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Related Experiment Video

Updated: Mar 29, 2026

Fa&#231;ade-Level Monitoring of CO2 Variability under Urban Heat Island Conditions using Low-Cost Sensor Data Loggers
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PurpleAir Sensor Deployment Trends and Uncertainties.

Chloe S Chung1, Annette C Rohr1

  • 1Electric Power Research Institute, Palo Alto, CA 94304, USA.

Sensors (Basel, Switzerland)
|March 28, 2026
PubMed
Summary

Low-cost fine particulate matter (PM2.5) sensors show long deployment times, especially in the western US. This persistence supports multi-year air quality analysis and exposure assessment.

Keywords:
PM2.5PurpleAirlow-cost air quality sensorssensor deployment

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Area of Science:

  • Environmental Science
  • Public Health
  • Sensor Technology

Background:

  • Low-cost fine particulate matter (PM2.5) sensors, like PurpleAir monitors, offer dense, hyper-local air quality data across the US.
  • Prior research concentrated on sensor accuracy, with limited understanding of deployment patterns and longevity for long-term studies.

Purpose of the Study:

  • To characterize the geographic distribution, deployment longevity, and persistence of outdoor PM2.5 sensors in the United States.
  • To assess the suitability of these sensor networks for multi-year exposure assessment and policy-relevant analyses.

Main Methods:

  • Utilized publicly available PurpleAir sensor data from 2016 to 2025.
  • Quantified deployment duration based on the time between the first and last publicly available observations.
  • Summarized deployment patterns nationally, by U.S. Census region, and by state.

Main Results:

  • Most publicly shared sensors demonstrated deployment durations exceeding three years.
  • The western United States exhibited the highest sensor density and longevity.
  • Descriptive summaries of PM2.5 concentrations were presented for four high-coverage states, stratified by deployment duration and urban-rural classification.

Conclusions:

  • The study establishes a national baseline for the availability and temporal continuity of low-cost PM2.5 sensor data.
  • Sensor persistence indicates significant potential for multi-year applications in exposure modeling and epidemiology.
  • Findings provide foundational context for expanding community air quality monitoring networks.