10.1 Air quality and gas sensing technologies

Air quality impacts our health and environment daily. MEMS/NEMS technologies offer innovative solutions for monitoring and analyzing air pollutants. From particulate matter to volatile organic compounds, these tiny sensors provide real-time data on air composition.

Gas sensing technologies have evolved rapidly, with various sensor types now available. Electrochemical, metal oxide, and optical sensors detect specific gases with high sensitivity. MEMS-based gas chromatography and miniaturized mass spectrometry enable detailed analysis of complex gas mixtures.

Sensor Types

Particulate Matter Sensors

Top images from around the web for Particulate Matter Sensors

• 

  AMT - Laboratory evaluation of particle-size selectivity of optical low-cost particulate matter ... View original

  Is this image relevant?

• 

  AMT - Field evaluation of low-cost particulate matter sensors in high- and low-concentration ... View original

  Is this image relevant?

• 

  AMT - Evaluation of optical particulate matter sensors under realistic conditions of strong and ... View original

  Is this image relevant?

• 

  AMT - Laboratory evaluation of particle-size selectivity of optical low-cost particulate matter ... View original

  Is this image relevant?

• 

  AMT - Field evaluation of low-cost particulate matter sensors in high- and low-concentration ... View original

  Is this image relevant?

1 of 3

Top images from around the web for Particulate Matter Sensors

• 

  AMT - Laboratory evaluation of particle-size selectivity of optical low-cost particulate matter ... View original

  Is this image relevant?

• 

  AMT - Field evaluation of low-cost particulate matter sensors in high- and low-concentration ... View original

  Is this image relevant?

• 

  AMT - Evaluation of optical particulate matter sensors under realistic conditions of strong and ... View original

  Is this image relevant?

• 

  AMT - Laboratory evaluation of particle-size selectivity of optical low-cost particulate matter ... View original

  Is this image relevant?

• 

  AMT - Field evaluation of low-cost particulate matter sensors in high- and low-concentration ... View original

  Is this image relevant?

1 of 3

• Measure concentration and size distribution of airborne particles (PM1.0, PM2.5, PM10)
• Utilize various sensing principles such as light scattering, electrical impedance, or mechanical resonance
• Enable real-time monitoring of air quality in indoor and outdoor environments
• Provide insights into health risks associated with exposure to particulate matter (respiratory issues, cardiovascular diseases)
• Examples of particulate matter sensors include optical particle counters (OPCs) and beta attenuation monitors (BAMs)

Electrochemical Gas Sensors

• Detect specific gases through electrochemical reactions at the sensor's electrodes
• Consist of a sensing electrode, a counter electrode, and a reference electrode immersed in an electrolyte
• Offer high selectivity and sensitivity to target gases (carbon monoxide, nitrogen dioxide, sulfur dioxide)
• Require minimal power consumption and can be miniaturized for portable applications
• Find applications in air quality monitoring, industrial safety, and breath analysis (alcohol detection)

Metal Oxide Semiconductor Sensors

• Rely on changes in electrical conductivity of metal oxide films upon exposure to target gases
• Operate at elevated temperatures (200-500°C) to enhance sensitivity and selectivity
• Detect a wide range of gases including volatile organic compounds (VOCs), carbon monoxide, and hydrogen
• Offer advantages such as low cost, long lifetime, and compatibility with MEMS fabrication processes
• Can be integrated into sensor arrays for improved selectivity and multi-gas detection capabilities

Optical Gas Sensors

• Exploit light-matter interactions to detect and quantify gas concentrations
• Utilize various optical sensing techniques such as absorption spectroscopy, fluorescence, or surface plasmon resonance
• Provide high sensitivity, selectivity, and fast response times
• Enable remote sensing and long-distance monitoring of gas concentrations (open-path sensors)
• Examples include non-dispersive infrared (NDIR) sensors for carbon dioxide detection and tunable diode laser absorption spectroscopy (TDLAS) for methane monitoring

Detection and Analysis

Volatile Organic Compound (VOC) Detection

• Focus on detecting and quantifying VOCs in air, which are common indoor and outdoor pollutants
• Utilize various sensing technologies such as photoionization detectors (PIDs), metal oxide sensors, and electrochemical sensors
• Enable monitoring of total VOC (TVOC) levels and identification of specific VOCs (benzene, formaldehyde)
• Provide insights into indoor air quality, occupational health, and environmental pollution
• Find applications in air purification systems, industrial emissions monitoring, and breath analysis for disease diagnosis

MEMS-based Gas Chromatography

• Miniaturize conventional gas chromatography systems using MEMS technology
• Integrate microfluidic channels, micro-preconcentrators, and microsensors on a single chip
• Enable rapid and efficient separation of gas mixtures based on their interactions with a stationary phase
• Offer advantages such as reduced analysis time, low sample volume, and portable operation
• Find applications in environmental monitoring, industrial process control, and homeland security (detection of chemical warfare agents)

Miniaturized Mass Spectrometry

• Downscale traditional mass spectrometry systems using MEMS fabrication techniques
• Utilize microfabricated ion traps, ion guides, and detectors for compact and portable designs
• Enable real-time analysis of gas composition with high sensitivity and mass resolution
• Offer potential for in-situ monitoring of air quality, industrial emissions, and breath analysis
• Examples include microelectromechanical systems (MEMS) ion traps and miniature time-of-flight (TOF) mass spectrometers

Sensor Arrays

• Combine multiple gas sensors with different sensing principles or target gases into an array configuration
• Utilize pattern recognition algorithms and machine learning techniques to analyze the sensor responses
• Enable improved selectivity, sensitivity, and discrimination of gas mixtures compared to individual sensors
• Provide a "fingerprint" response pattern for different gas compositions and concentrations
• Find applications in electronic noses for odor detection, food quality monitoring, and medical diagnostics (breath analysis)

Calibration and Data Processing

Calibration and Drift Compensation

• Ensure accurate and reliable measurements by calibrating gas sensors against known reference standards
• Compensate for sensor drift caused by aging, environmental factors, or cross-sensitivity to interfering gases
• Utilize techniques such as zero and span calibration, multivariate calibration, and adaptive algorithms
• Implement periodic calibration routines and online drift correction methods to maintain sensor performance
• Develop calibration transfer strategies to enable interchangeability and comparability of sensor data across different devices and locations

Data Fusion and Machine Learning in Gas Sensing

• Combine data from multiple gas sensors or sensing modalities to enhance information extraction and decision-making
• Apply machine learning algorithms (neural networks, support vector machines) to gas sensor data for improved classification and quantification
• Utilize data fusion techniques (Kalman filtering, Bayesian inference) to integrate sensor measurements with contextual information (temperature, humidity)
• Enable advanced features such as gas source localization, plume tracking, and early warning systems
• Develop cloud-based platforms and IoT architectures for real-time data processing, visualization, and remote monitoring of gas sensor networks