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A Wearable Sensor Node for Measuring Air Quality Through Citizen Science Approach: Insights from the SOCIO-BEE

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This study introduces a wearable wireless sensor node (WSN) for citizen science air quality monitoring. The low-cost sensors provide reliable data on pollutants like PM2.5, empowering communities and informing policy.

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Area of Science:

  • Environmental Science
  • Public Health
  • Sensor Technology

Background:

  • Air pollution poses significant environmental and public health risks, particularly in urban settings.
  • Traditional air quality monitoring networks often lack the spatial resolution and public engagement needed for effective interventions.
  • Citizen science (CS) offers a promising approach to augment traditional monitoring efforts.

Purpose of the Study:

  • To develop and validate a novel wearable wireless sensor node (WSN) for citizen science-based air quality monitoring.
  • To assess the reliability and usability of low-cost sensors for measuring key air pollutants (NO2, O3, PM2.5).
  • To evaluate user engagement and perceptions of the developed system.

Main Methods:

  • Development of a body-mounted, low-cost WSN capable of measuring NO2, O3, and PM2.5.
  • Three pilot campaigns involving diverse user groups (seniors, commuters, students) in Italy, Greece, and Spain.
  • Validation of PM2.5 sensor data using direct comparison with reference stations and K-means spatial clustering analysis.
  • Assessment of user engagement and system usability through pre-/post-campaign surveys.

Main Results:

  • PM2.5 sensor data demonstrated a strong correlation with official data (R² = 0.75) and low average absolute error (0.54 µg/m³).
  • Spatial clustering analysis indicated high internal consistency and spatial homogeneity of measurements in locations without reference stations.
  • Over 70% of participants reported satisfaction with the system's usability and inclusiveness across all pilot studies.

Conclusions:

  • Wearable low-cost sensors, integrated with citizen science frameworks, can generate reliable and actionable air quality data.
  • The developed WSN empowers citizens to participate in environmental monitoring, contributing to evidence-based policy-making.
  • This approach enhances spatial resolution and public engagement in air quality monitoring initiatives.