Swiss Study on 5G Adolescent RF Exposure

EMFSA 14th August 2026

This article presents our interpretation of the Jalilian et al. study published in Environmental Research (2026). We aim to summarise the findings accurately while highlighting important methodological caveats that may not be immediately apparent from reading the original paper.

What Was Measured?

The Swiss Study on 5G Adolescent RF Exposure—led by Jalilian et al.—measured personal RF-EMF exposure in 143 Swiss adolescents (mean age 13.5 years) during approximately 72-hour periods between June 2023 and January 2025.

Participants carried an ExpoM-RF4 exposimeter measuring 35 frequency bands from 80 MHz–6 GHz, including mobile-network signals, Wi-Fi/Bluetooth, broadcast and DECT.

Key Findings

Main exposure levels:

• 24-hour mean exposure: 0.09 mW/m²
• Peak exposure time: Afternoon (0.12 mW/m²)
• Lowest exposure time: Night (0.06 mW/m²)

Source contributions to total exposure:

• Wi-Fi/Bluetooth: 35% (largest contributor)
• Broadcast (FM/DAB): 31%
• Mobile uplink: 19%
• Mobile downlink: 10%
• TDD bands (used as an indicator of 5G-related exposure): 4%
• DECT: 0.7%

Average exposure by environment:

• Transport systems: 0.47 mW/m² (highest)
• Outdoor: 0.27 mW/m²
• School: 0.08 mW/m²
• Home: 0.07 mW/m² (lowest)

What Does This Tell Us About 5G?

According to the authors, despite widespread 5G deployment in Switzerland (~99% population coverage by 2025), overall personal exposure among adolescents remains similar to pre-5G levels.

The TDD bands used by the authors as an indicator of 5G-related exposure averaged only 0.003 mW/m².

But there’s an important caveat. The authors explicitly acknowledge that the study cannot provide a causal estimate of the independent effect of 5G deployment. In short, this study shows exposure levels after 5G rollout, not what 5G caused.

Why Was Transport Exposure Highest?

Transport systems showed the highest average RF-EMF exposure at 0.47 mW/m², compared with 0.08 mW/m² at school and 0.07 mW/m² at home.

Several factors may help explain the higher measurements:

• Mobile-network activity: Uplink, downlink and TDD exposure were substantially higher in transport.
• Network characteristics: The authors suggest that differences between environments may reflect network density and infrastructure.
• User activity: Greater mobile-phone use and the presence of multiple active devices may contribute to higher uplink exposure.
• Train environments: Mean exposure in trains reached up to 0.89 mW/m², the highest value reported for a specific transport setting.

The authors suggest that network characteristics and user behaviour may both contribute to the elevated transport exposure. However, as discussed in the Important Limitations section below, the measurements cannot determine precisely how much originated from passengers’ phones versus network infrastructure. 

Important Limitations

Near-body exposure may be underestimated

The exposimeter does not capture total RF-EMF exposure from all sources. The authors explain that personal exposimeters have reduced ability to measure signals from sources very close to the body, particularly the participant’s own mobile phone and other wireless personal devices. Consequently, the measurements primarily characterise environmental RF-EMF exposure rather than total exposure from all sources. Exposure from devices operating close to the body is therefore likely to be underestimated.

5G-user classification did not confirm actual 5G use

The study classified participants as potential 5G-users if they had both a 5G-compatible smartphone and an active 5G subscription. This classification identified eligibility to use 5G, but did not confirm that a participant’s own phone actually connected to or transmitted on a 5G network during the measurement period.

Participants’ own smartphones were not reported as restricted

The researchers provided a separate Android smartphone for the electronic diary and kept that device in flight mode. However, the paper does not report that they required participants to switch off, disable, or otherwise restrict their own smartphones or other personal wireless devices during the measurement period. This distinction matters because the exposimeter may underestimate exposure from devices operating close to the body, including participants’ own phones.

Additional methodological considerations:

• The study applied corrections for charging effects, crosstalk and an anomalously high Wi-Fi measurement. Charging-effect correction reduced mean FM exposure by approximately 82% and DAB exposure by 61%. The correction reduced overall mean Wi-Fi exposure by approximately 45%, largely because one participant had an unusually high Wi-Fi measurement.
• A single ExpoM-RF4 measurement has an uncertainty of ±34.1%; averaging multiple measurements reduces this uncertainty.
• Only 143 participants from German-speaking Switzerland
• The study used TDD bands as an indicator of 5G-related exposure, but this approach does not capture all possible 5G exposure.

Does This Establish Safety?

No. This is an exposure-characterisation study, not a health-effects study. It was not designed to determine whether RF-EMF causes disease or to establish a biological threshold. The authors note that measured levels fell below current ICNIRP guideline values, but the study was not designed to draw conclusions about health risks. “Below guideline limits” should not be rewritten as proof that there is no health risk.

A separate 2026 Swiss study examined ambient RF-EMF exposure during the 5G rollout. It found that overall median RF-EMF levels remained broadly stable or increased only slightly between 2021/22 and 2023/24, while median TDD exposure, associated with 5G, increased from virtually zero to 0.04 V/m.

Reference: Loizeau, N., Haas, D., Zahner, M. et al. Spatiotemporal trends of ambient radiofrequency electromagnetic fields (RF-EMF) during the 5G rollout in Switzerland. J Expo Sci Environ Epidemiol (2026). https://doi.org/10.1038/s41370-026-00909-z

These findings provide useful context for interpreting the present study:although overall ambient RF-EMF levels did not substantially increase, TDD exposure related to 5G did increase. This reinforces the importance of distinguishing between overall RF-EMF exposure and exposure specifically associated with 5G.

Bottom Line

The data from this useful and reasonably well-designed exposure-monitoring study support its central finding: environmental RF-EMF exposure among these adolescents was broadly comparable with earlier pre-5G HERMES measurements. But it cannot establish that 5G has not increased RF exposure generally, cannot quantify total individual RF exposure, and cannot demonstrate that the measured exposure levels are biologically or medically harmless.

The dominance of WiFi/BT and uplink signals highlights the contribution of personal device use to overall measured RF-EMF exposure.

Reference: Jalilian H, Jaki Waibl V, Wipf I, et al. Personal radio frequency electromagnetic field exposure among Swiss adolescents in the 5G era. Environmental Research, 2026, 304: 124775. DOI: 10.1016/j.envres.2026.124775 https://doi.org/10.1016/j.envres.2026.124775

This is an open access article distributed under the terms of the Creative Commons CC BY 4.0 License (http://creativecommons.org/licenses/by/4.0/). 

*Edited Unsplash photograph (original by Lesli Whitecotton on Unsplash). Faces intentionally obscured to protect subject privacy. Used for illustrative purposes only; the individuals depicted are not study participants in the Jalilian et al. (2026) study.