 10-min increase in mobile phone screen time. Sleep duration and quality were not associated with either cordless or mobile phone calls, or with screen time. DISCUSSION: The study did not find associations between short-term RF-EMF markers and cognitive performance, HRQoL, or sleep duration and quality. The most consistent finding was increased stress in relation to more screen time, but no association with cordless or mobile phone call time.

Statistical Characterization and Modeling of Indoor RF-EMF Down-Link Exposure.

With the increasing use of wireless communication systems, assessment of exposure to radio-frequency electromagnetic field (RF-EMF) has now become very important due to the rise of public risk perception. Since people spend more than 70% of their daily time in indoor environments, including home, office, and car, the efforts devoted to indoor RF-EMF exposure assessment has also increased. However, assessment of indoor exposure to RF-EMF using a deterministic approach is challenging and time consuming task as it is affected by uncertainties due to the complexity of the indoor environment and furniture structure, existence of multiple reflection, refraction, diffraction and scattering, temporal variability of exposure, and existence of many obstructions with unknown dielectric properties. Moreover, it is also affected by the existence of uncontrolled factors that can influence the indoor RF-EMF exposure such as the constant movement of people and random movement of furniture and doors as people are working in the building. In this study, a statistical approach is utilized to characterize and model the total indoor RF-EMF down-link (DL) exposure from all cellular bands on each floor over the length of a wing since the significance of distance is very low between any two points on each floor in a wing and the variation of RF-EMF DL exposure is mainly influenced by the local indoor environment. Measurements were conducted in three buildings that are located within a few hundred meters vicinity of two base station sites supporting several cellular technologies (2G, 3G, 4G, and 5G). We apply the one-sample Kolmogorov-Smirnov test on the measurement data, and we prove that the indoor RF-EMF DL exposure on each floor over the length of a wing is a random process governed by a Gaussian distribution. We validate this proposition using leave-one-out cross validation technique. Consequently, we conclude that the indoor RF-EMF DL exposure on each floor over the length of a wing can be modeled by a Gaussian distribution and, therefore, can be characterized by the mean and the standard deviation parameters.

Modelling of daily radiofrequency electromagnetic field dose for a prospective adolescent cohort.

INTRODUCTION: Radiofrequency electromagnetic fields originate from a variety of wireless communication sources operating near and far from the body, making it challenging to quantify daily absorbed dose. In the framework of the prospective cohort SCAMP (Study of Cognition, Adolescents and Mobile Phones), we aimed to characterize RF-EMF dose over a 2-year period. METHODS: The SCAMP cohort included 6605 children from greater London, UK at baseline (age 12.1 years; 2014-2016) and 5194 at follow-up (age 14.2; 2016-2018). We estimated the daily dose of RF-EMF to eight tissues including the whole body and whole brain, using dosimetric algorithms for the specific absorption rate transfer into the body. We considered RF-EMF dose from 12 common usage scenarios such as mobile phone calls or data transmission. We evaluated the association between sociodemographic factors (gender, ethnicity, phone ownership and socio-economic status), and the dose change between baseline and follow-up. RESULTS: Whole body dose was estimated at an average of 170 mJ/kg/day at baseline and 178 mJ/kg/day at follow-up. Among the eight tissues considered, the right temporal lobe received the highest daily dose (baseline 1150 mJ/kg/day, follow-up 1520 mJ/kg/day). Estimated daily dose [mJ/kg/day] increased between baseline and follow-up for head and brain related tissues, but remained stable for the whole body and heart. Doses estimated at baseline and follow-up showed low correlation among the 3384 children who completed both assessments. Asian ethnicity (compared to white) and owning a bar phone or no phone (as opposed to a smartphone) were associated with lower estimated whole-body and whole-brain RF-EMF dose, while black ethnicity, a moderate/low socio-economic status (compared to high), and increasing age (at baseline) were associated with higher estimated RF-EMF dose. CONCLUSION: This study describes the first longitudinal exposure assessment for children in a critical period of development. Dose estimations will be used in further epidemiological analyses for the SCAMP study.

