Radiofrequency Electromagnetic Fields Measurements Research Articles

Comprehensive Analysis of Magnetic Flux Density and RF-EMF Exposure in Electric Buses: A Case Study from Samsun, Turkey.

This study investigates magnetic flux density (B) and radiofrequency electromagnetic field (RF-EMF) measurements on electric buses operating in Samsun, Turkey, focusing on two bus routes (called E1 and E4) during the morning and evening hours. Measurements were taken under diverse operational conditions, including acceleration, cruising, and braking, at locations of peak passenger density. Along the E1 route, the magnetic field intensity varied significantly based on the bus position, road slope, and passenger load, with notable increases during braking. In contrast, the E4 route showed a lower magnetic field intensity and RF-EMF values due to its straighter trajectory and reduced operational stops. The highest RF-EMF measurement recorded was 6.01 V/m, which is below the maximum levels established by the ICNIRP guidelines. In 11 out of the 12 different band-selective RF-EMF measurements, the highest contribution came from the downlink band of the base stations, while in only one measurement, the highest contribution originated from the uplink bands of the base stations. All data were subject to the Anderson-Darling test, confirming the generalized extreme value distribution as the best fit for both B and RF-EMF measurements. Additionally, the study assessed B levels inside and outside the bus during charging, revealing heightened readings near the pantograph. These findings significantly contribute to our understanding of electromagnetic field exposure in electric bus environments, highlighting potential health implications and informing the development of targeted mitigation strategies.

Prospective cohort study on non-specific symptoms, cognitive, behavioral, sleep and mental health in relation to electronic media use and transportation noise among adolescents (HERMES): study protocol

Electronic media (eMedia) devices along with exposure to transportation noise are integral to the daily routines of adolescents. The concerns associated with excessive eMedia usage extend beyond sleep deprivation to include the heightened exposure to radiofrequency electromagnetic fields (RF-EMF) emitted by these wireless devices. The aim of HERMES (Health Effects Related to Mobile PhonE Use in AdolescentS) study is to better understand biophysical and psychological pathways in relation to eMedia, RF-EMF exposure use and transportation noise that may effect on cognitive, behavioral, sleep and mental health, as well as non-specific symptoms. Following two previous HERMES cohorts conducted between 2012 and 2015 we have initiated the third wave of HERMES study as a prospective cohort with intermediate (every four months) and one year follows-up. Eligible participants are adolescents attending 7th or 8th school grades in Northwest and Central Switzerland. Baseline examinations are a questionnaire on eMedia usage and selected health outcomes, as well as computerized cognitive tests. In addition, parents/guardians are asked to fill in a questionnaire about their child’s health and potential eMedia use determinants. Far-field RF-EMF exposure and transportation noise at the place of residence and school are predicted based on a propagation model. Cumulative RF-EMF brain dose is calculated based on self-reported eMedia use, mobile phone operator data, and RF-EMF modelling. A follow-up visit is conducted one year later, and two interim questionnaires are sent to adolescents to be completed at home. Between baseline and 1-year follow-up, a subsample of 150 study participants is invited to collect personal RF-EMF measurements as well as sleep and physical activity data using accelerometers. This new recruitment wave of HERMES study provides a greater understanding of causal pathways between eMedia, RF EMF, and transportation noise exposure and their effects on health outcomes, with relevant implications for both governmental health policy and lay people alike.

Artificial Neural Network Based Prediction of Long-Term Electric Field Strength Level Emitted by 2G/3G/4G Base Station

Accurate predictions of radio frequency electromagnetic field (RF-EMF) levels can help implement measures to reduce exposure and check regulatory compliance. Therefore, this study aims to predict the RF-EMF levels in the medium using an artificial neural network (ANN). The work was conducted at Ondokuz Mayis University, Kurupelit Campus, where the measurement location has line-of-sight to the base stations. Band selective measurements were also performed to assess the contribution of 2G/3G/4G services to the total RF-EMF level, which was found to be the highest among all services within the total band. Long-term RF-EMF measurements were carried out for 35 days within the frequencies of 100 kHz to 3 GHz. Then, an ANN model with Levenberg–Marquardt (LM) and Bayesian Regulation (BR) algorithms was proposed, which utilized inputs from real-time RF-EMF measurements. The performance of the models was assessed in terms of mean squared error (MSE) and regression performance. The average MSE and regression performances of the models were similar, with the lowest testing MSEs of 2.78 × 10−3 and 3.76 × 10−3 for LM and BR methods, respectively. The analysis of the models showed that the proposed models help to predict the RF-EMF level in the medium with up to 99% accuracy.

