Perfluorocarbon tracers (PFTs) are commonly proposed tracers for use in carbon capture and sequestration (CCS) leak detection and vadose zone monitoring programs. Tracers are co-injected with supercritical CO₂ and monitored in the vadose zone to identify leakage and calculate leakage rates. These calculations assume PFTs exhibit “ideal” tracer behavior (i.e. do not sorb onto or react with porous media, partition into liquid phases or undergo decay). This assumption has been brought into question by lab and field evaluations showing PFT partitioning into soil contaminants and sorbing onto clay. The objective of this study is to identify substrates in which PFTs behave conservatively and quantify non-conservative behavior. PFT breakthrough curves are compared to those of a second, conservative tracer, sulfur hexafluoride (SF₆). Breakthrough curves are generated in 1D flow-through columns packed with 5 different substrates: silica beads, quartz sand, illite, organic-rich soil, and organic-poor soil. Constant flow rate of carrier gas, N₂, is maintained. A known mass of tracer is injected at the head of the columns and the effluent analyzed at regular intervals for tracers at picogram levels by gas chromatography. PFT is expected to behave conservatively with respect to SF₆ in silica beads or quartz sand and non-conservatively in columns with clay or organics. However, results demonstrate PFT retardation with respect to SF₆ in all media (retardation factor is 1.1 in silica beads and quartz sand, 2.5 in organic-rich soil, >20 in organic-poor soil, and >100 in illite). Retardation is most likely due to sorption onto clays and soil organic matter or condensation to the liquid phase. Sorption onto clays appears to be the most significant factor. Experimental data are consistent with an analytical advection/diffusion model. These results show that PFT retardation in the vadose zone has not been adequately considered for interpretation of PFT data for CCS monitoring. These results are preliminary and do not take into account more realistic vadose zone conditions such as the presence of water, in which PFTs are insoluble. Increased moisture content will likely decrease sorption onto porous media and retardation in the vadose zone may be less than determined in these experiments. / text

A central issue in climate change research is to identify what species will be most affected by variations in temperature, precipitation or CO2 and via which underlying mechanisms. Dynamic global vegetation models (DGVMs) have been used to address questions of habitat shifts, extinctions and changes in carbon and nutrient cycling. However, DGVMs have been criticized for assuming full migration and using the most generic of plant functional types (PFTs) to describe vegetation cover. My doctoral research addresses both of these concerns. In the first study, I added two new tropical PFTs to an existing regional model (LPJ-GUESS) to improve vegetation representation in Central America. Although there was an improvement in the representation of some biomes such as the pine-oak forests, LPJ-GUESS was still unable to capture the distribution of arid ecosystems. The model representations of fire, soil, and processes unique to desert vegetation are discussed as possible explanations. The remaining three chapters deal with the assumption of full migration, where plants can arrive at any location regardless of distance or physical barriers. Using LPJ-GUESS, I imposed migration limitations by using fat-tailed seed dispersal kernels. I used three temperate tree species with different life history strategies to test the new dispersal functionality. Simulated migration rates for Acer rubrum (141 m year-1) and Pinus rigida (76 m year-1) correspond well to pollen and genetic reconstructed rates. However, migration rates for Tsuga canadensis (85 m year-1) were considerably slower than historical rates. A sensitivity analysis showed that maturation age is the most important parameter for determining rates of spread, but it is the dispersal kernel which determines if there is any long distance dispersal or not. The final study demonstrates how northerly refugia populations could have impacted landscape recolonization following the retreat of the last glacier. Using three species with known refugia (Acer rubrum, Fagus grandifolia, Picea glauca), colonization rates were faster with a northerly refugia population present. The number of refugia locations also had a positive effect on landscape recolonization rates, which was most pronounced when populations were separated. The results from this thesis illustrate the improvements made in vegetation-climate models, giving us increasing confidence in the quality of future climate change predictions.