Towards Outdoor Electromagnetic Field Exposure Mapping Generation Using Conditional GANs.

With the ongoing fifth-generation cellular network (5G) deployment, electromagnetic field exposure has become a critical concern. However, measurements are scarce, and accurate electromagnetic field reconstruction in a geographic region remains challenging. This work proposes a conditional generative adversarial network to address this issue. The main objective is to reconstruct the electromagnetic field exposure map accurately according to the environment's topology from a few sensors located in an outdoor urban environment. The model is trained to learn and estimate the propagation characteristics of the electromagnetic field according to the topology of a given environment. In addition, the conditional generative adversarial network-based electromagnetic field mapping is compared with simple kriging. Results show that the proposed method produces accurate estimates and is a promising solution for exposure map reconstruction.

Estimation of RF and ELF dose by anatomical location in the brain from wireless phones in the MOBI-Kids study.

Wireless phones (both mobile and cordless) emit not only radiofrequency (RF) electromagnetic fields (EMF) but also extremely low frequency (ELF) magnetic fields, both of which should be considered in epidemiological studies of the possible adverse health effects of use of such devices. This paper describes a unique algorithm, developed for the multinational case-control MOBI-Kids study, that estimates the cumulative specific energy (CSE) and the cumulative induced current density (CICD) in the brain from RF and ELF fields, respectively, for each subject in the study (aged 10-24 years old). Factors such as age, tumour location, self-reported phone models and usage patterns (laterality, call frequency/duration and hands-free use) were considered, as was the prevalence of different communication systems over time. Median CSE and CICD were substantially higher in GSM than 3G systems and varied considerably with location in the brain. Agreement between RF CSE and mobile phone use variables was moderate to null, depending on the communication system. Agreement between mobile phone use variables and ELF CICD was higher overall but also strongly dependent on communication system. Despite ELF dose distribution across the brain being more diffuse than that of RF, high correlation was observed between RF and ELF dose. The algorithm was used to systematically estimate the localised RF and ELF doses in the brain from wireless phones, which were found to be strongly dependent on location and communication system. Analysis of cartographies showed high correlation across phone models and across ages, however diagonal agreement between these cartographies suggest these factors do affect dose distribution to some level. Overall, duration and number of calls may not be adequate proxies of dose, particularly as communication systems available for voice calls tend to become more complex with time.

Near-Field Exposure in FM Frequencies: New Methodology and Estimation Formulas.

Workers inside transmission pylons with FM antenna arrays are likely to be exposed to near-field radiation exceeding reference levels for occupational exposure. In this study, the near-field behavior of 64 FM pylons was studied using a new methodology. Near-field characterization was done using field metrics without taking into account field sources' size or distance from field source. The specific absorption rate (SAR) was assessed in five hundred different near-field cases using a human phantom. Estimation formulas for both local and whole-body SAR are provided and validated numerically. Local and whole-body SAR are linked to electric field strength. © 2022 Bioelectromagnetics Society.

Estimated all-day and evening whole-brain radiofrequency electromagnetic fields doses, and sleep in preadolescents.

OBJECTIVE: To investigate the association of estimated all-day and evening whole-brain radiofrequency electromagnetic field (RF-EMF) doses with sleep disturbances and objective sleep measures in preadolescents. METHODS: We included preadolescents aged 9-12 years from two population-based birth cohorts, the Dutch Generation R Study (n = 974) and the Spanish INfancia y Medio Ambiente Project (n = 868). All-day and evening overall whole-brain RF-EMF doses (mJ/kg/day) were estimated for several RF-EMF sources including mobile and Digital Enhanced Cordless Telecommunications (DECT) phone calls (named phone calls), other mobile phone uses, tablet use, laptop use (named screen activities), and far-field sources. We also estimated all-day and evening whole-brain RF-EMF doses in these three groups separately (i.e. phone calls, screen activities, and far-field). The Sleep Disturbance Scale for Children was completed by mothers to assess sleep disturbances. Wrist accelerometers together with sleep diaries were used to measure sleep characteristics objectively for 7 consecutive days. RESULTS: All-day whole-brain RF-EMF doses were not associated with self-reported sleep disturbances and objective sleep measures. Regarding evening doses, preadolescents with high evening whole-brain RF-EMF dose from phone calls had a shorter total sleep time compared to preadolescents with zero evening whole-brain RF-EMF dose from phone calls [-11.9 min (95%CI -21.2; -2.5)]. CONCLUSIONS: Our findings suggest the evening as a potentially relevant window of RF-EMF exposure for sleep. However, we cannot exclude that observed associations are due to the activities or reasons motivating the phone calls rather than the RF-EMF exposure itself or due to chance finding.

