Observation Analysis Based On Multi-wavelength Raman Lidar And Research On The Impact Of Different Models On The Retrieval Of Atmospheric Optical Products

Aerosols are diverse,and different types of aerosols have different optical and microphysical properties and can have significant effects on climate,the environment and even human health.Therefore,real-time and accurate acquisition of atmospheric aerosol properties,types and distribution is essential for research in geoscience and human health.The multi-wavelength Raman lidar is an advanced technology that can accurately obtain aerosol optical properties(aerosol extinction and backscatter coefficient)and provide the researcher with reliable data.In the inversion of aerosol optical properties based on multi-wavelength Raman lidar data,the atmospheric molecular number density is an important input parameter,which can be calculated from the atmospheric temperature and pressure,both of which can be obtained from atmospheric models(forecast or reanalysis models).In general,reanalyzes are more accurate than forecast,but,typically,they are not delivered in time for allowing nearreal-time lidar data analysis.So the forecast model is therefore the optimal choice for achieving lidar near-real-time observations.The main purpose of this study is to assess the impact of different atmospheric models(forecast and reanalysis models)on the inversion of aerosol optical properties and aerosol classification and to provide a reference for the model selection for lidar near-real-time observations.The first two chapters of the thesis focus on the main sources of aerosol,the importance of studying aerosols,the basic principles of lidar,and a description of the components of a multi-wavelength Raman lidar(MUSA)located at the CNR-IMAA site in Potenza,Italy.In the third section,the data from four stations(Potenza,Leipzig,Lille,Evora)of the European Aerosol Research Lidar Network(EARLINET)during two intensive measurement campaigns were used to analyse the influence of temperature and pressure information provided by different atmospheric models(forecast and reanalysis models)on the aerosol optical properties inversions from lidar observations.The results show that the different atmospheric models can have a significant impact on the aerosol extinction coefficient,with a maximum deviation of 20%at both 355 nm and 532 nm,mainly due to the difference in the gradient of the temperature profile provided by forecast and reanalysis models.For aerosol backscatter coefficient retrievals,different models can have a larger impact when the backscatter coefficient is retrieved with the elastic method than when the backscatter coefficient is calculated using the Raman method at both 355 nm and 532 nm.In addition,the atmospheric aerosol load can also influence the deviations in the aerosol extinction and backscatter coefficients,showing a large impact under low aerosol loading scenarios.Then,four observation cases from four different EARLINET stations are used for the further study of the influence of different atmospheric models on aerosol classification,and also give suggestions for the use of atmospheric models in the retrieve aerosol optical properties based on multi-wavelength Raman lidar and for subsequent aerosol classification studies.Finally,the results of a one-year observation of aerosol optical properties over Potenza by the MUSA system from October 2020 to September 2021 are analysed and the vertical distribution of seasonally averaged aerosol optical properties at different wavelengths in the low troposphere region is obtained.In addition,some cases of Saharan dust intrusion selected during the observation period were also studied.