Bioelectromagnetics. 2025 Dec;46(8):e70033. doi: 10.1002/bem.70033.
ABSTRACT
This paper presents a comprehensive measurement-based assessment of radio-frequency (RF) electromagnetic field (EMF) exposure level in a French city. Three types of assessment methods are used to collect measurement data: drive test (DT), spot measurements, and sensor networks. The DT measurements were conducted by a portable spectrum analyzer, i.e., Tektronix RSA 306B, connected to a 3-axis antenna mounted on the roof of the vehicle. DT system continuously recorded frequency-dependent electric field (E-field) values on a pre-defined outdoor route. The spot measurements were done in the same region, covered by DT, with both broadband and frequency-selective systems. Additionally, 19 sensors were installed on streetlamps in the same part of the city to measure the broadband E-field level. The overall statistical analysis on raw data shows good agreement on RF-EMF exposure level from three types of measurements. Then a distance-based moving average method was carried out to remove the random noise in the DT data, where the optimized window size is explored using Kolmogorov-Smirnov test. The smoothed DT data show a good correlation with nearby spot measurement values, as well as with base station antenna (BSA) density. Specific fifth-generation (5G) spot measurements, performed with and without traffic-attracting downloads, demonstrate the impact of beamforming on exposure levels in 5G new radio (NR) bands. Then spot measurements were used to build the exposure map using the kriging method, where the kriging prediction from the trained model is further compared with DT. Furthermore, the temporal variations observed in the sensor network were analyzed in relation to distance from the nearest BSA, revealing an inverse proportional relationship between E-field level and proximity to the nearest BSA. This study shows good reliability in assessing the RF-EMF exposure level using different systems. The advantages and limitations of different systems are also demonstrated by performing the intercomparison between data sets.
PMID:41230687 | DOI:10.1002/bem.70033