Personal exposure to radiofrequency electromagnetic fields in various occupations in Spain and France

BackgroundA preliminary job-exposure matrix (JEM) for radiofrequency electromagnetic fields (RF-EMF) was created based on self-reported occupational information from a multi-country population-based study of approximately 10,000 participants combined with available measurement data compiled in a source-exposure matrix (spot measurements). In order to address the limited personal occupational RF-EMF measurement data available in the literature, we performed a measurement campaign among workers in various occupations in Spain and France. MethodsPersonal full-shift measurements were conducted using RadMan 2XT™ (Narda) devices. A worker diary was used to capture information on occupational and background sources of RF exposure during the shift. Inclusion of occupations to be measured was initially based on exposure prevalence and level information in the preliminary JEM and expert judgment. ResultsPersonal full-shift measurements were conducted among 333 workers representing 46 ISCO88 occupations. Exposure to electric (E) and magnetic (H) fields was infrequent with >99% of measurements below the detection limit of the device (≥1% of the 1998 ICNIRP standards). A total of 50.2% and 77.2% of workers were ever exposed to E and H fields respectively (having at least one recorded 1-second measurement above the detection limit). Workers in elementary occupations, technicians and associate professionals, plant and machine operators and assemblers had somewhat greater numbers of measurements above the detection limit, higher maximum values and longer exposure durations. A small proportion of measurements were ≥100% of the standards, though these exceedances were brief (generally a few seconds in duration). Female workers and workers reporting use of any RF-EMF emitting source were more likely to have a measured exposure to E and H fields. ConclusionWe conducted personal RF-EMF measurements among workers in various occupations in Spain and France. Overall, RF-EMF exposure ≥1 % ICNIRP was infrequent, despite some intermittent exposures ≥100% observed among workers in some occupations.

Personal exposure to radiofrequency electromagnetic fields in various occupations in Spain

Background: A Job-Exposure Matrix (JEM) for radiofrequency electromagnetic fields (RF-EMF) was previously created based on measurements collected from the literature and individualized EMF source-based information. In the context of an international study aimed at enhancing this preliminary JEM, personal measurements of occupational exposure to RF-EMF were conducted among various occupations in Spain. Methods: Identification and prioritization of occupations to be measured were based on the levels and prevalence of exposure to RF fields in the preliminary RF-JEM and expert judgements. A screening questionnaire developed within our project was used to identify potential participants, based on job titles, tasks, and reported sources of RF exposure. Personal full-shift measurements were conducted using 10 Narda RadMan 2XT personal measurement devices. Results: Personal full-shift measurements were collected for 285 workers of various occupations in Spain. Exposures to electric (E) and magnetic (H) fields were low (99.74% of (E-fields) measurements <1% ICNIRP standards). Results exceeded the ICNIRP limits for only 3% of the workers, though these exceedances lasted a few seconds. Overall, almost 50% of workers had values above 1% of the ICNIRP standards (exposure duration between 1 second and 27.13 minutes). Electric and magnetic fields peaks exceeding 100% of the standards were observed among 8% of the physiotherapists (N=59) and 7% of the nursing auxiliaries (N=28), with exposure durations ranging from 1 to 13 seconds (E-fields) and 2 to 36 seconds (H-fields) of exposure above the limits, respectively. Conclusion: We performed the first phase of data collection of personal RF-EMF measurements among various occupations in Spain in the framework of an international study. The initial results in Spain showed low prevalence and low overall levels of exposure to RF fields, despite some short-term peaks. Additional measurements will be conducted in France and the Netherlands. Keywords: Radiofrequency electromagnetic fields, occupational exposure assessment, job-exposure-matrix

