NO2, O3, PM10 and PM2.5 concentrations - Daily geographical aggregates at ZIP-code level from CAMS European Air Quality Re-analyses.

This dataset offers daily aggregated measurements of air pollutants – NO2, O3, PM10, and PM2.5 – across distinct ZIP-code areas in Germany. The temporal coverage spans from January 1, 2013, to December 31, 2022, providing a comprehensive temporal context for analyzing long-term air quality dynamics.

Each daily entry comprises key statistical descriptors, encompassing mean, maximum, minimum, and standard deviation values of pollutant concentrations specific to each ZIP-code area. Additionally, for O3, the dataset includes an eight-hour rolling mean daily maximum.

Spatial reference is established via shapefiles provided by ESRI Deutschland (https://opendata-esri-de.opendata.arcgis.com/datasets/5b203df4357844c8a6715d7d411a8341_0). These shapefiles link the air quality data to precise ZIP-code areas .

The concentration data spanning from 2018 to 2022 originate from the European Air Quality Reanalyses dataset of the Atmosphere Data Store (ADS), an initiative by the Copernicus Atmosphere Monitoring Service (CAMS). Accessible via https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-europe-air-quality-reanalyses?tab=doc, this dataset offers a robust foundation for assessing air quality. For the years 2013 to 2017, data were previously obtained from a former download platform for the same dataset. Important: in future all data will be migrated to the Atmosphere Data Store (ADS) platform.

The native resolution of the CAMS data is 0.1° x 0.1° spatially and hourly temporally. To enhance spatial accuracy, the spatial resolution was virtually increased by a factor of 5 using bilinear interpolation, resulting in a refined grid. The daily mean concentrations were subsequently computed for this augmented grid.

Aggregated statistics were derived for each ZIP-code polygon, employing all grid cells intersecting with the polygons. The computation was based on the proportion of cell area included within the respective polygons.

This dataset constitutes a valuable resource for conducting ecologically designed epidemiological studies, as it facilitates the exploration of potential associations between air quality and health trends across broad geographical areas.

Generated using Copernicus Atmosphere Monitoring Service Information 2013-2022

本数据集提供德国各邮政编码区域内空气污染物（NO₂、O₃、PM10、PM2.5）的每日聚合测量数据。时间覆盖范围为2013年1月1日至2022年12月31日，为分析长期空气质量动态提供了完整的时间维度支撑。

每条每日记录包含关键统计指标，涵盖各邮政编码区域内污染物浓度的均值、最大值、最小值与标准差。此外，针对臭氧（O₃），数据集还包含每日最大8小时滑动平均值。

空间参考依托ESRI德国分部提供的形状文件（https://opendata-esri-de.opendata.arcgis.com/datasets/5b203df4357844c8a6715d7d411a8341_0），该文件可将空气质量数据与精确的邮政编码区域进行关联。

2018至2022年的浓度数据源自哥白尼大气监测服务（Copernicus Atmosphere Monitoring Service, CAMS）下属大气数据商店（Atmosphere Data Store, ADS）发布的《欧洲空气质量再分析数据集》，可通过https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-europe-air-quality-reanalyses?tab=doc获取，为空气质量评估提供了可靠的数据基础。2013至2017年的数据则取自该数据集的旧版下载平台。重要提示：未来所有数据将迁移至大气数据商店（ADS）平台。

CAMS原始数据的空间分辨率为0.1°×0.1°，时间分辨率为逐小时。为提升空间精度，研究人员通过双线性插值（bilinear interpolation）将空间分辨率提升5倍，得到精细化网格。随后基于该增强网格计算每日平均浓度。

针对每个邮政编码多边形区域，通过统计与该多边形相交的所有网格单元的面积占比，聚合得到各区域的统计指标。

本数据集为开展生态学设计的流行病学研究提供了宝贵资源，可用于探索大范围地理区域内空气质量与健康趋势间的潜在关联。

本数据集基于2013-2022年哥白尼大气监测服务信息生成。