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EMF Monitoring-Concepts, Activities, Gaps and Options

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Abstract and Figures

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.
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Int. J. Environ. Res. Public Health 2014, 11, 9460-9479; doi:10.3390/ijerph110909460
International Journal of
Environmental Research and
Public Health
ISSN 1660-4601
www.mdpi.com/journal/ijerph
Article
EMF MonitoringConcepts, 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: j.froehlich@ifh.ee.ethz.ch
3 Swiss Tropical and Public Health Institute (Swiss TPH), Socinstrasse 59, Postfach, 4002 Basel,
Switzerland; E-Mail: martin.roosli@unibas.ch
4 University of Basel, 4002 Basel, Switzerland
5 Austrian Institute of Technology (AIT), Konrad-Lorenz-Strasse 24, 3430 Tulln, Austria;
E-Mail: mats-olof.mattsson@ait.ac.at
These authors contributed equally to this work.
* Author to whom correspondence should be addressed; E-Mail: gregor@emf.ethz.ch;
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.
OPEN ACCESS
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
1. Introduction
Public exposure to electromagnetic fields (EMF) is continuously changing in the two main
frequency domains, i.e. radiofrequency (RF; 100 kHz300 GHz) and extremely low frequency
(ELF; 0 Hz300 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 Hz100 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 [5]. 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 [5]).
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) [8]. 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 [9].
Moreover, in Europe, telecommunications equipment should comply with the RTTE directive which
requires that products comply with the European Council recommendation [10].
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 [11]. 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
and implemented.
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.
2. Concepts
In conceptual terms, we differentiate in this paper between emission, ambient exposure (sometimes
also termed ―immission), personal exposure and dose monitoring [12]. 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 [13]. In 2010 and
2014, reports by the European Health Risk Assessment Network on Electromagnetic Fields Exposure
(EFHRAN), a project funded by the European CommissionExecutive Agency for Health and
Consumers (EAHC), were issued [5,14], in 2011 a French study summarized ongoing monitoring
activities in Europe [15], and in 2012 an international survey on RF exposure was published [16].
The most comprehensive report, which will be discussed in this paper, was published in Switzerland [12].
Int. J. Environ. Res. Public Health 2014, 11 9463
Table 1. Key monitoring concepts.
Monitoring Concept
Characterisation
Emission Monitoring
Monitoring of radiated power levels of
infrastructure equipment and consumer
devices. Used by regulators to control
legislated/standardised maximum
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 measuresgenerally in close proximity to the
sourcethe 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,
absorbed dose).
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
propagation modelling.
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
GPS data.
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
device (exposimeter).
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
campaign.
Dose Monitoring
Assessment of the in-body fields
induced by personal exposure to
external sources. Several dose metrics
exist.
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 [17].
3.2. Survey
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
short clarifications.
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.
Country
Measurements
Radio/TV
Mobile
ELF
Radio/TV
Mobile
ELF
Austria
Bulgaria
Cyprus
Denmark
Germany
Spain
Finland
France
Greece
Hungary
Ireland
Italy
Croatia
Malta
Netherlands
Norway
Portugal
Romania
Sweden
Slovakia
Slovenia
Switzerland
U.K.
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.
Country
Radio/TV
Mobile Communication Networks
ELF
Austria
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
suspected problems
with limits
Bulgaria
only when antenna characteristics
change
only when antenna characteristics
change
measurements when
antenna characteristics
change
Cyprus
all sites every 6 months
all sites every 6 months
measurements at about
10,000 locations
Int. J. Environ. Res. Public Health 2014, 11 9466
Table 3. Cont.
Country
Radio/TV
Mobile Communication Networks
ELF
Denmark
no activities whatsoever
no activities whatsoever
no activities whatsoever
Germany
yearly measurements, sample size 2000 (Radio/TV/Mobile) selected by
chance, total immission
no monitoring
Spain
yearly measurements, sample size 150, various selection criteria,
changing sites, total RF immission
new infrastructure;
measurement protocol
not specified
Finland
ad hoc
ad hoc
ad hoc
France
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
Greece
ad hoc
20% of all sites selected by chance
ad hoc
Hungary
sample of 5 installations, yearly
measurements and calculations
sample of 60 installations
(yearly measurements), 25
installations selected for calculations
sample of 5 sites for
yearly measurements
Ireland
since 2003, measurements at 900 installations (mainly base stations).