Artificial Neural Network-Based Uplink Power Prediction From Multi-Floor Indoor Measurement Campaigns in 4G Networks.

Paving the path toward the fifth generation (5G) of wireless networks with a huge increase in the number of user equipment has strengthened public concerns on human exposure to radio-frequency electromagnetic fields (RF EMFs). This requires an assessment and monitoring of RF EMF exposure, in an almost continuous way. Particular interest goes to the uplink (UL) exposure, assessed through the transmission power of the mobile phone, due to its close proximity to the human body. However, the UL transmit (TX) power is not provided by the off-the-shelf modem and RF devices. In this context, we first conduct measurement campaigns in a multi-floor indoor environment using a drive test solution to record both downlink (DL) and UL connection parameters for Long Term Evolution (LTE) networks. Several usage services (including WhatsApp voice calls, WhatsApp video calls, and file uploading) are investigated in the measurement campaigns. Then, we propose an artificial neural network (ANN) model to estimate the UL TX power, by exploiting easily available parameters such as the DL connection indicators and the information related to an indoor environment. With those easy-accessed input features, the proposed ANN model is able to obtain an accurate estimation of UL TX power with a mean absolute error (MAE) of 1.487 dB.

Radio-frequency electromagnetic field exposure and contribution of sources in the general population: an organ-specific integrative exposure assessment.

In order to achieve an integrated radio-frequency electromagnetic fields (RF-EMF) dose assessment, detailed information about source-specific exposure duration and output power is needed. We developed an Integrated Exposure Model (IEM) to combine energy absorbed due to use of and exposure to RF-EMF sources and applied it to a sample of the general population to derive population RF-EMF estimates. The IEM used specific absorption rate transfer algorithms to provide RF-EMF daily dose estimates (mJ/kg/day) using source-specific attributes (e.g. output power, distance), personal characteristics and usage patterns. Information was obtained from an international survey performed in four European countries with 1755 participants. We obtained median whole-body and whole-brain doses of 183.7 and 204.4 mJ/kg/day. Main contributors to whole-brain dose were mobile phone near the head for calling (2G networks) and far-field sources, whereas the latter together with multiple other RF-EMF sources were main contributors for whole-body dose. For other anatomical sites, 2G phone calls, mobile data and far-field exposure were important contributors. The IEM provides insight into main contributors to total RF-EMF dose and, applied to an international survey, provides an estimate of population RF-dose. The IEM can be used in future epidemiological studies, risk assessments and exposure reduction strategies.

Radiofrequency electromagnetic fields from mobile communication: Description of modeled dose in brain regions and the body in European children and adolescents.

