A comprehensive review of 5G NR RF-EMF exposure assessment technologies: fundamentals,

Environmental Research · 2024 · Unclear · Insufficient evidence

← Research stream

UnclearInsufficient evidencePaper 93

Study snapshot

PublicationEnvironmental Research · 2024

Study typereview

Reported directionUnclear

Evidence ratingInsufficient

Abstract

A comprehensive review of 5G NR RF-EMF exposure assessment technologies: fundamentals, advancements, challenges, niches, and implications Korkmaz E, Aerts S, Coesoij R, Bhatt CR, Velghe M, Colussi L, Land D, Petroulakis N, Spirito M, Bolte J. A comprehensive review of 5G NR RF-EMF exposure assessment technologies: fundamentals, advancements, challenges, niches, and implications. Environ Res. 2024 Jul 6;260:119524. doi: 10.1016/j.envres.2024.119524. Highlights • Monitoring exposure to radiofrequency electromagnetic fields (RF-EMF) is crucial for environmental health and risk assessment • A comprehensive review of the diverse landscape of RF-EMF assessment tools was missing. • There is a definite need for cost-effective and long-lasting EMF sensors. • Custom-developed RF-EMF measurement tools lack a standardized framework for comparison and validation. Abstract This review offers a detailed examination of the current landscape of radio frequency (RF) electromagnetic field (EMF) assessment tools, ranging from spectrum analyzers and broadband field meters to area monitors and custom-built devices. The discussion encompasses both standardized and non-standardized measurement protocols, shedding light on the various methods employed in this domain. Furthermore, the review highlights the prevalent use of mobile apps for characterizing 5G NR radio network data. A growing need for low-cost measurement devices is observed, commonly referred to as “sensors” or “sensor nodes”, that are capable of enduring diverse environmental conditions. These sensors play a crucial role in both microenvironmental surveys and individual exposures, enabling stationary, mobile, and personal exposure assessments based on body-worn sensors, across wider geographical areas. This review revealed a notable need for cost-effective and long-lasting sensors, whether for individual exposure assessments, mobile (vehicle-integrated) measurements, or incorporation into distributed sensor networks. However, there is a lack of comprehensive information on existing custom-developed RF-EMF measurement tools, especially in terms of measuring uncertainty. Additionally, there is a need for real-time, fast-sampling solutions to understand the highly irregular temporal variations EMF distribution in next-generation networks. Given the diversity of tools and methods, a comprehensive comparison is crucial to determine the necessary statistical tools for aggregating the available measurement data. Conclusions The objective of this review was to establish a groundwork for progress in the field of RF-EMF exposure assessment, ultimately contributing to a more thorough and efficient assessment. This review provides a comprehensive overview of the current state-of-the-art concerning RF-EMF measuring instruments. It covers a wide array of tools, such as spectrum analyzers, broadband field meters, area monitors, personal exposimeters, and custom-built instruments, as well as the existing measurement protocols, encompassing both standardized and non-standardized methods. In addition, we also have presented some of the most commonly used mobile apps for collecting 5G NR radio network data, which have also been used in RF-EMF exposure assessments. However, it is not yet clear on how accurate the measurement results of these apps are and how they compare among themselves and to more sophisticated tools. Most importantly, this review revealed the need for cost-effective and long-lasting measurement devices or sensors that are capable of collecting data at a high time resolution in various frequency bands, as well as withstanding various environmental conditions. These sensors are essential for conducting stationary, mobile, and personal exposure assessments across larger geographical areas, time intervals, and populations than current capabilities allow. Additionally, it is important to recognize that the specific requirements for these sensors differ based on their intended usage, e.g., on-body measurement devices need to take into account the influence of the body, vehicle-integrated sensors the influence of the speed and the relative position of the sensor on the vehicle, and sensors on infrastructure the influence of the height and the building materials. Furthermore, there exists a demand for real-time, fast-sampling solutions to comprehend the highly irregular temporal variations in EMF distribution within next-generation networks. Moreover, there is a notable absence of extensive information regarding currently employed custom- developed RF-EMF measurement tools, particularly with respect to measuring uncertainty. Considering the diversity of tools and methodologies in use, conducting a thorough comparison becomes crucial to identify the necessary statistical tools for aggregating the available measurement data. A more in-depth discussion relating the current 5G NR assessment methods to measurement equipment is intended for a follow-up study, which will describe more in detail the requirements, opportunities, and priorities for new, low-cost, custom-built measurement equipment. Open access paper: sciencedirect.com

Machine Enhanced Logic

AI evidence extraction

Structured fields below were generated from the paper’s abstract and metadata to make the evidence easier to inspect. Automated extraction may be incomplete or incorrect; verify important details against the original paper.

