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OPINION article

Front. Public Health, 24 October 2022
Sec. Radiation and Health
This article is part of the Research Topic Experts' Opinions in Radiation and Health: Emerging Issues in the Field View all 8 articles

It is mandatory to review environmental radiofrequency electromagnetic field measurement protocols and exposure regulations: An opinion article

  • 1Departamento de Fotónica y Bioingeniería (TFB), Escuela Técnica Superior de Ingenieros de Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain
  • 2Laboratorio de Bioelectromagnetismo, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Madrid, Spain
  • 3Departamento de Arquitectura y Tecnología de Sistemas Informáticos (DATSI), Escuela Técnica Superior de Ingenieros Informáticos, Universidad Politécnica de Madrid, Madrid, Spain
  • 4CIBER–BBN Centro de Investigación Biomédica en Red, Madrid, Spain

Introduction

In recent years, there has been a considerable increase in the use of telecommunication technologies. This has led to an increase in the number of users and, consequently, in the number of operational terminals. Mobile networks are continuously improving, which is why, from 2004 to the present, three consecutive generations of mobile networks have been developed (3G, 4G, and 5G) with the consequent improvement in their characteristics, such as higher transmission speed and bandwidths for the transmission of signals. According to the International Telecommunication Union (ITU) World Telecommunication/ICT Indicators Database in 2004 there, were 1.76 billion mobile phone subscriptions in the world, in 2020 this figure increased to 8.27 billion (1). By 2023, there are expected to be 13.1 billion mobile terminals, almost 10% of which will be 5G technology (2).

As technology grows, so does the concern of the public, who feels that they are not adequately informed about the possible effects of long-term exposure to radiofrequency electromagnetic waves (3). There are different sources of radiofrequency electromagnetic field radiation like base stations that allow communication between wireless devices. These base stations are located outdoors on the rooftops of buildings, and indoors like routers, laptops, and mobile phones, using wireless communication technologies such as Bluetooth or WiFi.

Several scientific studies evaluate the possible effects of prolonged exposure to microwaves at the epidemiological level (411) and in vitro or in vivo models (1219). However, the use of different methodologies in radiation measurement processes and different configurations of exposure equipment, such as frequency, radiation power density, and exposure time; do not allow adequate comparison of results, which makes it difficult to draw conclusions.

The International Commission of Non-Ionizing Radiation Protection (ICNIRP), which is a nongovernmental organization, but recognized by the World Health Organization (WHO), develops international guidelines on exposure limits to EMFs in the range of 0–300 GHz (20). Although most countries such as Spain, Germany, France or Finland adopt the limits proposed by the ICNIRP, the existing regulations in other are different, with limits more restrictive in countries such as Denmark, Bulgaria, Italy, Switzerland, China or Russia (2123).

Old standards and measurement methodologies are not adapted to the new communications standards and technologies

There are regulatory organizations in different countries that establish the regulations regarding exposure to EMFs and also offer measurement protocols that attempt to homogenize the sampling process. Some examples are the ICNIRP (20), the ITU (24), the Institute of Electrical and Electronics Engineers (IEEE) (25), the Federal Communication Commission (FCC) (26), or the European Committee for Electrotechnical Standardization (CENELEC) (27).

Most studies related to environmental EMFs in specific populations can be divided into two groups. On the one hand, epidemiological studies assess health parameters such as the presence of headaches, dizziness, sleep problems or others pathologies as a cause of continuous exposure to wireless devices (410, 2835). This first group does not usually perform real-time, in situ measurements, and their exposure data is based on the use of different wireless devices, making simple estimates concerning time (28, 31), distance to antennas (29), or mathematical prediction models (36). Secondly, studies that measure in real-time use different protocols and measurement systems (4, 6, 7, 30, 34). On the other hand, publications characterizing EMFs aim to observe that the RF-EMF exposures to which the general population is exposed are within the legal limits of each area (3740). The main drawback of both kinds of studies is that there is no consensus on the methodology used and, therefore, the results are not comparable or conclusive. Studies of this type require continuous monitoring over time of the evolution of pathologies in the population, as well as any changes that may occur in the radiation levels of the emitting sources.

