Int. J. Environ. Res. Public Health 2014, 11, 9460-9479; doi:10.3390/ijerph110909460
International Journal of
Environmental Research and
EMF Monitoring—Concepts, Activities, Gaps and Options
Gregor Dürrenberger 1,2,*, Jürg Fröhlich 2,†, Martin Röösli 3,4,† and Mats-Olof Mattsson 5,†
1 Swiss Research Foundation for Electricity and Mobile Communication, c/o Eidgenössische
Technische Hochschule Zürich (ETH Zürich), Gloriastrasse 35, 8092 Zurich, Switzerland
2 Institute for Electromagnetic Fields, Eidgenössische Technische Hochschule Zürich (ETH Zürich),
Gloriastrasse 35, 8092 Zurich, Switzerland; E-Mail: email@example.com
3 Swiss Tropical and Public Health Institute (Swiss TPH), Socinstrasse 59, Postfach, 4002 Basel,
Switzerland; E-Mail: firstname.lastname@example.org
4 University of Basel, 4002 Basel, Switzerland
5 Austrian Institute of Technology (AIT), Konrad-Lorenz-Strasse 24, 3430 Tulln, Austria;
† These authors contributed equally to this work.
* Author to whom correspondence should be addressed; E-Mail: email@example.com;
Tel.: +41-44-632-2815; Fax: +41-44-632-1198.
Received: 26 May 2014; in revised form: 28 August 2014 / Accepted: 29 August 2014 /
Published: 11 September 2014
Abstract: 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.
Int. J. Environ. Res. Public Health 2014, 11 9461
Keywords: electromagnetic fields; exposure monitoring; exposure metrics;
exposure assessment; monitoring paradigm; personal exposure; exposure policy;
epidemiology; public health policy
Public exposure to electromagnetic fields (EMF) is continuously changing in the two main
frequency domains, i.e. radiofrequency (RF; 100 kHz–300 GHz) and extremely low frequency
(ELF; 0 Hz–300 Hz), due to new infrastructure deployments (4th generation mobile phone networks,
smart grids for efficient electricity distribution), smart environments (small-scale wireless sensors,
monitoring and access networks), and new wireless consumer devices. Furthermore, exposure from
applications in the intermediate frequency (IF; 300 Hz–100 kHz) and the terahertz frequency
(TF; >300 GHz) domains will become more prominent in the future [1,2].
Against this background, crucial deficits in current EMF exposure assessment and monitoring have
to be overcome. The key deficit relates to the determination of personal exposure levels. Little reliable
data about personal exposure levels and patterns is available, and nothing is known about (potential)
lifetime exposure of young people. This lack of knowledge increases public concerns about
electromagnetic exposure and potential health risks [3,4], and impedes effective exposure policies
including appropriate risk communication.
Apparently, the lack of monitoring data creates even among experts quite unrealistic perceptions
about the EMF exposure of the population. A recent systematic evaluation of European ELF-EMF
measurement studies concluded that median exposure is about 0.02 µT and only about 5% of the
population is exposed above 0.1 µT . In contrast, according to average exposure ratings done by
39 European experts, roughly 50% of the population would be exposed above 0.1 µT and about
5% above 2 µT (supplementary material B in ).
Regarding exposure policy, protection limits have been suggested by international bodies like the
International Commission on Non-Ionizing Radio Protection (ICNIRP) [6,7] or the International
Commission on Electromagnetic Safety (ICES) . These guidelines protect people from known
health effects with a substantial safety margin (often 50 for the public and 10 for occupationally
exposed people). The fundamental limits (called basic restrictions) refer to the biological effects
induced by incident electromagnetic fields. In the RF range, the relevant quantity of the basic
restriction is the SAR (see next section). In the low frequency and intermediate frequency domain the
induced electric field strength in human tissues is quantified. In the terahertz range power density is
defined as the basic quantity. In 1999, the EU established a common protective framework with a
recommendation on the limitation of the exposure of the general public to electromagnetic fields .
Moreover, in Europe, telecommunications equipment should comply with the RTTE directive which
requires that products comply with the European Council recommendation .
