Abstract:
Accurate knowledge on the sources of pollutants and greenhouse gases (GHG) and of their emission rates would support political actions to improve air quality and mitigate climate change. Statistical atmospheric inversions techniques allow for quantifying pollutant and GHG emissions based on atmospheric concentration measurements and transport modeling. They have been used to monitor continental to industrial site scale emissions based on dedicated near surface measurement networks or satellite data. Measurements of the concentrations of air pollutants in cities have been mainly dedicated to the monitoring of the quality of air breathed by population. In principle, their analysis could support a fine grained mapping of the emission in urban areas, but several challenges are associated with the use of atmospheric inversion techniques for such an application. These include a suitable modeling of the chemistry and transport of gaseous species and particles at street scale, and solving for a high dimensional inversion problem due to the spatial heterogeneity of the urban sources. We first present our effort to develop efficient but robust street scale simulation of the chemistry transport of pollutants with the MUNICH model and its embedding in a classical regional eulerian model to establish a multi-scale modeling framework. We then present examples of our atmospheric inversion systems and their application at local scales to monitor the budget of city emissions of CO2 or of the CH4 emissions from industrial sites. These examples provide insights on the capabilities for solving emissions at fine spatial scales in the urban canopy. The presentation concludes on the perspectives to develop street scale atmospheric inversion frameworks which could assimilate data from existing networks of fixed monitoring stations or from the increasing number of routine mobile measurements.
Bio:
LSCE, CEREA and LISA are public laboratories of the Paris region dedicated to climate and environmental studies, members of the IPSL federation. The three laboratories cover activities for the modeling of the atmospheric chemistry, dynamics and composition at the global to the site scales, and applications of data assimilation techniques to control model state and parameters.
Yelva Roustan, research scientist at CEREA since 2009, has over 18 years of experience in air quality modeling. Its research has covered a range of pollutants (such as metals, particles and radionuclides) for environmental issues at different spatial and temporal scales (continental transboundary air pollution, chronic deterioration of air quality in urban areas, accidental releases, etc.). One of the current focus of his research activities concerns the interactions between scales and their modeling (e.g. between urban background and traffic vicinity).
Gregoire Broquet has a 17-year expertise in data assimilation for ocean modeling and for the atmospheric inverse modeling of GHG fluxes. After a PhD thesis at LEGI (Grenoble, France) and a postdoc at UCSC (Santa Cruz, California), both in ocean sciences, he joined LSCE in 2009. Since then, he has lead a range of activities for the monitoring of natural and anthropogenic GHG fluxes from the continental to the city / industrial site scales, based on the assimilation of in situ and satellite data.