The characterization of environmental EMFs in a specific population is mostly performed with exposimeter systems such as: EME Spy-−120, 121, 140 (SATIMO, Courtaboeuf, France), ESM 140 (Maschek Electronik, Bad Wörishfen, Germany) or ExpoM—RF (Fields at Work GmbH, Zürich, Switzerland) (4143). These devices only measure up to 20 spectrum bands, and they do not record the whole frequency spectrum. Furthermore, their bandwidth is determined by the entire frequency band to be measured (41, 44). This does not allow the correct detection of multiple sources that occupy the same communications band, which generally results in a poor estimation of the EMF strength. According to the recommendations of ICNIRP (20) and ITU (4547), the effect of multiple sources operating at different frequencies should be considered independently, so it is recommended to use systems that allow differentiation of emitting sources using resolution bandwidths determined by the channel width. They also recommend the use of max-hold trace (45) to store the peak value of the measurements made in environmental EMFs, because the RF signals have an irregular or random behavior. Therefore, the use of extrapolation factors in broadband is not enough to compensate the overestimation of the power density of these signals. According to the ITU guidelines for measuring RF-EMF intensity, the average of the signals over 6-min periods should be used to assess compliance of the source(s) (47). However, since the signals behave randomly, so, the information of the maximum, minimum, and average over 6-min periods using wide bandwidths is not sufficient to characterize the EMF strength for different sources. For all of the above reasons, the use of systems such as spectrum analyzers (45) or new exposimeter systems (43) that integrate functionalities of the previous ones that allow discrimination between multiple sources operating at different frequencies, can characterize the behavior of EMFs, obtaining maximum power density per unit of time. These systems would allow the three-dimensional representation of the main RF-EMF characterization parameters: frequency, power density and time.

Underestimation of non-thermal effects in the development of measurement methodologies

Today, the population is chronically exposed to RF-EMFs, characterized by low intensity, variety, and complexity of signals and long-term exposure durations. ICNIRP sets exposure limits according to the specific absorption rate (SAR) and power density (20). SAR is defined as the rate of energy absorption per defined unit of volume or mass. Many researchers consider the choice of the SAR criterion as the only parameter for assessing effects on biological systems as insufficient, as it only takes into account the thermal effects resulting from exposure (4850). The ICNIRP guidelines state that a one Celsius degree increase in body temperature is the acceptable limit to avoid adverse health effects (20). Although a reduction factor of 50 is applied to the SAR value capable of increasing the temperature by 1°C, no account is taken of other effects not related to temperature increase. These effects, have been reported in numerous in vitro and in vivo studies to occur at lower intensities than those required to cause thermal effects by low and high frequency EMFs, such as alterations in gene expression (51, 52), oxidation processes (12, 14, 19, 5356), the flow of calcium ions (5759), proteins (60) or cell viability (13, 17).

The first studies to evaluate non-thermal effects were carried out by research groups in the USSR and USA in the 1960s (6163) and by researchers such as Blackman, Adey, and Bawin later (6466). An important aspect pointed out by the authors is the modulation parameter that could be responsible for the occurrence of the main effects found in biological systems in vitro and in vivo as it has a bioactive characteristic and can interfere with some normal and non-linear biological processes. In 1986 the NCRP in its RF exposure guidelines document included a risk assessment with an exception for modulated RF–EMFs (67). However, all other standards, such as those issued by the ICNIRP and the IEEE, ignore the NCRP and revert to considering only the conditions of analysis of thermal effects. The existence of non-thermal effects is reported in those studies using RF-EMF with the same intensity and frequency but with different modulation that find different results with the same experimental setup (6870). Therefore, existing regulations do not considered a chronic exposure to a pulsed or modulated signal, such as mobile phone signals.

Frequency, defined as the inverse of the wavelength, is an indispensable parameter in the biological response of the cellular body. Research subsequent to that carried out between the 1960s and the 1980s (7174) allowed us to discuss the existence of frequency and power density windows in which there were biological effects that disappeared with different values of the same parameter, even lower than those proposed by the standards (16, 19, 55, 68, 69).

The studies assessing the possible effects of RF-EMFs in vitro should consider all important parameters in the exposure: intensity, frequency, modulation and time of exposure. The possible existence of bioactive windows in frequency, intensity or modulation, as well as the non-linear response of biological systems that could produce differences in cellular behavior should be considered in the development of measurement methodologies and the establishment of exposure limits and could serve as a precedent to establish mechanisms of action of these RF-EMFs in relation to biological systems.

Conclusions

In conclusion, two main ideas arise: the review of the environmental EMFs measurement protocols and the need for a comprehensive assessment of all the effects of EMFs not only thermal effects.

