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Related Experiment Videos

Mapping carbon monoxide using GPS tracked sensors.

Richard Milton1, Anthony Steed

  • 1Department of Computer Science, University College London, Gower St., London, WC1E 6BT, UK. rwmilton@gmail.com

Environmental Monitoring and Assessment
|October 19, 2006
PubMed
Summary

This study mapped urban air pollution using mobile carbon monoxide (CO) sensors and Global Positioning System (GPS) receivers. Enhanced GPS data processing revealed fine-scale CO variations and pollution sources, highlighting the potential of mobile sensor networks.

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Area of Science:

  • Environmental Science
  • Urban Planning
  • Sensor Technology

Background:

  • Urban air pollution monitoring traditionally relies on fixed sensor sites, which can miss localized, high-concentration events.
  • Mobile sensing offers a promising approach to capture spatial variability in air quality.
  • Integrating Global Positioning System (GPS) data with mobile sensors presents challenges due to positional inaccuracies.

Purpose of the Study:

  • To pilot a mobile sensing system for mapping urban air pollution, specifically carbon monoxide (CO).
  • To investigate methods for improving the accuracy of GPS-tracked mobile sensor data.
  • To explore the potential of ad hoc mobile sensor networks for detailed air quality assessment.

Main Methods:

  • Utilized inexpensive mobile carbon monoxide (CO) sensors coupled with Global Positioning System (GPS) receivers.

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  • Developed data processing techniques to enhance GPS position accuracy using route knowledge and building geometry.
  • Collected mobile CO data along urban roads and compared it with fixed sensor site measurements.

    • Main Results:

    • Achieved significant improvements in position accuracy for mobile sensor data.
    • Successfully detected localized CO variations and specific events, such as road crossings.
    • Identified significant CO peaks near a fixed sensor site and mapped pollution gradients along urban canyons.

    Conclusions:

    • Mobile CO sensors, with enhanced GPS data processing, can provide high-resolution urban air quality mapping.
    • This approach effectively identifies pollution hotspots and variations influenced by urban structure and wind.
    • The study demonstrates the substantial potential of mobile sensor networks for future air pollution monitoring and smart city initiatives.