Determination of exposure due to mobile phone base stations in an epidemiological study

Evidence for a health risk by RF on humans living around mobile phone base stations: From radiofrequency sickness to cancer

The objective of this work was to perform a complete review of the existing scientific literature to update the knowledge on the effects of base station antennas on humans. Studies performed in real urban conditions, with mobile phone base stations situated close to apartments, were selected. Overall results of this review show three types of effects by base station antennas on the health of people: radiofrequency sickness (RS), cancer (C) and changes in biochemical parameters (CBP). Considering all the studies reviewed globally (n = 38), 73.6% (28/38) showed effects: 73.9% (17/23) for radiofrequency sickness, 76.9% (10/13) for cancer and 75.0% (6/8) for changes in biochemical parameters. Furthermore, studies that did not meet the strict conditions to be included in this review provided important supplementary evidence. The existence of similar effects from studies by different sources (but with RF of similar characteristics), such as radar, radio and television antennas, wireless smart meters and laboratory studies, reinforce the conclusions of this review. Of special importance are the studies performed on animals or trees near base station antennas that cannot be aware of their proximity and to which psychosomatic effects can never be attributed.

Study of the correlation between outdoor and indoor electromagnetic exposure near cellular base stations in Leuven, Belgium

A measuring campaign for the assessment of electromagnetic radiation near base stations in the city center of Leuven, Belgium, has been carried out. The main objective of this assessment is to study the correlation between the outdoor and the indoor exposure produced by cellular base stations and to investigate the changes of electromagnetic exposure within a typical day and over 1 month in the vicinity of these base stations. The study was also carried out as a function of location and time using highly precise measurement equipment. The measurements were performed in both public and private areas in sixty (30 indoor and 30 outdoor) different locations in Leuven. The measurement was focused on mobile communication networks: GSM (Global System for Mobile Communication, 900 MHz and 1800 MHz) and UMTS (Universal Mobile Telecommunications System, 2110 MHz) were the frequency bands of interest. The data at these frequencies were extracted from raw measurements in the 824-2170 MHz frequency band. The results show that all analyzed locations are in compliance with the exposure limits recommended by ICNIRP (International Commission on Non-Ionizing Radiation Protection) and that the (maximum) indoor exposure correlates to the outdoor exposure with a factor of about 0.5.

Children's exposure assessment of radiofrequency fields: Comparison between spot and personal measurements

INTRODUCTION

Radiofrequency (RF) fields are widely used and, while it is still unknown whether children are more vulnerable to this type of exposure, it is essential to explore their level of exposure in order to conduct adequate epidemiological studies. Personal measurements provide individualized information, but they are costly in terms of time and resources, especially in large epidemiological studies. Other approaches, such as estimation of time-weighted averages (TWAs) based on spot measurements could simplify the work.

OBJECTIVES

The aims of this study were to assess RF exposure in the Spanish INMA birth cohort by spot measurements and by personal measurements in the settings where children tend to spend most of their time, i.e., homes, schools and parks; to identify the settings and sources that contribute most to that exposure; and to explore if exposure assessment based on spot measurements is a valid proxy for personal exposure.

METHODS

When children were 8 years old, spot measurements were conducted in the principal settings of 104 participants: homes (104), schools and their playgrounds (26) and parks (79). At the same time, personal measurements were taken for a subsample of 50 children during 3 days. Exposure assessment based on personal and on spot measurements were compared both in terms of mean exposures and in exposure-dependent categories by means of Bland-Altman plots, Cohen's kappa and McNemar test.

RESULTS

Median exposure levels ranged from 29.73 (in children's bedrooms) to 200.10 μW/m² (in school playgrounds) for spot measurements and were higher outdoors than indoors. Median personal exposure was 52.13 μW/m² and median levels of assessments based on spot measurements ranged from 25.46 to 123.21 μW/m². Based on spot measurements, the sources that contributed most to the exposure were FM radio, mobile phone downlink and Digital Video Broadcasting-Terrestrial, while indoor and personal sources contributed very little (altogether <20%). Similar distribution was observed with personal measurements. There was a bias proportional to power density between personal measurements and estimates based on spot measurements, with the latter providing higher exposure estimates. Nevertheless, there were no systematic differences between those methodologies when classifying subjects into exposure categories. Personal measurements of total RF exposure showed low to moderate agreement with home and bedroom spot measurements and agreed better, though moderately, with TWA based on spot measurements in the main settings where children spend time (homes, schools and parks; Kappa = 0.46).

