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CleanMat
Article . 2026 . Peer-reviewed
License: CC BY
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Detection of Particulate Matter With Lock‐In Thermography

Authors: Alina Oetsen; Christoph Geers; Andreas Traube; Gunter Festel; Daniel Fehr; Mathias Bonmarin;

Detection of Particulate Matter With Lock‐In Thermography

Abstract

ABSTRACT Ultrafine particles (UFPs), particularly black carbon (BC), are major contributors to air pollution, climate change, and health risks. Conventional quantification techniques such as Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), and Raman Spectroscopy, while effective, suffer from limitations in real‐time analysis, sample representativeness, and scalability. Lock‐in thermography (LIT) has emerged as a promising alternative, offering enhanced sensitivity and real‐time monitoring for nanoparticle detection. In this study, we employ LIT to quantify black carbon. Two measurement configurations—transmission and reflection mode—are utilized to assess spatial distribution and concentration dependence of BC particles collected on filter substrates. Our results demonstrate a strong correlation between measured thermal signals and reference concentrations, confirming LIT's precision in quantifying BC with high reproducibility. The imaging capability further reveals non‐homogeneous particle deposition patterns, which would be challenging to capture using conventional point‐based techniques. These findings establish LIT as a viable tool for real‐time BC quantification in environmental monitoring and industrial applications, overcoming the constraints of traditional measurement approaches.

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Keywords

Lock‐in thermography, Black carbon, 621.3: Elektro-, Kommunikations-, Steuerungs- und Regelungstechnik, Health, Quantification, Climate change, Ultrafine particle, Pollution, Measuring

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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