Panagopoulos DJ (Ed.). (2022). Electromagnetic Fields of Wireless Communications: Biological and Health Effects (1st ed.). CRC Press. doi: 10.1201/9781003201052.
Friday, January 13, 2023
Tuesday, January 3, 2023
- ICBE-EMF scientists report that exposure limits for radiofrequency (or wireless) radiation set by ICNIRP and the FCC are based on invalid assumptions and outdated science, and are not protective of human health and wildlife.
- ICBE-EMF calls for an independent assessment of the effects and risks of radiofrequency radiation based on scientific evidence from peer-reviewed studies conducted over the past 25 years. The aim of such assessment would be to establish health protective exposure standards for workers, the public, and the environment.
- The public should be informed of the health risks of wireless radiation and encouraged to take precautions to minimize exposures, especially for children, pregnant women and people who are electromagnetically hypersensitive.
- ICBE-EMF calls for an immediate moratorium on further rollout of 5G wireless technologies until safety is demonstrated and not simply assumed.
Hinrikus H, Koppel T, Lass J, Roosipuu P, Bachmann M. Limiting exposure to radiofrequency radiation: the principles and possible criteria for health protection. International Journal of Radiation Biology. 2022. doi:10.1080/09553002.2023.2159
Purpose. The current paper is aimed to discuss the principles and criteria for health protection to radiofrequency electromagnetic field (RF EMF) considering both thermal and non-thermal mechanisms to evaluate the reasonable level for the limits relevant to control the level of RF EMF for the general public in the living environment. The study combines the conclusions of analyses published in recent reviews on RF EMF effects and the data from RF EMF measurements in different countries to select the possible criteria and to derive proposals for the health protection limits on the level of RF EMF following the ALARA principle - as low as reasonably achievable.
Conclusions. Consideration of not only energetic but also coherent qualities of RF EMF leads to two different models for determining the impact of non-ionizing radiation on human health. The thermal model, based on absorption of electromagnetic energy, has a threshold limiting the heating of tissues. The non-thermal model, based on the ability of coherent electric fields to introduce biological effects at constant temperature, has no threshold. Therefore, the impact of RF EMF on human health cannot be excluded but can be minimized by limiting the level of the radiation. The limits can be selected based on indirect criteria. The minimal level of RF EMF that has caused a biological effect is about 2 V/m. The level of long-term broadcast radiation is 6 V/m and the people can be assumed to be adapted to that level without observable health problems. The level of RF EMF measured during last years does not exceed 5 V/m and the level is decreasing with newer generations of telecommunication technology. Limiting the level of RF EMF to the peak value of 6 V/m hopefully reduces the health risk to a minimal level people are adapted to and does not restrict the further development of telecommunication technology.
The consideration of not only energetic but also coherent qualities of RF EMF leads to two different models in investigation of RF EMF biological effects and determining the impact of the non-ionizing radiation on human health. The thermal model based on absorption of electromagnetic energy has a threshold limiting the heating of tissues. The non-thermal model based on the ability of coherent electric fields to introduce biological effects at the constant temperature has no threshold. The impact of RF EMF on human health cannot be excluded but can be reduced, limiting the level of the radiation.
The limit, due to the missing threshold, can be selected based on indirect criteria. The minimal levels of RF EMF that have caused a biological effect are 1.4 - 2.45 V/m. The level of long-term broadcast radiation is 6 V/m; people can be assumed to be adapted to that level. The results of measurements over the last decade indicated the level of RF EMF lower than 5 V/m. The majority of measurements have indicated much lower levels. All these values are of the same order of magnitude.
Limiting the level of EF EMF to the peak value of 6 V/m hopefully reduces the health risk to a minimal level determined by long existing broadcast radiation people are adapted to without restricting the further development of telecommunication technology. The technology of telecommunication systems is in permanent progress. The newer generations of technology employ lower levels of radiation, shorter time intervals and less energy to provide high quality and speed for transmission of information. Switching off older generations (2G, 3G), accompanying the development of technology today, significantly reduces the level of RF EMF and therefore also reduces the possible health risk.