Measurement protocols must identify the specific frequencies of each of the currently established major frequency bands, the temporal behavior of the signal and the power density. Measurement systems must not only determine averaged field strengths but must be able to measure the peak amplitude over time and, consequently, the cumulative radiation. This would make the characterization of EMFs much more realistic.

In addition, parameters such as frequency and modulation could be important when considering potential biological effects. Choosing intensity as the only determining parameter for the occurrence of effects is a reductionist conception. The consideration of all EMFs parameters in the assessment of biological response should be mandatory.

Author contributions

IL and MR: drafting the manuscript. MR and NF: revising the manuscript. CM: manuscript direction and supervision. IL, MR, NF, and CM: opinions included in the manuscript. All authors contributed to the article and approved the submitted version.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

1. ITU. Mobile Cellular Subscriptions Data. World Bank Gr (2019). Available online at: https://data.worldbank.org/indicator/IT.CEL.SETS (accessed May 9, 2022).

Google Scholar

2. Cisco. Cisco Annual Internet Report (2018–2023). Cisco (2020). p. 1–41. Available online at: http://grs.cisco.com/grsx/cust/grsCustomerSurvey.html?SurveyCode=4153&ad_id=US-BN-SEC-M-CISCOASECURITYRPT-ENT&KeyCode=000112137

Google Scholar

3. European Commission. Eurobarometer 73.3: National and European Identity, and Electromagnetic Fields and Health, March-April 2010. Ann Arbor, MI: Inter-university Consortium for Political and Social Research (2010). p. 1–100. doi: 10.3886/ICPSR30161.v2

CrossRef Full Text | Google Scholar

4. López I, Félix N, Rivera M, Alonso A, Maestú C. What is the radiation before 5G?: a correlation study between measurements in situ and in real time and epidemiological indicators in Vallecas, Madrid. Environ Res. (2021) 194:110734. doi: 10.1016/j.envres.2021.110734

PubMed Abstract | CrossRef Full Text | Google Scholar

5. Santini R, Santini P, Danze JM, Le Ruz P, Seigne M. Survey on the health of residents living near mobile phone base stations: impact of distance and gender. Pathol Biol. (2002) 50:621. doi: 10.1016/S0369-8114(02)00367-X

CrossRef Full Text | Google Scholar

6. Navarro EA, Segura J, Portolés M, Gómez-Perretta C. The microwave syndrome: a preliminary study in Spain. Electromagn Biol Med. (2003) 22:161–9. doi: 10.1081/JBC-120024625

CrossRef Full Text | Google Scholar

7. Oberfeld G, Navarro E, Portoles M, Maestu C, Gomez-Perretta C. The Microwave Syndrome: Further Aspects of a Spanish Study. EBEA Congr Kos-Greece (2004). p. 1–9.

Google Scholar

8. Singh K, Nagaraj A, Yousuf A, Ganta S, Pareek S, Vishnani P. Effect of electromagnetic radiations from mobile phone base stations on general health and salivary function. J Int Soc Prev Community Dent. (2016) 6:54–9. doi: 10.4103/2231-0762.175413

PubMed Abstract | CrossRef Full Text | Google Scholar

9. Hardell L, Carlberg M. Mobile phones, cordless phones and rates of brain tumors in different age groups in the Swedish national inpatient register and the Swedish cancer register during 1998–2015. PLoS ONE. (2017) 12:1–13. doi: 10.1371/journal.pone.0185461

PubMed Abstract | CrossRef Full Text | Google Scholar

10. Carlberg M, Hardell L. Evaluation of mobile phone and cordless phone use and glioma risk using the Bradford Hill viewpoints from 1965 on association or causation. Biomed Res Int. (2017) 2017:17. doi: 10.1155/2017/9218486

PubMed Abstract | CrossRef Full Text | Google Scholar

11. Bodewein L, Dechent D, Graefrath D, Kraus T, Krause T, Driessen S. Systematic review of the physiological and health-related effects of radiofrequency electromagnetic field exposure from wireless communication devices on children and adolescents in experimental and epidemiological human studies. PLoS ONE. (2022) 17:e0268641. doi: 10.1371/journal.pone.0268641

