Assessment of long-term spatio-temporal radiofrequency electromagnetic field exposure

Abstract

Assessment of long-term spatio-temporal radiofrequency electromagnetic field exposure Aerts S, Wiart J, Martens L, Joseph W. Assessment of long-term spatio-temporal radiofrequency electromagnetic field exposure. Environ Res. 2017 Nov 13;161:136-143. doi: 10.1016/j.envres.2017.11.003. Abstract As both the environment and telecommunications networks are inherently dynamic, our exposure to environmental radiofrequency (RF) electromagnetic fields (EMF) at an arbitrary location is not at all constant in time. In this study, more than a year's worth of measurement data collected in a fixed low-cost exposimeter network distributed over an urban environment was analysed and used to build, for the first time, a full spatio- temporal surrogate model of outdoor exposure to downlink Global System for Mobile Communications (GSM) and Universal Mobile Telecommunications System (UMTS) signals. Though no global trend was discovered over the measuring period, the difference in measured exposure between two instances could reach up to 42dB (a factor 12,000 in power density). Furthermore, it was found that, taking into account the hour and day of the measurement, the accuracy of the surrogate model in the area under study was improved by up to 50% compared to models that neglect the daily temporal variability of the RF signals. However, further study is required to assess the extent to which the results obtained in the considered environment can be extrapolated to other geographic locations. ncbi.nlm.nih.gov

AI evidence extraction

Main findings

More than a year of fixed low-cost exposimeter network data in an urban environment was used to build a full spatio-temporal surrogate model of outdoor downlink GSM and UMTS exposure. No global trend over the measuring period was found, but exposure differences between two instances could reach up to 42 dB; incorporating hour and day improved model accuracy by up to 50% versus models neglecting daily temporal variability.

Outcomes measured

• Outdoor RF-EMF exposure (power density) spatio-temporal variability
• Surrogate model accuracy for outdoor downlink GSM/UMTS exposure

Limitations

• No global trend detected but large temporal variability; generalizability to other geographic locations is uncertain and requires further study
• Frequency details beyond GSM/UMTS not specified in the abstract

Suggested hubs

• exposure-assessment (0.9)
  Builds a spatio-temporal surrogate model using long-term RF-EMF measurement data from an exposimeter network.

{
    "study_type": "exposure_assessment",
    "exposure": {
        "band": "RF",
        "source": "base station (downlink GSM/UMTS)",
        "frequency_mhz": null,
        "sar_wkg": null,
        "duration": "more than a year of measurements"
    },
    "population": null,
    "sample_size": null,
    "outcomes": [
        "Outdoor RF-EMF exposure (power density) spatio-temporal variability",
        "Surrogate model accuracy for outdoor downlink GSM/UMTS exposure"
    ],
    "main_findings": "More than a year of fixed low-cost exposimeter network data in an urban environment was used to build a full spatio-temporal surrogate model of outdoor downlink GSM and UMTS exposure. No global trend over the measuring period was found, but exposure differences between two instances could reach up to 42 dB; incorporating hour and day improved model accuracy by up to 50% versus models neglecting daily temporal variability.",
    "effect_direction": "unclear",
    "limitations": [
        "No global trend detected but large temporal variability; generalizability to other geographic locations is uncertain and requires further study",
        "Frequency details beyond GSM/UMTS not specified in the abstract"
    ],
    "evidence_strength": "moderate",
    "confidence": 0.7399999999999999911182158029987476766109466552734375,
    "peer_reviewed_likely": "yes",
    "keywords": [
        "radiofrequency",
        "RF-EMF",
        "exposure assessment",
        "spatio-temporal model",
        "exposimeter network",
        "urban environment",
        "GSM",
        "UMTS",
        "downlink",
        "power density",
        "temporal variability"
    ],
    "suggested_hubs": [
        {
            "slug": "exposure-assessment",
            "weight": 0.90000000000000002220446049250313080847263336181640625,
            "reason": "Builds a spatio-temporal surrogate model using long-term RF-EMF measurement data from an exposimeter network."
        }
    ]
}

Comments

Log in to comment.

No comments yet.