IRCELINE, Sciensano, UHasselt, ULB-ERASME, Zeepreventorium
Reconstructing four decades of spatio-temporal airborne pollen levels for Belgium to assess the health impact
To date there is a global increase in the burden of allergic respiratory diseases enhanced by air pollution. Anthropogenic emissions may affect both the allergens as well as the allergic subjects by increasing the immune reaction and by an intensified biogenic emissions of airborne pollen. In Europe, a quarter of the population suffers from pollinosis, whereas in some countries the prevalence is over 40%.
Sciensano has a longstanding history of observing various types of pollen in Belgium with a well-established time series over Brussels since the start of 1980s. The aerobiological network of Sciensano, i.e. the observation of pollen on other locations in Belgium, has been submitted to quiet some changes over time. Consequently, this results in a spatial and temporal heterogeneous datasets of airborne pollen levels over the Belgian territory.
Chemical transport models (CTMs) are able to estimate airborne pollen levels both in a consistent spatial as well as temporal way by dealing with pollen as large biogenic aerosols emitted by vegetation and subjected to transportation and deposition under various meteorological conditions. At the Royal Meteorological Institute of Belgium, the CTM SILAM has been successfully used to model time series of airborne pollen of birches and grasses based on ECMWF’s reanalysed meteorological datasets.
By combining the CTM SILAM with the heterogeneous observations of airborne pollen an opportunity is created to reconstruct the spatio-temporal distributions of airborne pollen levels near the surface and to investigate associations between pollen, air pollution and health. This requires the timely reconstruction of land-use and land-use change over four decades in order to produce the proper spatio-temporal distributions of emissions sources ingested by SILAM. Changes of land-use will be estimated using the heritage of long time series of vegetation indices derived from satellite remote sensing platforms such as NOAA-AVHRR and its successors. RMI has an in-house long time series of climate data at their disposal useful for further data analysis. Air quality data starting in the 1990s will be consulted from IRCELINE.
Dr. ir. Willem Verstraeten (Co-PI and principal scientist) and Dr. ir. Andy Delcloo (PI)
Royal Meteorological Institute of Belgium