Instrument for Measuring Particulate Aerosol Elemental Composition

Tech ID: 34646 / UC Case 2026-433-0

Abstract

Researchers at the University of California, Davis have developed advanced spectroscopy devices enabling real-time, cost-effective measurement of elemental composition in airborne particulate aerosols.

Full Description

This technology features spark-induced breakdown spectroscopy devices designed to measure the elemental composition of particulate aerosols in real time. Using a combination of air sampling, spark generation, optical signal detection, and spectral analysis, the device detects trace metals emitted from various sources such as industry and traffic. The system includes a removable spark electrode cartridge, high-voltage circuitry to generate plasma from captured particles, an optical fiber to relay light signals, a spectrometer for spectrum generation, and a microcontroller to analyze elemental composition and source identification. The technology is optimized for rapid, accurate analysis while overcoming the limitations of costly and maintenance-heavy traditional instruments.

Applications

  • Environmental justice and community air quality monitoring. 
  • Industrial emissions compliance and process control. 
  • Mobile air quality monitoring platforms for rapid response. 
  • Regulatory agencies requiring real-time data for decision-making. 
  • Urban and traffic pollution surveillance. 
  • Research in atmospheric sciences and environmental health.

Features/Benefits

  • Reduces costs by providing an affordable alternative to high-priced X-ray fluorescence instruments. 
  • Delivers real-time, continuous measurement of particulate metal concentrations. 
  • Simplifies maintenance through a modular design with a removable spark electrode cartridge. 
  • Lowers operational costs by minimizing power and service requirements. 
  • Detects trace metals such as lead, chromium, nickel, cadmium, and manganese with high sensitivity. 
  • Enhances precision in elemental identification and concentration estimation using integrated machine learning. 
  • Attributes particulate sources accurately via spectral analysis and mixture modeling. 
  • Facilitates deployment in diverse settings with a compact, portable design. 
  • Eliminates the high cost and operational complexity associated with traditional real-time particulate metal analyzers. 
  • Expands accessibility to advanced monitoring for community-based and mobile applications. 
  • Provides rapid detection for acute emission events and fluctuating airborne metal concentrations. 
  • Addresses the need for low-maintenance, energy-efficient devices in environmental monitoring. 
  • Improves source attribution and exposure risk assessment of particulate metals.

Contact

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Inventors

  • Jang, Junbeom
  • Lopez-Reyna, Brenda E.
  • Wallis, Christopher
  • Wexler, Anthony S.

Other Information

Keywords

air sampling, airborne pollutants, aerosol elemental analysis, environment sensing, machine learning, particulate metals, plasma spectroscopy, real-time monitoring, spark-induced breakdown spectroscopy, spectrometer

Categorized As