Particulate matters (PM) have adverse effects with particular efficiency on human health. Climate effects through cloud and aerosol loading are of main importance. The PM physico-chemical behaviour is linked to hazardous air pollutants (HAP) chemistry and depends on emission speciation. Although useful data are provided by air pollution models, lack of knowledge in PM prediction and uncertainties in source emission, still remain. Multiplying field measurements, improving formulations of PM formation in models, are required to reduce these uncertainties for a better support of decision-makers related to policy and emission abatement strategies. The goal of this project consists in gaining new competencies, strengthening specialities in: air pollution modelling and PM2.5 concentration retrieval from satellite observations. The objectives consist in providing a holistic approach of PM2.5 prediction over European urban and regional areas composed by: • providing PM2.5 concentration map over Europe retrieved from satellite observations; • predicting PM2.5 map by improving PM2.5 formulation in existing air pollution multi-scale models; • valorising the candidate experiences and assets in multi-scale modelling and field observations, particularly of PM1 and HAP. In order to achieve such objectives the following tasks will be performed : WP1:Retrieving Aerosol Optical Depths derived from satellite observations and using Harvard techniques to deduce the PM2.5 distribution; WP2:Adapting existing multi-scale Eulerian models by integrating HAP chemistry including VOC/NOx/NH3/O3/SOx and speciated emission data developed under European projects, to provide PM2.5 concentration over European regions. Nesting techniques focusing on urban and regional scales are emphasized for Paris urban areas. WP3:Quality management of the “holistic” air pollution investigation tool: satellite& ground observations combined to multi-scale model results.
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