Regarding public concerns: In spite of above mentioned protection limits and regulations, there are
still considerable public concerns about possible health effects induced by EMF, as indicated by the
EUROBAROMETER 2010 survey . There is also considerable public confusion and
Int. J. Environ. Res. Public Health 2014, 11 9462
misunderstandings regarding the ratio and magnitude of the electromagnetic fields within the different
bands as well as the qualitative differences between various sources, for instance close-to-body devices
and infrastructure installations, and their contribution to the total exposure. To respond to these
concerns improved exposure assessment methods and monitoring concepts that generate valid data
about real personal (and average population) exposures in harmonized campaigns have to be developed
In a nutshell: without knowledge about real exposures, health risk assessments cannot be carried
out, policymakers cannot establish evidence-based management measures and effective health risk
communication programs, and industries cannot anticipate neither potential exposure impacts of new
technologies nor potential regulatory developments, entailing, for instance, delays in the growth
of new technology-markets. From this overall perspective, the following scientific challenges
need to be overcome:
Collection of systematic data and establishment of a paradigm to monitor EMF exposure;
Development of appropriate equipment to assess and monitor personal EMF exposures;
Development of appropriate equipment and data interpretation standards for near-field sources
(devices used close to the body) in particular;
Development of reliable exposure assessment methods tailored to the needs of epidemiological studies;
Reduction of the large uncertainties in EMF exposure assessment when carried out by computational
electromagnetics (mostly related to fixed installations).
This paper, first, briefly focuses on the current concepts for EMF exposure monitoring and
associated research challenges. Second, it presents the status of monitoring activities in Europe.
Third, options for personal EMF monitoring approaches will be described and evaluated against the
background of existing concepts. Finally, we conclude with highlighting the relevance of personal
exposure monitoring in light of technology dynamics, research needs and policy requirements.
In conceptual terms, we differentiate in this paper between emission, ambient exposure (sometimes
also termed ―immission‖), personal exposure and dose monitoring . Table 1 characterizes the
concepts as well as the strengths and limitations of these different monitoring concepts.
3. EMF monitoring activities in European Countries
3.1. Existing Reports
The EIS-EMF Project (European Information System on Electromagnetic Fields Exposure and
Health Impacts) performed a general review of the exposure assessment activities . In 2010 and
2014, reports by the European Health Risk Assessment Network on Electromagnetic Fields Exposure
(EFHRAN), a project funded by the European Commission—Executive Agency for Health and
Consumers (EAHC), were issued [5,14], in 2011 a French study summarized ongoing monitoring
activities in Europe , and in 2012 an international survey on RF exposure was published .
The most comprehensive report, which will be discussed in this paper, was published in Switzerland .
Int. J. Environ. Res. Public Health 2014, 11 9463
Table 1. Key monitoring concepts.
Monitoring of radiated power levels of
infrastructure equipment and consumer
devices. Used by regulators to control
power output from single sources
(devices or installations).
Emission monitoring primarily records the power (in Watt) or current
(in Ampere) fed into a source, or measures—generally in close proximity to the
source—the radiated electromagnetic field; i.e., E (electric) fields and H
(magnetic) fields. Well developed for fixed site installations.
For devices worn or carried by a person it is restricted to worst case scenarios
(not to actual emissions). No information about total ambient exposure levels
(distribution, field strengths) or human exposure levels (incident field strengths,
Ambient Exposure Monitoring
Detection of indoor and/or outdoor
field levels. Spatial resolution may vary
from single spot data to rather
comprehensive local or regional data
sets produced by systematic
measurement campaigns or by
Ambient exposure monitoring records the downstream fields (E fields,
H fields), i.e., the fields in the wider environment of a source.
At most places ambient exposures consist of more than just a single source.
Exposure levels are measured either with broadband antennas,
or summed up from frequency selective measurements, or they are calculated by
simulation software. Allows detection of spatial and temporal trends. Outdoor
data cannot be used to extrapolate to indoor data and vice versa. No information
about personal or population exposure because human exposure depends on the
time people spend in a specific environment and includes the exposure from
close-to-body devices. These sources are generally not accounted for in ambient
exposure monitoring campaigns.
Personal Exposure Monitoring
Monitoring of incident field levels at
the location of persons. Measurement
duration ranges typically from a few
hours to a maximum of one week.
Measurement data may be
complemented with activity diary and
Personal exposure monitoring records the fields (E fields, H fields) at the
location of the body, or very close to this location. Because people move,
personal exposure monitoring requires mobile measurements with a portable
This approach takes into consideration the behaviour of the people.