PubMed Abstract | CrossRef Full Text | Google Scholar

12. Dasdag S, Akdag MZ, Ulukaya E, Uzunlar AK, Ocak AR. Effect of mobile phone exposure on apoptotic glial cells and status of oxidative stress in rat brain. Electromagn Biol Med. (2009) 28:342–54. doi: 10.3109/15368370903206556

PubMed Abstract | CrossRef Full Text | Google Scholar

13. García Minguillán-López O, Jiménez Valbuena A, Maestú Unturbe C. Significant cellular viability dependence on time exposition at ELF-EMF and RF-EMF in vitro studies. Int J Environ Res Public Health. (2019) 16:2085. doi: 10.3390/ijerph16122085

PubMed Abstract | CrossRef Full Text | Google Scholar

14. Alkis ME, Bilgin HM, Akpolat V, Dasdag S, Yegin K, Yavas MC, et al. Effect of 900-, 1800-, and 2100-MHz radiofrequency radiation on DNA and oxidative stress in brain. Electromagn Biol Med. (2019) 38:32–47. doi: 10.1080/15368378.2019.1567526

PubMed Abstract | CrossRef Full Text | Google Scholar

15. Park J, Kwon JH, Kim N, Song K. Effects of 1950 MHz radiofrequency electromagnetic fields on Aβ processing in human neuroblastoma and mouse hippocampal neuronal cells. J Radiat Res. (2018) 59:18–26. doi: 10.1093/jrr/rrx045

PubMed Abstract | CrossRef Full Text | Google Scholar

16. Gulati S, Kosik P, Durdik M, Skorvaga M, Jakl L, Markova E, et al. Effects of different mobile phone UMTS signals on DNA, apoptosis and oxidative stress in human lymphocytes. Environ Pollut. (2020) 267:115632. doi: 10.1016/j.envpol.2020.115632

PubMed Abstract | CrossRef Full Text | Google Scholar

17. Eghlidospour M, Ghanbari A, Mortazavi SMJ, Azari H. Effects of radiofrequency exposure emitted from a GSM mobile phone on proliferation, differentiation, and apoptosis of neural stem cells. Anat Cell Biol. (2017) 50:115–23. doi: 10.5115/acb.2017.50.2.115

PubMed Abstract | CrossRef Full Text | Google Scholar

18. Falcioni L, Bua L, Tibaldi E, Lauriola M, De Angelis L, Gnudi F, et al. Report of final results regarding brain and heart tumors in Sprague-Dawley rats exposed from prenatal life until natural death to mobile phone radiofrequency field representative of a 18 GHz GSM base station environmental emission. Environ Res. (2018) 165:496–503. doi: 10.1016/j.envres.2018.01.037

PubMed Abstract | CrossRef Full Text | Google Scholar

19. Megha K, Deshmukh PS, Banerjee BD, Tripathi AK, Ahmed R, Abegaonkar MP. Low intensity microwave radiation induced oxidative stress, inflammatory response and DNA damage in rat brain. Neurotoxicology. (2015) 51:158–65. doi: 10.1016/j.neuro.2015.10.009

PubMed Abstract | CrossRef Full Text | Google Scholar

20. International Commission on Non-Ionizing Radiation Protection (ICNIRP)1. Guidelines for limiting exposure to electromagnetic fields (100 kHz to 300 GHz). Health Phys. (2020) 118:483–524. doi: 10.1097/HP.0000000000001210

PubMed Abstract | CrossRef Full Text | Google Scholar

21. GSM Association (GSMA). Base Station Planning Permission in Europe 2013. (2013). Available online at: www.gsma.com (accessed May 9, 2022).

Google Scholar

22. Politechnika Wrocławska Institute Institute of Electrical and Electronics Engineers. 2016 International Symposium on Electromagnetic Compatibility—EMC EUROPE : Proceedings : Wroclaw, Poland, September 5–9, 2016. IEEE Int Symp Electromagn Compat—EMC Eur (2016)

Google Scholar

23. Grigoriev Y. Electromagnetic fields and the public: EMF standards and estimation of risk. IOP Conf Ser Earth Environ Sci. (2010) 10:012003. doi: 10.1088/1755-1315/10/1/012003

PubMed Abstract | CrossRef Full Text | Google Scholar

24. International Telecommunication Union (ITU-T Rec),. K.83 (06/2020) Monitoring of Electromagnetic Field Levels (2022). Available online at: https://www.itu.int/rec/T-REC-K.83/en (accessed May 12, 2022).