Personal radiofrequency electromagnetic field exposure of adolescents in the Greater London area in the SCAMP cohort and the association with restrictions on permitted use of mobile communication technologies at school and at home

Personal measurements of radiofrequency electromagnetic fields (RF-EMF) have been used in several studies to characterise personal exposure in daily life, but such data are limitedly available for adolescents, and not yet for the United Kingdom (UK). In this study, we aimed to characterise personal exposure to RF-EMF in adolescents and to study the association between exposure and rules applied at school and at home to restrict wireless communication use, likely implemented to reduce other effects of mobile technology (e.g. distraction).We measured exposure to RF-EMF for 16 common frequency bands (87.5 MHz–3.5 GHz), using portable measurement devices (ExpoM-RF), in a subsample of adolescents participating in the cohort Study of Cognition, Adolescents and Mobile Phones (SCAMP) from Greater London (UK) (n = 188). School and home rules were assessed by questionnaire and concerned the school's availability of WiFi and mobile phone policy, and parental restrictions on permitted mobile phone use. Adolescents recorded their activities in real time using a diary app on a study smartphone, while characterizing their personal RF-EMF exposure in daily life, during different activities and times of the day.Data analysis was done for 148 adolescents from 29 schools who recorded RF-EMF data for a median duration of 47 h. The majority (74%) of adolescents spent part of their time at school during the measurement period. Median total RF-EMF exposure was 40 μW/m2 at home, 94 μW/m2 at school, and 100 μW/m2 overall. In general, restrictions at school or at home made little difference for adolescents’ measured exposure to RF-EMF, except for uplink exposure from mobile phones while at school, which was found to be significantly lower for adolescents attending schools not permitting phone use at all, compared to adolescents attending schools allowing mobile phone use during breaks. This difference was not statistically significant for total personal exposure.Total exposure to RF-EMF in adolescents living in Greater London tended to be higher compared to exposure levels reported in other European countries. This study suggests that school policies and parental restrictions are not associated with a lower RF-EMF exposure in adolescents.

Measurements of radiofrequency electromagnetic fields, including 5G, in the city of Columbia, SC, USA

The present study aimed to characterize the wireless infrastructure and public exposure to radiofrequency (RF) electromagnetic fields, including the sub‑millimeter wave 5G, in the city center of Columbia, SC, USA. A downtown measurement route was designed to cover popular outdoor areas, including business, recreational and shopping areas. The route was measured five times during different days and times. An exposimeter, was used to cover all the main civilian wireless broadcasting and downlink sources in frequencies 88‑5,850 MHz. The measurement route at the streets and squares calculated 1.240 V/m as a mean exposure (total as a sum of all frequency bands) and 6.867 V/m as all times maximum. The most common contributors to the exposure budget were bands FM US, 14DL, 27DL, 25DL and 66DL - mainly indicating 4G. The exposure levels were found to be 12‑16% lower during weekends as compared to business hours (P<0.001). The spatial analysis of the field distribution revealed 15‑20 hotspot areas. A number of hotspots were found where cell phone base station antennas were mounted on top of the utility poles and therefore positioned at low levels, close to street level. On the whole, the findings of the present study suggest that cell phone base station antennas should be distinct and noticeable, as this would assist individuals who need to limit their exposure by distancing themselves from RF sources.

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

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. The BWDM measured power density in 10 frequency bands (800, 900, 1800, 2100, 2600MHz, DECT 1900MHz, WiFi 2.4GHz; with separate uplink/downlink bands for 900, 1800 and 2100MHz); 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 1-4s 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. 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. 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.

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

BackgroundLittle 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. MethodsUsing 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). ResultsAdolescents 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). ConclusionThis 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.