All sources (fixed installations, mobile devices, indoor, outdoor) can be
included. However, exposure from equipment used close to the body (electric
appliances, DECT and mobile phones, other wireless consumer goods) cannot
yet be reliably assessed. The statistical significance of personal exposure data
strongly depends on the number of persons included into a measurement
Assessment of the in-body fields
induced by personal exposure to
external sources. Several dose metrics
The electromagnetic dose is quantified in terms of electric or magnetic fields
strengths or in terms of absorption of energy either per unit mass of tissues (the
Specific Absorption Rate, SAR) or per unit area of exposed tissues (power
density). In the absence of an established biomarker no in-situ measurements
are possible. Dose assessment is based on comprehensive computer simulations.
It is widely used for worst-case calculations in compliance testing. For
monitoring purposes, dose monitoring is not feasible.
According to these documents, most national monitoring activity is oriented towards measurement
campaigns. Modelling is rather exceptional. Monitoring of intermediate frequencies (IF) does not exist
at all, and monitoring of extremely low frequency (ELF) fields is only exceptionally applied.
The most common activity concerns ambient radio frequency (RF) field measurements in response to
citizen requests, mostly in the context of newly erected mobile communication base-station antennas.
Int. J. Environ. Res. Public Health 2014, 11 9464
The design of measurement campaigns in terms of number of sites and applied measurement
protocols differs very much between the countries. This is all the more true for regional monitoring as
implemented, for instance, in some German and some Swiss states. Several campaigns communicate
the data on a web-based platform.
With the notable exception of some epidemiological studies virtually nothing exists on the level of
personal exposure monitoring. One reason for that is the fact that averaging of RF exposure signals is
complex and that a large proportion of collected data is generally below the detection limits of
available measurement equipment .
In the context of a feasibility study on EMF-monitoring options for Switzerland, a small survey
about the state of monitoring activities in Europe was performed in fall 2011. Questionnaires
(Excel sheets) were e-mailed to the country representatives of the COST Action BM0704.
The following countries replied to the questionnaire: Austria, Bulgaria, Croatia, Cyprus, Denmark,
Finland, France, Germany, Greece, Hungary, Ireland, Malta, Norway, The Netherlands, Portugal,
Romania, Slovenia, Slovakia, Spain, Sweden, Switzerland, United Kingdom. For Italy, an important
country in the context of EMF-monitoring, the relevant information was retrieved from published
documents [14,15]. This data was included into the survey-results. The received Excel-sheets were
analyzed manually.If answers were hard to interpret, the respondents were contacted and asked for
We present the findings separately for measurement activities and for modelling/calculation exercises.
For both activities, results are broken down into the ranges ELF (electricity), broadcasting services and
mobile communication services. All responses have been categorized into: no activity, ad-hoc activity
small/limited, ad-hoc activity large, systematic activity small/limited, systematic activity large,
full inventory, no response/other.
The findings (Tables 2 and 3) probably represent the most complete and most up-to-date picture
about EMF monitoring activities in Europe available today. Table 2 summarizes the findings,
Table 3 gives the necessary background information to the summary table. The overall picture
looks as follows:
EMF-monitoring activities are quite common and widely applied in Europe.
Scale and scope of the activities are very diverse (absence of any common framework/paradigm).
Most activity is oriented towards measurement campaigns. Modelling is rather exceptional.
Monitoring of ELF fields does almost not exist.
The most frequent activity concerns field measurements in response to citizen requests, mostly in
the context of newly erected base-station antennas.
The design of measurement campaigns in terms of number of sites and applied measurement
protocol differs very much between the countries.
Several ―systematic‖ measurement campaigns (including web-based communication of the data)
exist in Europe. In some countries (e.g., France), citizen requests led to the collection of a large
amount of measurement data that is analysed as a whole every few years.
Int. J. Environ. Res. Public Health 2014, 11 9465
As a consequence little is known about the real exposure distribution in the population. New
avenues in exposure monitoring would be needed as a countermeasure.
Table 2. Overview of country activities.
Notes: brown color indicates ―yearly, full inventory‖; orange color indicates ―yearly,
large sample‖; yellow color indicates ―yearly, small sample‖; dark green color indicates
―ad hoc, many‖; light green color indicates ―ad hoc, few‖; blue color indicates
―no monitoring‖; grey color indicates ―not specified/other‖.