Google Scholar

25. Institute of Electrical Electronics Engineers (IEEE). IEEE C95.1-2019. IEEE Standard for Safety Levels with Respect to Human Exposure to Electric, Magnetic, and Electromagnetic Fields, 0 Hz−300 GHz (2019). Available online at: https://standards.ieee.org/ieee/C95.1/4940/ (accessed May 12, 2022).

Google Scholar

26. Federal Communication Commision (FCC),. RF Exposure Procedures Equipment Authorization Policies for Mobile Portable Devices. (2019). p. 1–34. Available online at: https://www.fcc.gov/document/fcc-maintains-current-rf-exposure-safety-standards (accessed May 12, 2022).

Google Scholar

27. European Committee for Electrotechnical Standardization (CENELEC). EN 50413:2019. Basic Standard on Measurement and Calculation Procedures for Human Exposure to Electric, Magnetic and Electromagnetic Fields (0 Hz–300 GHz). Brussels: European Committee for Electrotechnical Standardization (2019).

Google Scholar

28. Balikci K, Cem Ozcan I, Turgut-Balik D, Balik HH. A survey study on some neurological symptoms and sensations experienced by long term users of mobile phones. Pathol Biol. (2005) 53:30–4. doi: 10.1016/j.patbio.2003.12.002

PubMed Abstract | CrossRef Full Text | Google Scholar

29. Chia SE, Chia HP, Tan JS. Prevalence of headache among handheld cellular telephone users in Singapore: a community study. Environ Health Perspect. (2000) 108:1059–62. doi: 10.1289/ehp.001081059

PubMed Abstract | CrossRef Full Text | Google Scholar

30. Berg-Beckhoff G, Blettner M, Kowall B, Breckenkamp J, Schlehofer B, Schmiedel S, et al. Mobile phone base stations and adverse health effects: phase 2 of a cross-sectional study with measured radio frequency electromagnetic fields. Occup Environ Med. (2009) 66:124–30. doi: 10.1136/oem.2008.039834

PubMed Abstract | CrossRef Full Text | Google Scholar

31. Heinrich S, Thomas S, Heumann C, Von Kries R, Radon K. Association between exposure to radiofrequency electromagnetic fields assessed by dosimetry and acute symptoms in children and adolescents: a population based cross-sectional study. Environ Heal A Glob Access Sci Source. (2010) 9:75. doi: 10.1186/1476-069X-9-75

PubMed Abstract | CrossRef Full Text | Google Scholar

32. Carlberg M, Hardell L. Pooled analysis of Swedish case-control studies during 1997–2003 and 2007–2009 on meningioma risk associated with the use of mobile and cordless phones. Oncol Rep. (2015) 33:3093–8. doi: 10.3892/or.2015.3930

PubMed Abstract | CrossRef Full Text | Google Scholar

33. Abdel-Rassoul G, El-Fateh OA, Salem MA, Michael A, Farahat F, El-Batanouny M, et al. Neurobehavioral effects among inhabitants around mobile phone base stations. Neurotoxicology. (2007) 28:434–40. doi: 10.1016/j.neuro.2006.07.012

PubMed Abstract | CrossRef Full Text | Google Scholar

34. Hutter HP, Moshammer H, Wallner P, Kundi M. Subjective symptoms, sleeping problems, and cognitive performance in subjects living near mobile phone base stations. Occup Environ Med. (2006) 63:307–13. doi: 10.1136/oem.2005.020784

PubMed Abstract | CrossRef Full Text | Google Scholar

35. Mortazavi SMJ, Ahmadi J, Shariati M. Prevalence of subjective poor health symptoms associated with exposure to electromagnetic fields among university students. Bioelectromagnetics. (2007) 28:326–30. doi: 10.1002/bem.20305

PubMed Abstract | CrossRef Full Text | Google Scholar

36. Frei P, Mohler E, Braun-Fahrländer C, Fröhlich J, Neubauer G, Röösli M. Cohort study on the effects of everyday life radio frequency electromagnetic field exposure on non-specific symptoms and tinnitus. Environ Int. (2012) 38:29–36. doi: 10.1016/j.envint.2011.08.002

PubMed Abstract | CrossRef Full Text | Google Scholar

37. Massardier-Pilonchery A, Nerrière E, Croidieu S, Ndagijimana F, Gaudaire F, Martinsons C, et al. Assessment of personal occupational exposure to radiofrequency electromagnetic fields in libraries and media libraries, using calibrated on-body exposimeters. Int J Environ Res Public Health. (2019) 16:2087. doi: 10.3390/ijerph16122087