BACKGROUND: Little is known about radiofrequency electromagnetic fields (RF) from mobile technology and resulting dose in young people. We describe modeled integrated RF dose in European children and adolescents combining own mobile device use and surrounding sources. METHODS: Using an integrated RF model, we estimated the daily RF dose in the brain (whole-brain, cerebellum, frontal lobe, midbrain, occipital lobe, parietal lobe, temporal lobes) and the whole-body in 8358 children (ages 8-12) and adolescents (ages 14-18) from the Netherlands, Spain, and Switzerland during 2012-2016. The integrated model estimated RF dose from near-field sources (digital enhanced communication technology (DECT) phone, mobile phone, tablet, and laptop) and far-field sources (mobile phone base stations via 3D-radiowave modeling or RF measurements). RESULTS: Adolescents were more frequent mobile phone users and experienced higher modeled RF doses in the whole-brain (median 330.4 mJ/kg/day) compared to children (median 81.8 mJ/kg/day). Children spent more time using tablets or laptops compared to adolescents, resulting in higher RF doses in the whole-body (median whole-body dose of 81.8 mJ/kg/day) compared to adolescents (41.9 mJ/kg/day). Among brain regions, temporal lobes received the highest RF dose (medians of 274.9 and 1786.5 mJ/kg/day in children and adolescents, respectively) followed by the frontal lobe. In most children and adolescents, calling on 2G networks was the main contributor to RF dose in the whole-brain (medians of 31.1 and 273.7 mJ/kg/day, respectively). CONCLUSION: This first large study of RF dose to the brain and body of children and adolescents shows that mobile phone calls on 2G networks are the main determinants of brain dose, especially in temporal and frontal lobes, whereas whole-body doses were mostly determined by tablet and laptop use. The modeling of RF doses provides valuable input to epidemiological research and to potential risk management regarding RF exposure in young people.

Association between estimated whole-brain radiofrequency electromagnetic fields dose and cognitive function in preadolescents and adolescents.

OBJECTIVE: To investigate the association between estimated whole-brain radiofrequency electromagnetic fields (RF-EMF) dose, using an improved integrated RF-EMF exposure model, and cognitive function in preadolescents and adolescents. METHODS: Cross-sectional analysis in preadolescents aged 9-11 years and adolescents aged 17-18 years from the Dutch Amsterdam Born Children and their Development Study (n = 1664 preadolescents) and the Spanish INfancia y Medio Ambiente Project (n = 1288 preadolescents and n = 261 adolescents), two population-based birth cohort studies. Overall whole-brain RF-EMF doses (mJ/kg/day) were estimated for several RF-EMF sources together including mobile and Digital Enhanced Cordless Telecommunications phone calls (named phone calls), other mobile phone uses than calling, tablet use, laptop use (named screen activities), and far-field sources. We also estimated whole-brain RF-EMF doses in these three groups separately (i.e. phone calls, screen activities, and far-field) that lead to different patterns of RF-EMF exposure. We assessed non-verbal intelligence in the Dutch and Spanish preadolescents, information processing speed, attentional function, and cognitive flexibility in the Spanish preadolescents, and working memory and semantic fluency in the Spanish preadolescents and adolescents using validated neurocognitive tests. RESULTS: Estimated overall whole-brain RF-EMF dose was 90.1 mJ/kg/day (interquartile range (IQR) 42.7; 164.0) in the Dutch and Spanish preadolescents and 105.1 mJ/kg/day (IQR 51.0; 295.7) in the Spanish adolescents. Higher overall estimated whole-brain RF-EMF doses from all RF-EMF sources together and from phone calls were associated with lower non-verbal intelligence score in the Dutch and Spanish preadolescents (-0.10 points, 95% CI -0.19; -0.02 per 100 mJ/kg/day increase in each exposure). However, none of the whole-brain RF-EMF doses was related to any other cognitive function outcome in the Spanish preadolescents or adolescents. CONCLUSIONS: Our results suggest that higher brain exposure to RF-EMF is related to lower non-verbal intelligence but not to other cognitive function outcomes. Given the cross-sectional nature of the study, the small effect sizes, and the unknown biological mechanisms, we cannot discard that our resultsare due to chance finding or reverse causality. Longitudinal studies on RF-EMF brain exposure and cognitive function are needed.

EVALUATION OF SPECIFIC ABSORPTION RATE IN THE FAR-FIELD, NEAR-TO-FAR FIELD AND NEAR-FIELD REGIONS FOR INTEGRATIVE RADIOFREQUENCY EXPOSURE ASSESSMENT.

