Das Projekt "Transport related Air Pollution and Health impacts Integrated Methodologies for Assessing Particulate Matter (TRANSPHORM)" wird/wurde gefördert durch: Kommission der Europäischen Gemeinschaften Brüssel. Es wird/wurde ausgeführt durch: University of Hertfordshire, Higher Education Corporation.Objective: TRANSPHORM brings together leading air quality and health researchers and users to improve the knowledge of transport related airborne particulate matter (PM) and its impact on human health and to develop and implement assessment tools for scales ranging from city to Europe. Over four years, TRANSPHORM will aim to develop and implement an integrated methodology to assess the health impacts of PM air pollution covering the whole chain from emissions to disease burden. The objectives will be: - To improve our understanding of transport sources of size-resolved and speciated PM air pollution including non-exhaust, shipping, aviation and railways - To improved emission factors of ultrafine particle number (PN0.1) and mass fractions of PM1, PM2.5 and PM10 for key transport sources - To conduct targeted measurements in Rotterdam, Helsinki and Thessaloniki for source apportionment, exposure assessment and model evaluation - To quantify exposure to airborne PM in urban environments resulting from traffic, road, shipping, rail and aviation - To improve and integrate air quality dispersion and exposure models for urban and regional scales including long-range transport - To develop new concentration-response (CRF) linking long and short-term ambient residential exposure to size-resolved and speciated PM with key health endpoints - To develop and implement integrated assessment tool to investigate and analyse the whole chain of processes for selected cities and Europe - To incorporate micro-environmental PM concentrations, time-activity patterns, and estimates of internal dose into the health impact assessment - To conduct integrated health assessment of selected European cities - To design and implement mitigation and adaptation strategies for European and international policy refinement and development - To exploit the results of TRANSPHORM through global dissemination and interactions with stakeholders.
Das Projekt "Schwerpunktprogramm (SPP) 1167: Quantitative Niederschlagsvorhersage, Quantitative evaluation of regional precipitation forecasts using multi-dimensional remote sensing observations (QUEST)" wird/wurde gefördert durch: Deutsche Forschungsgemeinschaft. Es wird/wurde ausgeführt durch: Freie Universität Berlin, Institut für Meteorologie, Institut für Weltraumwissenschaften.Quantitative precipitation forecasts will be evaluated by considering the spatial-temporal structure of water in all its three phases using new remote sensing observations. By studying the whole process chain from the water vapour distribution through cloud processes to the amount of precipitation reaching the ground, weaknesses in the treatment of cloud processes in weather forecasting models will be identified. Improvements in predictions should be achieved by improving the assumptions about cloud and precipitation microphysics (e.g. conversion rates, drop size distributions, particle phase and shape) as well as the sub-grid variability. Existing observational datasets will be used in both observation-to-model and model-to-observation approaches. The most important are: detailed observations of the vertical hydrometeor distribution available at observatories equipped with advanced ground-based remote sensors, three dimensional distributions of polarimetric radar parameters and simultaneous observations of the 3D wind field, and high spatial resolution water vapour fields, cloud parameters, and precipitation-relevant microwave radiances from satellite. The use of forward operators allows the full exploitation of the information content of the remote Sensors and is an important step towards future data assimilation methods. The focus of the proposed research is an short-term predictions by the Lokal-Modell of the German Weather Service, however, the created tools will be transferable to other models.