Metal nanoparticles (Au, Pt, Cu and Ni) were generated in the aerosol phase using spark ablation and analysed for size, shape and number concentration. Particles as small as 1 nm and up to > 60 nm show shapes from fully spherical to fractal-like as characterized by electron microscopy. Furthermore, the metal particles were mixed with TiO₂ nanoparticles, and the number and size of metal particles coating the TiO₂ were determined.

Quantitative real-time aerosol sampling on board aircraft platforms is challenging, especially at higher altitudes. Herein, we present comprehensive analyses of a new aircraft inlet system and tools for aerosol beam diagnostics for aerosol mass spectrometers (AMSs). The beam focusing of aerodynamic lenses and the thermal decomposition on the vaporizer were investigated. The new inlet system can be operated at higher altitudes while sampling aerosols over a broader size range than previous versions.

This study evaluates the performance of energy-dispersive X-ray fluorescence (ED-XRF) on particulate matter (PM₁₀) samples collected on quartz and Teflon filters through an inter-laboratory comparison. Detection limits were higher on quartz, but measurement repeatability was similar. Strong elemental correlations suggest that, with proper corrections, quartz filters can provide reliable results. These findings support their feasibility for ED-XRF analysis.

Quantification of autoxidation chemistry is a complex task essential to our understanding of atmospheric secondary aerosol formation and its impact on climate. In this work, we introduce the autoCONSTRAINT module, a semi-empirical method for deducing reaction rate coefficients for lumped autoxidation chemistry schemes based on experimental data. The theoretical approach is analytical and provides mathematically correct though non-unique solutions with low computational cost.

This study examines how sampling frequency influences the accuracy of low-cost particulate matter (PM) sensors. It finds that high sampling rates (15 s) are vital for detecting short pollution spikes like vehicle emissions, while lower rates (1 h) are enough for tracking long-term trends. Conducted in real-world outdoor conditions, the research offers practical guidance to balance energy use and data accuracy, supporting scalable, cost-effective air quality monitoring solutions.

New particle formation (NPF) is a process of forming new aerosol particles in the atmosphere. It was widely studied in boreal forest areas in Finland and Estonia, but its features and precursors in a Siberian boreal forest remained unclear. We did a comprehensive analysis using data from state-of-the-art instruments and implement both traditional and new methods of data analysis. Understanding these processes helps us grasp how Siberia’s atmosphere evolves and contributes to global climate dynamics.

This study investigates the decay of particle lung-deposited surface area (LDSA) concentrations following indoor particle emissions, with a focus on cooking activities. Two decay functions were derived and validated using measurement data. Applying the functions, it is shown that from 66.5 to 82.9 % of the exposure to cooking-generated particles occurred during the decay phase following the active cooking event. This highlights both the applicability and importance of the derived decay functions.

Back carbon is an atmospheric pollutant from combustion and contributes to the Arctic warming. However, its properties change as it travels through the atmosphere, affecting its impact. We recreated Arctic transport conditions in a laboratory to study how black carbon evolves over time. Our findings show that temperature and altitude strongly influence its transformation, providing key insights for improving climate models and understanding Arctic pollution.