A central issue in climate change research is to identify what species will be most affected by variations in temperature, precipitation or CO2 and via which underlying mechanisms. Dynamic global vegetation models (DGVMs) have been used to address questions of habitat shifts, extinctions and changes in carbon and nutrient cycling. However, DGVMs have been criticized for assuming full migration and using the most generic of plant functional types (PFTs) to describe vegetation cover. My doctoral research addresses both of these concerns. In the first study, I added two new tropical PFTs to an existing regional model (LPJ-GUESS) to improve vegetation representation in Central America. Although there was an improvement in the representation of some biomes such as the pine-oak forests, LPJ-GUESS was still unable to capture the distribution of arid ecosystems. The model representations of fire, soil, and processes unique to desert vegetation are discussed as possible explanations. The remaining three chapters deal with the assumption of full migration, where plants can arrive at any location regardless of distance or physical barriers. Using LPJ-GUESS, I imposed migration limitations by using fat-tailed seed dispersal kernels. I used three temperate tree species with different life history strategies to test the new dispersal functionality. Simulated migration rates for Acer rubrum (141 m year-1) and Pinus rigida (76 m year-1) correspond well to pollen and genetic reconstructed rates. However, migration rates for Tsuga canadensis (85 m year-1) were considerably slower than historical rates. A sensitivity analysis showed that maturation age is the most important parameter for determining rates of spread, but it is the dispersal kernel which determines if there is any long distance dispersal or not. The final study demonstrates how northerly refugia populations could have impacted landscape recolonization following the retreat of the last glacier. Using three species with known refugia (Acer rubrum, Fagus grandifolia, Picea glauca), colonization rates were faster with a northerly refugia population present. The number of refugia locations also had a positive effect on landscape recolonization rates, which was most pronounced when populations were separated. The results from this thesis illustrate the improvements made in vegetation-climate models, giving us increasing confidence in the quality of future climate change predictions.

Efficient and accurate sensing of various parameters is needed for numerous applications. In this regard, different categories of sensors play a significant role and different applications require diverse sensing mechanisms owing to the operating conditions and field constraints. Among the several sensor methodologies available, optical fiber sensors have found significant attention, because of their advantages such as negligible foot print, small mass, immunity to Electromagnetic Interference, etc. In the category of optical fiber sensors, Fiber Bragg Grating (FBG) sensors have found importance in many fields such as health monitoring of civil structures, environmental monitoring involving gas & humidity sensing, monitoring parameters like pressure, tilt, displacement, etc. In the recent times, FBGs have found applications in biomedical, biomechanical and biosensing fields. A FBG is a periodic change of the refractive index of the core of a single mode optical fiber along its longitudinal axis. The periodic modulation in the index of refraction is obtained by exposing a photosensitive germanium-doped silica fiber to an intense UV laser beam. FBGs, in the basic form, can sense strain and temperature. However, in recent years, several newer sensing applications of FBGs have been demonstrated. Some of the main features of the FBG sensor which qualify them for diverse sensing applications are high sensitivity, large operational bandwidth, multiplexing & multi modal sensing capability, etc. In this thesis work, FBG sensor based devices have been developed for newer applications in bio-medical fields for the measurement of force, flow and temperature. Particularly, novel transduction methodologies have been proposed, in order to convert the measurand parameter into a secondary parameter that can be sensed by the FBG sensor. The evaluation of the force required for a spinal needle to penetrate various tissue layers from skin to the epidural space is vital. In this work, a novel technique for dynamic monitoring of force experienced by a spinal needle during lumbar puncture using Fiber Bragg Grating (FBG) sensor has been developed. The Fiber Bragg Grating Force Device (FBGFD) developed, measures the force on the spinal needle due to varied resistance offered by different tissue layers during its traversal. The effect of gauge of the spinal needle used for the lumbar puncture procedure affects the force required for its insertion into the tissue. The FBGFD developed, has been further utilized for a comparative study of the force required for lumbar puncture of various tissue layers with spinal needle of different gauges. The results obtained may serve as a guideline for selection of suitable gauge spinal needle during lumbar puncture minimizing post puncture side effects on patients. The pulmonary function test carried out using a spirometer, provides vital information about the functional status of the respiratory system of the subject. A Fiber Bragg Grating Spirometer (FBGS) has been developed which has the ability to convert the rate of air flow into a shift in wavelength that can be acquired by the FBG sensor. The FBGS can dynamically acquire the complete breathing sequence comprising of the inhalation phase, pause phase and exhalation phase in terms of the air flow rate along with the time duration of each phase. Methods are adopted to analyse and determine important pulmonary parameters using FBGS and compare these parameters with those obtained with a commercially available hospital grade pneumotachograph spirometer. Thermal imaging is one of the emerging non-invasive neuro-imaging techniques which can potentially indicate the boundaries of a brain tumor. The variation in tissue surface temperature is indicative of a tumor existence. In this work a FBG temperature sensor (FBGTS) has been developed for thermography of a simulated tissue using Agar material. The temperature of the embedded heater which mimics a brain tumor along with the surface temperature of the tissue model, is acquired using FBGTSs simultaneously. Further, the surface temperatures are studied for varying heater temperatures as well as varying positions of the heater in the simulated tissue model. To conclude, FBG based devices have been developed in this work, for applications in biomedical domain, with appropriate transduction methodologies for sensing different parameters such as force, flow and temperature.