Development and Validation of an Automated FlowCAM Method for Detecting and Quantifying Spheroidal Carbonaceous Fly-Ash Particles in Peat Samples

Abstract The increasing use of fly-ash particles generated from high-temperature industrial combustion in Anthropocene proxy research has increased interest in studying historical atmospheric contamination trends. Spheroidal carbonaceous particles (SCPs), a specific type of fly-ash, provide a direct anthropogenic marker preserved in stratigraphic archives, complementing isotopic approaches and strengthening chronological frameworks. Chemically robust and environmentally persistent, SCPs are widely used as indicators of industrial pollution. However, conventional SCP microscopy methods are time-consuming, motivating exploration of automated imaging systems for more efficient detection and quantification in peat records. This study develops a semi-automated SCP analysis method using a FlowCAM imaging system by creating a dedicated particle-recognition library. A FlowCAM equipped with a 10 × objective and an 80-µm flow cell was used, and SCP reference materials were incorporated to enhance classification accuracy. The resulting library was applied to peat samples spanning a concentration gradient. SCP concentrations obtained by FlowCAM were strongly linearly correlated with expected values. The method’s limit of detection was 350 g DM⁻ 1 , corresponding to the detection of a single SCP. Analysis of gradient samples showed that FlowCAM performs best when SCP concentrations are high, providing robust and reproducible counts when samples contain large numbers of particles. At very low concentrations, detection becomes less reliable because the standard protocol is based on a fixed sample volume, which inherently limits the probability of capturing rare particles. Although sensitivity could be increased by processing larger volumes, this was beyond the scope of this study. Overall, the method is well suited for screening and quantifying SCPs in moderately to highly contaminated samples—such as typical European industrial-era peat records—rather than targeting the detection of single or extremely sparse SCPs. This work demonstrates that FlowCAM offers a rapid, semi-automated, and cost-effective tool for analysing SCP trends in natural peat archives and represents a promising complement to conventional microscopy-based techniques.