The current level of knowledge allows us to formulate the suggestions only for the threshold and frequency dependence in the models for RF EMF impact. The dynamic relationships between the intensity of the effect and the level of RF EMF or time spent in the radiation are still unknown. The temporal dynamics is most complicated to be assessed because people and animals are living permanently in RF EMF. Further investigations are highly needed for long-term RF EMF effects and in the frequency range higher than 6000 MHz.https://www.tandfonline.com/
McCredden JE, Cook N, Weller S, Leach V. Wireless technology is an environmental stressor requiring new understanding and approaches in health care Front. Public Health, 20 December 2022. doi: 10.3389/fpubh.2022.986315.
Indeed, the data from ODEB (see Table 1) corroborates the above research findings, by showing that the type of signal used: real or simulated, can affect study outcomes. Within the 1,106 relevant experimental papers selected from ODEB using the quality of reporting criteria above, there were proportionally more “Effect” outcomes when the experiments used real-world signals and proportionally more “No Effect” outcomes when simulated signals were used. This relationship between signal type and biological effect outcome was statistically significant (p < 0.05), indicating that signal type needs to be clearly articulated in reporting because it can potentially bias outcomes. This result also supports our decision to investigate further only the experimental papers that used real-world signals. For these papers, shown in the final column of Table 1, there was a significantly higher proportion of papers showing effects (79.1%) than those reporting no effects (15.3%).
The dramatic increase in electromagnetic fields (EMFs) in the environment has led to public health concerns around the world. Based on over 70 years of research in this field, the World Health Organization (WHO) has concluded that scientific knowledge in this area is now more extensive than for most chemicals and that current evidence does not confirm the existence of any health consequences from exposure to low-level electromagnetic fields. However, controversy on electromagnetic safety continues. Two international groups, the International Committee on Electromagnetic Safety of the Institute of Electrical and Electronics Engineers (IEEE) and the International Commission on Non-Ionizing Radiation Protection, have been addressing this issue for decades. While the goal of both groups is to provide human exposure limits that protect against established or substantiated adverse health effects, there are groups that advocate more stringent exposure limits, based on possible biological effects. Both biological and engineering complexities make the validity of many EMF studies questionable. Controversies in research, publication, standards, regulations and risk communication concerning electromagnetic safety will be addressed in this article. The WHO is conducting systematic reviews on the RF biological effects literature. If scientists would discuss the safety issues of EMFs based on validated scientific facts and not on unreproducible possible effects and opinions, the controversy would be minimized or resolved.
Chartres N, Sass JB, Gee D, Bălan SA, Birnbaum L, Cogliano VJ, Cooper C, Fedinick KP, Harrison RM, Kolossa-Gehring M, Mandrioli D, Mitchell MA, Norris SL, Portier CJ, Straif K, Vermeire T. Conducting evaluations of evidence that are transparent, timely and can lead to health-protective actions. Environ Health. 2022 Dec 5;21(1):123. doi: 10.1186/s12940-022-00926-z.
Background: In February 2021, over one hundred scientists and policy experts participated in a web-based Workshop to discuss the ways that divergent evaluations of evidence and scientific uncertainties are used to delay timely protection of human health and the environment from exposures to hazardous agents. The Workshop arose from a previous workshop organized by the European Environment Agency (EEA) in 2008 and which also drew on case studies from the EEA reports on 'Late Lessons from Early Warnings' (2001, 2013). These reports documented dozens of hazardous agents including many chemicals, for which risk reduction measures were delayed for decades after scientists and others had issued early and later warnings about the harm likely to be caused by those agents.
Results: Workshop participants used recent case studies including Perfluorooctanoic acid (PFOA), Extremely Low Frequency - Electrical Magnetic Fields (ELF-EMF fields), glyphosate, and Bisphenol A (BPA) to explore myriad reasons for divergent outcomes of evaluations, which has led to delayed and inadequate protection of the public's health. Strategies to overcome these barriers must, therefore, at a minimum include approaches that 1) Make better use of existing data and information, 2) Ensure timeliness, 3) Increase transparency, consistency and minimize bias in evidence evaluations, and 4) Minimize the influence of financial conflicts of interest.
