Air Pollution and Health: Kick-off for BioClis
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:
- In BioKlis a tool is to be created that makes possible to determine for large areas the so-called aggregate risk index (ARI) using the environmental parameters air temperature, irradiance, humidity, wind, and the chemical composition of the air.
- Mit BioKlis wird ein Web-basiertes Informationssystem mit Analysen und Vorhersagen bzgl. dieses Gesundheitsrisikos entstehen und als Service der Umweltforschungsstation Schneefernerhaus über das Alpine Environmental Data Analysis Center, AlpEnDAC, angeboten.
- In BioKlis a web-based Information system that includes analyses and forecasts relating to this health risk will be developed and offered as a service of the Schneefernerhaus Environmental Research Station via the Alpine Environmental Data Analysis Center, AlpEnDAC.
- Die Information soll umweltmedizinisch beurteilt werden. Für spezifische Erkrankungen sollen je nach Morbiditäts- und Mortalitätsrisiko Empfehlungen zum persönlichen Verhalten der Betroffenen gegeben und Gegenmaßnahmen erarbeitet werden, die in Hinblick auf künftige Klimaänderungen die Folgen minimieren können.
- The information will be evaluated from the point of view of environmental medicine. For specific illnesses, recommendations concerning personal habits will be given depending on the morbidity and mortality risk of those concerned, and countermeasures will be compiled that can minimise the consequences of future climate change.
- Zur Förderung der präventiven Medizin und besseren Anpassung an den Klimawandel wird mit BioKlis ein erster Schritt hin zu einem umfassenden Informationssystem geschaffen werden, das den Bürger über sein Umwelt- und Gesundheitsrisiko aufklärt.
- To support preventive medicine and better adaption to climate change, BioKlis will take the first step toward creating a comprehensive information system that informs people about their environmental and health risks.
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).
Figures: Determining an aggregate risk index requires extensive processing of various kinds of data such as information on land cover (fig. 1), a cadastral register of emissions (fig. 2) 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. 3). 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. 4)