CONCLUSIONS

Exposure assessment based on spot measurements could be a feasible proxy to rank personal RF exposure in children population, providing that all relevant locations are being measured.

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

BACKGROUND

Spatial 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.

METHODS

Using 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.

RESULTS

Mean 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).

CONCLUSIONS

This 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.

Clinically defined non-specific symptoms in the vicinity of mobile phone base stations: A retrospective before-after study

The number of mobile phone base station(s) (MPBS) has been increasing to meet the rapid technological changes and growing needs for mobile communication. The primary objective of the present study was to test possible changes in prevalence and number of NSS in relation to MPBS exposure before and after increase of installed MPBS antennas. A retrospective cohort study was conducted, comparing two time periods with high contrast in terms of number of installed MPBS. Symptom data were based on electronic health records from 1069 adult participants, registered in 9 general practices in different regions in the Netherlands. All participants were living within 500m from the nearest bases station. Among them, 55 participants reported to be sensitive to MPBS at T1. A propagation model combined with a questionnaire was used to assess indoor exposure to RF-EMF from MPBS at T1. Estimation of exposure at T0 was based on number of antennas at T0 relative to T1. At T1, there was a >30% increase in the total number of MPBS antennas. A higher prevalence for most NSS was observed in the MPBS-sensitive group at T1 compared to baseline. Exposure estimates were not associated with GP-registered NSS in the total sample. Some significant interactions were observed between MPBS-sensitivity and exposure estimates on risk of symptoms. Using clinically defined outcomes and a time difference of >6years it was demonstrated that RF-EMF exposure to MPBS was not associated with the development of NSS. Nonetheless, there was some indication for a higher risk of NSS for the MPBS-sensitive group, mainly in relation to exposure to UMTS, but this should be interpreted with caution. Results have to be verified by future longitudinal studies with a particular focus on potentially susceptible population subgroups of large sample size and integrated exposure assessment.

Lessons learnt on biases and uncertainties in personal exposure measurement surveys of radiofrequency electromagnetic fields with exposimeters

Personal exposure measurements of radio frequency electromagnetic fields are important for epidemiological studies and developing prediction models. Minimizing biases and uncertainties and handling spatial and temporal variability are important aspects of these measurements. This paper reviews the lessons learnt from testing the different types of exposimeters and from personal exposure measurement surveys performed between 2005 and 2015. Applying them will improve the comparability and ranking of exposure levels for different microenvironments, activities or (groups of) people, such that epidemiological studies are better capable of finding potential weak correlations with health effects. Over 20 papers have been published on how to prevent biases and minimize uncertainties due to: mechanical errors; design of hardware and software filters; anisotropy; and influence of the body. A number of biases can be corrected for by determining multiplicative correction factors. In addition a good protocol on how to wear the exposimeter, a sufficiently small sampling interval and sufficiently long measurement duration will minimize biases. Corrections to biases are possible for: non-detects through detection limit, erroneous manufacturer calibration and temporal drift. Corrections not deemed necessary, because no significant biases have been observed, are: linearity in response and resolution. Corrections difficult to perform after measurements are for: modulation/duty cycle sensitivity; out of band response aka cross talk; temperature and humidity sensitivity. Corrections not possible to perform after measurements are for: multiple signals detection in one band; flatness of response within a frequency band; anisotropy to waves of different elevation angle. An analysis of 20 microenvironmental surveys showed that early studies using exposimeters with logarithmic detectors, overestimated exposure to signals with bursts, such as in uplink signals from mobile phones and WiFi appliances. Further, the possible corrections for biases have not been fully applied. The main findings are that if the biases are not corrected for, the actual exposure will on average be underestimated.

Characterisation of exposure to non-ionising electromagnetic fields in the Spanish INMA birth cohort: study protocol

BACKGROUND

Analysis of the association between exposure to electromagnetic fields of non-ionising radiation (EMF-NIR) and health in children and adolescents is hindered by the limited availability of data, mainly due to the difficulties on the exposure assessment. This study protocol describes the methodologies used for characterising exposure of children to EMF-NIR in the INMA (INfancia y Medio Ambiente- Environment and Childhood) Project, a prospective cohort study.

