DEVELOPMENT OF A CONDENSED PHASE VELOCITY MAP IMAGING APPARATUS: DISSOCIATION PHOTODYNAMICS OF NITROGEN DIOXIDE AT 355 NM

The photochemistry of the polar regions of Earth, as well as the interstellar medium, is driven by the effect of ultraviolet radiation on ice surfaces and on the materials trapped within them. While the area of ice photochemistry is vast and much research has been completed, it has only recently been possible to study the dynamics of these processes on a microscopic level. One of the leading techniques for studying photoreaction dynamics is Velocity Map Imaging (VMI). This technique has been used extensively to study several types of reaction dynamics processes. Although the majority of these studies have utilized molecular beams as the main medium for reactants, new studies showed the versatility of the technique when applied to molecular dynamics of molecules adsorbed on metal surfaces. Herein the development of a velocity map imaging apparatus capable of studying the photochemistry of condensed phase materials is described. The apparatus is used to study of the photo-reactivity of NO2 condensed within argon matrices to illustrate its capabilities. A doped ice surface is formed by condensing Ar and NO2 gas onto a sapphire rod which is cooled using a helium compressor to 20 K. The matrix is irradiated using an Nd:YAG laser at 355 nm, and the resulting NO fragment is state-selectively ionized using an excimer-pumped dye laser. In all, we are able to detect transient photochemically generated species and can collect information on their quantum state and kinetic energy distribution. It is found that the REMPI spectra changes as different sections of the dissociating cloud are probed. The rotational and translational energy populations are found to be bimodal with a low temperature component roughly at the temperature of the matrix, and a second component with much higher temperature, the rotational temperature showing a possible population inversion, and the translational temperature of 100-200 K. The low temperature translational component is found to dominate at long delay times between dissociation and ionization, while at short time delays the high temperature component plays a larger role. The velocity map imaging technique allows for the detection of both the axial and radial components of the translational energy. The distribution of excess energy over the rotational, electronic and translational states of the NO photofragments provides evidence for collisional quenching of the fragments in the Ar-matrix prior to their desorption.

Karst hazard analysis towards the development of predictive karst models for southern Ontario

An investigation into karst hazard in southern Ontario has been undertaken with the intention of leading to the development of predictive karst models for this region. The reason these are not currently feasible is a lack of sufficient karst data, though this is not entirely due to the lack of karst features. Geophysical data was collected at Lake on the Mountain, Ontario as part of this karst investigation. This data was collected in order to validate the long-standing hypothesis that Lake on the Mountain was formed from a sinkhole collapse. Sub-bottom acoustic profiling data was collected in order to image the lake bottom sediments and bedrock. Vertical bedrock features interpreted as solutionally enlarged fractures were taken as evidence for karst processes on the lake bottom. Additionally, the bedrock topography shows a narrower and more elongated basin than was previously identified, and this also lies parallel to a mapped fault system in the area. This suggests that Lake on the Mountain was formed over a fault zone which also supports the sinkhole hypothesis as it would provide groundwater pathways for karst dissolution to occur. Previous sediment cores suggest that Lake on the Mountain would have formed at some point during the Wisconsinan glaciation with glacial meltwater and glacial loading as potential contributing factors to sinkhole development. A probabilistic karst model for the state of Kentucky, USA, has been generated using the Weights of Evidence method. This model is presented as an example of the predictive capabilities of these kind of data-driven modelling techniques and to show how such models could be applied to karst in Ontario. The model was able to classify 70% of the validation dataset correctly while minimizing false positive identifications. This is moderately successful and could stand to be improved. Finally, suggestions to improving the current karst model of southern Ontario are suggested with the goal of increasing investigation into karst in Ontario and streamlining the reporting system for sinkholes, caves, and other karst features so as to improve the current Ontario karst database.