Table 3. Specification of country activities.
Mobile Communication Networks
ad hoc, and workplace conformity
check by AUVA in case of
suspected problems with limits
ad hoc, and workplace conformity
check by AUVA in case of suspected
problems with limits
ad hoc, and workplace
conformity check by
AUVA in case of
only when antenna characteristics
only when antenna characteristics
all sites every 6 months
all sites every 6 months
measurements at about
Int. J. Environ. Res. Public Health 2014, 11 9466
Table 3. Cont.
Mobile Communication Networks
no activities whatsoever
no activities whatsoever
no activities whatsoever
yearly measurements, sample size 2000 (Radio/TV/Mobile) selected by
chance, total immission
yearly measurements, sample size 150, various selection criteria,
changing sites, total RF immission
about 2500 measurements p.a. at hot spots, mostly requested by
citizens, mostly mobile basestations. 2007 last synthesis report. No
differentiation between broadcasting and mobile communication
ad hoc measurements
20% of all sites selected by chance
sample of 5 installations, yearly
measurements and calculations
sample of 60 installations
(yearly measurements), 25
installations selected for calculations
sample of 5 sites for
since 2003, measurements at 900 installations (mainly base stations).
At present, roughly 20–30 measurements p.a. Frequency selective peak
measurements, no calculations
yearly measurements (various and variable) at several hundred
installations (mainly base stations), broadband measurements, no
differentiation between broadcasting and mobile communication
measurements in Torino
yearly ±10% of all installations
yearly ±10% of all installations
(measurements and calculations)
yearly, all installations (20)
yearly, all installations (500)
measurements: yearly, all installations, and ad hoc on public request;
ad hoc calculations
ad hoc measurements
ad hoc (about 100 measurements p.a., no differentiation between
broadcasting and mobile communication
ad hoc on request, about 20 p.a.
ad hoc on request, about 100 p.a.
10 sites permanent measurements,
and 5 sites annually selected by
chance. Calculations at selected hot
at least all 3 years
measurements at all installation
at least all 3 years measurements at
all installation sites
ad hoc measurements
measurements at a few dozen
yearly monitoring measurements at a
few dozen installations
measurements at a few
Calculations and measurements
at new installations
Calculations and measurements at
new installations, ad hoc
measurements at selected locations,
(24 h data for all sites), systematic
ambient exposure monitoring in
central Switzerland (measurements
ad hoc measurements on request,
roughly 50 sites per year
a few ad hoc
measurements on request
Note: p.a. = per annum
Int. J. Environ. Res. Public Health 2014, 11 9467
4. Moving from Ambient to Personal Exposure Monitoring
The major current monitoring deficiency concerns personal exposure. Ambient data as well as
compliance data do not allow any firm conclusions about levels of personal or population exposure.
Reasons therefore are, among others, first: ambient data are not informative for assessing exposure of
people when the trajectories of movements are unknown. Second, the resolution of ambient data is
often low, especially in the vertical dimension, or very uncertain, for instance regarding absorption and
scattering by environmental structures. Third, worst case data from compliance measurements do not
inform about the power emitted by close-to-body devices in daily use, e.g. mobile phones and tablets.
Personal exposure assessment relating to such devices requires specific equipment and software [18,19]
and is still a research challenge.
In the last few years, this deficiency has been addressed in research. Most past studies have focused
on personal exposure induced by infrastructures like base stations or high voltage power lines or has
considered separately the exposure from infrastructure (e.g., base stations) and those from devices used
close to the body (e.g., mobile phones). The real exposure is in fact induced by both sources
(in the case of mobile communication: the up- and down-link together, for an example see ).
Several studies in the radiofrequency (RF) domain have demonstrated that exposure induced by
devices used close to the body is clearly higher compared to exposure from far-field sources,
i.e., mobile networks, broadcasting or WLAN antennas [19,21–25]. As noted earlier, however,
no exposure assessment paradigm for close-to-body sources that meets monitoring requirements is
available to date. A key objective of current research is therefore to develop monitoring tools for all
types of human exposure.
In the following sub-section we will list and discuss the most common exposure monitoring
options, including gaps and limitations regarding personal exposure assessment. We will differentiate
between options for ambient, personal and close-to-body monitoring approaches (see Table 4),
with latter still lacking any implementable methodology.
