Caseiro Alexandre, von Schneidemesser Erika
RIFS Research Institute for Sustainability at GFZ, Germany.
Data Brief. 2025 Jun 24;61:111833. doi: 10.1016/j.dib.2025.111833. eCollection 2025 Aug.
The link between exposure to polluted air and the outcome of diseases (e.g., cardio-vascular diseases, COVID-19) has been established. Nevertheless, research on the quantification of the relationship is still relevant today. Quantifying the link between the ambient atmospheric concentrations of pollutants and the outcome of diseases requires knowledge on the levels of the pollutants through time at various scales. In the present work, an improved and updated version of the APExpose_DE dataset is described. The dataset provides air pollution metrics at the yearly time resolution and at the spatial resolution of the NUTS-3 level, corresponding to the in Germany. The dataset evolved from its initial form by expanding the years covered and by refining the gap-filling methodology. The dataset can serve as input to, e.g., observational studies.
接触污染空气与疾病(如心血管疾病、新冠肺炎)的结果之间的联系已经确立。然而,如今对这种关系进行量化的研究仍然具有重要意义。量化污染物的环境大气浓度与疾病结果之间的联系需要了解不同尺度下污染物随时间的水平。在本研究中,描述了APExpose_DE数据集的一个改进和更新版本。该数据集以年度时间分辨率和德国NUTS-3级别的空间分辨率提供空气污染指标。该数据集从其初始形式演变而来,通过扩大涵盖的年份范围和改进数据填补方法。该数据集可作为例如观察性研究的输入。