METHODS/DESIGN

Indirect (proximity to emission sources, questionnaires on sources use and geospatial propagation models) and direct methods (spot and fixed longer-term measurements and personal measurements) were conducted in order to assess exposure levels of study participants aged between 7 and 18 years old. The methodology used varies depending on the frequency of the EMF-NIR and the environment (homes, schools and parks). Questionnaires assessed the use of sources contributing both to Extremely Low Frequency (ELF) and Radiofrequency (RF) exposure levels. Geospatial propagation models (NISMap) are implemented and validated for environmental outdoor sources of RFs using spot measurements. Spot and fixed longer-term ELF and RF measurements were done in the environments where children spend most of the time. Moreover, personal measurements were taken in order to assess individual exposure to RF. The exposure data are used to explore their relationships with proximity and/or use of EMF-NIR sources.

DISCUSSION

Characterisation of the EMF-NIR exposure by this combination of methods is intended to overcome problems encountered in other research. The assessment of exposure of INMA cohort children and adolescents living in different regions of Spain to the full frequency range of EMF-NIR extends the characterisation of environmental exposures in this cohort. Together with other data obtained in the project, on socioeconomic and family characteristics and development of the children and adolescents, this will enable to evaluate the complex interaction between health outcomes in children and adolescents and the various environmental factors that surround them.

Do car-mounted mobile measurements used for radio-frequency spectrum regulation have an application for exposure assessments in epidemiological studies?

Knowing the spatial and temporal trends in environmental exposure to radiofrequency electromagnetic fields is important in studies investigating whether there are associated health effects on humans and ecological effects on plants and animals. The main objective of this study is to assess whether the RFeye car-mounted mobile measurement system used for radio frequency spectrum monitoring in The Netherlands and the United Kingdom could be of value in assessing exposure over large areas as an alternative to measuring exposure with personal exposure meters or using complex modelling techniques. We evaluated the responses of various body-worn personal exposure meters in comparison with the mobile measurement system for spectrum monitoring. The comparison was restricted to downlink mobile communication in the GSM900 and GSM1800 frequency bands. Repeated measurements were performed in three areas in Cambridge, United Kingdom and in three areas in Amersfoort, The Netherlands. We found that exposure assessments through the car-mounted measurements are at least of similar quality to exposure modelling and better than the body worn exposimeter data due to the absence of the shielding effect. The main conclusion is that the mobile measurements provide an efficient and low cost alternative particularly in mapping large areas.

Validity of at home model predictions as a proxy for personal exposure to radiofrequency electromagnetic fields from mobile phone base stations

BACKGROUND

Epidemiological studies on the potential health effects of RF-EMF from mobile phone base stations require efficient and accurate exposure assessment methods. Previous studies have demonstrated that the 3D geospatial model NISMap is able to rank locations by indoor and outdoor RF-EMF exposure levels. This study extends on previous work by evaluating the suitability of using NISMap to estimate indoor RF-EMF exposure levels at home as a proxy for personal exposure to RF-EMF from mobile phone base stations.

METHODS

For 93 individuals in the Netherlands we measured personal exposure to RF-EMF from mobile phone base stations during a 24h period using an EME-SPY 121 exposimeter. Each individual kept a diary from which we extracted the time spent at home and in the bedroom. We used NISMap to model exposure at the home address of the participant (at bedroom height). We then compared model predictions with measurements for the 24h period, when at home, and in the bedroom by the Spearman correlation coefficient (rsp) and by calculating specificity and sensitivity using the 90th percentile of the exposure distribution as a cutpoint for high exposure.

RESULTS

We found a low to moderate rsp of 0.36 for the 24h period, 0.51 for measurements at home, and 0.41 for measurements in the bedroom. The specificity was high (0.9) but with a low sensitivity (0.3).

DISCUSSION

These results indicate that a meaningful ranking of personal RF-EMF can be achieved, even though the correlation between model predictions and 24h personal RF-EMF measurements is lower than with at home measurements. However, the use of at home RF-EMF field predictions from mobile phone base stations in epidemiological studies leads to significant exposure misclassification that will result in a loss of statistical power to detect health effects.

Actual and perceived exposure to electromagnetic fields and non-specific physical symptoms: an epidemiological study based on self-reported data and electronic medical records

BACKGROUND

There is continuing scientific debate and increasing public concern regarding the possible effects of electromagnetic fields (EMF) on general population's health. To date, no epidemiological study has investigated the possible association between actual and perceived EMF exposure and non-specific physical symptoms (NSPS) and sleep quality, using both self-reported and general practice (GP)-registered data.