At present, roughly 2030 measurements p.a. Frequency selective peak
measurements, no calculations
ad hoc
Italy
yearly measurements (various and variable) at several hundred
installations (mainly base stations), broadband measurements, no
differentiation between broadcasting and mobile communication
measurements in Torino
(20062008)
Croatia
yearly ±10% of all installations
(measurements and
calculations)
yearly ±10% of all installations
(measurements and calculations)
not specified
Malta
yearly, all installations (20)
yearly, all installations (500)
not specified
Netherlands
measurements: yearly, all installations, and ad hoc on public request;
ad hoc calculations
ad hoc measurements
Norway
ad hoc
ad hoc
ad hoc
Portugal
ad hoc (about 100 measurements p.a., no differentiation between
broadcasting and mobile communication
not specified
Romania
ad hoc on request, about 20 p.a.
ad hoc on request, about 100 p.a.
not specified
Sweden
no monitoring
10 sites permanent measurements,
and 5 sites annually selected by
chance. Calculations at selected hot
spots
no monitoring
Slovakia
at least all 3 years
measurements at all installation
sites
at least all 3 years measurements at
all installation sites
ad hoc measurements
and calculations
Slovenia
yearly monitoring
measurements at a few dozen
installations
yearly monitoring measurements at a
few dozen installations
yearly monitoring
measurements at a few
dozen installations
Switzerland
Calculations and measurements
at new installations
Calculations and measurements at
new installations, ad hoc
measurements at selected locations,
emission monitoring
(24 h data for all sites), systematic
ambient exposure monitoring in
central Switzerland (measurements
and calculations)
Calculations and
measurements at
new installations
UK
no 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 [20]).
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 [19,2125]. 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.
Approach
Section
in the Paper
Exposure
to Installations
Exposure to
Close-to-Body Devices
Ambient Exposure Monitoring
Fixed Site Transmitter Modelling
4.2
Outdoor
No
High Spatial Resolution Modelling
4.3
Outdoor, indoor
From third parties devices
Personal Exposure Monitoring
Representative Sample with Exposimeters
4.4
Outdoor, indoor
From third parties devices
Quota Sample with Exposimeters
4.4
Outdoor, indoor
From third parties devices
Close-to-body Exposure Monitoring
Emission Monioring
4.1
No
From own devices
Exposure Measurements
4.5
No
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. [25]. 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 [28]. The FP7 EU LEXNET project [29] 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 [30] 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
numerically determined.
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 [3139]. 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% (34 dB) for total field strength (data derived from short term
measurements representative for average daytime conditions [32]). 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) [40]. 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 [41].
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 [34,37,4246].
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 [4749]. In case of long-term or
periodic measurements at different locations, the time-series data allow to identify exposure
trends [50]. 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 [51]. 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 510 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 34 times.
A time slot may cover 1030 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 [53] (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 [54]. 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 anddepending on the
Int. J. Environ. Res. Public Health 2014, 11 9470
vehicles usedlimited 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 [5767].
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
(quota sampling).
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 moveand 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 [68].
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 [6973]. 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 [74].
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 [28], source modelling and measurement data will be combined
with detailed digital human models [75], 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) [26,28,7678] 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 [79]:
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 evenespecially for young people being heavy users of these commoditiesthe
dominant, source of personal exposure [69]. 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 [7984]? Also the impact of body shielding on the measurements has to be
considered [8587]. Recently, an approach using body worn antennase.g., integrated into textiles
for a distributed personal exposimeter [68]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 [88]. 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.