Table 4. Exposure monitoring approaches.
in the Paper
Ambient Exposure Monitoring
Fixed Site Transmitter Modelling
High Spatial Resolution Modelling
From third parties’ devices
Personal Exposure Monitoring
Representative Sample with Exposimeters
From third parties’ devices
Quota Sample with Exposimeters
From third parties’ devices
Close-to-body Exposure Monitoring
From own devices
From own devices
Int. J. Environ. Res. Public Health 2014, 11 9468
4.1. Emission Monitoring
So far, most emission monitoring has focused on fixed site transmitters such as mobile phone base
stations or broadcast transmitters. However, for personal exposure monitoring a better understanding
of the emissions from sources close-to body in daily life is needed. Currently, very little is known
about the typical output power of mobile phones in a network and even less when being in
stand-by mode. Output power in stand-by mode is expected to be heavily affected by many factors
such as the type of phone, the configuration of the network, the number of ―apps‖ installed on smart
phones, the behavior of the person (travelling, being inside, outside) etc. . Without such
knowledge, dose estimation cannot be done for real life scenarios.
A main challenge towards this objective is to substitute the current exposure assessment methods
for close-to-body sources, based on worst-case scenarios [26,27], with methods and equipment able to
quantify levels of daily use . The FP7 EU LEXNET project  has started to work to define an
exposure index for selected RF exposures that will aggregate the downlink exposure caused by mobile
phone base stations, the uplink exposure caused by the devices in communication, the different usage
patterns, the category of users, the user posture and device position, the different environments,
the different radio access technologies and layers in the network.
Further, the FP7 EU SEAWIND project  provided a comprehensive assessment of the incident
field exposure of installed wireless local area networks (WLAN or WiFi) or wireless metropolitan area
networks (WMAN or WiMAX), body-mounted and body-worn wireless personal area networks
(WPAN) and WLAN devices. Using high-resolution anatomically MRI-based surface models that
represent a wide spectrum of the human population, the induced fields in the human body will be
4.2. Fixed Site Transmitter Modelling
By means of propagation models, the spatial distribution of average or peak field strengths,
from mainly large infrastructures, is calculated and mapped [31–39]. Radio engineers, for instance,
use such software for radio planning purposes. In the radiofrequency domain, simulation software
generally calculates ambient electric field strengths. The uncertainty of such calculations depends on
the quality of the input data such as the antennae characteristics, building and topographic data.
The application of GISMap software in Switzerland, for instance, resulted in a general uncertainty in
the order of magnitude of ±50% (3–4 dB) for total field strength (data derived from short term
measurements representative for average daytime conditions ). This uncertainty may increase with
a focus on single services or with a reduction of average times; it may decrease with longer average
times and with averaged validation data (instead of spot measurement data). In a sample of
164 volunteers Spearman rank correlation between mean personal mobile phone base station exposure
during one week at all places where people stayed and modeled exposure at home was 0.71 (95%-CI:
0.63 to 0.78) . Similar thinking applies to ELF exposure. However, variability is somewhat less
accentuated and the simulated H-field strengths distribution in space is much more robust compared to
radiofrequency fields. However, the exposure patterns are very local with significant field strengths
(>0.4 µT) in the very close vicinity (±200 m) of power lines only .
Int. J. Environ. Res. Public Health 2014, 11 9469
4.3. High Spatial Resolution Monitoring
In ambient measurement campaigns, exposures at defined locations are recorded [34,37,42–46].
The measurement may be a spot, a short-time (from a few hours to a few days), a long-term
(several weeks or months), or a periodic measurement (e.g., periodic short-time measurements).
Locations for the probes may be selected by random or by systematic sampling. Generally, outdoor
locations are selected, however, indoor levels may also be monitored [47–49]. In case of long-term or
periodic measurements at different locations, the time-series data allow to identify exposure
trends . Depending on the detected frequencies, such data cover selected frequency bands only or
the whole spectrum, i.e., they show trends in background radiation.
Recently ambient field levels have been recorded on pre-defined measurement trajectories in
selected compartments (microenvironments) using portable measurement . A compartment is
defined as a locality which matters in terms of daily human behavior. Examples of compartments are
indoor environments like households, workplaces, shopping centers, etc., outdoor environments like
inner cities, rural recreational areas, suburbs, villages, etc., and mobile environments like commuting
by car, train, bus, or long-distance travelling by car or train.
