We present a roadmap for providing standardised BC measurements, which follows a top-down approach, beginning with SI-traceable measurements of the aerosol absorption coefficient (babs) using in-situ reference methods with a target measurement uncertainty of ≤ 10 % (coverage factor k=2). Two measurement workshops have been successfully conducted, providing essential data to achieve the research goals: 1) two primary reference methods for aerosol light absorption have been tested and validated; these include photo-thermal interferometry and extinction-minus-scattering for at least two different wavelengths. 2) MACBC has been determined for different aerosol mixtures including bare BC, coated BC and externally mixed BC.

This study presents the first experimental analysis of the thermal response time (𝜏) of single aerosol particles using multi-frequency photothermal interferometry (nω-PTI). Optically trapped tetraethylene glycol droplets were excited by a modulated infrared laser, and their frequency-dependent photothermal response was analyzed. A theoretical model was developed to separate the frequency-dependent particle temperature from the effects due to thermal wave propagation and the interferometric detection. Results showed good agreement with simulations for particles between 2 and 5 µm. The study highlights nω-PTI as a promising method to retrieve optical and thermophysical properties and analyze heat transport in the Knudsen transition regime.

Fine particulate matter (PM) poses significant health risks, necessitating accurate monitoring. Low-cost sensors (LCS) are increasingly used for PM measurement in citizen science and pollution mapping, but their reliability is affected by environmental factors and particle properties. Traditional calibration methods often fail to address non-linearities, prompting the use of Machine Learning (ML) for in-situ calibration. This study leverages the SensEURcity dataset from Antwerp, comparing ML models like linear regression, random forests, and Long Short-Term Memory (LSTM) networks. LSTM outperformed others models, achieving the lowest RMSE (8.79 µg/m³) . Model transferability revealed improved data reliability for deployed sensors across urban areas.

Measuring large aerosol particles in a wide size range is challenging due to sampling inefficiencies above 20 µm. The SwisensPoleno Jupiter addresses this with a three-stage virtual impactor, enabling efficient sampling and single-particle characterization using light scattering, holography, fluorescence, and polarization. A combined sizing approach integrates light scattering (0.5–15 µm) and holography (>10 µm) based on confidence metrics. Validation with PSL beads (0.6–100 µm) shows <6% error for 2–20 µm but larger deviations at detection limits.