Study typereview

Effect directionunclear

PopulationNot supplied

Sample sizeNot supplied

ExposureRF

Evidence strengthInsufficientConfidence: 78% · Peer reviewed: unknown

Main findings

The review summarizes the state-of-the-art RF-EMF measurement instruments and protocols used for 5G NR-related exposure assessment, including spectrum analyzers, broadband meters, area monitors, personal exposimeters, custom-built tools, and mobile apps for 5G NR radio network data. It identifies needs for cost-effective, durable, high-time-resolution sensors, improved information on custom-built tools (including measurement uncertainty), and real-time fast-sampling approaches to capture irregular temporal variations; it also notes that the accuracy and comparability of mobile app measurements are not yet clear.

Outcomes measured

RF-EMF exposure assessment technologies and tools (e.g., spectrum analyzers, broadband field meters, area monitors, personal exposimeters, custom-built devices)
Measurement protocols (standardized and non-standardized)
Use of mobile apps for collecting 5G NR radio network data for exposure assessment
Needs/gaps in exposure assessment (cost-effective/long-lasting sensors, uncertainty characterization, real-time fast-sampling for temporal variability, data aggregation/statistical tools)

Limitations

Accuracy of mobile app-based measurements is stated as not yet clear and comparability to other tools is uncertain
Lack of comprehensive information on existing custom-developed RF-EMF measurement tools, particularly regarding measurement uncertainty
Review indicates a more in-depth discussion of 5G NR assessment methods vs equipment is deferred to a follow-up study

View raw extracted JSON

{
  "study_type": "review",
  "exposure": {
    "band": "RF",
    "source": "5G NR",
    "frequency_mhz": null,
    "sar_wkg": null,
    "duration": null
  },
  "population": null,
  "sample_size": null,
  "outcomes": [
    "RF-EMF exposure assessment technologies and tools (e.g., spectrum analyzers, broadband field meters, area monitors, personal exposimeters, custom-built devices)",
    "Measurement protocols (standardized and non-standardized)",
    "Use of mobile apps for collecting 5G NR radio network data for exposure assessment",
    "Needs/gaps in exposure assessment (cost-effective/long-lasting sensors, uncertainty characterization, real-time fast-sampling for temporal variability, data aggregation/statistical tools)"
  ],
  "main_findings": "The review summarizes the state-of-the-art RF-EMF measurement instruments and protocols used for 5G NR-related exposure assessment, including spectrum analyzers, broadband meters, area monitors, personal exposimeters, custom-built tools, and mobile apps for 5G NR radio network data. It identifies needs for cost-effective, durable, high-time-resolution sensors, improved information on custom-built tools (including measurement uncertainty), and real-time fast-sampling approaches to capture irregular temporal variations; it also notes that the accuracy and comparability of mobile app measurements are not yet clear.",
  "effect_direction": "unclear",
  "limitations": [
    "Accuracy of mobile app-based measurements is stated as not yet clear and comparability to other tools is uncertain",
    "Lack of comprehensive information on existing custom-developed RF-EMF measurement tools, particularly regarding measurement uncertainty",
    "Review indicates a more in-depth discussion of 5G NR assessment methods vs equipment is deferred to a follow-up study"
  ],
  "evidence_strength": "insufficient",
  "confidence": 0.78,
  "peer_reviewed_likely": "unknown",
  "keywords": [
    "5G NR",
    "RF-EMF",
    "exposure assessment",
    "measurement tools",
    "spectrum analyzer",
    "broadband field meter",
    "area monitor",
    "personal exposimeter",
    "sensor nodes",
    "mobile apps",
    "measurement protocols",
    "measurement uncertainty",
    "fast sampling",
    "distributed sensor networks"
  ],
  "suggested_hubs": [
    {
      "slug": "5g-policy",
      "weight": 0.72,
      "reason": "Focuses on 5G NR RF-EMF exposure assessment methods and tools, relevant to 5G exposure monitoring and assessment discussions."
    }
  ]
}

AI can be wrong. Always verify against the paper.

AI-extracted fields are generated from the abstract and metadata and may be incomplete or incorrect. This material is for informational purposes and is not medical advice.

Identifiers and source

DOI: 10.1016/j.envres.2024.119524
PubMed: Not supplied

Read the original paper →

Related papers

← Back to the Research Library