A campaign may look like this: ten types of compartments (e.g., residential areas, downtown, trains,
railway station, shopping centers, etc.) will be defined and about 5–10 specific compartments per type
will be selected. Measurements will be done on two different measurement trajectories in each
compartment. The measurements are performed twice at different time slots and repeated 3–4 times.
A time slot may cover 10–30 min. The whole campaign can be scheduled once or repeated several
times, e.g., every year, depending on budgetary and statistical requirements.
This monitoring approach allows, first, to identify typical (not: statistically representative) exposure
levels in interested compartments, second, to record overall and compartment specific exposure trends,
third to construct personal exposure profiles based on lifestyles. A lifestyle can be defined with the
help of the number of times a person spends in specific compartments. Personal exposure can then
roughly be assessed for such ideal lifestyles. The approach can also be combined with exposure
modelling [40,52], although exposure from very small installations that do not need an authorization
(e.g., femto cells) can only be included in the measurements but not in the modelling due to lack of
input data. Exposure to fields from electric and wireless appliances used by third parties in the vicinity
is included. However, exposure to devices worn or carried by persons has to be assessed
separately  (see also section 4.4).
In statistical terms, data variability strongly depends on the number of measurement series
performed. In general, the data does not adequately account for daily variations in field levels but is
able to capture long term trends. Weekly variations may be slightly better represented. Because the
equipment is handled and the measurements are performed by professional personnel, following a
defined protocol, the data is reliable and credible.
Another possibility of ambient exposure monitoring is mobile probing . Measurement equipment is
mounted on vehicles, for instance buses, tramways, cabs, rental cars, cars of a business fleet, etc.
Both measurement locations (with the help of GPS data), and measurement times are logged.
This allows covering a larger area and if the data is ―thick‖ enough, it allows mapping ambient
exposures over time. However, the approach is not suitable for indoor sources and—depending on the
Int. J. Environ. Res. Public Health 2014, 11 9470
vehicles used—limited to locations with high population density (e.g., cities) and/or public transportation
coverage. Additionally, the exposure contribution from other people’s mobile phones will be
underestimated, as the distance to the people will be larger than for a person carrying a mobile device.
4.4. Personal Monitoring
The most comprehensive personal exposure monitoring approach consists in selecting a
representative population sample that records for several days personal exposure with the help of an
exposimeter, as in [55,56] and in an exploratory spirit or for feasibility purposes in [57–67].
However, costs for such a campaign are quite high. Representativity of the study sample is difficult to
ensure, since such measurements are demanding for the volunteers and participation rate may be low.
Thus, selection bias is of concern. An alternative is to select subjects from interested lifestyle groups
A personal measurement campaign may look like this: Definition of, for instance, six lifestyle
groups (young urban employee, older urban employee, young rural employee, older rural employee,
older non-employed person, pupil/student). In case of 20 subjects per group and 48-hour measurements
during one week, 240 days of data will be recorded. If six measurement devices are available,
the campaign can be performed in roughly three to four months. Depending on budgetary and
statistical requirements, the sample size could be increased or the measurements could be repeated.
Such data does not allow generalizations to the population at large. Nevertheless, it informs about
typical exposure levels and patterns, about exposure differences between lifestyle groups, and about
exposure trends. Yet, interpretation of the data is challenging. A diary that logs the activities of the
subjects and links this information with the exposure data strongly supports data analysis and
interpretation. It allows, for instance, to identify and compare exposures in/between different
compartments (microenvironments)—indoor, outdoor, on the move—and for different activities. The
latter is especially important for assessing the contribution of exposure from devices used close to the
body to overall personal exposure. However, it has to be noted that presently,
no methodology exists to readily account for this contribution. Such methodology had to meet,
among others, the following challenges associated with the correction of measurement data:
(i) accounting for the distance between consumer device (source) and exposimeter, (ii) respecting the
variability of this distance due to changes in device handling, (iii) incorporating the shielding effects of
the body. It has been suggested that personal distributed exposure meter may be a solution to deal with
this problem .
The validity of the data is lower compared to measurements in compartments because the
equipment is handled by laypersons. Whether the measurement protocols are followed by the subjects
cannot be easily verified.
