Design of an Integrated Platform for Mapping Residential Exposure to Rf-Emf Sources

Abstract

Design of an Integrated Platform for Mapping Residential Exposure to Rf-Emf Sources Corentin Regrain, Julien Caudeville, René de Seze, Mohammed Guedda, Amirreza Chobineh, Philippe de Doncker, Luca Petrillo, Emma Chiaramello, Marta Parazzini, Wout Joseph, Sam Aerts, Anke Huss , Joe Wiart. Design of an Integrated Platform for Mapping Residential Exposure to Rf-Emf Sources. Int J Environ Res Public Health. 2020 Jul 24;17(15):E5339. doi: 10.3390/ijerph17155339. Abstract Nowadays, information and communication technologies (mobile phones, connected objects) strongly occupy our daily life. The increasing use of these technologies and the complexity of network infrastructures raise issues about radiofrequency electromagnetic fields (Rf-Emf) exposure. Most previous studies have assessed individual exposure to Rf-Emf, and the next level is to assess populational exposure. In our study, we designed a statistical tool for Rf-Emf populational exposure assessment and mapping. This tool integrates geographic databases and surrogate models to characterize spatiotemporal exposure from outdoor sources, indoor sources, and mobile phones. A case study was conducted on a 100 × 100 m grid covering the 14th district of Paris to illustrate the functionalities of the tool. Whole-body specific absorption rate (SAR) values are 2.7 times higher than those for the whole brain. The mapping of whole-body and whole-brain SAR values shows a dichotomy between built-up and non-built-up areas, with the former displaying higher values. Maximum SAR values do not exceed 3.5 and 3.9 mW/kg for the whole body and the whole brain, respectively, thus they are significantly below International Commission on Non-Ionizing Radiation Protection (ICNIRP) recommendations. Indoor sources are the main contributor to populational exposure, followed by outdoor sources and mobile phones, which generally represents less than 1% of total exposure. Conclusions We have designed a statistical tool that uses surrogate models for spatiotemporal mapping of Rf-Emf exposure. Using a mathematical and probabilistic approach, this tool aggregates spatiotemporal surrogate models of Rf- Emf exposure with geographical data, population distributions, socioeconomic data, and ICT use patterns. Data fusion of all this heterogeneous information results in an innovative and advanced mapping of residential exposure providing information on variability, occurrence, and exposure quantiles relevant for the public, health researchers, political decision-makers, and risk assessors. Future works will improve the approaches developed. For the Rf-Emf exposure, some exposure sources (laptop, 4G, 5G, and other future technology) will have to be integrated into the exposure assessment to consider the evolution of technologies and usages. Certain exposure mechanisms such as outdoor-to-indoor attenuation or electric-field propagation will need to be better characterized. For the methodological aspect, some methods used in this study will also be applied to larger and heterogeneous territories as well as for exposure assessment to chemical agents or biological risk factors. Open access paper: mdpi.com

AI evidence extraction

Main findings

The authors designed a statistical tool integrating geographic databases and surrogate models to map spatiotemporal residential RF-EMF exposure from outdoor sources, indoor sources, and mobile phones, illustrated on a 100 × 100 m grid in Paris’ 14th district. Whole-body SAR values were reported as 2.7 times higher than whole-brain SAR, with higher mapped values in built-up versus non-built-up areas. Maximum SAR values did not exceed 3.5 mW/kg (whole body) and 3.9 mW/kg (whole brain), stated to be significantly below ICNIRP recommendations; indoor sources were the main contributor, followed by outdoor sources, with mobile phones generally <1% of total exposure.

Outcomes measured

• Modeled/mapped whole-body SAR
• Modeled/mapped whole-brain SAR
• Relative contribution of indoor vs outdoor vs mobile phone sources to population exposure
• Spatial variability of exposure (built-up vs non-built-up areas)
• Comparison of modeled SAR values to ICNIRP recommendations

Limitations

• Case study limited to a 100 × 100 m grid covering Paris’ 14th district (generalizability not established in abstract)
• Exposure assessment relies on surrogate models and data fusion (model uncertainty not quantified in abstract)
• Some sources/technologies noted as not yet integrated (e.g., laptop, 4G, 5G, future technologies)
• Certain exposure mechanisms noted as needing better characterization (e.g., outdoor-to-indoor attenuation, electric-field propagation)

Suggested hubs

• who-icnirp (0.7)
  Abstract explicitly compares modeled SAR values to ICNIRP recommendations.

{
    "study_type": "exposure_assessment",
    "exposure": {
        "band": "RF",
        "source": "residential (outdoor sources, indoor sources, and mobile phones)",
        "frequency_mhz": null,
        "sar_wkg": null,
        "duration": null
    },
    "population": "Residents/population in the 14th district of Paris (case study grid-based mapping)",
    "sample_size": null,
    "outcomes": [
        "Modeled/mapped whole-body SAR",
        "Modeled/mapped whole-brain SAR",
        "Relative contribution of indoor vs outdoor vs mobile phone sources to population exposure",
        "Spatial variability of exposure (built-up vs non-built-up areas)",
        "Comparison of modeled SAR values to ICNIRP recommendations"
    ],
    "main_findings": "The authors designed a statistical tool integrating geographic databases and surrogate models to map spatiotemporal residential RF-EMF exposure from outdoor sources, indoor sources, and mobile phones, illustrated on a 100 × 100 m grid in Paris’ 14th district. Whole-body SAR values were reported as 2.7 times higher than whole-brain SAR, with higher mapped values in built-up versus non-built-up areas. Maximum SAR values did not exceed 3.5 mW/kg (whole body) and 3.9 mW/kg (whole brain), stated to be significantly below ICNIRP recommendations; indoor sources were the main contributor, followed by outdoor sources, with mobile phones generally <1% of total exposure.",
    "effect_direction": "unclear",
    "limitations": [
        "Case study limited to a 100 × 100 m grid covering Paris’ 14th district (generalizability not established in abstract)",
        "Exposure assessment relies on surrogate models and data fusion (model uncertainty not quantified in abstract)",
        "Some sources/technologies noted as not yet integrated (e.g., laptop, 4G, 5G, future technologies)",
        "Certain exposure mechanisms noted as needing better characterization (e.g., outdoor-to-indoor attenuation, electric-field propagation)"
    ],
    "evidence_strength": "insufficient",
    "confidence": 0.7800000000000000266453525910037569701671600341796875,
    "peer_reviewed_likely": "yes",
    "keywords": [
        "RF-EMF",
        "population exposure",
        "residential exposure",
        "exposure mapping",
        "surrogate models",
        "SAR",
        "whole-body SAR",
        "whole-brain SAR",
        "indoor sources",
        "outdoor sources",
        "mobile phones",
        "ICNIRP",
        "Paris"
    ],
    "suggested_hubs": [
        {
            "slug": "who-icnirp",
            "weight": 0.6999999999999999555910790149937383830547332763671875,
            "reason": "Abstract explicitly compares modeled SAR values to ICNIRP recommendations."
        }
    ]
}

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