Matching Items (3)
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- All Subjects: Carbon Sequestration
- All Subjects: Land Use Planning
- Genre: Academic theses
- Creators: Amresh, Ashish
Description
Increasing concentrations of carbon dioxide in the atmosphere will inevitably lead to long-term changes in climate that can have serious consequences. Controlling anthropogenic emission of carbon dioxide into the atmosphere, however, represents a significant technological challenge. Various chemical approaches have been suggested, perhaps the most promising of these is based on electrochemical trapping of carbon dioxide using pyridine and derivatives. Optimization of this process requires a detailed understanding of the mechanisms of the reactions of reduced pyridines with carbon dioxide, which are not currently well known. This thesis describes a detailed mechanistic study of the nucleophilic and Bronsted basic properties of the radical anion of bipyridine as a model pyridine derivative, formed by one-electron reduction, with particular emphasis on the reactions with carbon dioxide. A time-resolved spectroscopic method was used to characterize the key intermediates and determine the kinetics of the reactions of the radical anion and its protonated radical form. Using a pulsed nanosecond laser, the bipyridine radical anion could be generated in-situ in less than 100 ns, which allows fast reactions to be monitored in real time. The bipyridine radical anion was found to be a very powerful one-electron donor, Bronsted base and nucleophile. It reacts by addition to the C=O bonds of ketones with a bimolecular rate constant around 1* 107 M-1 s-1. These are among the fastest nucleophilic additions that have been reported in literature. Temperature dependence studies demonstrate very low activation energies and large Arrhenius pre-exponential parameters, consistent with very high reactivity. The kinetics of E2 elimination, where the radical anion acts as a base, and SN2 substitution, where the radical anion acts as a nucleophile, are also characterized by large bimolecular rate constants in the range ca. 106 - 107 M-1 s-1. The pKa of the bipyridine radical anion was measured using a kinetic method and analysis of the data using a Marcus theory model for proton transfer. The bipyridine radical anion is found to have a pKa of 40±5 in DMSO. The reorganization energy for the proton transfer reaction was found to be 70±5 kJ/mol. The bipyridine radical anion was found to react very rapidly with carbon dioxide, with a bimolecular rate constant of 1* 108 M-1 s-1 and a small activation energy, whereas the protonated radical reacted with carbon dioxide with a rate constant that was too small to measure. The kinetic and thermodynamic data obtained in this work can be used to understand the mechanisms of the reactions of pyridines with carbon dioxide under reducing conditions.
ContributorsRanjan, Rajeev (Author) / Gould, Ian R (Thesis advisor) / Buttry, Daniel A (Thesis advisor) / Yarger, Jeff (Committee member) / Seo, Dong-Kyun (Committee member) / Arizona State University (Publisher)
Created2015
Description
Large datasets of sub-meter aerial imagery represented as orthophoto mosaics are widely available today, and these data sets may hold a great deal of untapped information. This imagery has a potential to locate several types of features; for example, forests, parking lots, airports, residential areas, or freeways in the imagery. However, the appearances of these things vary based on many things including the time that the image is captured, the sensor settings, processing done to rectify the image, and the geographical and cultural context of the region captured by the image. This thesis explores the use of deep convolutional neural networks to classify land use from very high spatial resolution (VHR), orthorectified, visible band multispectral imagery. Recent technological and commercial applications have driven the collection a massive amount of VHR images in the visible red, green, blue (RGB) spectral bands, this work explores the potential for deep learning algorithms to exploit this imagery for automatic land use/ land cover (LULC) classification. The benefits of automatic visible band VHR LULC classifications may include applications such as automatic change detection or mapping. Recent work has shown the potential of Deep Learning approaches for land use classification; however, this thesis improves on the state-of-the-art by applying additional dataset augmenting approaches that are well suited for geospatial data. Furthermore, the generalizability of the classifiers is tested by extensively evaluating the classifiers on unseen datasets and we present the accuracy levels of the classifier in order to show that the results actually generalize beyond the small benchmarks used in training. Deep networks have many parameters, and therefore they are often built with very large sets of labeled data. Suitably large datasets for LULC are not easy to come by, but techniques such as refinement learning allow networks trained for one task to be retrained to perform another recognition task. Contributions of this thesis include demonstrating that deep networks trained for image recognition in one task (ImageNet) can be efficiently transferred to remote sensing applications and perform as well or better than manually crafted classifiers without requiring massive training data sets. This is demonstrated on the UC Merced dataset, where 96% mean accuracy is achieved using a CNN (Convolutional Neural Network) and 5-fold cross validation. These results are further tested on unrelated VHR images at the same resolution as the training set.
ContributorsUba, Nagesh Kumar (Author) / Femiani, John (Thesis advisor) / Razdan, Anshuman (Committee member) / Amresh, Ashish (Committee member) / Arizona State University (Publisher)
Created2016
Description
Despite public demand for climate change mitigation and natural open space conservancy, existing political and design efforts are only beginning to address the declining efficacy of the biotic carbon pool (C-pool) to sequester carbon. Advances in understanding of biogeochemical processes have provided methods for estimating carbon embodied in natural open spaces and enhancing carbon sequestration efficacy. In this study, the benefits of carbon embodied in dryland open spaces are determined by estimating carbon flux and analyzing ecological, social, and economic benefits provided by sequestered carbon. Understanding the ecological processes and derived benefits of carbon exchange in dryland open spaces will provide insight into enhancing carbon sequestration efficacy. Open space carbon is estimated by calculating the amount of carbon sequestration (estimated in Mg C / ha / y) in dryland open space C-pools. Carbon sequestration in dryland open spaces can be summarized in five open space typologies: hydric, mesic, aridic, biomass for energy agriculture, and traditional agriculture. Hydric (wetland) systems receive a significant amount of moisture; mesic (riparian) systems receive a moderate amount of moisture; and aridic (dry) systems receive low amounts of moisture. Biomass for energy production (perennial biomass) and traditional agriculture (annual / traditional biomass) can be more effective carbon sinks if managed appropriately. Impacts of design interventions to the carbon capacity of dryland open space systems are calculated by estimating carbon exchange in existing open space (base case) compared to projections of carbon sequestered in a modified system (prototype design). A demonstration project at the Lower San Pedro River Watershed highlights the potential for enhancing carbon sequestration. The site-scale demonstration project takes into account a number of limiting factors and opportunities including: availability of water and ability to manipulate its course, existing and potential vegetation, soil types and use of carbon additives, and land-use (particularly agriculture). Specific design challenges to overcome included: restoring perennial water to the Lower San Pedro River, reestablishing hydric and mesic systems, linking fragmented vegetation, and establishing agricultural systems that provide economic opportunities and act as carbon sinks. The prototype design showed enhancing carbon sequestration efficacy by 128-133% is possible with conservative design interventions.
ContributorsHuck, Erick (Author) / Cook, Edward (Thesis advisor) / Green, Douglas (Committee member) / Brooks, Kenneth (Committee member) / Montemayor, Gabriel (Committee member) / Arizona State University (Publisher)
Created2012