Approach
Selection Criteria
Significance
Limitations
High Spatial
Resolution Monitoring
Different types of
compartments
(microenvironments)
Quick collection of
highly reproducible
measurements for a
wider range
of compartments
Representativiy of the measurements
for larger areas, no account for
exposure to own use of
close-to-body devices
Representative Sample
with Exposimeters
Random or
convenient
population sample
Data for real exposure
of population
Limited reliability of data gathering,
no account for exposure to own use
of close-to-body devices, very
expensive, possible bias in
volunteer selection
Quota Sample with
Exposimeters
Life-style groups
Data for real exposure of
selected sub-populations
(real types)
Limited reliability of data gathering,
no account for exposure to own use
of close-to-body devices,
very expensive
5. Conclusions
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 [89] 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
exposure levels.
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.
Acknowledgments
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 hn,
Niels Kuster, Oliver Lauer, Marta Parazzini, Paolo Ravazzani, Joe Wiart.
Int. J. Environ. Res. Public Health 2014, 11 9474
Author Contributions
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 rg Fröhlich are among FSM grant
holders. Jürg Fröhlich is also with the company Fields at Work LLC which develops exposure
measurement equipment.
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... Assessment of RF environmental EMF is needed to investigate real-life in situ exposure to EMF caused by existing and new (5G) telecommunication and broadcasting technologies. These environmental fields are not only caused by telecommunication base stations and broadcasting antennas, but also by the users (mobile) devices [86], [87]. ...
... To assess environmental RF-EMF, different measurement setups and protocols have been proposed. These can be categorized as: spot measurements using accurate spectral equipment (narrow-band measurements) or broadband meters [86], [87]; personal exposure meter (exposimeter) setups for microenvironmental (urban, rural, schools, homes, and public places) or population studies (surveys) (e.g., [88]); and spatial-temporal field mapping using fixed and mobile RF sensors placed in cities [89]. ...
Article
This article reviews recent standardization activities and scientific studies related to the assessment of human exposure to electromagnetic fields (EMF). The differences of human exposure standards and assessment of consumer products and medical applications are summarized. First, we reviewed human body modeling and tissue dielectric properties. Then, we explain the rationale of current exposure standards from the viewpoint of EMF and the standardization process for product compliance based on these exposure standards. The assessment of wireless power transfer, as an example of emerging wireless devices, and environmental EMFs in our daily lives are reviewed. Safety in magnetic resonance systems, where the EMF exposure is much larger than from typical consumer devices, is also reviewed. Finally, we summarize future research directions and research needs for EMF safety.
... With the introduction of new generation of wireless communication technologies and the Smart Concept worldwide, an expanding demand with huge increase in data transmission has presented, mostly, in the last decade, outpacing current capacity and increasing the RF-EMF exposure associated [29]- [31]. Nevertheless, communication technology systems have become more efficient and effective at the same time [32]- [35]. ...
... Nevertheless, communication technology systems have become more efficient and effective at the same time [32]- [35]. Consequently, personal RF-EMF exposure assessment is influenced by many variables which in turn, contribute to a complex and challenging characterization and evaluation where generalization do not apply [29], [36]- [41]. ...
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This work provides an intensive and comprehensive in-depth study from an empirical and modeling approach of the environmental radiofrequency electromagnetic fields (RF-EMF) radiation exposure in public shopping malls, as an example of an indoor high-node user density context aware environment, where multiple wireless communication systems coexist. For that purpose, current personal mobile communications (2G-5G FR 1) as well as Wi-Fi services (IEEE 802.11n/ac) have been precisely analyzed in order to provide clear RF-EMF assessment insight and to verify compliance with established regulation limits. In this sense, a complete measurements campaign has been performed in different countries, with frequency-selective exposimeters (PEMs), providing real empirical datasets for statistical analysis and allowing discussion and comparison regarding current health effects and safety issues between some of the most common RF-EMF exposure safety standards: ICNIRP 2020 (Spain), IEEE 2019 (Mexico) and a more restrictive regulation (Poland). In addition, environmental RF-EMF exposure assessment simulation results, in terms of spatial E-field characterization and Cumulative Distribution Function (CDF) probabilities, have been provided for challenging incremental high-node user dense scenarios in worst case conditions, by means of a deterministic in-house 3D Ray-Launching (3D-RL) RF-EMF safety simulation technique, showing good agreement with the experimental measurements. Finally, discussion highlighting the contribution and effects of the coexistence of multiple heterogenous networks and services for the environmental RF-EMF radiation exposure assessment has been included, showing that for all measured results and simulated cases, the obtained E-Field levels are well below the exposure limits established in the internationally accepted standards and guidelines. In consequence, the obtained results and the presented methodology could become a starting point to stablish the RF-EMF assessment basis of future complex heterogeneous 5G FR 2 developments on the millimeter wave (mmWave) frequency range, where massive high-node user density networks are expected.