Another issue is the statistical precision. In several studies personal exposure data was analyzed
with regard to its statistical characteristics [69–73]. In the QUALIFEX project, for instance,
160 subjects were equipped with a personal exposimeter carried during one week. The estimated
uncertainty (expressed as the 95% confidence interval of the estimated mean) for 100 weekly
measurements ranged from ±10% for total exposure, up to ±50% for some specific frequency bands.
Int. J. Environ. Res. Public Health 2014, 11 9471
The data validity from smaller samples can be increased by longer measurement periods, although the
sample size seems to be more crucial than the measurement period.
A future alternative to personal measurements may be crowd sensing, i.e., EMF recording with
modified and/or expanded smartphones used by large populations. This approach may become feasible
at a later stage when enough experiences with personal exposure meters have been collected .
4.5. Dose Modelling, Gaps and Open Issues
To finally model and monitor the EMF dose of the population, the above mentioned components
have to be integrated since direct dose monitoring is very difficult to conduct. First, direct dose
measurements cannot be performed in the absence of an established biomarker. Second, simulations
are subject to significant uncertainties stemming from, among others, complexities of the anatomy of
the human body, uncertainties of tissue parameters, arbitrary choices about the modelling framework,
computer power constraints, and, probably most important, uncertainties about the exposure source
data. In the case of sources used close to the body the uncertainties are even more pronounced because
of large variations in the individual device handlings und usage patterns and of the generally
huge variety of models and technical characteristics of the devices. All these factors contribute
strongly to the dose.
In order to estimate real life doses , source modelling and measurement data will be combined
with detailed digital human models , derived from MRI-scans. In this way not only whole-body
doses, but also organ and tissue specific local doses (e.g., mobile phone radiation, exposures by
electric household appliances) [26,28,76–78] can be estimated. Depending on the health outcome of
interest, different organ or tissue exposures may be relevant. However, this dose modelling is faced
with a series of challenges that have not yet been sufficiently investigated and where only limited
experiences exist :
Near-field (close-to-body) sources: exposure from portable consumer goods (mobile phones,
DECT phones, Bluetooth and WiFi equipment, to list but devices from the RF domain) represent a
major, or even—especially for young people being heavy users of these commodities—the
dominant, source of personal exposure . Better knowledge about the emission patterns of these
sources is needed as mentioned in section 4.1., and has to be combined with not yet existing data on
detailed usage behavior (e.g., duration and posture of use). Potentially, crowd sensing approaches
may also be useful for gaining such data.
Uncertainty assessment: which uncertainty budgets have to be taken into account due to emission
variability of the devices, due to the variability in handling devices (frequency, duration and
practice), and due to the variability in the location of measurement antennas?
Measurement accuracy: what is the uncertainty of personal measurement devices, in particular
regarding crosstalk between adjacent frequency bands, harmonics, or lack of frequency bands in
many current devices [79–84]? Also the impact of body shielding on the measurements has to be
considered [85–87]. Recently, an approach using body worn antennas—e.g., integrated into textiles
for a distributed personal exposimeter —has been proposed to address this problem.
Int. J. Environ. Res. Public Health 2014, 11 9472
Reference volume: what is a biologically sensible and technically feasible reference volume and
what measurement locations (single point, multiple points) have to be selected to realistically cover
the defined volume for personal exposure assessment of far-field sources?
Exposure metrics: no scientifically convincing personal exposure metrics for monitoring purposes
have been established so far. The basic quantity metrics inside the body relates to induced
biological effects, i.e., nerve stimulation and heating. These well-established biological effects are
controlled, for instance, in the ICNIRP guidelines by the basic restrictions [6,7]. However, endpoints
relating to potential non-thermal effects require an exposure metric that takes signal forms and
strengths into account . Such exposure information collected in the context of monitoring
campaigns and/or epidemiological research would have considerable practical relevance.
For instance, the explanatory power of future prospective cohort studies strongly depends on an
exposure metric comprehensive enough to address several potential health endpoints.
Against the background above, Table 5 summarises the significance and limitations of the three
discussed options of personal (population) exposure assessment, i.e., modelling exposure by means of
high spatial resolution monitoring, measuring exposure by means of exposimeters in a representative
sample, measuring exposure by means of exposimeters in a quota sample. In all three approaches,
the assessment of exposure by the (own) use of devices used close to the body still needs to be resolved.
Table 5. Options for Personal Exposure Monitoring.
