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<p>Measuring airborne fine particulate matter (PM<sub>2.5</sub>) in the context of health-based field research introduces many logistical challenges including remote equipment setup, data access, and maintenance by both researchers and participants. In preparation for a 17-site, 228-household clinical trial, we developed methods to validate low-cost, light-scattering PM<sub>2.5</sub> sensors (model PAII-SD, PurpleAir, Inc, USA) against a Federal Equivalent Method instrument (model BAM 1020, Met One Instruments, USA) for remote measurement of indoor PM<sub>2.5</sub> concentrations among participating households over 6&#xa0;months. To allow real-time, remote data access by the research team, we developed procedures for pairing the light-scattering PM<sub>2.5</sub> sensors for each household with a portable Wi-Fi hotspot device (model Solis Lite, Skyroam, Inc, USA) prior to shipping them to participants. Armed with this remote data access, we created a process for daily automated data extractions to ensure sensors remained online and to assess data quality. Our methods support the feasibility of obtaining long-term, continuous PM<sub>2.5</sub> measurement reliably and accurately in the context of a research trial using low-cost, light-scattering sensors. The framework we describe in this methods paper can serve as a model for future environmental health research studies.</p>

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A novel methodology for using light-scattering sensors to measure indoor particulate matter in a multi-site clinical trial

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月31日

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  • Ethan S. Walker,
  • Sara M. Cox,
  • David Jones,
  • Taylor Stewart,
  • Jennifer Faiella,
  • Cindy S. Leary,
  • Laurie Chassereau,
  • Linda Y. Fu,
  • Jeannette Y. Lee,
  • Paul G. Smith,
  • Kelly Cowan,
  • Erin O. Semmens

摘要

Measuring airborne fine particulate matter (PM2.5) in the context of health-based field research introduces many logistical challenges including remote equipment setup, data access, and maintenance by both researchers and participants. In preparation for a 17-site, 228-household clinical trial, we developed methods to validate low-cost, light-scattering PM2.5 sensors (model PAII-SD, PurpleAir, Inc, USA) against a Federal Equivalent Method instrument (model BAM 1020, Met One Instruments, USA) for remote measurement of indoor PM2.5 concentrations among participating households over 6 months. To allow real-time, remote data access by the research team, we developed procedures for pairing the light-scattering PM2.5 sensors for each household with a portable Wi-Fi hotspot device (model Solis Lite, Skyroam, Inc, USA) prior to shipping them to participants. Armed with this remote data access, we created a process for daily automated data extractions to ensure sensors remained online and to assess data quality. Our methods support the feasibility of obtaining long-term, continuous PM2.5 measurement reliably and accurately in the context of a research trial using low-cost, light-scattering sensors. The framework we describe in this methods paper can serve as a model for future environmental health research studies.