Radiofrequency exposure of people living near mobile-phone base stations in France

In response to the demand from a growing number of people concerned about the possible impact of RF-EMF on health, the French National Frequency Agency (ANFR) has published a standardized protocol for in-situ measurements of radiofrequency electromagnetic fields (RF-EMF). This protocol was based on the search for the point of highest field strength and the use of spot measurement.In the framework of an epidemiological study, such spot measurements were implemented in the homes of 354 participants located in urban areas within 250 m of a mobile-phone base station (MPBS) and in the main beam direction of the antenna. Among the participants, more than half accepted to be enrolled in a longer-term study, among whom 152 were equipped with a personal exposure meter (PEM) for 48 h and 40 for seven continuous days. Both spot and PEM measurements quantified downlink field strengths, i.e. FM, TV3-4-5, TETRA I-II-III, 2 GHz–5GHz Wi-Fi, WiMax, GSM900, GSM1800, UMTS900, UMTS 2100, LTE800, LTE1800, and LTE2600.Spot measurements showed a mean/median field strength of 0.58/0.44 V/m for total RF-EMF and 0.43/0.27 V/m from the MPBS. RF-EMF from the MPBS was the dominant source of exposure in 64% of households. Exposure to RF-EMF was influenced by the position of the windows with respect to the MPBS, in particular line-of-site visibility, the distance of the antenna and the floor of the apartment. The PEM surveys showed the measured exposure to be higher during outings than at home and during the day than at night, but there was no difference between the weekends and working days. There was a strong correlation between exposure quantified by both spot and PEM measurements, although spot measures were approximately three times higher than those by PEMs.This study is the first to assess exposure to RF-EMF of people living near a MPBS in urban areas in France. These preliminary results suggest the value of using spot measurements to estimate the impact of the evolution of the mobile-phone network and technology on the exposure of populations to RF-EMF. The low levels of RF-RMF expressed as mean values do not necessarily rule out possible health effects of this exposure.

Exposure assessment of radio frequency electromagnetic field levels in hospitals of Samsun Province, Turkey.

With the increase in the use of different types of electronic systems used inside and outside the hospital, the electromagnetic medium in the hospital has changed significantly. The increase in the number and type of EMF sources in sensitive mediums such as hospitals has led researchers to measure EMFs to assess the potential risk to patients and staff. For this reason, this study aims to determine the radio frequency electromagnetic field (RF-EMF) levels to which patients and staff are exposed voluntarily or unintentionally in the hospital environment and to control their compliance with the limits defined in the standards. In order to achieve these goals, three different types of RF-EMF measurements were carried out as, short-term, long-term, and band selective in 21 state hospitals in the Samsun Province, Turkey. Total RF-EMF in the band between 100kHz and 3GHz is measured using PMM-8053, while band selective is conducted using SRM-3006 in the frequency range from 27MHz up to 3GHz. The recorded RF-EMF values were statistically analyzed, and the main RF-EMF sources in the medium were determined. The highest average RF-EMF exposure level obtained for short-term measurements was 2.52V/m. For long-term measurements, the highest average RF-EMF was 3.11V/m and the highest mean RF-EMF was 2.29V/m. Within our measurements, the limit of 3V/m set by the Information and Communication Technologies Authority (ICTA) was exceeded in the hospital, although the highest RF-EMF was below the limit level set by the International Commission on Non-Ionizing Radiation Protection (ICNIRP). Long-term measurement results showed that the RF-EMF level at midday was higher than at night; the highest RF-EMF was measured in the afternoon and during evening hours. The mean RF-EMF levels are 1.01V/m, 1.15V/m, 1.12V/m, and 0.84V/m, for morning, afternoon, evening, and night respectively. The RF-EMF level measured during the afternoon hours maybe about 37% higher than the RF-EMF levels measured at night. The main sources of total RF-EMF in the environment determined from the band-selective RF-EMF results were base stations located outside the hospital and their contribution to total RF-EMF was 92.6%. Systems that make the most contribution to the RF-EMF in the environment are base stations using the LTE 800, GSM 900, GSM 1800, LTE 1800, and UMTS 2100 frequency bands. Among these, the UMTS 2100 frequency band gave the highest contribution with 40.42%. With the use of these main RF-EMF sources, an empirical model that helps in computing the total E of the medium with 99.8% accuracy was proposed.

Comprehensive radiofrequency electromagnetic field measurements and assessments: a city center example.

