APExpose_DE
Authors/Creators
- 1. Institute for Advanced Sustainability Studies
Description
The APExpose_DE dataset is a long-term (2010-2019) dataset providing ambient air pollution metrics at yearly time resolution for NO2, NO, O3, PM10 and PM2.5 at the NUTS-3 spatial resolution level (corresponding to the Landkreis/Kreisfreie Stadt in Germany).
The sources used for the production of the dataset were Airbase, from the European Environmental Agency (https://www.eea.europa.eu/themes/air/explore-air-pollution-data)
and the CAMS global reanalysis EAC4 (https://www.ecmwf.int/en/forecasts/dataset/cams-global-reanalysis). Stations of the types "Traffic" and "Industrial" were left out for being considered unrepresentative to long-term exposure, those of the type "Background" were included. Each station was geo-located within, and each computed yearly value associated to, a NUTS-3 unit. Within each NUTS-3 unit and for each metric, the yearly values per station were averaged in three ways, giving preference to different station sitings, each representing a different scenario: average, urban, remote.
The monitoring data were produced for the NUTS-3 units and the years where monitoring data for a given pollutant is available. In order to complete the dataset for the NUTS-3 units where no monitoring data for a given pollutant is available, the Copernicus Atmospheric Monitoring Service (CAMS) EAC4 reanalysis (https://www.ecmwf.int/en/forecasts/dataset/cams-global-reanalysis) was used. The yearly-averaged rasters from CAMS were vectorized and scaled to available monitoring data to obtain values for each NUTS-3 units.
As a final step, the Airbase and CAMS derived data were combined to produce the APExpose_DE dataset.
Files
APExpose_DE__2010-2019.csv
Files
(9.4 MB)
| Name | Size | Download all |
|---|---|---|
|
md5:b274073186433609d646ad81b061455b
|
2.7 MB | Preview Download |
|
md5:f5d72b060e9efe18fd67ebaba2a2bdc3
|
3.9 kB | Download |
|
md5:3119c6ee6ca6b9cf3561ca4a74af8af5
|
1.3 MB | Preview Download |
|
md5:cff8843552df93350adc4be1c1771c39
|
1.3 MB | Preview Download |
|
md5:e0a9c14b41514fd05139bcf08a0b32c6
|
4.1 MB | Preview Download |