Optimal design of electromagnetic field exposure maps in large areas

Abstract

Optimal design of electromagnetic field exposure maps in large areas López-Espí PL, Sánchez-Montero R, Guillén-Pina J, Chocano-del-Cerro R, Rojas JAM. Optimal design of electromagnetic field exposure maps in large areas. Environmental Impact Assessment Review. Volume 106, 2024, doi: 10.1016/j.eiar.2024.107525. Abstract The mapping of electromagnetic field (EMF) exposure over large areas is a very useful tool for the analysis of epidemiological data and risk assessment. Its production requires a costly measurement process. To optimize the effort and ensure the representativeness of the exposure map, criteria for the selection of the sites to be measured must be established. This paper presents a methodology for conducting EMF exposure maps suitable for risk assessment evaluation in large areas. The proposal combines radio wave propagation criteria and GIS methods to optimize the sampling effort. The design criteria are based on the determination of a rectangular grid of 250 m side and the identification of the emitters within the area under study. Both urban and rural sites are analysed in the proposal and line of sight conditions (LOS) are considered to reduce the number of points required and thus optimize the measurement effort. Depending on the extent and regularity of the surface, the density of measurement points has been estimated to be between 8 and 10 points per square kilometre in the urban area. The proposed methodology has been applied to a case study of a 2.8 km2 urban area within a 35.11 km2 municipality, obtaining an average point density of 9.64 points/km2 in the urban area. The differences in exposure depending on the application of the criteria have been analysed by means of the statistical values of the sets and the subtraction of the maps generated using kriging techniques. According to our results, if LOS measurements are not properly incorporated, the mean value of the EMF is underestimated in the area under study. Conclusions In this proposal, the methodology for EMF exposure mapping in large areas has been analysed. To optimize the measurement effort over a large area, a division into 250 × 250 m2 urban grids should be considered, in which the possible sources of radiation should be known. A measurement under LOS conditions must be performed in each of the grids in which any of the emitters is present. The absence of measurements under LOS conditions implies an underestimation of the mean values. To select the rest of the grids to be measured, the viewshed analysis allows to simplify the number of measurements by grouping those grids determined as N-LOS. To achieve optimal interpolation results over the entire surface, sufficient measurements must also be available on its perimeter. Interpolation by ordinary stable kriging obtains adequate results under LOS and N-LOS conditions. The generated maps contribute to a better perception of risk as they provide an objective and simple tool to show the level of EMF. They do not require complex propagation models but are based on interpolations made within a GIS. They can also be combined, using these techniques, for risk assessment and even, if epidemiological data are available, for possible correlations studies. The proposal considers the differences between urban areas, with the possibility of multipath, and rural (non-urban) areas. For the analysis of urban areas, a grid of 250 × 250 m2 has been proposed as a guideline for the spatial organisation of the territory in urban areas and 500 × 500 m2 in rural areas. Depending on the extent and regularity of the surface, the density of measurement points has been estimated to be between 8 and 10 points per square kilometre in the urban area. Lower point densities result in IDW representations and higher densities increase the measurement effort excessively. In the case under study, for the urban area, a density of 9.64 points/km2 has been reached. The study has been performed following the six-minute averaging criterion and in a bandwidth from 100 kHz to 3 GHz. The latest ICNIRP recommendations modify these values to take into account, among others, the new 5G signals, not yet present in the area. The urban study was carried out in a mainly residential area, where there are no concentrations of the general public, which could lead to areas of greater exposure due to greater use of the network. For future studies, therefore, the measurement and comparison according to the latest ICNIRP recommendations is still pending in areas where the new 5G networks have been incorporated and in urban micro-environments where there is a higher population density or uses significantly different from residential. Another point of continuation of this research is the correlation of the measured values with tumor statistics and other diseases. The opportunity provided by exposure maps created for entire urban environments may allow, where appropriate, to find possible relationships. sciencedirect.com

AI evidence extraction

Main findings

The paper proposes a GIS- and propagation-criteria-based methodology for designing EMF exposure maps over large areas using grid-based sampling and LOS/N-LOS considerations. In the case study, an average measurement point density of 9.64 points/km² was achieved in the urban area, and results indicate that if LOS measurements are not properly incorporated, the mean EMF value is underestimated.

Outcomes measured

• EMF exposure mapping methodology for large areas
• Optimization of measurement site selection (LOS/N-LOS, grid-based sampling)
• Comparison of exposure maps/interpolations (kriging) and impact of LOS inclusion on mean EMF estimates

Limitations

• No health outcomes or epidemiological associations are reported; focus is on mapping methodology.
• 5G signals were not present in the study area; authors note newer ICNIRP recommendations and 5G-related assessment as future work.
• Details such as number of measurements/points taken are not explicitly stated in the abstract (only densities and areas).

Suggested hubs

• who-icnirp (0.6)
  Abstract explicitly discusses ICNIRP recommendations and measurement averaging criteria.

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    "study_type": "exposure_assessment",
    "exposure": {
        "band": "RF",
        "source": "environmental/area mapping (multiple emitters)",
        "frequency_mhz": null,
        "sar_wkg": null,
        "duration": "six-minute averaging criterion"
    },
    "population": null,
    "sample_size": null,
    "outcomes": [
        "EMF exposure mapping methodology for large areas",
        "Optimization of measurement site selection (LOS/N-LOS, grid-based sampling)",
        "Comparison of exposure maps/interpolations (kriging) and impact of LOS inclusion on mean EMF estimates"
    ],
    "main_findings": "The paper proposes a GIS- and propagation-criteria-based methodology for designing EMF exposure maps over large areas using grid-based sampling and LOS/N-LOS considerations. In the case study, an average measurement point density of 9.64 points/km² was achieved in the urban area, and results indicate that if LOS measurements are not properly incorporated, the mean EMF value is underestimated.",
    "effect_direction": "unclear",
    "limitations": [
        "No health outcomes or epidemiological associations are reported; focus is on mapping methodology.",
        "5G signals were not present in the study area; authors note newer ICNIRP recommendations and 5G-related assessment as future work.",
        "Details such as number of measurements/points taken are not explicitly stated in the abstract (only densities and areas)."
    ],
    "evidence_strength": "insufficient",
    "confidence": 0.7800000000000000266453525910037569701671600341796875,
    "peer_reviewed_likely": "yes",
    "keywords": [
        "electromagnetic field",
        "EMF exposure map",
        "GIS",
        "sampling design",
        "line of sight",
        "viewshed analysis",
        "kriging",
        "ordinary stable kriging",
        "urban",
        "rural",
        "risk assessment",
        "100 kHz to 3 GHz",
        "ICNIRP"
    ],
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