METHODS

A health survey of adult (≥ 18) participants (n=5933) in the Netherlands was combined with the electronic medical records (EMRs) of NSPS as registered by general practitioners. Characterization of actual exposure was based on several proxies, such as prediction models of radiofrequency (RF)-EMF exposure, geo-coded distance to high-voltage overhead power lines and self-reported use/distance of/to indoor electrical appliances. Perceived exposure and the role of psychological variables were also examined.

RESULTS

Perceived exposure had a poor correlation with the actual exposure estimates. No significant association was found between modeled RF-EMF exposure and the investigated outcomes. Associations with NSPS were observed for use of an electric blanket and close distance to an electric charger during sleep. Perceived exposure, perceived control and avoidance behavior were associated with the examined outcomes. The association between perceived exposure was stronger for self-reported than for GP-registered NSPS. There was some indication, but no consistent pattern for an interaction between idiopathic environmental intolerance (IEI-EMF) and the association between actual exposure and NSPS.

CONCLUSIONS

In conclusion, there is no convincing evidence for an association between everyday life RF-EMF exposure and NSPS and sleep quality in the population. Better exposure characterization, in particular with respect to sources of extremely low frequency magnetic fields (ELF-MF) is needed to draw more solid conclusions. We argue that perceived exposure is an independent determinant of NSPS.

What input data are needed to accurately model electromagnetic fields from mobile phone base stations?

The increase in mobile communication technology has led to concern about potential health effects of radio frequency electromagnetic fields (RF-EMFs) from mobile phone base stations. Different RF-EMF prediction models have been applied to assess population exposure to RF-EMF. Our study examines what input data are needed to accurately model RF-EMF, as detailed data are not always available for epidemiological studies. We used NISMap, a 3D radio wave propagation model, to test models with various levels of detail in building and antenna input data. The model outcomes were compared with outdoor measurements taken in Amsterdam, the Netherlands. Results showed good agreement between modelled and measured RF-EMF when 3D building data and basic antenna information (location, height, frequency and direction) were used: Spearman correlations were >0.6. Model performance was not sensitive to changes in building damping parameters. Antenna-specific information about down-tilt, type and output power did not significantly improve model performance compared with using average down-tilt and power values, or assuming one standard antenna type. We conclude that 3D radio wave propagation modelling is a feasible approach to predict outdoor RF-EMF levels for ranking exposure levels in epidemiological studies, when 3D building data and information on the antenna height, frequency, location and direction are available.

Electromagnetic field exposure assessment in Europe radiofrequency fields (10 MHz-6 GHz)

Average levels of exposure to radiofrequency (RF) electromagnetic fields (EMFs) of the general public in Europe are difficult to summarize, as exposure levels have been reported differently in those studies in which they have been measured, and a large proportion of reported measurements were very low, sometimes falling below detection limits of the equipment used. The goal of this paper is to present an overview of the scientific literature on RF EMF exposure in Europe and to characterize exposure within the European population. A comparative analysis of the results of spot or long-term RF EMF measurements in the EU indicated that mean electric field strengths were between 0.08 V/m and 1.8 V/m. The overwhelming majority of measured mean electric field strengths were <1 V/m. It is estimated that <1% were above 6 V/m and <0.1% were above 20 V/m. No exposure levels exceeding European Council recommendations were identified in these surveys. Most population exposures from signals of radio and television broadcast towers were observed to be weak because these transmitters are usually far away from exposed individuals and are spatially sparsely distributed. On the other hand, the contribution made to RF exposure from wireless telecommunications technology is continuously increasing and its contribution was above 60% of the total exposure. According to the European exposure assessment studies identified, three population exposure categories (intermittent variable partial body exposure, intermittent variable low-level whole-body (WB) exposure and continuous low-level WB exposure) were recognized by the authors as informative for possible future risk assessment.

EMF monitoring-concepts, activities, gaps and options

Exposure to electromagnetic fields (EMF) is a cause of concern for many people. The topic will likely remain for the foreseeable future on the scientific and political agenda, since emissions continue to change in characteristics and levels due to new infrastructure deployments, smart environments and novel wireless devices. Until now, systematic and coordinated efforts to monitor EMF exposure are rare. Furthermore, virtually nothing is known about personal exposure levels. This lack of knowledge is detrimental for any evidence-based risk, exposure and health policy, management and communication. The main objective of the paper is to review the current state of EMF exposure monitoring activities in Europe, to comment on the scientific challenges and deficiencies, and to describe appropriate strategies and tools for EMF exposure assessment and monitoring to be used to support epidemiological health research and to help policy makers, administrators, industry and consumer representatives to base their decisions and communication activities on facts and data.