... Wo sinnvoll und informativ, wird aber ergänzend auf entsprechende Befunde hingewiesen. (Dürrenberger, Fröhlich et al. 2014) oder (Dürrenberger, Leuchtmann et al. 2017). ...
... Ungenauer sind Messungen (der persönlichen Exposition) mit am Körper getragenen Messgerätenvgl. etwa mit (Hwang, Kwak et al. 2016), (Dürrenberger, Fröhlich et al. 2014). ...
Technical Report
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Der vorliegende Bericht stellt den Stand des Wissens zu gesundheitlichen Effekten von Hochspan-nungsleitungen (HSL) zusammen, wobei Hybridleitungen speziell beachtet werden. Es werden alle von HSL verursachten Expositionen behandelt, also magnetische Felder, elektrische Felder, Lärm, Ionen-ströme, Aerosole und Luftschadstoffe.
... 2) Population-based Studies: The studies belonging to this category aim at investigating the relationship between people affected by severe diseases (e.g., brain tumors) and the level exposure from base stations and/or UE. We do not intentionally focus on population-based studies tailored to base stations exposure, due to the following reasons: 1) base stations represent a minor source of exposure compared to UE (as proven by previous works e.g., [61], [62]); 2) the exposure from base stations tend to be notably reduced as the distance between the base stations, and the user is increased (see, e.g., [63], [64]) and more in general when indoor conditions are experienced (see, e.g., [65]); 3) previous population-based studies (see, e.g., the note [66] of the American Cancer Society and the comprehensive work of [67]) did not found any causal relationship between the exposure from base stations and the increase in the risk of developing tumors. ...
... Focusing then on population-based studies on UE exposure, it is well known that this RF source represents a major source of exposure in proximity to users (see e.g. [61], [62]). Therefore, we consider here population-based studies that aim at finding a causal correlation between emergence of tumors and UE exposure. ...
Preprint
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The deployment of the fifth-generation (5G) wireless communication services requires the installation of 5G next-generation Node-B Base Stations (gNBs) over the territory and the wide adoption of 5G User Equipment (UE). In this context, the population is concerned about the potential health risks associated with the Radio Frequency (RF) emissions from 5G equipment, with several communities actively working toward stopping the 5G deployment. To face these concerns, in this work, we analyze the health risks associated with 5G exposure by adopting a new and comprehensive viewpoint, based on the communications engineering perspective. By exploiting our background, we investigate the alleged health effects of 5G exposure and critically review the latest works that are often referenced to support the health concerns from 5G. We then precisely examine the up-to-date metrics, regulations, and assessment of compliance procedures for 5G exposure, by evaluating the latest guidelines from the Institute of Electrical and Electronics Engineers (IEEE), the International Commission on Non-Ionizing Radiation Protection (ICNIRP), the International Telecommunication Union (ITU), the International Electrotechnical Commission (IEC), and the United States Federal Communications Commission (FCC), as well as the national regulations in more than 220 countries. We also thoroughly analyze the main health risks that are frequently associated with specific 5G features (e.g., multiple-input multiple-output (MIMO), beamforming, cell densification, adoption of millimeter waves, and connection of millions of devices). Finally, we examine the risk mitigation techniques based on communications engineering that can be implemented to reduce the exposure from 5G gNB and UE. Overall, we argue that the widely perceived health risks that are attributed to 5G are not supported by scientific evidence from communications engineering. In addition, we explain how the solutions to minimize the health risks from 5G (including currently unknown effects) are already mature and ready to be implemented. Finally, future works, e.g., aimed at evaluating long-term impacts of 5G exposure, as well as innovative solutions to further reduce the RF emissions, are suggested.