In this study, radiofrequency electromagnetic field (RF-EMF) measurements were carried out between 2016 and 2018 in one the largest provinces of Turkey; measurement results are compared with the limit values determined by International Commission on Non-Ionizing Radiation Protection (ICNIRP) and Turkey's Information and Communication Technologies Authority (ICTA). In the first stage of a three-phase evaluation, short-term RF-EMF measurements were conducted in 500 locations over a 2-year period. In the second stage, short-term RF-EMF measurement results were analyzed to determine selected locations for long-term RF-EMF measurements to be carried out, including variation of RF-EMF during the day. In the last stage, band selective measurements were taken and the main sources of RF-EMF in the environment were determined. Overall, RF-EMF values do not exceed the limits determined by ICNIRP and ICTA, and they are below levels that threaten public health. In the short-term RF-EMF measurements, RF-EMF levels doubled after fourth generation (4G) systems were introduced. In the long-term RF-EMF measurements, RF-EMF values in the day are 35.4% more than at night. The total measured RF-EMF within the city center is 99.3% base station sourced. Among the six main RF-EMF sources, the devices operating in UMTS2100 band have the most contribution to total RF-EMF of medium with 31.2%. Additionally, we found short-term average electric field strength data are best described by the "exponential distribution," while long-term RF-EMF measurement data is best described by the "Burr distribution."

Dealing with crosstalk in electromagnetic field measurements of portable devices.

Portable devices measuring radiofrequency electromagnetic fields (RF-EMF) are affected by crosstalk: signals originating in one frequency band that are unintentionally registered in another. If this is not corrected, total exposure to RF-EMF is biased, particularly affecting closely spaced frequency bands such as GSM 1800 downlink (1,805-1,880 MHz), DECT (1,880-1,900 MHz), and UMTS uplink (1,920-1,980 MHz). This study presents an approach to detect and correct crosstalk in RF-EMF measurements, taking into account the real-life setting in which crosstalk is intermittently present, depending on the exact frequency of the signal. Personal measurements from 115 volunteers from Zurich canton, Switzerland were analyzed. Crosstalk-affected observations were identified by correlation analysis, and replaced by the median value of the unaffected observations, measured during the same activity. DECT is frequently a victim of crosstalk, and an average of 43% of observations was corrected, resulting in an average exposure reduction of 38%. GSM 1800 downlink and UMTS uplink were less often corrected (6.9% and 8.9%), resulting in minor reductions in exposure (7.1% and 0.92%). The contribution of DECT to total RF-EMF exposure is typically already low (3.2%), but is further reduced after correction (3.0%). Crosstalk corrections reduced the total exposure by 1.0% on average. Some individuals had a larger reduction of up to 16%. The code developed to make the corrections is provided for free as an R function which is easily applied to any time series of EMF measurements. Bioelectromagnetics. 39:529-538, 2018. © 2018 Wiley Periodicals, Inc.

Personal exposure to radio-frequency electromagnetic fields in Europe: Is there a generation gap?

