Epidemiological research around the world has shown that exposure of urban populations to fine microparticles (PM2.5) suspended in air from, among other things, car combustion, is responsible for many cases of lung and cardiovascular disease and even mortality. However, most of these studies examine urban centers as ensembles without considering that population exposure to microparticles is not homogeneous across an urban space. For example, individuals living near major arterial roads are much more exposed to microparticles than others living in low traffic neighborhoods. Unfortunately, ground stations measuring PM2.5 are few and far between to generate accurate microparticle concentration maps at fine scales. One way to spatialize information on microparticle concentrations is to introduce remotely sensed images that allows to calculate an optical parameter of aerosols, their optical depth. The use of medium-to-fine-resolution images is not common in this area. So, we wanted to look at their potential. Tests with hyperspectral and multispectral images at these resolutions have shown that optical depth can be estimated with enough accuracy. The AODFinder software developed for this purpose performs well. Unfortunately, the small sample of AOD values and PM2.5 concentration measurements did not allow us to conclude on the possibility of using AOD as a proxy for PM2.5 and thus on the possibility of refining microparticle monitoring at the local level. / Des recherches épidémiologiques à travers le monde ont mis en évidence que l’exposition des populations urbaines aux microparticules fines (PM2.5) en suspension dans l’air provenant, entre autres, de la combustion automobile, est à l’origine des nombreux cas des maladies pulmonaires et cardiovasculaires et même des cas de mortalité. Cependant, la plupart de ces études examinent les centres urbains comme des ensembles sans tenir compte que l’exposition des populations aux microparticules n’est pas homogène à travers un espace urbain. À titre d’exemple, les individus demeurant à proximité de grandes artères routières sont beaucoup plus exposés aux microparticules que d’autres demeurant dans des quartiers de faible circulation. Malheureusement, les stations terrestres de mesure des PM2.5 sont peu nombreuses pour permettre de générer des cartes de concentration des microparticules précises à des échelles fines. Un moyen pour spatialiser l’information sur les concentrations des microparticules est d’introduire l’imagerie de télédétection qui permet de calculer un paramètre optique des aérosols, leur profondeur optique. L’utilisation des images à résolution moyenne à fine n’est pas chose courante dans ce domaine. Ainsi nous avons voulu examiner leur potentiel. Les tests avec des images hyperspectrale et multispectrale à ces résolutions ont montré que la profondeur optique peut être estimer avec suffisamment de précision. Le logiciel AODFinder développé à cette fin se comporte bien. Malheureusement le faible échantillon des valeurs de AOD et des mesures des concentrations des PM2.5 ne nous a pas permis de se prononcer sur la possibilité d’utiliser le AOD comme proxy des PM2.5 et ainsi sur la possibilité de raffiner le monitoring des microparticules à l’échelle locale.

In this thesis, we present the Monte Carlo study of two prototypes of tele- scopes for the Cherenkov Telescope Array (CTA) observatory, followed by the first data analysis partially using our reconstruction pipeline based on Random Forests. The Monte Carlo model of the SST-1M prototype is created and val- idated by comparison with data. Using the precise Monte Carlo models, we evaluate the performance of the SST-1M and LST-1 prototypes, working so-far in mono-regime as standalone telescopes, resulting in their energy and angular resolution, and the differential sensitivity. We also present an analysis of the data from the first two Crab Nebula observation campaigns conducted with the LST-1 telescope. In the last part of the thesis, we present a study of aerosol optical depth of the atmosphere above both future sites of the CTA observa- tory, retrieved from photometric measurements of Sun/Moon photometers. We focus on the photometer in-situ calibration for nocturnal measurements and introduce corrections to minimize systematic shifts between diurnal and noc- turnal measurements. Using the developed methods, we present the aerosol characterization of both CTA sites based on the photometric data. 1

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Aerosols are small, micrometer-sized particles, whose optical effects coupled with their impact on cloud properties is a source of large uncertainty in climate models. While their radiative forcing impact is largely of a cooling nature, there can be significant variations in the degree of their impact, depending on the size and the nature of the aerosols. The radiative and optical impact of aerosols are, first and foremost, dependent on their concentration or number density (an extensive parameter) and secondly on the size and nature of the aerosols (intensive, per particle, parameters). We employed passive (sunphotmetry) and active (backscatter lidar) measurements to retrieve extensive optical signals (aerosol optical depth or AOD and backscatter coefficient respectively) and semi-intensive optical signals (fine and coarse mode OD and fine and coarse mode backscatter coefficient respectively) and compared the optical coherency of these retrievals over a variety of aerosol and thin cloud events (pollution, dust, volcanic, smoke, thin cloud dominated). The retrievals were performed using an existing spectral deconvolution method applied to the sunphotometry data (SDA) and a new retrieval technique for the lidar based on a colour ratio thresholding technique. The validation of the lidar retrieval was accomplished by comparing the vertical integrations of the fine mode, coarse mode and total backscatter coefficients of the lidar with their sunphotometry analogues where lidar ratios (the intensive parameter required to transform backscatter coefficients into extinction coefficients) were (a) computed independently using the SDA retrievals for fine mode aerosols or prescribed for coarse mode aerosols and clouds or (b) computed by forcing the computed (fine, coarse and total) lidar ODs to be equal to their analog sunphotometry ODs. Comparisons between cases (a) and (b) as well as the semi-qualitative verification of the derived fine and coarse mode vertical profiles with the expected backscatter coefficient behavior of fine and coarse mode aerosols yielded satisfactory agreement (notably that the fine, coarse and total OD errors were <~ sunphotometry instrument errors). Comparisons between cases (a) and (b) also showed a degree of optical coherency between the fine mode lidar ratios.