Different types of
Quick collection of
measurements for a
Representativiy of the measurements
for larger areas, no account for
exposure to own use of
Data for real exposure
Limited reliability of data gathering,
no account for exposure to own use
of close-to-body devices, very
expensive, possible bias in
Quota Sample with
Data for real exposure of
Limited reliability of data gathering,
no account for exposure to own use
of close-to-body devices,
As a key challenge for future EMF monitoring we recognize the need to change from ambient to
personal exposure assessments and eventually to estimate dose for corresponding monitoring.
The drivers behind this need are both technological developments, and increased scientific insights
into biological and health related effects of EMF exposures. The RF studies that have been performed
previously have mainly considered infrastructure or mobile devices separately and therefore do not
provide a clear view of the real personal exposure induced by wireless communication systems.
Int. J. Environ. Res. Public Health 2014, 11 9473
Furthermore, it is expected that the complexity of EMF exposures continues to increase.
This is underlined by the fact that according to EU  the worldwide mobile traffic alone will be
33 times higher by 2030 compared to 2010 figures. To enable such an increase, the future
communication networks will involve, to name but two, more powerful provider infrastructures or/and
mobile data offloading, i.e. the use of complementary small cell technologies like femtocells or WiFi
for delivering data originally targeted for 3G/4G networks. In addition, the current technology
development in the electricity sector towards smart grids will very likely involve new exposure
patterns in the context of smart home technologies and electric vehicles. All these developments will
make exposure assessment and monitoring both complex and inevitably necessary.
The complexity of the assessment and monitoring task is also illustrated by the foreseen expansion
into the IF and TF bands in the near future. An increasing number of devices and processes employing
these frequency domains (household appliances, security devices, telecommunication etc.) will be/are
already introduced into everyday life. Almost nothing is known about these exposures and potential
We identified as a major challenge in the shift from ambient to personal exposure monitoring the
development and implementation of appropriate measurement equipment and methods, and of monitoring
campaigns. Current equipment used to assess EMF exposure has a series of deficiencies for estimating
the real exposure of a person or the population, and / or to reliably monitor personal exposure.
A key deficiency concerns the assessment of exposure from devices used close to the body.
The contribution of this exposure to total personal exposure is significant and cannot be neglected.
In light of these shortcomings and in face of the pressing need to monitor personal EMF exposure
for both health and policy purposes, we discussed two options for assessing human exposure:
first, high resolution measurements of ambient exposure levels in selected compartments
(microenvironments) relevant for daily life; second, personal exposure measurements with portable
devices. Our suggestions are preliminary and have to be further investigated. Epidemiology is
currently the main driver for equipment innovations, and for the paradigm shift from ambient to
personal exposure assessment.
Any sustainable exposure policy relies on public support and acceptance. Without such backing,
it will face citizen and/or local authority opposition, at least in democratic countries.
As the EUROBAROMETER data show, the EMF topic is characterised by general concerns,
and partly inappropriate and volatile perceptions. Without robust data about the real exposure of
people, policy decisions and legislations are hard to ―sell‖, and science and risk communication is
prone to fail. In this view, the development and implementation of a new EMF monitoring paradigm
and approach oriented towards personal exposure is a necessary step for both an evidence-based
exposure policy and a pro-active communication about human EMF exposure.
This paper was partly funded by BAFU, grant 07.0111.PJ/273-0769, and AWEL. We thank the
following colleagues for support and input: Alfred Bürgi, Patrizia Frei, Wout Joseph, Sven Kühn,
Niels Kuster, Oliver Lauer, Marta Parazzini, Paolo Ravazzani, Joe Wiart.
Int. J. Environ. Res. Public Health 2014, 11 9474
Gregor Dürrenberger prepared the original draft, which was revised by all authors. All authors read
and approved the final manuscript.
Conflicts of Interest
The authors declare no conflict of interest. Gregor Dürrenberger is with the Swiss Research
Foundation for Electricity and Mobile Communication (FSM), a not-for-profit organization which
receives funds from industry. Firewalls guarantee full scientific independence of both funding
decisions and researching. Martin Röösli is member of the board, Jürg Fröhlich is member of the FSM
scientific committee, and Gregor Dürrenberger, Martin Röösli and Jürg Fröhlich are among FSM grant
holders. Jürg Fröhlich is also with the company Fields at Work LLC which develops exposure
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