Indicator: Population exposure to particulate matter (PM2.5) | Umweltbundesamt

At a glance

• Since 2010, the population's PM2.5 exposure above an annual average of 10 µg/m³ (interim target 4 of the new guideline values of the World Health Organisation (WHO) from 2021, equal to the old WHO guideline value from 2005) has decreased significantly in Germany.
• However, between 2010 and 2021, almost the entire population was exposed to particulate matter levels above the current WHO guideline value.
• Further measures to reduce particulate matter exposure in Germany are therefore required at national and European level to improve health protection.

Environmental importance

Particulate matter in ambient air is harmful to human health. The particles enter the human body through the respiratory system. Depending on the size of the particles, they can penetrate deeply into the respiratory system. Particularly small particles can enter the blood stream when penetrating the pulmonary tissue. There is clear evidence that particulate matter can trigger various diseases (see 'Particulate matter').

Particulate matter is mainly the result of human activities (e.g. combustion processes), but is also released by mechanical processes (e.g. the abrasion of tires and brakes). Part of the particulate matter is produced in the atmosphere by chemical reactions of other pollutants (such as nitrogen oxides and ammonia) and is therefore referred to as "secondary" particulate matter.

The indicator focuses on the particulate matter exposure levels from rural and urban background areas, but does not consider areas with increased particulate matter concentrations such as roads with high traffic volumes or areas that are close to large industrial plants. It can therefore be assumed that the approach used here slightly underestimates the overall exposure levels of the German population.

Assessing the development

During the entire period under consideration, almost the entire population of Germany was exposed to particulate matter concentrations above the current WHO guideline value for the PM2.5 fraction. This is 5 µg/m³ as an annual mean. The number of people affected in Germany increased slightly from 81.7 million to 83.2 million in the comparison between 2010 and 2021. However, this is due to the increase in the total population over this period. At the same time, the proportion of the population with PM2.5 exposure above the WHO interim target 4 (10 µg/m³ annual average) fell from 81.7 million in 2010 to 23.5 million in 2021 (corresponding to approx. 28.2 % of the population). This proves that measures to reduce emissions in recent years have already led to a significant reduction in particulate matter pollution in Germany.

A further reduction in exposure is expected by 2030 as a result of the emission reduction obligations under the NEC Directive. If the measures from the national air pollution control programmes are implemented (in Germany, these include the "coal phase-out", the reduction of ammonia emissions from agriculture and the transformation of transport (e-mobility)), emissions of fine particulate matter and its precursor gases can be further reduced by 2030. To protect health, however, even more far-reaching measures are also required at European level to further reduce particulate matter pollution. The EU Air Quality Directive (EU Directive 2008/50/EC) is currently being revised with the aim of aligning it more closely with the WHO recommendations in future. The proposal for a new EU limit value for PM2.5 from 2030 of 10 µg/m³ as an annual average is currently being discussed, which would correspond to the WHO's interim target 4.

Methodology

For the indicator, model data of the chemical transport model REM-CALGRID are combined with PM2.5 measurement data of the immission measurement networks of the federal states and the UBA and transferred to the entire area of Germany. Only those measuring stations that are not directly exposed to particulate matter emissions, for example from traffic, are considered for the indicator. The PM2.5 data is then combined with spatial information on population distribution. The methodological approach is described in Kienzler et al. 2024 (UMID 1/2024; in press).