BackgroundExposure to radiofrequency electromagnetic fields (RF-EMF) from mobile communication technologies is changing rapidly. To characterize sources and associated variability, we studied the differences and correlations in exposure patterns between children aged 8 to 18 and their parents, over the course of the day, by age, by activity pattern, and for different metrics of exposure. MethodsUsing portable RF-EMF measurement devices, we collected simultaneous real-time personal measurements of RF-EMF over 24 to 72 h in 294 parent-child pairs from Denmark, the Netherlands, Slovenia, Switzerland, and Spain. The devices measured the power flux density (mW/m2) in 16 different frequency bands every 4 s, and activity diary Apps kept by the participants were used to collect time-activity information in real-time. We analyzed their exposures by activity, for the different source constituents of exposure: downlink (radiation emitted from mobile phone base stations), uplink (transmission from phone to base station), broadcast, DECT (digital enhanced cordless telecommunications) and Wi-Fi. We looked at the correlations between parents and children overall, during day (06:00–22.00) and night (22:00–06:00) and while spending time at home. ResultsThe mean of time-weighted average personal exposures was 0.16 mW/m2 for children and 0.15 mW/m2 for parents, on average predominantly originating from downlink sources (47% for children and 45% for parents), followed by uplink (18% and 27% respectively) and broadcast (25% and 19%). On average, exposure for downlink and uplink were highest during the day, and for Wi-Fi and DECT during the evening. Exposure during activities where most of the time is spent (home, school and work) was relatively low whereas exposure during travel and outside activities was higher. Exposure to uplink increased with age among young people, while DECT decreased slightly. Exposure to downlink, broadcast, and Wi-Fi showed no obvious trend with age. We found that exposure to total RF-EMF is correlated among children and their parents (Rspearman = 0.45), especially while at home (0.62) and during the night (0.60). Correlations were higher for environmental sources such as downlink (0.57) and broadcast (0.62) than for usage-related exposures such as uplink (0.29). ConclusionThe generation gap between children and their parents is mostly evident in uplink exposure, due to more and longer uplink and cordless phone calls among parents, and their tendency to spend slightly more time in activities with higher environmental RF-EMF exposure, such as travel. Despite these differences in personal behavior, exposure to RF-EMF is moderately correlated between children and their parents, especially exposures resulting from environmental RF-EMF sources.

Estimates of Environmental Exposure to Radiofrequency Electromagnetic Fields and Risk of Lymphoma Subtypes.

We investigated the association between environmental exposure to radiofrequency electromagnetic fields (RF-EMF) and risk of lymphoma subtypes in a case-control study comprised of 322 patients and 444 individuals serving as controls in Sardinia, Italy in 1998-2004. Questionnaire information included the self-reported distance of the three longest held residential addresses from fixed radio-television transmitters and mobile phone base stations. We georeferenced the residential addresses of all study subjects and obtained the spatial coordinates of mobile phone base stations. For each address within a 500-meter radius from a mobile phone base station, we estimated the RF-EMF intensity using predictions from spatial models, and we performed RF-EMF measurements at the door in the subset of the longest held addresses within a 250-meter radius. We calculated risk of lymphoma and its major subtypes associated with the RF-EMF exposure metrics with unconditional logistic regression, adjusting by age, gender and years of education. In the analysis of self-reported data, risk associated with residence in proximity (within 50 meters) to fixed radio-television transmitters was likewise elevated for lymphoma overall [odds ratio = 2.7, 95% confidence interval = 1.5-4.6], and for the major lymphoma subtypes. With reference to mobile phone base stations, we did not observe an association with either the self-reported, or the geocoded distance from mobile phone base stations. RF-EMF measurements did not vary by case-control status. By comparing the self-reports to the geocoded data, we discovered that the cases tended to underestimate the distance from mobile phone base stations differentially from the controls ( P = 0.073). The interpretation of our findings is compromised by the limited study size, particularly in the analysis of the individual lymphoma subtypes, and the unavailability of the spatial coordinates of radio-television transmitters. Nonetheless, our results do not support the hypothesis of a link between environmental exposure to RF-EMF from mobile phone base stations and risk of lymphoma subtypes.

Assessment of radiofrequency electromagnetic field exposure from personal measurements considering the body shadowing effect in Korean children and parents

We aimed to assess the personal radiofrequency electromagnetic field (RF-EMF) exposure levels of children and adults through their activities, with consideration to the body shadowing effect. We recruited 50 child-adult pairs, living in Seoul, Cheonan, and Ulsan, South Korea. RF-EMF measurements were performed between September and December 2016, using a portable exposure meter tailored to capture 14 Korean radiofrequency (RF) bands ranging from 87.5 to 5875MHz. The participants carried the device for 48h and kept a time-activity diary using a smartphone application in flight mode. To enhance accuracy of the exposure assessment, the body shadowing effect was compensated during the statistical analysis with the measured RF-EMF exposure. The compensation was conducted using the hybrid model that represents the decrease of the exposure level due to the body shadowing effect. A generalized linear mixed model was used to compare the RF-EMF exposure levels by subjects and activities. The arithmetic (geometric) means of the total power density were 174.9 (36.6) μW/m2 for all participants, 226.9 (44.6) for fathers, 245.4 (44.8) for mothers, and 116.2 (30.1) for children. By compensating for the body shadowing effect, the total RF-EMF exposure increased marginally, approximately 1.4 times. Each frequency band contribution to total RF-EMF exposure consisted of 76.7%, 2.4%, 9.9%, 5.0%, 3.3%, and 2.6% for downlink, uplink, WiFi, FM Radio, TV, and WiBro bands, respectively. Among the three regions, total RF-EMF exposure was highest in Seoul, and among the activities, it was highest in the metro, followed by foot/bicycle, bus/car, and outside. The contribution of base-station exposure to total RF-EMF exposure was the highest both in parents and children. Total and base-station RF-EMF exposure levels in Korea were higher than those reported in European countries.