... Other sources such as Wi-Fi, other communications systems, and some household appliances contribute greater or lesser amounts to the total exposure depending on local circumstances. Dürrenberger et al. noted that the dramatic increase in data traffic in the coming decades added to the emergence of smart electrical grids will alter exposure characteristics throughout the population (Dürrenberger et al. 2014). Thus, it seems apparent that extrapolating from the current exposure patterns to those in the future is not possible with any certainty. ...
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This COMAR Technical Information Statement (TIS) addresses health and safety issues concerning exposure of the general public to radiofrequency (RF) fields from 5G wireless communications networks, the expansion of which started on a large scale in 2018 to 2019. 5G technology can transmit much greater amounts of data at much higher speeds for a vastly expanded array of applications compared with preceding 2-4G systems; this is due, in part, to using the greater bandwidth available at much higher frequencies than those used by most existing networks. Although the 5G engineering standard may be deployed for operating networks currently using frequencies extending from 100s to 1,000s of MHz, it can also operate in the 10s of GHz where the wavelengths are 10 mm or less, the so-called millimeter wave (MMW) band. Until now, such fields were found in a limited number of applications (e.g., airport scanners, automotive collision avoidance systems, perimeter surveillance radar), but the rapid expansion of 5G will produce a more ubiquitous presence of MMW in the environment. While some 5G signals will originate from small antennas placed on existing base stations, most will be deployed with some key differences relative to typical transmissions from 2-4G base stations. Because MMW do not penetrate foliage and building materials as well as signals at lower frequencies, the networks will require "densification," the installation of many lower power transmitters (often called "small cells" located mainly on buildings and utility poles) to provide for effective indoor coverage. Also, "beamforming" antennas on some 5G systems will transmit one or more signals directed to individual users as they move about, thus limiting exposures to non-users. In this paper, COMAR notes the following perspectives to address concerns expressed about possible health effects of RF field exposure from 5G technology. First, unlike lower frequency fields, MMW do not penetrate beyond the outer skin layers and thus do not expose inner tissues to MMW. Second, current research indicates that overall levels of exposure to RF are unlikely to be significantly altered by 5G, and exposure will continue to originate mostly from the "uplink" signals from one's own device (as they do now). Third, exposure levels in publicly accessible spaces will remain well below exposure limits established by international guideline and standard setting organizations, including ICNIRP and IEEE. Finally, so long as exposures remain below established guidelines, the research results to date do not support a determination that adverse health effects are associated with RF exposures, including those from 5G systems. While it is acknowledged that the scientific literature on MMW biological effect research is more limited than that for lower frequencies, we also note that it is of mixed quality and stress that future research should use appropriate precautions to enhance validity. The authorship of this paper includes a physician/biologist, epidemiologist, engineers, and physical scientists working voluntarily and collaboratively on a consensus basis.
... However, the reader should be aware that this chapter only explores one facet of the problem: other potential risks, which are less criticized, may exist, in particular with regards to the personal consumption of new communication technologies. Indeed, a more frequent utilization of smartphones determined by the growing compulsion for mobile services causes an inherent higher exposure of individuals to the EMFs generated by the end terminals themselves -which, in fact, are often the main source of EMFs in the proximity of users already today [3,4,5,6]. ...
