Department of Physics, University of Cordoba, 14071 Córdoba, Spain.
Department of Energy Engineering, University of the Basque Country, 48013 Bilbao, Spain.
Int J Environ Res Public Health. 2023 Jan 4;20(2):917. doi: 10.3390/ijerph20020917.
This paper presents a meteorological approach to identify local and remote sources driving the variability of surface daily radon concentrations. To this purpose, hourly Rn concentration and surface meteorological measurements, and air mass trajectories at Bilbao station (northern Iberian Peninsula) during the period 2017-2018 have been taken as reference. To investigate the potential transport pathways and potential Rn sources, the backward trajectory cluster analysis, trajectory sector analysis (TSA), and potential source contribution function (PSCF) are applied. On average, the diurnal Rn cycle shows the expected behaviour, with larger concentrations during the night and minimum concentrations during the daylight hours, with differences in the seasonal amplitudes. According to daily differences between maximum and baseline values, Rn daily cycles were grouped into six groups to identify meteorological conditions associated with each amplitude, and potential source areas and transport routes of Rn over Bilbao. The trajectory cluster and the TSA method show that the main airflow pathways are from the south, with small displacement, and the northeast, while the analysis of surface wind speed and direction indicates that the highest amplitudes of Rn concentrations are registered under the development of sea-land breezes. The PSCF method identified south-western and north-eastern areas highly contributing to the Rn concentration. These areas are confirmed by comparing with the radon flux map and the European map of uranium concentration in soil. The results have demonstrated the need in combining the analysis of local and regional/synoptic factors in explaining the origin and variability of Rn concentrations.
本研究采用气象方法识别导致地表日氡浓度变化的局地和远程源。为此，参考了 2017-2018 年期间毕尔巴鄂站（伊比利亚半岛北部）的每小时氡浓度和地面气象测量值以及大气轨迹。为了研究潜在的输运途径和潜在的氡源，应用了后向轨迹聚类分析、轨迹扇区分析（TSA）和潜在源贡献函数（PSCF）。平均而言，氡的日循环表现出预期的行为，夜间浓度较大，白天浓度最小，季节性幅度存在差异。根据每日最大值和基线值之间的差异，将氡的日循环分为六组，以识别与每个幅度相关的气象条件，以及毕尔巴鄂上空氡的潜在源区和输运路径。轨迹聚类和 TSA 方法表明，主要气流路径是来自南方，位移较小，还有东北方向，而地面风速和风向的分析表明，在海陆风发展时，氡浓度的最高幅度最大。PSCF 方法确定了对氡浓度贡献最大的西南和东北地区。这些地区与氡通量图和欧洲土壤铀浓度图进行比较后得到了证实。结果表明，需要结合局地和区域/天气因素的分析来解释氡浓度的起源和变化。