The specific absorption rate (SAR) induced by wireless radiofrequency (RF) systems depends on different parameters. Previously, SAR was mainly assessed under conditions of a single frequency and technology and for a limited number of localized RF sources. The current and emerging mobile systems involve a wider range of usage scenarios and are frequently used simultaneously, leading to combined exposures for which almost no exposure evaluation exists. The aim and novelty of this study is to close this gap of knowledge by developing new methods to rapidly evaluate the SAR induced by RF systems in such scenarios at frequencies from 50 MHz to 5.5 GHz. To this aim, analytical methods for SAR estimation in several usage scenarios were derived through a large-scale numerical study. These include subject-specific characteristics, properties of the RF systems and provide an estimation of the SAR in the whole body, tissues and organs, and different brain regions.

Design of an Integrated Platform for Mapping Residential Exposure to Rf-Emf Sources.

Nowadays, information and communication technologies (mobile phones, connected objects) strongly occupy our daily life. The increasing use of these technologies and the complexity of network infrastructures raise issues about radiofrequency electromagnetic fields (Rf-Emf) exposure. Most previous studies have assessed individual exposure to Rf-Emf, and the next level is to assess populational exposure. In our study, we designed a statistical tool for Rf-Emf populational exposure assessment and mapping. This tool integrates geographic databases and surrogate models to characterize spatiotemporal exposure from outdoor sources, indoor sources, and mobile phones. A case study was conducted on a 100 × 100 m grid covering the 14th district of Paris to illustrate the functionalities of the tool. Whole-body specific absorption rate (SAR) values are 2.7 times higher than those for the whole brain. The mapping of whole-body and whole-brain SAR values shows a dichotomy between built-up and non-built-up areas, with the former displaying higher values. Maximum SAR values do not exceed 3.5 and 3.9 mW/kg for the whole body and the whole brain, respectively, thus they are significantly below International Commission on Non-Ionizing Radiation Protection (ICNIRP) recommendations. Indoor sources are the main contributor to populational exposure, followed by outdoor sources and mobile phones, which generally represents less than 1% of total exposure.

Reply to "Comment on Liu et al. 'Discrepancies of Measured SAR between Traditional and Fast Measuring Systems' Int. J. Environ. Res. Public Health, 2020, 17, 2111".

The authors of this reply published an article in International Journal of Environmental Research and Public Health and received comments from Douglas and Kuster. Responses are made to these comments with complementary explanations and numerical results.

Estimated whole-brain and lobe-specific radiofrequency electromagnetic fields doses and brain volumes in preadolescents.

OBJECTIVE: To assess the association between estimated whole-brain and lobe-specific radiofrequency electromagnetic fields (RF-EMF) doses, using an improved integrated RF-EMF exposure model, and brain volumes in preadolescents at 9-12 years old. METHODS: Cross-sectional analysis in preadolescents aged 9-12 years from the Generation R Study, a population-based birth cohort set up in Rotterdam, The Netherlands (n = 2592). An integrated exposure model was used to estimate whole-brain and lobe-specific RF-EMF doses (mJ/kg/day) from different RF-EMF sources including mobile and Digital Enhanced Cordless Telecommunications (DECT) phone calls, other mobile phone uses than calling, tablet use, laptop use, and far-field sources. Whole-brain and lobe-specific RF-EMF doses were estimated for all RF-EMF sources together (i.e. overall) and for three groups of RF-EMF sources that lead to a different pattern of RF-EMF exposure. Information on brain volumes was extracted from magnetic resonance imaging scans. RESULTS: Estimated overall whole-brain RF-EMF dose was 84.3 mJ/kg/day. The highest overall lobe-specific dose was estimated in the temporal lobe (307.1 mJ/kg/day). Whole-brain and lobe-specific RF-EMF doses from all RF-EMF sources together, from mobile and DECT phone calls, and from far-field sources were not associated with global, cortical, or subcortical brain volumes. However, a higher whole-brain RF-EMF dose from mobile phone use for internet browsing, e-mailing, and text messaging, tablet use, and laptop use while wirelessly connected to the internet was associated with a smaller caudate volume. CONCLUSIONS: Our results suggest that estimated whole-brain and lobe-specific RF-EMF doses were not related to brain volumes in preadolescents at 9-12 years old. Screen activities with mobile communication devices while wirelessly connected to the internet lead to low RF-EMF dose to the brain and our observed association may thus rather reflect effects of social or individual factors related to these specific uses of mobile communication devices. However, we cannot discard residual confounding, chance finding, or reverse causality. Further studies on mobile communication devices and their potential negative associations with brain development are warranted, regardless whether associations are due to RF-EMF exposure or to other factors related to their use.