PubMed Abstract | CrossRef Full Text | Google Scholar

38. Iyare RN, Volskiy V, Vandenbosch GAE. Study of the electromagnetic exposure from mobile phones in a city like environment: the case study of Leuven, Belgium. Environ Res. (2019) 175:402–13. doi: 10.1016/j.envres.2019.05.029

PubMed Abstract | CrossRef Full Text | Google Scholar

39. Velghe M, Joseph W, Debouvere S, Aminzadeh R, Martens L, Thielens A. Characterization of spatial and temporal variability of RF-EMF exposure levels in urban environments in Flanders, Belgium. Environ Res. (2019) 175:351–66. doi: 10.1016/j.envres.2019.05.027

PubMed Abstract | CrossRef Full Text | Google Scholar

40. Chiaramello E, Bonato M, Fiocchi S, Tognola G, Parazzini M, Ravazzani P, et al. Radio frequency electromagnetic fields exposure assessment in indoor environments: a review. Int J Environ Res Public Health. (2019) 16:955. doi: 10.3390/ijerph16060955

PubMed Abstract | CrossRef Full Text | Google Scholar

41. Bhatt CR, Redmayne M, Abramson MJ, Benke G. Instruments to assess and measure personal and environmental radiofrequency-electromagnetic field exposures. Australas Phys Eng Sci Med. (2016) 39:29–42. doi: 10.1007/s13246-015-0412-z

PubMed Abstract | CrossRef Full Text | Google Scholar

42. Bolte JFB. Lessons learnt on biases and uncertainties in personal exposure measurement surveys of radiofrequency electromagnetic fields with exposimeters. Environ Int. (2016) 94:724–35. doi: 10.1016/j.envint.2016.06.023

PubMed Abstract | CrossRef Full Text | Google Scholar

43. Rivera González MX, Félix González N, López I, Ochoa Zambrano JS, Miranda Martínez A, Maestú Unturbe C. Compact exposimeter device for the characterization and recording of electromagnetic fields from 78 MHz to 6 GHz with several narrow bands (300 kHz). Sensors. (2021) 21:7395. doi: 10.3390/s21217395

PubMed Abstract | CrossRef Full Text | Google Scholar

44. Bhatt CR, Henderson S, Brzozek C, Benke G. Instruments to measure environmental and personal radiofrequency-electromagnetic field exposures: an update. Phys Eng Sci Med. (2022) 45:687–704. doi: 10.1007/s13246-022-01146-y

PubMed Abstract | CrossRef Full Text | Google Scholar

45. International Telecommunication Union (ITU-T Rec),. K.100 (06/2021) Measurement of Radiofrequency Electromagnetic Fields to Determine Compliance with Human Exposure Limits When a Base Station is put Into Service Recommendation. (2021). p. 38. Available online at: https://www.itu.int/rec/T-REC-K.100/en (accessed May 12, 2022).

Google Scholar

46. International Telecommunication Union (ITU-T Rec),. K.61 (01/2018): Guidance to Measurement Numerical Prediction of Electromagnetic Fields for Compliance with Human Exposure Limits for Telecommunication Installations. (2018). Available online at: https://www.itu.int/rec/T-REC-K.61-200309-S/en (accessed May 12, 2022).

Google Scholar

47. Union International Telecommunication (ITU-T Rec),. K.52 (06/2021) Guidance on Complying with Limits for Human Exposure to Electromagnetic Fields. (2014). p. 52. Available online at: https://www.itu.int/rec/T-REC-K.52/en (accessed May 12, 2022).

Google Scholar

48. Blackman C. Cell phone radiation: evidence from ELF and RF studies supporting more inclusive risk identification and assessment. Pathophysiology. (2009) 16:205–16. doi: 10.1016/j.pathophys.2009.02.001

PubMed Abstract | CrossRef Full Text | Google Scholar

49. Nyberg NR, McCredden JE, Weller SG, Hardell L. The European union prioritizes economics over health in the rollout of radiofrequency technologies. Rev Environ Health. (2022). doi: 10.1515/reveh-2022-0106. [Epub ahead of print].