Conclusion: The recommendations should enhance the production of "actionable evidence," that is, reliable evaluations of the scientific evidence to support timely actions to protect health and environments from exposures to hazardous agents. The recommendations are applicable to policy and regulatory settings at the local, state, federal and international levels.
Taken together, the effects of electromagnetic fields on individual organisms have now been widely investigated for a multitude of plant and animal species. However, this does not yet address the ecological consequences of this perception in the context of increased anthropogenic EMF emissions. This will require studies of natural populations in their natural habitat and entire ecosystems, including the evaluation of the relevant physical variables over Earth’s surface, along the seabed, in space and time, and detailed biological information on the relevant states of populations. Besides deciphering the action mechanism, this is a field of great demand for assessing the actual environmental effects of steadily increasing EMF emissions. Finally, and importantly, many results from isolated but often paradigm-forming studies have to be independently reproduced.
• Ecological consequences of the known behavioral effects of electric and magnetic fields from widespread marine cables;
• Ecological consequences of electromagnetic noise, known to disrupt animal (e.g., migratory bird) orientation in the laboratory, on animal orientation in the natural environment; • Ecological consequences of observed behavioral effects of ELF-EMFs from powerlines, e.g., on insects and mammals; and
• Pinpointing sensory structures and action mechanism, whereby it is expected that progress for one species can fertilize progress in others
Effect of Radiofrequency Electromagnetic Radiation Emitted by Modern Cellphones on Sperm Motility and Viability: An In Vitro Study
Chu KY, Khodamoradi K, Blachman-Braun R, et al. Effect of Radiofrequency Electromagnetic Radiation Emitted by Modern Cellphones on Sperm Motility and Viability: An In Vitro Study. Eur Urol Focus. 2022;S2405-4569(22)00247-4. doi:10.1016/j.euf.2022.11.004.
Background: Cellphones emit radiofrequency electromagnetic radiation (RF-EMR) for transmission of data for social media communication, web browsing, and music/podcast streaming. Use of Bluetooth ear buds has probably prolonged the time during which cellphones reside in the trouser pockets of men. It has been postulated that RF-EMR increases oxidative stress and induces free radical formation.
Objective: To investigate the effect of wireless-spectrum (4G, 5G, and WiFi) RF-EMR emitted by modern smartphones on sperm motility and viability and explore whether these effects can be mitigated using a physical barrier or distance.
Design, setting, and participants: Semen samples were obtained from fertile normozoospermic men aged 25-35 yr. A current-generation smartphone in talk mode was used as the RF-EMR source. A WhatsApp voice call was made using either 4G, 5G, or WiFi wireless connectivity. We determined if exposure effects were mitigated by either a cellphone case or greater distance from the semen sample.
Outcome measurements and statistical analysis: The semen samples were analyzed according to 2010 World Health Organization laboratory guidelines. Statistical analysis was performed using SPSS v.28.
Results and limitations: We observed decreases in sperm motility and viability with WiFi exposure but not with exposure to 4G or 5G RF-EMR. With large variability among smartphones, continued research on exposure effects is needed.
Conclusions: Our exploratory study revealed that sperm motility and viability are negatively impacted by smartphones that use the WiFi spectrum for data transmission.
Patient summary: We looked at the effect of cellphone use on sperm motility and viability. We found that cellphones using WiFi connectivity for data usage have harmful effects on semen quality in men.
4.4. Master Theme 4: Electromagnetic Pollution
This is generally an identified problem with the deployment of smart buildings using 5G and IoT devices. Many countries have called to ban 5G in general until impartial research data can be made available, and several researchers around the globe have submitted a “5G appeal” . The radiation effects could range from causing headaches, insomnia, to DNA alteration, along with the possibility of creating other biological damages such as hormonal imbalances, reproductive issues, tumors, nerve damage, and eye damage [65,106]. Belpomme (2015) concluded from a comprehensive study that the EMF effect could worsen health conditions related to oxidative stress, a deficit in melatonin metabolism, and is more reflected among electro-sensitive people . Several studies by bio-chemical and medical researchers found that high frequencies can significantly change the heart rate, chromatin (DNA complex and proteins), and melatonin, as well as other hormonal changes [59,71,108]. Kojima et al., (2018) revealed that though most of the effects were thermally related as millimeter frequencies are quickly absorbed by water, it can induce damaging effects without the heating of the tissues, i.e., nonthermal effects that are more dangerous .