Sensor-Aided EMF Exposure Assessments in an Urban Environment Using Artificial Neural Networks.

This paper studies the time and space mapping of the electromagnetic field (EMF) exposure induced by cellular base station antennas (BSA) using artificial neural networks (ANN). The reconstructed EMF exposure map (EEM) in urban environment is obtained by using data from EMF sensor networks, drive testing and information accessible in a public database, e.g., locations and orientations of BSA. The performance of EEM is compared with Exposure Reference Map (ERM) based on simulations, in which parametric path loss models are used to reflect the complexity of urban cities. Then, a new hybrid ANN, which has the advantage of sorting and utilizing inputs from simulations efficiently, is proposed. Using both hybrid ANN and conventional regression ANN, the EEM is reconstructed and compared to the ERM first by the reconstruction approach considering only EMF exposure assessed from sensor networks, where the required number of sensors towards good reconstruction is explored; then, a new reconstruction approach using the sensors information combined with EMF along few streets from drive testing. Both reconstruction approaches use simulations to mimic measurements. The influence of city architecture on EMF exposure reconstruction is analyzed and the addition of noise is considered to test the robustness of ANN as well.

A Surrogate Model Based on Artificial Neural Network for RF Radiation Modelling with High-Dimensional Data.

This paper focuses on quantifying the uncertainty in the specific absorption rate valuesof the brain induced by the uncertain positions of the electroencephalography electrodes placed onthe patient's scalp. To avoid running a large number of simulations, an artificial neural networkarchitecture for uncertainty quantification involving high-dimensional data is proposed in this paper.The proposed method is demonstrated to be an attractive alternative to conventional uncertaintyquantification methods because of its considerable advantage in the computational expense andspeed.

Discrepancies of Measured SAR between Traditional and Fast Measuring Systems.

Human exposure to mobile devices is traditionally measured by a system in which the human body (or head) is modelled by a phantom and the energy absorbed from the device is estimated based on the electric fields measured with a single probe. Such a system suffers from low efficiency due to repeated volumetric scanning within the phantom needed to capture the absorbed energy throughout the volume. To speed up the measurement, fast SAR (specific absorption rate) measuring systems have been developed. However, discrepancies of measured results are observed between traditional and fast measuring systems. In this paper, the discrepancies in terms of post-processing procedures after the measurement of electric field (or its amplitude) are investigated. Here, the concerned fast measuring system estimates SAR based on the reconstructed field of the region of interest while the amplitude and phase of the electric field are measured on a single plane with a probe array. The numerical results presented indicate that the fast SAR measuring system has the potential to yield more accurate estimations than the traditional system, but no conclusion can be made on which kind of system is superior without knowledge of the field-reconstruction algorithms and the emitting source.

Radio Frequency Electromagnetic Fields Exposure Assessment in Indoor Environments: A Review.

Exposure to radiofrequency (RF) electromagnetic fields (EMFs) in indoor environments depends on both outdoor sources such as radio, television and mobile phone antennas and indoor sources, such as mobile phones and wireless communications applications. Establishing the levels of exposure could be challenging due to differences in the approaches used in different studies. The goal of this study is to present an overview of the last ten years research efforts about RF EMF exposure in indoor environments, considering different RF-EMF sources found to cause exposure in indoor environments, different indoor environments and different approaches used to assess the exposure. The highest maximum mean levels of the exposure considering the whole RF-EMF frequency band was found in offices (1.14 V/m) and in public transports (0.97 V/m), while the lowest levels of exposure were observed in homes and apartments, with mean values in the range 0.13⁻0.43 V/m. The contribution of different RF-EMF sources to the total level of exposure was found to show slightly different patterns among the indoor environments, but this finding has to be considered as a time-dependent picture of the continuous evolving exposure to RF-EMF.