Modelling indoor electromagnetic fields (EMF) from mobile phone base stations for epidemiological studies

Radio frequency electromagnetic fields (RF-EMF) from mobile phone base stations can be reliably modelled for outdoor locations, using 3D radio wave propagation models that consider antenna characteristics and building geometry. For exposure assessment in epidemiological studies, however, it is especially important to determine indoor exposure levels as people spend most of their time indoors. We assessed the accuracy of indoor RF-EMF model predictions, and whether information on building characteristics could increase model accuracy. We performed 15-minute spot measurements in 263 rooms in 101 primary schools and 30 private homes in Amsterdam, the Netherlands. At each measurement location, we collected information on building characteristics that can affect indoor exposure to RF-EMF, namely glazing and wall and window frame materials. Next, we modelled RF-EMF at the measurement locations with the 3D radio wave propagation model NISMap. We compared model predictions with measured values to evaluate model performance, and explored if building characteristics modified the association between modelled and measured RF-EMF using a mixed effect model. We found a Spearman correlation of 0.73 between modelled and measured total downlink RF-EMF from base stations. The average modelled and measured RF-EMF were 0.053 and 0.041mW/m(2), respectively, and the precision (standard deviation of the differences between predicted and measured values) was 0.184mW/m(2). Incorporating information on building characteristics did not improve model predictions. Although there is exposure misclassification, we conclude that it is feasible to reliably rank indoor RF-EMF from mobile phone base stations for epidemiological studies.

Comparing non-specific physical symptoms in environmentally sensitive patients: prevalence, duration, functional status and illness behavior

OBJECTIVE

Little is known about the potential clinical relevance of non-specific physical symptoms (NSPS) reported by patients with self-reported environmental sensitivities. This study aimed to assess NSPS in people with general environmental sensitivity (GES) and idiopathic environmental intolerance attributed to electromagnetic fields (IEI-EMF) and to determine differences in functional status and illness behavior.

METHODS

An epidemiological study was conducted in the Netherlands, combining self-administered questionnaires with the electronic medical records of the respondents as registered by general practitioners. Analyses included n=5789 registered adult (≥18 years) patients, comprising 5073 non-sensitive (NS) individuals, 514 in the GES group and 202 in the IEI-EMF group.

RESULTS

Participants with GES were about twice as likely to consult alternative therapy compared to non-sensitive individuals; those with IEI-EMF were more than three times as likely. Moreover, there was a higher prevalence of symptoms and medication prescriptions and longer symptom duration among people with sensitivities. Increasing number and duration of self-reported NSPS were associated with functional impairment, illness behavior, negative symptom perceptions and prevalence of GP-registered NSPS in the examined groups.

CONCLUSION

Even after adjustment for medical and psychiatric morbidity, environmentally sensitive individuals experience poorer health, increased illness behavior and more severe NSPS. The number and duration of self-reported NSPS are important components of symptom severity and are associated with characteristics similar to those of NSPS in primary care. The substantial overlap between the sensitive groups strengthens the notion that different types of sensitivities might be part of one, broader environmental illness.

Assessment of outdoor radiofrequency electromagnetic field exposure through hotspot localization using kriging-based sequential sampling

In this study, a novel methodology is proposed to create heat maps that accurately pinpoint the outdoor locations with elevated exposure to radiofrequency electromagnetic fields (RF-EMF) in an extensive urban region (or, hotspots), and that would allow local authorities and epidemiologists to efficiently assess the locations and spectral composition of these hotspots, while at the same time developing a global picture of the exposure in the area. Moreover, no prior knowledge about the presence of radiofrequency radiation sources (e.g., base station parameters) is required. After building a surrogate model from the available data using kriging, the proposed method makes use of an iterative sampling strategy that selects new measurement locations at spots which are deemed to contain the most valuable information-inside hotspots or in search of them-based on the prediction uncertainty of the model. The method was tested and validated in an urban subarea of Ghent, Belgium with a size of approximately 1 km2. In total, 600 input and 50 validation measurements were performed using a broadband probe. Five hotspots were discovered and assessed, with maximum total electric-field strengths ranging from 1.3 to 3.1 V/m, satisfying the reference levels issued by the International Commission on Non-Ionizing Radiation Protection for exposure of the general public to RF-EMF. Spectrum analyzer measurements in these hotspots revealed five radiofrequency signals with a relevant contribution to the exposure. The radiofrequency radiation emitted by 900 MHz Global System for Mobile Communications (GSM) base stations was always dominant, with contributions ranging from 45% to 100%. Finally, validation of the subsequent surrogate models shows high prediction accuracy, with the final model featuring an average relative error of less than 2dB (factor 1.26 in electric-field strength), a correlation coefficient of 0.7, and a specificity of 0.96.

