Abstract
Exposure to poor air quality is considered a major influence on the occurrence of cardiovascular and respiratory diseases. Air pollution has also been linked to the severity of the effects of epidemics such as COVID-19 caused by the SARS-CoV-2 virus. Epidemiological studies require datasets of the long-term exposure to air pollution. We present the APExpose_DE dataset, 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 for Germany (corresponding to the Landkreis or Kreisfreie Stadt in Germany, 402 in total).
Highlights
Background & SummaryAir pollution is the largest environmental risk factor for premature mortality
The average European loses 2.2 years of life expectancy due to air pollution[1,2] A number of recent studies have shown that the impact of air pollution on the respiratory system has an adverse influence on the effects of the COVID-19 disease, with particulate air pollution contributing globally to 15 percent of COVID-19 mortality[3,4,5,6,7,8]
There are exceptions to this, such as the air pollution datasets published by Aaron van Donkelaar and co-workers which incorporate satellite data, modelling, and observational data[11,12,13], the latter of which was used in the Harvard study on the role of air pollution on COVID-19 mortality in the United States[4]
Summary
Background & SummaryAir pollution is the largest environmental risk factor for premature mortality. The dataset presented here was created in the context of a study investigating the role of long-term air pollution in the severity of COVID-19 outcomes for Germany. In this context we needed a long-term air pollution dataset at the county level for Germany, which we did not find available elsewhere.
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