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.