Geospatial modelling of electromagnetic fields from mobile phone base stations

There is concern that exposure to radio frequency electromagnetic fields (RF-EMF) from mobile phone base stations might lead to adverse health effects. In order to assess potential health risks, reliable exposure assessment is necessary. Geospatial exposure modelling is a promising approach to quantify ambient exposure to RF-EMF for epidemiological studies involving large populations. We modelled RF-EMF for Amsterdam, The Netherlands by using a 3D RF-EMF model (NISMap). We subsequently compared modelled results to RF-EMF measurements in five areas with differing built-up characteristics (e.g., low-rise residential, high-rise commercial). We performed, in each area, repeated continuous measurements along a predefined ~2 km long path. This mobile monitoring approach captures the high spatial variability in electric field strengths. The modelled values were in good agreement with the measurements. We found a Spearman correlation of 0.86 for GSM900 and 0.85 for UMTS between modelled and measured values. The average measured GSM900 field strength was 0.21 V/m, and UMTS 0.09 V/m. The model underestimated the GSM900 field strengths by 0.07 V/m, and slightly overestimated the UMTS field strengths by 0.01 V/m. NISMap provides a reliable way of assessing environmental RF-EMF exposure for epidemiological studies of RF-EMF and health in urban areas.

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 km(2) 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.

Comparative international analysis of radiofrequency exposure surveys of mobile communication radio base stations

This paper presents analyses of data from surveys of radio base stations in 23 countries across five continents from the year 2000 onward and includes over 173,000 individual data points. The research compared the results of the national surveys, investigated chronological trends and compared exposures by technology. The key findings from this data are that irrespective of country, the year and cellular technology, exposures to radio signals at ground level were only a small fraction of the relevant human exposure standards. Importantly, there has been no significant increase in exposure levels since the widespread introduction of 3G mobile services, which should be reassuring for policy makers and negate the need for post-installation measurements at ground level for compliance purposes. There may be areas close to antennas where compliance levels could be exceeded. Future potential work includes extending the study to additional countries, development of cumulative exposure distributions and investigating the possibility of linking exposure measurements to population statistics to assess the distribution of exposure levels relative to population percentiles.

Assessment of exposure to mobile telecommunication electromagnetic fields

Typical general public exposures around mobile radio service base stations consume only tiny fractions of exposure levels. Maximal immissions at maximal transmit power of base stations amount to several percent of power density reference levels; typical immission levels are about one tenth of a percent or even less. The distance to base stations is no reliable exposure classifier. More important are the orientation relative to the main lobe of the station and sight conditions from measurement point to the base station. Mobile phones cause higher exposures to the user than base stations. At maximal transmit power up to 80 percent of the basic restrictions are consumed. Therefore, actions to minimize exposure to mobile phones, e.g. by using a headset, have a larger potential than shielding against emissions from base stations. Both base stations and mobile phones apply power control mechanisms, capable to significantly reducing the transmit power and the associated exposure depending on the communication traffic. Present research investigates, whether children are more exposed to mobile telecommunication systems than adults.

Classification of personal exposure to radio frequency electromagnetic fields (RF-EMF) for epidemiological research: Evaluation of different exposure assessment methods