As a guideline, the Federal Communication Commission (FCC) adopted the SAR (specific absorption rate) limit value of 1.6 W/Kg for 1 g of tissue approved by ANSI and IEEE . However, current FCC regulations check only the SAR value, which is only a measure of the thermal effects; on the contrary, several studies have concluded that evaluations other than SAR are necessary to fully understand the impact of biological effects other than the thermal effect [111,112]. Scientific evidence suggests that even radiation limits well below the regulatory standards cause severe damage to health even from 2G and 3G [67,105]. Hardell (2017) pointed out that the World Health Organization (WHO) and International Agency for Research on Cancer (IARC) have only classified the risk from wireless cellphones as carcinogenic 2B (for instance, potentially cancerous).
Buildings are generally subjected to electromagnetic radiation (EMR) pollution from two sources: extremely-low-frequency (ELF) and high-frequency wireless devices. Leukemia in children, immunization loss, genes and DNA alteration, cancers, and tumors have been associated with increased exposure from these indoor sources since the 1960s . A smart building that is operated wirelessly with very high frequencies (up to 300 GHz) can put the occupants at risk, particularly the most vulnerable. Moreover, humans have natural bio-electromagnetism  in them, and cells, tissues, and skin regeneration, including the sleep process, rely on natural frequencies from 0 to 30 Hz [114,115,116]. It has been reported that, regardless of the frequency level, being exposed to artificial frequencies is detrimental to human health .
Furthermore, 5G cellular networks deploy many small cells placed at shorter distances on poles and buildings , which can easily aggravate, to a greater extent, the biological effects [68,72]. Hence, many scientists, health professionals, and environmentalists have enquired about the potential problems of continually being in a smart building with numerous IoT devices emitting radiation at high frequencies, including bio-wearable devices [73,94].
Electropollution radiation can also be a hazard to the living organisms of the ecosystem [61,66,69,70]. This problem is specifically crucial for organisms (living on land and in water) that depend strongly on Earth’s natural electromagnetic field for their nutrition and survival [63,112]. The most significant example of such phenomena is the collapse of bee colonies as their navigation is affected by wireless radiation, making them unable to return to their hives or even find food [62,118]. A study spanning almost a decade by Selsam et al., (2016) found out that trees are significantly damaged by radiation, particularly those situated near cellular base stations, and the damage intensifies with aging .
Castellanos G, De Gheselle S, Martens L, Kuster N, Joseph W, Deruyck M, Kuehn S. Multi-objective optimisation of human exposure for various 5G network topologies in Switzerland. Computer Networks.216, 2022. doi: 10.1016/j.comnet.2022.109255.
The constant increase in the required user capacity and the evolution of wireless network technologies impact the exposure that users experience from wireless networks. This paper evaluates various 5G network topologies regarding human exposure, mobile communication quality, and sustainability. We assess human exposure, based on a novel Exposure Ratio (ER) metric, in 5G networks that include Massive Multiple-Input Multiple-Output (MaMIMO) and compare them with existing 4G deployments in three environments in Switzerland. The quality and sustainability of mobile communication are evaluated by extrapolating data rates from mobile operators to the year 2030. A multi-objective optimisation algorithm is implemented to design the 5G network topologies, maximising the user coverage while minimising the downlink (DL) and uplink (UL) exposure. An extensive set of simulations investigated three municipalities, three operators plus one unified network, three use cases (UL/DL data rates), three scenarios (indoor and outdoor coverage), and two optimisation methods. The study results confirm that the human exposure in a 5G network is dominated by the UL being ten times larger than the DL exposure. Furthermore, comparing a 5G deployment with 10 times the traffic capacity of a real 4G network, DL exposure increases by 36% on average, and UL exposure decreases by up to 75% depending on the scenario. Regarding indoor coverage versus outdoor only, our results show that DL exposure can be reduced by a factor of 10 if only outdoor coverage is targeted. Finally, the study concludes that from the human exposure perspective, the ideal network should use 5G MaMIMO and be optimised for both UL and DL exposure.