Chapter
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The deployment of a new generation of mobile communication networks requires the installation of a dedicated radio access infrastructure. In the case of 5G, this unavoidable practice is creating a controversy about the potential issues for the public health that new radio base stations may entail. In this chapter, we discuss five major health risk allegations against 5G, namely: (i) the links between insurgence of tumors and exposure to ElectroMagnetic Fields (EMFs) generated by 5G; (ii) the increase of EMF levels due to an uncontrolled proliferation of 5G sites; (iii) the health risks associated to emissions in the new mm-Wave spectrum adopted by 5G; (iv) the uncertainty about the actual 5G EMF emission levels caused by the absence of dedicated measurements; (v) the impossibility to remove the previous uncertainty determined by the lack of measurement tools suitable for 5G technologies. We examine these arguments from an engineering perspective, by tacking into account the outcome of state-of-the-art scientific studies, the current relevant regulations and the technical features of 5G technologies. Our review indicates that there is no incontrovertible scientific evidence supporting any of the five claims. While we second the need for further investigations, we also remark a factual fabrication of fake news on the risks of 5G for the public health, which may severely distort the perception of this technology by the population at large.
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Hospitals and healthcare centers are experiencing a remarkable implementation of new systems based on wireless communications technologies. Many of these systems provide location services and identification of materials, instrumentation and even patients, which promotes the increase of the quality and the efficiency of healthcare. A tracking system based on short-range radio frequency, UHF-RFID is evaluated. This system helps with location of orthopedic prosthesis according to the criteria and requirements of a specific hospital environment. It is characterized the influence of UHF-RFID system in the electromagnetic environment by measuring the parameters and characteristics of the emission levels. The results of the assessment are represented through 2D contour maps and simulations have been performed by means of an in-house 3D-RL algorithm. The proposed graph aims to provide a methodology of studying the electromagnetic environments and the evaluation of the safety conditions of workers, patients, and people in general. E field exposure levels due to the RFID localization system were analyzed in order to verify regulations concerning the safety of patients and the general public in the labor and healthcare fields. Localized electromagnetic field exposure at levels which may cause electromagnetic hazards in the specific healthcare environment have been found and potentially excessive exposure to EMF emitted by UHF RFID devices may apply to patients or bystanders. In all cases, insufficient electromagnetic immunity of electronic devices (including AIMD and other medical devices) should be considered and the electromagnetic hazards may be limited also by relevant preventive measures, as also shown in this paper, together with the principles of an in-situ evaluation of electromagnetic hazards near the UHF-RFID devices.
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In an increasingly wireless world, spatiotemporal monitoring of the exposure to environmental radiofrequency (RF) electromagnetic fields (EMF) is crucial to appease public uncertainty and anxiety about RF-EMF. However, although the advent of smart city infrastructures allows for dense networks of distributed sensors, the costs of accurate RF sensors remain high, and dedicated RF monitoring networks remain rare. This paper describes a comprehensive study comprising the design of a low-cost RF-EMF sensor node capable of monitoring four frequency bands used by wireless telecommunications with an unparalleled temporal resolution, its application in a small-scale distributed sensor network consisting of both fixed (on building façades) and mobile sensor nodes (on postal vans), and the subsequent analysis of over a year of data between January 2019 and May 2020, during which slightly less than 10 million samples were collected. From the fixed nodes’ results, the potential errors were determined that are induced when sampling at lower speeds (e.g., one sample per 15 min) and measuring for shorter periods of time (e.g., a few weeks), as well as an adequate resolution (30 min) for diurnal and weekly temporal profiles which sufficiently preserves short-term variations. Furthermore, based on the correlation between the sensors, an adequate density of 100 sensor nodes per km² was deduced for future networks. Finally, the mobile sensor nodes were used to identify potential RF-EMF exposure hotspots in a previously unattainable area of more than 60 km². In summary, through the analysis of a small number of RF-EMF sensor nodes (both fixed and mobile) in an urban area, this study offers invaluable insights applicable to future designs and deployments of distributed RF-EMF sensor networks.
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The specific absorption rate (SAR) induced by wireless radiofrequency (RF) systems depends on different parameters. Previously, SAR was mainly assessed under conditions of a single frequency and technology and for a limited number of localized RF sources. The current and emerging mobile systems involve a wider range of usage scenarios and are frequently used simultaneously, leading to combined exposures for which almost no exposure evaluation exists. The aim and novelty of this study is to close this gap of knowledge by developing new methods to rapidly evaluate the SAR induced by RF systems in such scenarios at frequencies from 50 MHz to 5.5 GHz. To this aim, analytical methods for SAR estimation in several usage scenarios were derived through a large-scale numerical study. These include subject-specific characteristics, properties of the RF systems and provide an estimation of the SAR in the whole body, tissues and organs, and different brain regions.
