- Population-weighted exposure to PM10 in Germany was significantly lower in 2023 than in 2010.
- In 2023, the population-weighted PM10 exposure was 11.3 µg/m³—approximately 42 % lower than in 2010.
- This decline in exposure is due to decreasing emissions from stationary sources (such as power plants, waste incineration facilities, residential heating, and industrial plants) as well as measures implemented in the transport sector.
To assess the health risks associated with fine particulate matter, it is essential to determine the population’s exposure to PM10 in Germany and evaluate it in terms of potential health effects. The indicator presented here reflects the average annual exposure of the total population in Germany to fine particulate matter (measured in µg/m³). It refers specifically to airborne particles with a diameter of up to 10 micrometers (PM10). By continuously monitoring this indicator, it is possible to identify temporal trends in the average PM10 exposure of the population in Germany.
Over the observed period, there has been a general downward trend in population exposure to particulate matter in Germany: in 2010, the indicator value was 19.5 µg/m³, whereas in 2023 it had dropped to 11.3 µg/m³. This corresponds to a reduction of approximately 42 %.
The observed decline in PM10 exposure is largely due to emission reduction measures targeting stationary sources (e.g., power plants, waste incineration facilities, households/small-scale consumers, and various industrial processes), as well as efforts in the transport sector (for more information on the contributions of individual sources, click here). A further reduction in exposure is expected by 2030 as a result of the emission reduction commitments under the NEC Directive. If the measures outlined in national air pollution control programs are implemented (in Germany, for example, the coal phase-out, the reduction of ammonia emissions from agriculture, and the transition to sustainable mobility, including electric vehicles), emissions of particulate matter and its precursor gases could be further reduced by 2030.
Further, variable weather conditions have a direct impact on PM concentrations. In some years, this can lead to increases or decreases in PM levels and may therefore mask the effects of simultaneous changes in emissions (for more information click here).
For the indicator, model data from the chemical transport model REM-CALGRID are combined with PM10 measurement data from the air quality monitoring networks of the German federal states and the German Environment Agency (UBA), and applied to the entire area of Germany. This is done using a spatial resolution of 2 x 2 km². The PM10 data are then combined with information on the spatial distribution of population density. To calculate the indicator, the PM concentrations in each grid cell are multiplied by the respective number of people assigned to that cell. The total is then summed across all grid cells and divided by the total population of Germany.
Only monitoring stations located in rural and urban background areas are included in the calculation of the indicator. Stations directly exposed to particulate emissions—such as those near traffic—are excluded. As a result, the indicator may slightly underestimate the actual exposure situation in Germany. The methodological approach is described in more detail in the scientific article by Kienzler et al. 2024 (in German, abstract in English).
Detailed information on this topic can be found in the data article ‘Bedeutung der Feinstaubbelastung für die Gesundheit’ (in German only).
