During the last years perovskite materials have taken the photovoltaic community by storm, bringing promises of solar cells with efficiencies comparable to conventional silicon devices but at a lower price. However perovskite solar cells so far are facing two main obstacles, they are unstable in the presence of air, moisture and heat and they are usually toxic due to being based on lead-halide materials. This has spurred investigations into alternative materials with similar properties but without the mentioned drawbacks. Just next to Pb in the periodic table is bismuth (Bi) with just one more electron in its outer-shell, Bi however is less toxic. In this work the perovskite derived compounds of Ag-Bi-I and Cu-Bi-I are characterized and their properties as light absorbing material in solar cell devices are investigated. Devices are prepared by preparing Ag-Bi-I and Cu-Bi-I solutions which are then spin-coated on top of a mesoporous TiO2. A conducting polymer, P3HT, was then deposited and serve as hole transport material. For Ag-Bi-I, the molar ratios of AgI:BiI3= 1:2 and 2:1 were observed with SEM to form homogeneous crystal films with one dominating crystal phase, which by XRD could be determined to most likely have formed a cubic AgBi2I7 crystal structure for the 1:2 ratio and a hexagonal Ag2BiI5 crystal structure for the 2:1 ratio. The Cu-Bi-I materials were not successfully synthesized to form homogeneous films with a dominating crystal phase, although several molar ratios were investigated. All investigated compositions of both Cu and Ag devices showed to in principle work as light absorbing materials, the best Ag-Bi-I device showing a PCE of 1.92%, for the 2:1 ratio, while the Cu-Bi-I devices at best reached 0.32% for a ratio of 1:1. XPS measurements were carried out with a classical in-house XPS using an Al K X-ray source of 1486.7 eV as well as at the Diamond Light Source (UK) synchrotron facility using photon energies of 758 eV and 2200 eV so that a depth resolution of the composition could be observed. Because of their inhomogeneous crystal formation, XPS couldn’t give much useful quantitative information regarding the Cu devices. For Ag devices it was observed that the stoichiometry at the extreme surface deviated from that predicted by XRD, but deeper into the surface the relative ratio of elements approach the predicted ones, hinting towards a different structure at the outermost surface or a lot of surface defects. For all samples, two types of bismuth atoms were observed, metallic (Bi0) as well as a cationic (Bi+x), the later corresponding to Bi atoms which are partaking in the crystal bond. The ratio of metallic to cationic Bi was observed to decrease notably just a few nm below the extreme surface. The effect of the high presence of metallic Bi on final device performance was not concluded with certainty but not believed to be positive. By varying the annealing temperature, after spin coating the light absorber solution on the TiO2, it was observed that lower temperature resulted in a lower ratio of metallic Bi. As final conclusions, it was said that the synthesis method of Cu-Bi-I needs to be improved before those materials can be studied further. The synthesis of Ag-Bi-I is showing much more promise and one can start looking into further optimizing their final device structure to boost efficiency. Both Cu-Bi-I and Ag-Bi-I devices are relatively simple, cheap and energy efficient (with annealing temperatures around 150C) to produce, great aspects for solar cells. UVVis measurements showed they have band gaps around 1.6-1.7 eV which makes them a great potential material for use in tandem solar cells together with a semiconductor of lower band gap such as silicon.

Atmospheric particulate matter (PM) is linked to various adverse environmental and health impacts. PM in the atmosphere reduces visibility, alters precipitation patterns by acting as cloud condensation nuclei (CCN), and changes the Earth’s radiative balance by absorbing or scattering solar radiation in the atmosphere. The long-range transport of pollutants leads to increase in PM concentrations even in remote locations such as polar regions and mountain ranges. One significant effect of PM on the earth’s climate occurs while light absorbing PM, such as Black Carbon (BC), deposits over snow. In the Arctic, BC deposition on highly reflective surfaces (e.g. glaciers and sea ices) has very intense effects, causing snow to melt more quickly. Thus, characterizing PM sources, identifying long-range transport pathways, and quantifying the climate impacts of PM are crucial in order to inform emission abatement policies for reducing both health and environmental impacts of PM. Chemical transport models provide mathematical tools for better understanding atmospheric system including chemical and particle transport, pollution diffusion, and deposition. The technological and computational advances in the past decades allow higher resolution air quality and weather forecast simulations with more accurate representations of physical and chemical mechanisms of the atmosphere. Due to the significant role of air pollutants on public health and environment, several countries and cities perform air quality forecasts for warning the population about the future air pollution events and taking local preventive measures such as traffic regulations to minimize the impacts of the forecasted episode. However, the costs associated with the complex air quality forecast models especially for simulations with higher resolution simulations make “forecasting” a challenge. This dissertation also focuses on applications, performance analysis, and optimization of meteorology and air quality modeling forecasting models. This dissertation presents several modeling studies with various scales to better understand transport of aerosols from different geographical sources and economic sectors (i.e. transportation, residential, industry, biomass burning, and power) and quantify their climate impacts. The simulations are evaluated using various observations including ground site measurements, field campaigns, and satellite data. The sector-based modeling studies elucidated the importance of various economical sector and geographical regions on global air quality and the climatic impacts associated with BC. This dissertation provides the policy makers with some implications to inform emission mitigation policies in order to target source sectors and regions with highest impacts. Furthermore, advances were made to better understand the impacts of light absorbing particles on climate and surface albedo. Finally, for improving the modeling speed, the performances of the models are analyzed, and optimizations were proposed for improving the computational efficiencies of the models. Theses optimizations show a significant improvement in the performance of Weather Research and Forecasting (WRF) and WRF-Chem models. The modified codes were validated and incorporated back into the WRF source code to benefit all WRF users. Although weather and air quality models are shown to be an excellent means for forecasting applications both for local and hemispheric scale, further studies are needed to optimize the models and improve the performance of the simulations.