» POMI Po-Valley Modelling Intercomparison Exercise


>> POMI Po-Valley Modelling Intercomparison Exercise>> Background

The Po valley has been identified as one hot spot area where pollutant levels will remain problematic in spite of application of the current legislation devoted to air pollution control. By 2020, health impact on population and effects on ecosystems by ozone and eutrophication are calculated to be amongst the highest in Europe and anthropogenic PM2.5 levels are expected to be responsible for a loss of ten months of life expectancy. In general, long-range transported air pollution in the Po-Valley represents only a fraction of 30-40%. This stresses the importance of local control measures in the area to efficiently reduce the impact of air pollution. Similarly to other regions, Lombardy has designed a regional air quality plan which includes a series of control measures with the aim to abate air pollution levels.

In the frame of a collaboration agreement signed between JRC (Joint Research Centre of the European Commission) and the government of Lombardy region, the TAQU (Transport and Air Quality Unit) is coordinating a Model Intercomparison exercise over the Po Valley (POMI) to explore the changes in urban air-quality predicted by different atmospheric chemistry-transport-dispersion models (CTM’s) in response to changes in emissions in the Po Valley. POMI will focus on ambient levels of ozone, PM and also NO2. Because assessment of health impact requires information about the long-term exposure to the various air pollutants, as defined by the EU-Directives, the methodology of POMI will be based on long-term simulations with an hourly time resolution. It is hypothesized that the range of responses produced by the different models involved in this study will be representative of the uncertainty in our knowledge about the physics and the chemistry as currently accounted for in air quality modelling. The “average” between model responses (“model ensemble”) which has been shown in former studies to provide the “best” response in terms of validation will be used in POMI.