The use of personal exposure meters (exposimeters) has been recommended for measuring personal exposure to radio frequency electromagnetic fields (RF-EMF) from environmental far-field sources in everyday life. However, it is unclear to what extent exposimeter readings are affected by measurements taken when personal mobile and cordless phones are used. In addition, the use of exposimeters in large epidemiological studies is limited due to high costs and large effort for study participants. In the current analysis we aimed to investigate the impact of personal phone use on exposimeter readings and to evaluate different exposure assessment methods potentially useful in epidemiological studies. We collected personal exposimeter measurements during one week and diary data from 166 study participants. Moreover, we collected spot measurements in the participants' bedrooms and data on self-estimated exposure, assessed residential exposure to fixed site transmitters by calculating the geo-coded distance and mean RF-EMF from a geospatial propagation model, and developed an exposure prediction model based on the propagation model and exposure relevant behavior. The mean personal exposure was 0.13 mW/m(2), when measurements during personal phone calls were excluded and 0.15 mW/m(2), when such measurements were included. The Spearman correlation with personal exposure (without personal phone calls) was 0.42 (95%-CI: 0.29 to 0.55) for the spot measurements, -0.03 (95%-CI: -0.18 to 0.12) for the geo-coded distance, 0.28 (95%-CI: 0.14 to 0.42) for the geospatial propagation model, 0.50 (95%-CI: 0.37 to 0.61) for the full exposure prediction model and 0.06 (95%-CI: -0.10 to 0.21) for self-estimated exposure. In conclusion, personal exposure measured with exposimeters correlated best with the full exposure prediction model and spot measurements. Self-estimated exposure and geo-coded distance turned out to be poor surrogates for personal exposure.

Quality control for exposure assessment in epidemiological studies

In the framework of an epidemiological study, dosemeters were used for the assessment of radio frequency electromagnetic field exposure. To check the correct dosemeter's performance in terms of consistency of recorded field values over the entire study period, a quality control strategy was developed. In this paper, the concept of quality control and its results is described. From the 20 dosemeters used, 19 were very stable and reproducible, with deviations of a maximum of +/-1 dB compared with their initial state. One device was found to be faulty and its measurement data had to be excluded from the analysis. As a result of continuous quality control procedures, the confidence in the measurements obtained during the field work was strengthened significantly.

A model for radiofrequency electromagnetic field predictions at outdoor and indoor locations in the context of epidemiological research

We present a geospatial model to predict the radiofrequency electromagnetic field from fixed site transmitters for use in epidemiological exposure assessment. The proposed model extends an existing model toward the prediction of indoor exposure, that is, at the homes of potential study participants. The model is based on accurate operation parameters of all stationary transmitters of mobile communication base stations, and radio broadcast and television transmitters for an extended urban and suburban region in the Basel area (Switzerland). The model was evaluated by calculating Spearman rank correlations and weighted Cohen's kappa (kappa) statistics between the model predictions and measurements obtained at street level, in the homes of volunteers, and in front of the windows of these homes. The correlation coefficients of the numerical predictions with street level measurements were 0.64, with indoor measurements 0.66, and with window measurements 0.67. The kappa coefficients were 0.48 (95%-confidence interval: 0.35-0.61) for street level measurements, 0.44 (95%-CI: 0.32-0.57) for indoor measurements, and 0.53 (95%-CI: 0.42-0.65) for window measurements. Although the modeling of shielding effects by walls and roofs requires considerable simplifications of a complex environment, we found a comparable accuracy of the model for indoor and outdoor points.

Conduct of a personal radiofrequency electromagnetic field measurement study: proposed study protocol

BACKGROUND

The development of new wireless communication technologies that emit radio frequency electromagnetic fields (RF-EMF) is ongoing, but little is known about the RF-EMF exposure distribution in the general population. Previous attempts to measure personal exposure to RF-EMF have used different measurement protocols and analysis methods making comparisons between exposure situations across different study populations very difficult. As a result, observed differences in exposure levels between study populations may not reflect real exposure differences but may be in part, or wholly due to methodological differences.

METHODS

The aim of this paper is to develop a study protocol for future personal RF-EMF exposure studies based on experience drawn from previous research. Using the current knowledge base, we propose procedures for the measurement of personal exposure to RF-EMF, data collection, data management and analysis, and methods for the selection and instruction of study participants.

RESULTS

We have identified two basic types of personal RF-EMF measurement studies: population surveys and microenvironmental measurements. In the case of a population survey, the unit of observation is the individual and a randomly selected representative sample of the population is needed to obtain reliable results. For microenvironmental measurements, study participants are selected in order to represent typical behaviours in different microenvironments. These two study types require different methods and procedures.

CONCLUSION

Applying our proposed common core procedures in future personal measurement studies will allow direct comparisons of personal RF-EMF exposures in different populations and study areas.

