Nitrogen oxides, ozone, sulphur and particulate matter in the air we breathe have moved to the centre of public attention. Increasingly strict threshold values for these pollutants are being exceeded in numerous cities. However, whether and to what extent particular individuals suffer from air pollution depends on additional environmental parameters, as well as on personal disposition. In the recently launched BioClis project EOC is investigating these connections with the goal to inform people about their environmental and health risk.
Air pollution—and other environmental factors like intensive solar irradiation or large variations in temperature, humidity, and air pressure—can negatively affect health. But it is hard to describe the effects of such environmental variables on individuals. The connections between hazards and their impact are often nonlinear and can vary considerably from person to person. For that reason a statistically determined potential threat can only offer broad orientation.
However, it is possible today to measure with high spatial and temporal resolution many key environmentally-relevant quantities such as trace substances, irradiance, and meteorological parameters. In addition, computer models reliably describe the underlying physical processes taking place in the environment. Using powerful machine learning approaches these data and models can be analysed together with other information sources, for example from the medical sphere, and previously unknown relationships identified.
BioClis goals:
The BioClis project is part of the Bavarian collaborative research project Climate Change and Health, VKG, and is being financed by the Bavarian State Ministry of the Environment and Consumer Protection and the Bavarian Ministry of Health and Caregiving.
In addition to EOC, the project partners are the Department of Physics at Augsburg University (project lead), the Leibniz Supercomputing Centre in Garching (LRZ) and Augsburg University Clinic (UNIKA-T).
Nitrogen dioxide concentration on 15 Aug. 2017
Figures: Determining an aggregate risk index requires extensive processing of various kinds of data such as information on land cover (fig. top left), a cadastral register of emissions (fig. top right) and up-to-date measurements of pollutants by satellite-borne and ground-based instruments. These data are then correlated with numeric models that describe the chemical conversion processes (POLYPHEMUS/DLR) and the meteorology (WRF) (fig. left). These results are then converted into a so-called aggregate risk index using physiological information that describes the reaction of the human organism to environmental factors (fig. 2)
Figure 2: The aggregate risk index (ARI) is shown for cardiovascular diseases for Europe on 13 January 2018. An ARI can be supplied for various health risks such as respiratory problems or allergies. The basis for calculating ARI is a combination of the meteorological situation, the emission of pollutants, their dispersal by air flows, and the associated (photo)chemical conversion.