这项研究,在德布勒森进行,匈牙利,旨在通过冬季烟雾(1月23日至25日)和春季(5月15日至18日)季节的放射性碳和PIXE分析来分析大气颗粒物(APM或PM)。本试点研究中提供的信息旨在深入了解利用化石碳(ff)和当代碳(fC)含量的质量分布的详细特征的重要性。此外,它试图将这些特性与各种元素的尺寸分布进行比较,以实现更准确的PM源识别。在冬天,APM浓度为86.27μg/m3(总计),17.07μg/m3(fC)和10.4μg/m3(ff)。在春天,这些值分别变为29.5μg/m3、2.64μg/m3和7.01μg/m3。值得注意的是,在两个季节之间观察到质量大小分布模式的差异,提出了当代碳的各种来源。生物质燃烧成为烟雾期间的重要来源,由相似的MMAD(质量中值空气动力学直径)值和钾和fC之间的强相关性(r=0.95,p<0.01)支持。在春天,fC的浓度和分布发生了显著变化,一个广泛的,粗糙模式和不太突出的积累模式。Ff被发现具有与PM相似的分布,使用几乎相同的MMAD,在这两个时期。最后,对模态特征的综合比较确定了各种组件的特定来源,包括生物质燃烧,汽车尾气,煤和石油燃烧,车辆非排气,道路灰尘,轮胎磨损,矿物粉尘和生物排放。这项研究展示了如何在尺寸分布数据中使用放射性碳和PIXE分析可以增强我们对PM来源及其对PM不同尺寸分数的影响的理解。
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 (ff) and contemporary carbon (fC) 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 (fC) and 10.4 μg/m3 (ff). 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 fC. In spring, a significant change in the concentration and distribution of fC occurred, with a broad, coarse mode and a less prominent accumulation mode. Ff 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.