Real-Time Detection of Security Relevant Dusts using Single-Particle Mass Spectrometry: Explosives and Narcotics
Sunday, March 8, 2026 10:20 AM to 10:40 AM · 20 min. (America/Chicago)
Room 301A
Oral
Instrumentation & Nanoscience
Information
Beyond inhlable particles in air pollution (PM2.5), hazardous dusts pose serious risks to human health and safety, particularly in cases of accidental releases of toxic substances or the illegal transport and handling of drugs. The ongoing opioid crisis in the U.S. has underscored the urgent need for real-time detection technologies.
To address this gap, we developed an integrated approach comprising (I) pulsed particle resuspension, (II) aerosol concentration, (III) single-particle mass spectrometry (SPMS) detection, and (IV) real-time pattern recognition via machine learning. Furthermore airborne dust particles of explosives (e.g., TNT) can indicate threads.
Single-particle mass spectrometry (SPMS) serves as the core detection technology, enabling rapid on-line chemical characterization of individual airborne particles within complex aerosols (Pratt & Prather, 2012). Building on advancements in resonant laser ionization for particle-bound metals (Passig et al., 2020) and polycyclic aromatic hydrocarbons (Schade et al., 2019), we have tailored an advanced SPMS approach for the effective detection of drug- and explosive-related dusts. We present single-particle mass spectra of various drugs and explosives. SPMS-field tests have been performed. Measurements at the DHL-hub in Leipzig confirmed the successful identification of drug-containing packages. Additional experiments showcased the system’s ability to detect drug and tablet residues in real-time on contaminated surfaces and floors. To enable online screening and real-time risk assessment, we discuss implemented data analysis strategies.
The project is funded by the German Ministry of Education and Research (BMBF), project “HazarDust”, number 13N15567
Supported by German Research Foundation-SFB1477, project441234705.
Passig, J. et al. (2020) Atmos. Chem. Phys. 20, 7139–7152.
Pratt, K.A. and Prather, K.A. (2012) Mass Spectrom. Rev. 31 , 17 48.
Schade, J. et al. (2019) Anal. Chem. 91, 15, 10282–10288.
To address this gap, we developed an integrated approach comprising (I) pulsed particle resuspension, (II) aerosol concentration, (III) single-particle mass spectrometry (SPMS) detection, and (IV) real-time pattern recognition via machine learning. Furthermore airborne dust particles of explosives (e.g., TNT) can indicate threads.
Single-particle mass spectrometry (SPMS) serves as the core detection technology, enabling rapid on-line chemical characterization of individual airborne particles within complex aerosols (Pratt & Prather, 2012). Building on advancements in resonant laser ionization for particle-bound metals (Passig et al., 2020) and polycyclic aromatic hydrocarbons (Schade et al., 2019), we have tailored an advanced SPMS approach for the effective detection of drug- and explosive-related dusts. We present single-particle mass spectra of various drugs and explosives. SPMS-field tests have been performed. Measurements at the DHL-hub in Leipzig confirmed the successful identification of drug-containing packages. Additional experiments showcased the system’s ability to detect drug and tablet residues in real-time on contaminated surfaces and floors. To enable online screening and real-time risk assessment, we discuss implemented data analysis strategies.
The project is funded by the German Ministry of Education and Research (BMBF), project “HazarDust”, number 13N15567
Supported by German Research Foundation-SFB1477, project441234705.
Passig, J. et al. (2020) Atmos. Chem. Phys. 20, 7139–7152.
Pratt, K.A. and Prather, K.A. (2012) Mass Spectrom. Rev. 31 , 17 48.
Schade, J. et al. (2019) Anal. Chem. 91, 15, 10282–10288.
Day of Week
Sunday
Session or Presentation
Presentation
Session Number
OR-16-06
Application
Forensics/Homeland Security
Methodology
Mass Spectrometry
Primary Focus
Methodology
Morning or Afternoon
Morning
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