Personal radiofrequency electromagnetic field exposure measurements in Swiss adolescents

BackgroundAdolescents belong to the heaviest users of wireless communication devices, but little is known about their personal exposure to radiofrequency electromagnetic fields (RF-EMF). ObjectivesThe aim of this paper is to describe personal RF-EMF exposure of Swiss adolescents and evaluate exposure relevant factors. Furthermore, personal measurements were used to estimate average contributions of various sources to the total absorbed RF-EMF dose of the brain and the whole body. MethodsPersonal exposure was measured using a portable RF-EMF measurement device (ExpoM-RF) measuring 13 frequency bands ranging from 470 to 3600MHz. The participants carried the device for three consecutive days and kept a time-activity diary. In total, 90 adolescents aged 13 to 17years participated in the study conducted between May 2013 and April 2014. In addition, personal measurement values were combined with dose calculations for the use of wireless communication devices to quantify the contribution of various RF-EMF sources to the daily RF-EMF dose of adolescents. ResultsMain contributors to the total personal RF-EMF measurements of 63.2μW/m2 (0.15V/m) were exposures from mobile phones (67.2%) and from mobile phone base stations (19.8%). WLAN at school and at home had little impact on the personal measurements (WLAN accounted for 3.5% of total personal measurements). According to the dose calculations, exposure from environmental sources (broadcast transmitters, mobile phone base stations, cordless phone base stations, WLAN access points, and mobile phones in the surroundings) contributed on average 6.0% to the brain dose and 9.0% to the whole-body dose. ConclusionsRF-EMF exposure of adolescents is dominated by their own mobile phone use. Environmental sources such as mobile phone base stations play a minor role.

Radiofrequency radiation injures trees around mobile phone base stations

In the last two decades, the deployment of phone masts around the world has taken place and, for many years, there has been a discussion in the scientific community about the possible environmental impact from mobile phone base stations. Trees have several advantages over animals as experimental subjects and the aim of this study was to verify whether there is a connection between unusual (generally unilateral) tree damage and radiofrequency exposure. To achieve this, a detailed long-term (2006–2015) field monitoring study was performed in the cities of Bamberg and Hallstadt (Germany). During monitoring, observations and photographic recordings of unusual or unexplainable tree damage were taken, alongside the measurement of electromagnetic radiation. In 2015 measurements of RF-EMF (Radiofrequency Electromagnetic Fields) were carried out. A polygon spanning both cities was chosen as the study site, where 144 measurements of the radiofrequency of electromagnetic fields were taken at a height of 1.5m in streets and parks at different locations. By interpolation of the 144 measurement points, we were able to compile an electromagnetic map of the power flux density in Bamberg and Hallstadt. We selected 60 damaged trees, in addition to 30 randomly selected trees and 30 trees in low radiation areas (n=120) in this polygon. The measurements of all trees revealed significant differences between the damaged side facing a phone mast and the opposite side, as well as differences between the exposed side of damaged trees and all other groups of trees in both sides. Thus, we found that side differences in measured values of power flux density corresponded to side differences in damage. The 30 selected trees in low radiation areas (no visual contact to any phone mast and power flux density under 50μW/m2) showed no damage. Statistical analysis demonstrated that electromagnetic radiation from mobile phone masts is harmful for trees. These results are consistent with the fact that damage afflicted on trees by mobile phone towers usually start on one side, extending to the whole tree over time.

