Ce travail présente l’algorithme GARRLiC (Generalized Aerosol Retrieval from Radiometer and Lidar Combined data). Le but de cet algorithme est d’inverser simultanément les mesures co-localisées d’un LiDAR et d’un photomètre solaire. Cet algorithme original permet de déduire un ensemble très complet de paramètres descriptifs de l’aérosol atmosphérique, paramètres à la fois intégrés sur la colonne atmosphérique et résolus verticalement. GARRLiC est basée sur la recherche du meilleur ajustement de données multi-sources avec contraintes a priori. Il est basée sur la recherche de la meilleure solution selon un ensemble de critères statistiques. Les paramètres déduits sont de 2 types. Certains sont des quantités intégrées sur la colonne atmosphériques tandis que d’autres sont fonction de l’altitude comme la concentration en particules pour les deux modes dimensionnels fin et grossier. Une étude de sensibilité a montré que l’ensemble des paramètres peut être restitué avec une bonne précision dans toutes les situations considérées. L’étude indique une précision moins bonne pour le mode fin et qu’en général la précision est moindre à faible épaisseur optique. Elle a également montré que la précision sur l’indice de réfraction pouvait être accrue si l’on prenait en compte la mesure de polarisation issue du photomètre solaire. L’impact de la prise en compte de mesure LiDAR et de bruit sur les mesures a été étudié. GARRLiC a été appliqué à des mesures réelles obtenues à Minsk (Biélorussie) et Lille (France). L’approche employée ici peut être facilement modifiée pour retrouver les propriétés de l’aérosol à partir de multiples combinaisons d’instruments de télédétection passif et actif. / This thesis presents the GARRLiC algorithm (Generalized Aerosol Retrieval from Ra- diometer and Lidar Combined data) that simultaneously inverts co-incident lidar and sun-photometer observations and derives a united set of aerosol parameters that describe both columnar and vertical aerosol properties. GARRLiC searches for the best fit of the multi-source measurements together with a priori constraints on aerosol characteristics through the continuous space of all possi- ble solutions under statistically formulated criteria. It retrieves height independent size distribution, complex refractive index and fraction of spherical particles together with vertically resolved aerosol concentration, all differentiated between fine and coarse aerosol modes. The potential and limitations of the method are demonstrated by sensitivity tests. The tests showed that the complete set of aerosol parameters for each aerosol component can be robustly derived with acceptable accuracy in all considered situations. Limited sen- sitivity to the properties of the fine mode and dependence of retrieval accuracy on the aerosol optical thickness for both modes were found. It was shown that sensitivity to fine mode refractive index could be improved by accounting for polarization data provided by passive instruments. The effects of the presence of lidar data and random noise on aerosol retrievals were studied. The algorithm was also applied to the real lidar and radiometer observations obtained over Minsk (Belarus) and Lille (France) AERONET sites. Suggested approach could be easily modified to retrieve aerosol properties from all possible combinations of existing passive and active remote sensing instruments.

This work focuses on improving the quality of carbon-based core-shell materials for high performance liquid chromatography (HPLC) via the characterization of the core materials, and also the development of chromatographic methods (separations) for them. In the early part of this work, I applied organic synthesis to make uniform, spherical poly(divinylbenzene) (PDVB) microspheres, and then carbonized them to prepare carbon core materials for core-shell particle synthesis. Here, I studied in detail the surface and material properties of these particles with multiple instruments, which allowed me to describe the physical and chemical changes that took place during each treatment. The uniform, spherical carbon core materials greatly improved the efficiency of the previously developed carbon-based core-shell HPLC columns from ca. 70,000 plates per meter (N/m) to ca. 110,000 N/m for various alkyl benzenes. Later, I focused on generating application notes to showcase these mixed-mode HPLC columns. Here, liquid chromatography mass spectrometry (LC-MS) was used for the detection of analytes that lack chromophores for UV detection. In this dissertation, Chapter 1 contains a historical background and theory of HPLC along with a review of the use of carbon-based core-shell materials for elevated pH and temperature applications. Chapter 2 describes the improvement of the efficiency of carbon-based materials for HPLC using carbonized PDVB microspheres as the carbon core material. Chapter 3 is a study on the characterization of carbonized PDVB microspheres with multiple instruments. Chapter 4 describes the separation of cannabinoids using three types of carbon-based mixed-mode HPLC columns. Chapter 5 consists of (i) guidelines for the retention mechanism of the core-shell particles that have been commercialized for chromatography by Diamond Analytics, a US Synthetic Company in Orem, Utah, and (ii) application notes for these columns. Finally, Chapter 6 discusses possible future work.