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Over the last two decades residential exposure to extremely low frequency magnetic fields (ELF MF) has been associated with childhood leukaemia relatively consistently in epidemiological studies, though causality is still under investigation. We aimed to estimate the cases of childhood leukaemia that might be attributable to exposure to ELF MF in the European Union (EU27), if the associations seen in epidemiological studies were causal. We estimated distributions of ELF MF exposure using studies identified in the existing literature. Individual distributions of exposure were integrated using a probabilistic mixture distribution approach. Exposure-response functions were estimated from the most recently published pooled analysis of epidemiological data. Probabilistic simulation was used to estimate population attributable fractions (AFP) and attributable cases of childhood leukaemia in the EU27. By assigning the literature review-based exposure distribution to all EU27 countries, we estimated the total annual number of cases of leukaemia attributable to ELF MF at between ~50 (95% CIs: -14, 132) and ~60 (95% CIs: -9, 610), depending on whether exposure-response was modelled categorically or continuously, respectively, for a non-threshold effect. This corresponds to between ~1.5% and ~2.0% of all incident cases of childhood leukaemia occurring annually in the EU27. Considerable uncertainties are due to scarce data on exposure and the choice of exposure-response model, demonstrating the importance of further research into better understanding mechanisms of the potential association between ELF MF exposure and childhood leukaemia and the need for improved monitoring of residential exposures to ELF MF in Europe.
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Within the QUALIFEX project, personal radio frequency electromagnetic field (RF-EMF) exposure was measured. The aim of this publication is to give an overview of the RF-EMF exposure distribution in a Swiss population sample and to evaluate different exposure assessment methods regarding their application in epidemiological studies. Personal RF-EMF exposure of 166 volunteers from Basel, Switzerland, was measured during one week with portable exposure meters. In addition, a geospatial propagation model was developed to predict RF-EMF exposure from fixed site transmitters at study participants' residencies. Self-reported mobile and cordless phone use of a randomly selected population sample (n = 1.375) were collected and for a subsample (n = 437) objective operator data of network providers were available for the previous 4 to 6 months. Mean weekly exposure of all 166 volunteers was 0, 22 V/m (range: 0, 07-0, 58 V/m).Total exposure was mainly due to mobile phone base stations, mobile phone handsets and cordless phones. Predicted exposure at home from the geospatial propagation model correlated with the corresponding measured mean exposure (rank correlation: 0, 72) as well as with the measured mean exposure from fixed site transmitters at all places where study participants stayed during one week (rank correlation: 0, 57). The rank correlation between self-reported mobile phone use and operator data was 0, 78. The QUALIFEX study provides important information on the RF-EMF exposure distribution in the general population and for the conduct of epidemiological studies. With regard to future technical developments, it is important that exposure of the population is monitored continuously and that exposure assessment methods are adapted if necessary.
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A novel, car based, measuring system for estimation of general public outdoor exposure to radiofrequency fields (RF) has been developed. The system enables fast, large area, isotropic spectral measurements with a bandwidth covering the frequency range of 30 MHz to 3 GHz. Measurements have shown that complete mapping of a town with 15000 inhabitants and a path length of 115 km is possible to perform within 1 day. The measured areas were chosen to represent typical rural, urban and city areas of Sweden. The data sets consist of more than 70000 measurements. All measurements were performed during the daytime. The median power density was 16 µW/m(2) in rural areas, 270 µW/m(2) in urban areas, and 2400 µW/m(2) in city areas. In urban and city areas, base stations for mobile phones were clearly the dominating sources of exposure. Bioelectromagnetics © 2013 Wiley Periodicals, Inc.
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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.Journal of Exposure Science and Environmental Epidemiology advance online publication, 14 August 2013; doi:10.1038/jes.2013.40.