Recent studies have found associations between particle radioactivity and various human health outcomes. The aim of this study is to identify sources contributing to PM_2.5 (particulate matter with the aerodynamic diameter less than 2.5 μm) gross α- and β-activity levels. We used positive matrix factorization (PMF) to identify and apportion sources of PM_2.5 in Boston during the period of one year in Boston. Toward this end, we used daily concentrations of elements, black carbon (BC), and PM_2.5 mass. We identified six source types: regional pollution, motor vehicles, oil combustion, crustal, biomass burning, and sea salt. Subsequently, we performed multiple linear regression (MLR) analysis to examine the association between individual source contributions and PM_2.5 gross α- and β-activities. Our analysis suggested that regional pollution had the highest impact on both PM_2.5 α- and β-activities, followed by motor vehicles. Biomass burning and sea salt were not significantly associated with PM_2.5 β-activity.

最近的研究发现粒子放射性与各种人类健康结果之间存在关联。本研究的目的是确定导致 PM _2.5（空气动力学直径小于 2.5 μm 的颗粒物）总 α 和 β 活性水平的来源。我们使用正矩阵分解 (PMF) 来识别和分配波士顿一年期间PM _{2.5 的}来源。为此，我们使用了元素、黑碳 (BC) 和 PM _{2.5 的}每日浓度大量的。我们确定了六种来源类型：区域污染、机动车辆、石油燃烧、地壳、生物质燃烧和海盐。随后，我们进行了多元线性回归 (MLR) 分析，以检查单个源贡献与 PM _2.5总α-和β-活性之间的关联。我们的分析表明，区域污染对 PM _2.5 α- 和 β- 活动的影响最大，其次是机动车。生物质燃烧和海盐与 PM _2.5 β 活性没有显着相关性。