Practical Particulate Matter Sensing and Accurate Calibration System Using Low-Cost Commercial Sensors.

Area of Science:

• Environmental Science
• Sensor Technology
• Public Health

Background:

• Air pollution, particularly particulate matter (PM), poses significant health risks, contributing to cardiovascular and lung diseases.
• Accurate monitoring of ambient air quality is crucial for effective air purification and ventilation strategies.
• Commercial low-cost sensors often suffer from inaccuracies like noise, variation, and environmental interference.

Purpose of the Study:

• To develop a practical system for accurate particulate matter sensing using low-cost commercial sensors.
• To address and correct common errors encountered in light scattering-based PM measurement methods.
• To enhance the reliability and performance of low-cost air quality monitoring systems.

Main Methods:

• Implemented a short-term noise reduction technique to correct sensor measurement errors.
• Utilized auto-fitting calibration to address part-to-part variations and improve signal baseline accuracy.
• Developed a temperature and humidity compensation method to account for environmental interferences.

Main Results:

• The proposed system demonstrated high accuracy, with part-to-part repeatability below 2 μg/m³.
• The standard deviation of measurements in ambient air was approximately 1.1 μg/m³.
• The developed calibration and compensation methods significantly improved the performance of low-cost PM sensors.

Conclusions:

• The proposed system offers a practical and accurate solution for monitoring particulate matter air pollution.
• The applied methods for error correction are effective in enhancing the reliability of low-cost sensing technologies.
• This approach can be extended to improve the performance of other optical sensors for environmental monitoring.