A new air quality modelling approach at the regional scale using lidar data assimilation

Abstract : Assimilation of lidar observations for air quality modelling is investigated via the development of a new model, which assimilates ground-based lidar network measurements using optimal interpolation (OI) in a chemistry transport model. First, a tool for assimilating PM10 (particulate matter with a diameter lower than 10 um) concentration measurements on the vertical is developed in the air quality modelling platform POLYPHEMUS. It is applied to western Europe for one month from 15 July to 15 August 2001 to investigate the potential impact of future ground-based lidar networks on analysis and short-term forecasts (the description of the future) of PM10. The efficiency of assimilating lidar network measurements is compared to the efficiency of assimilating concentration measurements from the AirBase ground network, which includes about 500 stations in western Europe. A sensitivity study on the number and location of required lidars is also performed to help define an optimal lidar network for PM10 forecasts. Secondly, a new model for simulating normalised lidar signals (PR2) is developed and integrated in POLYPHEMUS. Simulated lidar signals are compared to hourly ground-based mobile and in-situ lidar observations performed during the MEGAPOLI (Megacities : Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation) summer experiment in July 2009. It is found that the model correctly reproduces the vertical distribution of aerosol optical properties and their temporal variability. Additionally, two new algorithms for assimilating lidar signals are presented and evaluated during MEGAPOLI. The aerosol simulations without and with lidar data assimilation are evaluated using the AIRPARIF (a regional operational network in charge of air quality survey around the Paris area) database to demonstrate the feasibility and the usefulness of assimilating lidar profiles for aerosol forecasts. Finally, POLYPHEMUS with the model for assimilating lidar signals is applied to the Mediterranean basin, where 9 ground-based lidar stations from the ACTRIS/EARLINET network and 1 lidar station in Corsica performed a 72-hour period of intensive and continuous measurements in July 2012. Several parameters of the assimilation system are also studied to better estimate the spatial and temporal influence of the assimilation of lidar signals on aerosol forecasts.
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Yiguo Wang. A new air quality modelling approach at the regional scale using lidar data assimilation. Atmospheric and Oceanic Physics [physics.ao-ph]. Ecole Polytechnique X, 2013. English. ⟨pastel-00957523⟩

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