Exposure triggered health questionnaires by linking real-time RF-EMF measurements to a smartphone application

Introduction Studying acute effects of radiofrequency electromagnetic fields (RF-EMF) in observational studies often involves retrospective collection of questionnaires with hours or days between exposure and experienced health effects, making it difficult to link symptoms to exposure events. We developed a smartphone app prompting health status related questions, when triggered by pre-set exposure events detected in real-time by an exposimeter. A feasibility study was performed. Methods Participants were asked to install the app on their smartphone and to carry a RF exposimeter for 48 hours. Data was sent via Bluetooth to the application every 8 seconds. A questionnaire was triggered if: 1) a tenfold relative exposure increase compared to the average of the past half hour occurred, 2) exposure exceeded 10 mW/m², 3) a phone call was registered, and 4) no questionnaire was triggered for the past 1.5 hours (control). The questionnaire comprised 10 questions concerning current wellbeing. Unanswered questionnaires disappeared after 10 minutes. Minimum time between questionnaires was 45 minutes. Participants were asked to fill in an evaluation questionnaire. We evaluated the percentage of completed questionnaires, trigger reasons, and whether participants perceived influence on daily activities. Results We obtained complete data of 33 out of 46 participants (average age 32 (18-59)). Data from 13 participants were unusable due to technical failures. Participants received on average 9 (IQR 9-11) questionnaires per day of which 75% (IQR 69%-79%) were filled in. Main trigger reason was relative increase (61%) followed by control conditions (28%). 27 participants reported minimal influence, 6 reported some influence on daily activities. Conclusions Asking real-time exposure triggered questions using a smartphone app is feasible and has the potential to be applied to other types of exposure. Response rates were about 75% having limited influence on daily activities of participants.

Use of portable exposimeters to monitor radiofrequency electromagnetic field exposure in the everyday environment

BackgroundSpatial and temporal distribution of radiofrequency electromagnetic field (RF-EMF) levels in the environment is highly heterogeneous. It is thus not entirely clear how to monitor spatial variability and temporal trends of RF-EMF exposure levels in the environment in a representative and efficient manner. The aim of this study was to test a monitoring protocol for RF-EMF measurements in public areas using portable devices. MethodsUsing the ExpoM-RF devices mounted on a backpack, we have conducted RF-EMF measurements by walking through 51 different outdoor microenvironments from 20 different municipalities in Switzerland: 5 different city centers, 5 central residential areas, 5 non-central residential areas, 15 rural residential areas, 15 rural centers and 6 industrial areas. Measurements in public transport (buses, trains, trams) were collected when traveling between the areas. Measurements were conducted between 25th March and 11th July 2014. In order to evaluate spatial representativity within one microenvironment, we measured two crossing paths of about 1km in length in each microenvironment. To evaluate repeatability, measurements in each microenvironment were repeated after two to four months on the same paths. ResultsMean RF-EMF exposure (sum of 15 main frequency bands between 87.5 and 5,875MHz) was 0.53V/m in industrial zones, 0.47V/m in city centers, 0.32V/m in central residential areas, 0.25V/m non-central residential areas, 0.23V/m in rural centers and rural residential areas, 0.69V/m in trams, 0.46V/m in trains and 0.39V/m in buses. Major exposure contribution at outdoor locations was from mobile phone base stations (>80% for all outdoor areas with respect to the power density scale). Temporal correlation between first and second measurement of each area was high: 0.89 for total RF-EMF, 0.90 for all five mobile phone downlink bands combined, 0.51 for all five uplink bands combined and 0.79 for broadcasting. Spearman correlation between arithmetic mean values of the first path compared to arithmetic mean of the second path within the same microenvironment was 0.75 for total RF-EMF, 0.76 for all five mobile phone downlink bands combined, 0.55 for all five uplink bands combined and 0.85 for broadcasting (FM and DVB-T). ConclusionsThis study demonstrates that microenvironmental surveys using a portable device yields highly repeatable measurements, which allows monitoring time trends of RF-EMF exposure over an extended time period of several years and to compare exposure levels between different types of microenvironments.