PubMed Abstract | CrossRef Full Text | Google Scholar

50. Belpomme D, Hardell L, Belyaev I, Burgio E, Carpenter DO. Thermal and non-thermal health effects of low intensity non-ionizing radiation: an international perspective. Environ Pollut. (2018) 242:643–58. doi: 10.1016/j.envpol.2018.07.019

PubMed Abstract | CrossRef Full Text | Google Scholar

51. Martin C, Percevault F, Ryder K, Sani E, Le Cun JC, Zhadobov M, et al. Effects of radiofrequency radiation on gene expression: a study of gene expressions of human keratinocytes from different origins. Bioelectromagnetics. (2020) 41:552–7. doi: 10.1002/bem.22287

PubMed Abstract | CrossRef Full Text | Google Scholar

52. Chen G, Lu D, Chiang H, Leszczynski D, Xu Z. Using model organism Saccharomyces cerevisiae to evaluate the effects of ELF-MF and RF-EMF exposure on global gene expression. Bioelectromagnetics. (2012) 33:550–60. doi: 10.1002/bem.21724

PubMed Abstract | CrossRef Full Text | Google Scholar

53. Kesari KK, Kumar S, Behari J. 900-MHz microwave radiation promotes oxidation in rat brain. Electromagn Biol Med. (2011) 30:219–34. doi: 10.3109/15368378.2011.587930

PubMed Abstract | CrossRef Full Text | Google Scholar

54. Kazemi E, Mortazavi SMJ, Ali-Ghanbari A, Sharifzadeh S, Ranjbaran R, Mostafavi-Pour Z, et al. Effect of 900 MHz electromagnetic radiation on the induction of ROS in human peripheral blood mononuclear cells. J Biomed Phys Eng. (2015) 5:105–14.

PubMed Abstract | Google Scholar

55. Durdik M, Kosik P, Markova E, Somsedikova A, Gajdosechova B, Nikitina E, et al. Microwaves from mobile phone induce reactive oxygen species but not DNA damage, preleukemic fusion genes and apoptosis in hematopoietic stem/progenitor cells. Sci Rep. (2019) 9:16182. doi: 10.1038/s41598-019-52389-x

PubMed Abstract | CrossRef Full Text | Google Scholar

56. Furtado-Filho OV, Borba JB, Maraschin T, Souza LM, Henriques JAP, Moreira JCF, et al. Effects of chronic exposure to 950 MHz ultra-high-frequency electromagnetic radiation on reactive oxygen species metabolism in the right and left cerebral cortex of young rats of different ages. Int J Radiat Biol. (2015) 91:891–7. doi: 10.3109/09553002.2015.1083629

PubMed Abstract | CrossRef Full Text | Google Scholar

57. Pall ML. Scientific evidence contradicts findings and assumptions of Canadian safety panel 6: microwaves act through voltage-gated calcium channel activation to induce biological impacts at non-thermal levels, supporting a paradigm shift for microwave/lower freque. Rev Environ Health. (2015) 30:99–116. doi: 10.1515/reveh-2015-0001

PubMed Abstract | CrossRef Full Text | Google Scholar

58. Pall ML. Electromagnetic fields act via activation of voltage-gated calcium channels to produce beneficial or adverse effects. J Cell Mol Med. (2013) 17:958–65. doi: 10.1111/jcmm.12088

PubMed Abstract | CrossRef Full Text | Google Scholar

59. Kim JH, Sohn UD, Kim HG, Kim HR. Exposure to 835 MHz RF-EMF decreases the expression of calcium channels, inhibits apoptosis, but induces autophagy in the mouse hippocampus. Korean J Physiol Pharmacol. (2018) 22:277–89. doi: 10.4196/kjpp.2018.22.3.277

PubMed Abstract | CrossRef Full Text | Google Scholar

60. Leszczynski D. Effects of radiofrequency-modulated electromagnetic fields on proteome. In:Leszczynsk, D, , editors. Radiation Proteomics. Advances in Experimental Medicine and Biology, Vol. 990. Dordrecht: Springer (2013). p. 101–6. doi: 10.1007/978-94-007-5896-4_6

PubMed Abstract | CrossRef Full Text | Google Scholar

61. Presman AS, IuI L, Levitina MA. [Biological effect of magnetic fields]. Usp Sovrem Biol. (1961) 51:84–103.

Google Scholar

62. Presman A. Problems of the Mechanism of the Biological Effect of Microwaves. Uspekhi sovremennoy biologii (1963). p. 161–79.

