A novel in-air PIXE (Particle Induced X-ray Emission) setup was developed which is capable of the fast, sensitive, fully quantitative characterization of elemental composition of thin and thick samples for elements with Z > 6.

In this study, the identification of PM sources during smog episodes in Debrecen is presented. The smog episodes were characterized by the high concentration of PM₁₀, and were linked to a thermal inversion period in November 2011 in Hungary, when an anticyclone occurred across Europe. The sources of PM_2.5 and PM_coarse were identified by positive matrix factorization (PMF). Additionally, the source locations were explored by using the conditional probability function (CPF). A numerical weather prediction model (WRF) was also applied to evaluate the air pollution situation. In order to meet the goals of the study, the elemental composition with high (2-h) time resolution, the elemental size distribution, and the planetary boundary layer were examined in an urban background site of downtown Debrecen, Hungary. Our results highlight the importance of biomass burning (39%) and traffic (31%) as the major contributors to PM_2.5. The main tracers of these sources (K, Cl, Pb, Zn) appeared mainly in droplet mode (0.5–1 μm). The major sources of PM_coarse fraction were soil (32%), and dust attributed to tramline construction (30%). The combination of PMF and CPF results revealed that the PM₁₀ concentrations were affected by sources within the urban agglomeration of Debrecen (city centre and suburban areas) under the given meteorological conditions. This conclusion is further validated by the fact that the diurnal variation of the identified source contributions presented a distinct pattern that depended strongly on the daily activities of the city’s residents (compared to the usually unstructured diurnals of transported sources).

Background: Nuclear reactions involving $\alpha$ particles play an important role in various astrophysical processes such as the $\gamma$ process of heavy element nucleosynthesis. The poorly known low-energy $\alpha$-nucleus optical potential is a key parameter to estimate the rates of these reactions.

Background: In several processes of stellar nucleosynthesis, like the astrophysical $\gamma$ process, nuclear reactions involving $\alpha$ particles play an important role. The description of these reactions necessitates the knowledge of the $\alpha$-nucleus optical model potential (AOMP) which is highly ambiguous at low, astrophysical energies. This ambiguity introduces a substantial uncertainty in the stellar models for predicting elemental and isotopic abundances.

This study, conducted in Debrecen, Hungary, aimed to analyse atmospheric particulate matter (APM or PM) through radiocarbon and PIXE analyses during the winter smog (23–25 January) and spring (15–18 May) seasons. The information presented in this pilot study aims to provide insight into the importance of utilising detailed characteristics of the mass size distributions of fossil carbon (f_f) and contemporary carbon (f_C) content. Additionally, it seeks to compare these characteristics with the size distributions of various elements to enable even more accurate PM source identification. In winter, APM concentrations were 86.27 μg/m³ (total), 17.07 μg/m³ (f_C) and 10.4 μg/m³ (f_f). In spring, these values changed to 29.5 μg/m³, 2.64 μg/m³ and 7.01 μg/m³, respectively. Notably, differences in mass size distribution patterns were observed between the two seasons, suggesting varied sources for contemporary carbon. Biomass burning emerged as a crucial source during the smog period, supported by similar MMAD (Mass Median Aerodynamic Diameter) values and a strong correlation (r = 0.95, p < 0.01) between potassium and f_C. In spring, a significant change in the concentration and distribution of f_C occurred, with a broad, coarse mode and a less prominent accumulation mode. F_f was found to have similar distributions as PM, with nearly the same MMADs, during both periods. Finally, a comprehensive comparison of modal characteristics identified specific sources for the various components, including biomass burning, vehicle exhaust, coal and oil combustion, vehicle non-exhaust, road dust, tyre abrasion, mineral dust and biogenic emission. This study showcases how using radiocarbon and PIXE analysis in size distribution data can enhance our understanding of the sources of PM and their effects on different size fractions of PM.