To provide enhanced mobile services, the 5G system is expected to further densify its network infrastructure and scale up the deployment of massive antenna arrays that emit high-energy beams using the millimeter wave spectrum. These radically new features will significantly impact the EMF exposure level in the 5G networks. In this paper, EMF exposure for 5G mobile networks in a dense urban environment is investigated using a raytracing approach for the uplink (UL) and downlink (DL). A massive multi-input multi-output antenna with multiuser beamforming capability is considered for the 5G base station. For DL, the maximum rate transmission (MRT) technique is used to direct the beams toward all the active users, and total power density (PD) is used to evaluate the EMF exposure level. On the other hand, EMF exposure due to UL is investigated using electric field strength and specific absorption rate (SAR). The proposed ray-tracing based EMF evaluation framework exploits detailed information of the scenarios, including 3D building geometry, EM characteristics, multipath propagation, user locations and beamforming radiation pattern, to effectively evaluate the EMF’s spatial variation levels. Following this evaluation procedure, the impact of different user densities and distributions is analyzed in terms of PD and SAR. Results show that for DL, the peak PD increases from 6.65 to 24.92 dBm/m2 when the number of active users in the area increases from a single user to 100%. Considering the worst-case scenario, the PD exposure reaches 62% of the ICNIRP’s limit. Saturation of the spatial EMF distribution occurs when the number of active DL beams is above 25%. For UL, within 5m radius of the user’s location, the average E-field may increase from 2.40 to 3.98 V/m. (increment of 66%) if the number of active users in the area increases from 25% to 100%. Moreover, when 100% of the users are actively transmitting, there is only a 10% probability that the SAR may exceed 0.06 W/kg (or 3% of the ICNIRP’s limit).
Open access paper: https://ijtech.eng.ui.ac.id/
Mortazavi, S. A., Tahmasebi, S., Parsaei, H., Taleie, A., Faraz, M., Rezaianzadeh, A., Zamani, A., Zamani, A., Mortazavi, S. M. J. (2022). Machine Learning Models for Predicting Breast Cancer Risk in Women Exposed to Blue Light from Digital Screens. Journal of Biomedical Physics and Engineering, 12(6), 637-644. doi: 10.31661/jbpe.v0i0.2105-1341.
Background: Nowadays, there is a growing global concern over rapidly increasing screen time (smartphones, tablets, and computers). An accumulating body of evidence indicates that prolonged exposure to short-wavelength visible light (blue component) emitted from digital screens may cause cancer. The application of machine learning (ML) methods has significantly improved the accuracy of predictions in fields such as cancer susceptibility, recurrence, and survival.
Objective: To develop an ML model for predicting the risk of breast cancer in women via several parameters related to exposure to ionizing and non-ionizing radiation.
Material and Methods: In this analytical study, three ML models Random Forest (RF), Support Vector Machine (SVM), and Multi-Layer Perceptron Neural Network (MLPNN) were used to analyze data collected from 603 cases, including 309 breast cancer cases and 294 gender and age-matched controls. Standard face-to-face interviews were performed using a standard questionnaire for data collection.
Results: The examined models RF, SVM, and MLPNN performed well for correctly classifying cases with breast cancer and the healthy ones (mean sensitivity> 97.2%, mean specificity >96.4%, and average accuracy >97.1%).
Conclusion: Machine learning models can be used to effectively predict the risk of breast cancer via the history of exposure to ionizing and non-ionizing radiation (including blue light and screen time issues) parameters. The performance of the developed methods is encouraging; nevertheless, further investigation is required to confirm that machine learning techniques can diagnose breast cancer with relatively high accuracies automatically.