PubMed Abstract | Google Scholar

63. Frey AH. Brain stem evoked responses associated with low-intensity pulsed UHF energy. J Appl Physiol. (1967) 23:984–8. doi: 10.1152/jappl.1967.23.6.984

PubMed Abstract | CrossRef Full Text | Google Scholar

64. Blackman CF, Benane SG, Elder JA, House DE, Lampe JA, Faulk JM. Induction of calcium-ion efflux from brain tissue by radiofrequency radiation: effect of sample number and modulation frequency on the power-density window. Bioelectromagnetics. (1980) 1:35–43. doi: 10.1002/bem.2250010104

PubMed Abstract | CrossRef Full Text | Google Scholar

65. Joines WT, Blackman CF, Hollis MA. Broadening of the RF power-density window for calcium-ion efflux from brain tissue. IEEE Trans Biomed Eng. (1981) 28:568–73. doi: 10.1109/TBME.1981.324829

PubMed Abstract | CrossRef Full Text | Google Scholar

66. Adey WR, Bawin SM, Lawrence AF. Effects of weak amplitude-modulated microwave fields on calcium efflux from awake cat cerebral cortex. Bioelectromagnetics. (1982) 3:295–307. doi: 10.1002/bem.2250030302

PubMed Abstract | CrossRef Full Text | Google Scholar

67. NCRP; National Council on Radiation Protection and Measurements. Biological Effects and Exposure Criteria for Radiofrequency Electromagnetic Fields. NCRP Report 86, Recommendations of the National Council on Radiation Protection and Measurements (1986). p. 400.

Google Scholar

68. Romeo S, Sannino A, Zeni O, Angrisani L, Massa R, Scarfi MR. Effects of radiofrequency exposure and co-exposure on human lymphocytes: the influence of signal modulation and bandwidth. IEEE J Electromagn RF Microwaves Med Biol. (2020) 4:17–23. doi: 10.1109/JERM.2019.2918023

CrossRef Full Text | Google Scholar

69. Gapeyev AB, Lukyanova NA. Pulse-modulated extremely high-frequency electromagnetic radiation protects cellular DNA from the damaging effects of physical and chemical factors in vitro. Biophysics. (2015) 60:732–8. doi: 10.1134/S0006350915050061

CrossRef Full Text | Google Scholar

70. Juutilainen J, Höytö A, Kumlin T, Naarala J. Review of possible modulation-dependent biological effects of radiofrequency fields. Bioelectromagnetics. (2011) 32:511–34. doi: 10.1002/bem.20652

PubMed Abstract | CrossRef Full Text | Google Scholar

71. Hamer J. Effects of low level, low frequency electric fields on human reaction time. Commun Behav Biol. (1968) 2:217–22.

Google Scholar

72. Gavalas RJ, Walter DO, Hamer J, Adey WR. Effect of low-level, low-frequency electric fields on EEG and behavior in Macaca nemestrina. Brain Res. (1970) 18:491–501. doi: 10.1016/0006-8993(70)90132-0

PubMed Abstract | CrossRef Full Text | Google Scholar

73. Gavalas-Medici R, Day-Magdaleno SR. Extremely low frequency, weak electric fields affect schedule—controlled behavior of monkeys. Nature. (1976) 261:256–9. doi: 10.1038/261256a0

PubMed Abstract | CrossRef Full Text | Google Scholar

74. Blackman CF, Kinney LS, House DE, Joines WT. Multiple power-density windows and their possible origin. Bioelectromagnetics. (1989) 10:115–28. doi: 10.1002/bem.2250100202

PubMed Abstract | CrossRef Full Text | Google Scholar

Keywords: non-thermal effects, radiofrequency measurements, frequency, exposimeter, power density

Citation: López I, Rivera M, Félix N and Maestú C (2022) It is mandatory to review environmental radiofrequency electromagnetic field measurement protocols and exposure regulations: An opinion article. Front. Public Health 10:992645. doi: 10.3389/fpubh.2022.992645

Received: 12 July 2022; Accepted: 12 October 2022;
Published: 24 October 2022.

Edited by:

Dariusz Leszczynski, University of Helsinki, Finland

Reviewed by:

Mats-Olof Mattsson, SciProof International, Sweden
Henry Lai, University of Washington, United States

Copyright © 2022 López, Rivera, Félix and Maestú. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Ceferino Maestú, ceferino.maestu@ctb.upm.es

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.