This exposure-assessment study compares RF-EMF exposure maps produced using a broadband meter versus a personal exposimeter and aims to correct personal exposimeter readings to match broadband-based maps. The authors report that LOS/NLOS-specific correction factors reduce discrepancies, particularly improving LOS measurements affected by body shielding. A genetic algorithm is used to optimize correction factors and support scalable urban exposure mapping, with the authors noting that additional validation in other environments is needed.

This paper presents a machine-learning method to estimate ground-level electromagnetic radiation (electric field strength) in the near field of 5G base stations, using multiple technical and environmental input parameters. The authors report experimental performance with a mean absolute percentage error of about 5.89% and suggest the approach can reduce costs compared with on-site measurements. The work is positioned as supporting exposure management and base-station placement, while noting the need for careful EMF management due to potential health-risk links.

This paper applies a model-based clustering approach (Log-Normal Mixture Model) to continuous RF-EMF monitoring data from the Serbian EMF RATEL network in Novi Sad to characterize temporal exposure patterns. The analysis reports separation of night versus day exposure values and identification of daytime periods where exposure persists longer. The work is positioned as supporting improved understanding of when and where elevated exposures occur in urban environments.

This paper describes measurements and simulations to support terahertz (THz) sensing of European honey bees for environmental monitoring. It reports dielectric characterization of bee body parts across 1–500 GHz, scattering-based validation of 3D-printed bee mockups, and THz imaging demonstrating detailed anatomical visualization. The work includes dosimetric simulations at 300 GHz to evaluate feasibility of non-invasive, continuous monitoring and notes potential relevance to assessing high-frequency EMF impacts on insect health and habitat safety.

This co-designed provocation study in IEI-EMF volunteers evaluated whether perceived exposure and symptom reporting tracked actual EMF exposure under double-blind conditions. The abstract reports no consistent alignment between perceived exposure certainty or symptoms and true exposure status at the group level, with limited individual exceptions. Symptom reporting was related to certainty of being exposed for about half of participants, which the authors interpret as supporting a nocebo-type mechanism and motivating refinement of provocation protocols.

This exposure assessment measured environmental and auto-induced RF-EMF across more than 800 microenvironments in ten European countries, with a focus on 5G-related bands. Non-user environmental exposure was reported to be below international guideline values and similar to prior European research, while induced traffic substantially increased measured exposure, especially in uplink scenarios. The study also reports systematic differences by setting (cities vs villages) and by national precautionary limit policies.

This exposure-assessment study analyzed two years of continuous frequency-selective monitoring from 13 sensors in the five largest cities in Greece, focusing on the 3.6 GHz 5G band. It reports a gradual increase in 3.6 GHz environmental EMF levels over time and greater variability than legacy cellular bands, with 30-minute averaging reducing observed fluctuations. Despite the upward trend and variability, all measurements were reported to remain well below Greek and ICNIRP reference levels, and the authors emphasize the value of continuous monitoring as 5G deployment expands.

This conference paper examines extrapolation factors used for in-situ EMF exposure assessment of 5G base stations in realistic indoor and outdoor scenarios. Using both frequency-selective and code-selective measurement approaches under varying traffic conditions, it reports substantial variability in extrapolated exposure estimates driven largely by antenna radiation patterns. Outdoor environments showed more stable extrapolation than indoor environments, highlighting challenges for reliable exposure assessment when antenna patterns and network configurations are not well characterized.

This exposure assessment study introduces a cost-efficient add-on sensor attached to a smartphone to quantify auto-induced uplink RF-EMF transmission across 100–6000 MHz in multiple microenvironments. Activity-based surveys were conducted in seven European countries under non-user, maximum downlink, and maximum uplink scenarios. Reported power levels were lowest for non-user scenarios and higher during active use, with variation by country, urbanization, and setting. The authors frame the work as supporting future epidemiological research and planned validation against other tools.

This pilot animal study exposed mature male Wistar rats to 4.9 GHz electromagnetic fields described as 5G-standard, for 15 days (2 hours/day) in a semi-anechoic shielded chamber. Open-field testing found no clear behavioral differences between unmodulated and modulated exposures. Statistically significant behavioral changes occurred in both exposed and control animals, which the authors attribute to changes in the environmental electromagnetic background, making causal interpretation uncertain.