What’s in the dust? GC×GC-MS based non-target screening of house dust (Andriy Rebryk, MDCW 2025)

We, 11.6.2025 | Original article from: The Multidimensional Chromatography (MDC) Workshop
Non-target screening of indoor dust revealed 2500+ contaminants, including phthalates and COVID-19-related chemicals. Samples from 4 cities show distinct pollutant profiles. Workflow under development.
  • Photo: MDCW: What’s in the dust? GC×GC-MS based non-target screening of house dust (Andriy Rebryk, MDCW 2025)
  • Video: LabRulez: Andriy Rebryk: What’s in the dust? GC×GC-MS based non-target screening of house dust (MDCW 2025)

🎤 Presenter: Andriy Rebryk (Umeå University, Umeå, Sweden)

💾 PDF presentation

💡 Book in your calendar: 17th Multidimensional Chromatography Workshop (MDCW) 13 - 15. January 2026

Abstract

Air pollution is a global health concern, leading to ca. 9 million premature deaths annually. The WHO reported that ca. 99% of individuals are exposed to polluted air. Furthermore, studies have shown that European citizens spend up to 90% of their time indoors being in contact with household chemical residues. Therefore, it is crucial to determine which chemicals are being emitted and at what levels they exist within indoor media to which residents are exposed, such as house dust.

For this, a non-target screening (NTS) workflow was developed. Samples included dust from Umeå (Sweden), Munich (Germany), Lviv (Ukraine), a collaborative trial from the NORMAN Network, and NIST Standard Reference Material 2585. A two-step ultrasonic extraction using dichloromethane (DCM) and acetone was applied, followed by fractionation using aminopropyl solid-phase extraction cartridges. Two fractions were collected with DCM and DCM:methanol (1:1, v/v), respectively, and analyzed using LECO Pegasus BT 4D GC×GC-TOFMS. The acquired data were matched against NIST23 library, filtered, and aligned.

Over 2500 compounds were tentatively identified and classified. Samples showed a significant presence of plastic additives, particularly phthalates, and tertiary amines, including DIMLA 1214, whose increased use was reported during the COVID-19 pandemic. Principal component analysis illustrated that samples from Munich, Lviv, and NORMAN displayed similarity, while samples from Umeå and NIST differed from those and each other, suggesting the presence of unique contaminant sets. The work is ongoing, with the aims of creating an easy-to-use NTS workflow and identifying as many as possible contaminants in dust.

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