A prediction model for personal radio frequency electromagnetic field exposure

Radio frequency electromagnetic fields (RF-EMF) in our daily life are caused by numerous sources such as fixed site transmitters (e.g. mobile phone base stations) or indoor devices (e.g. cordless phones). The objective of this study was to develop a prediction model which can be used to predict mean RF-EMF exposure from different sources for a large study population in epidemiological research. We collected personal RF-EMF exposure measurements of 166 volunteers from Basel, Switzerland, by means of portable exposure meters, which were carried during one week. For a validation study we repeated exposure measurements of 31 study participants 21 weeks after the measurements of the first week on average. These second measurements were not used for the model development. We used two data sources as exposure predictors: 1) a questionnaire on potentially exposure relevant characteristics and behaviors and 2) modeled RF-EMF from fixed site transmitters (mobile phone base stations, broadcast transmitters) at the participants' place of residence using a geospatial propagation model. Relevant exposure predictors, which were identified by means of multiple regression analysis, were the modeled RF-EMF at the participants' home from the propagation model, housing characteristics, ownership of communication devices (wireless LAN, mobile and cordless phones) and behavioral aspects such as amount of time spent in public transports. The proportion of variance explained (R2) by the final model was 0.52. The analysis of the agreement between calculated and measured RF-EMF showed a sensitivity of 0.56 and a specificity of 0.95 (cut-off: 90th percentile). In the validation study, the sensitivity and specificity of the model were 0.67 and 0.96, respectively. We could demonstrate that it is feasible to model personal RF-EMF exposure. Most importantly, our validation study suggests that the model can be used to assess average exposure over several months.

Temporal and spatial variability of personal exposure to radio frequency electromagnetic fields

BACKGROUND

Little is known about the population's exposure to radio frequency electromagnetic fields (RF-EMF) in industrialized countries.

OBJECTIVES

To examine levels of exposure and the importance of different RF-EMF sources and settings in a sample of volunteers living in a Swiss city.

METHODS

RF-EMF exposure of 166 volunteers from Basel, Switzerland, was measured with personal exposure meters (exposimeters). Participants carried an exposimeter for 1 week (two separate weeks in 32 participants) and completed an activity diary. Mean values were calculated using the robust regression on order statistics (ROS) method.

RESULTS

Mean weekly exposure to all RF-EMF sources was 0.13 mW/m(2) (0.22 V/m) (range of individual means 0.014-0.881 mW/m(2)). Exposure was mainly due to mobile phone base stations (32.0%), mobile phone handsets (29.1%) and digital enhanced cordless telecommunications (DECT) phones (22.7%). Persons owning a DECT phone (total mean 0.15 mW/m(2)) or mobile phone (0.14 mW/m(2)) were exposed more than those not owning a DECT or mobile phone (0.10 mW/m(2)). Mean values were highest in trains (1.16 mW/m(2)), airports (0.74 mW/m(2)) and tramways or buses (0.36 mW/m(2)), and higher during daytime (0.16 mW/m(2)) than nighttime (0.08 mW/m(2)). The Spearman correlation coefficient between mean exposure in the first and second week was 0.61.

CONCLUSIONS

Exposure to RF-EMF varied considerably between persons and locations but was fairly consistent within persons. Mobile phone handsets, mobile phone base stations and cordless phones were important sources of exposure in urban Switzerland.

Applicability of an exposure model for the determination of emissions from mobile phone base stations

Applicability of a model to estimate radiofrequency electromagnetic field (RF-EMF) strength in households from mobile phone base stations was evaluated with technical data of mobile phone base stations available from the German Net Agency, and dosimetric measurements, performed in an epidemiological study. Estimated exposure and exposure measured with dosemeters in 1322 participating households were compared. For that purpose, the upper 10th percentiles of both outcomes were defined as the 'higher exposed' groups. To assess the agreement of the defined 'higher' exposed groups, kappa coefficient, sensitivity and specificity were calculated. The present results show only a weak agreement of calculations and measurements (kappa values between -0.03 and 0.28, sensitivity between 7.1 and 34.6). Only in some of the sub-analyses, a higher agreement was found, e.g. when measured instead of interpolated geo-coordinates were used to calculate the distance between households and base stations, which is one important parameter in modelling exposure. During the development of the exposure model, more precise input data were available for its internal validation, which yielded kappa values between 0.41 and 0.68 and sensitivity between 55 and 76 for different types of housing areas. Contrary to this, the calculation of exposure-on the basis of the available imprecise data from the epidemiological study-is associated with a relatively high degree of uncertainty. Thus, the model can only be applied in epidemiological studies, when the uncertainty of the input data is considerably reduced. Otherwise, the use of dosemeters to determine the exposure from RF-EMF in epidemiological studies is recommended.