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- Genre: Doctoral Dissertation
This doctoral dissertation research aims to develop a comprehensive definition of urban open spaces and to determine the extent of environmental, social and economic impacts of open spaces on cities and the people living there. The approach I take to define urban open space is to apply fuzzy set theory to conceptualize the physical characteristics of open spaces. In addition, a 'W-green index' is developed to quantify the scope of greenness in urban open spaces. Finally, I characterize the environmental impact of open spaces' greenness on the surface temperature, explore the social benefits through observing recreation and relaxation, and identify the relationship between housing price and open space be creating a hedonic model on nearby housing to quantify the economic impact. Fuzzy open space mapping helps to investigate the landscape characteristics of existing-recognized open spaces as well as other areas that can serve as open spaces. Research findings indicated that two fuzzy open space values are effective to the variability in different land-use types and between arid and humid cities. W-Green index quantifies the greenness for various types of open spaces. Most parks in Tempe, Arizona are grass-dominant with higher W-Green index, while natural landscapes are shrub-dominant with lower index. W-Green index has the advantage to explain vegetation composition and structural characteristics in open spaces. The outputs of comprehensive analyses show that the different qualities and types of open spaces, including size, greenness, equipment (facility), and surrounding areas, have different patterns in the reduction of surface temperature and the number of physical activities. The variance in housing prices through the distance to park was, however, not clear in this research. This dissertation project provides better insight into how to describe, plan, and prioritize the functions and types of urban open spaces need for sustainable living. This project builds a comprehensive framework for analyzing urban open spaces in an arid city. This dissertation helps expand the view for urban environment and play a key role in establishing a strategy and finding decision-makings.
grass) offers unique opportunities to mitigate climate change through avoided fossil fuel use and associated greenhouse gas reduction. Although conversion of existing agriculturally intensive lands (e.g., maize and soy) to perennial bioenergy cropping systems has been shown to reduce near-surface temperatures, unintended consequences on natural water resources via depletion of soil moisture may offset these benefits. In the effort of the cross-fertilization across the disciplines of physics-based modeling and spatio-temporal statistics, three topics are investigated in this dissertation aiming to provide a novel quantification and robust justifications of the hydroclimate impacts associated with bioenergy crop expansion. Topic 1 quantifies the hydroclimatic impacts associated with perennial bioenergy crop expansion over the contiguous United States using the Weather Research and Forecasting Model (WRF) dynamically coupled to a land surface model (LSM). A suite of continuous (2000–09) medium-range resolution (20-km grid spacing) ensemble-based simulations is conducted. Hovmöller and Taylor diagrams are utilized to evaluate simulated temperature and precipitation. In addition, Mann-Kendall modified trend tests and Sieve-bootstrap trend tests are performed to evaluate the statistical significance of trends in soil moisture differences. Finally, this research reveals potential hot spots of suitable deployment and regions to avoid. Topic 2 presents spatio-temporal Bayesian models which quantify the robustness of control simulation bias, as well as biofuel impacts, using three spatio-temporal correlation structures. A hierarchical model with spatially varying intercepts and slopes display satisfactory performance in capturing spatio-temporal associations. Simulated temperature impacts due to perennial bioenergy crop expansion are robust to physics parameterization schemes. Topic 3 further focuses on the accuracy and efficiency of spatial-temporal statistical modeling for large datasets. An ensemble of spatio-temporal eigenvector filtering algorithms (hereafter: STEF) is proposed to account for the spatio-temporal autocorrelation structure of the data while taking into account spatial confounding. Monte Carlo experiments are conducted. This method is then used to quantify the robustness of simulated hydroclimatic impacts associated with bioenergy crops to alternative physics parameterizations. Results are evaluated against those obtained from three alternative Bayesian spatio-temporal specifications.
Using the individual building energy simulation approach, I also estimate the impact of climate change to different building types at over 900 US locations. Large increases in building energy consumption are found in the summer, especially during the daytime (e.g., >100% increase for warehouses, 5-6 pm). Large variation of impact is also found within climate zones, suggesting a potential bias when estimating climate-zone scale changes with a small number of representative locations.
As a result of climate change, the building energy expenditures increase in some states (as much as $3 billion/year) while in others, costs decline (as much as $1.4 billion/year). Integrated across the contiguous US, these variations result in a net savings of roughly $4.7 billion/year. However, this must be weighed against the cost (exceeding $19 billion) of adding electricity generation capacity in order to maintain the electricity grid’s reliability in summer.
Famine is the result of a complex set of environmental and social factors. Climate conditions are established as environmental factors contributing to famine occurrence, often through teleconnective patterns. This dissertation is designed to investigate the combined influence on world famine patterns of teleconnections, specifically the North Atlantic Oscillation (NAO), Southern Oscillation (SO), Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), or regional climate variations such as the South Asian Summer Monsoon (SASM). The investigation is three regional case studies of famine patterns specifically, Egypt, the British Isles, and India.
The first study (published in Holocene) employs the results of a Principal Component Analysis (PCA) yielding a SO-NAO eigenvector to predict major Egyptian famines between AD 1049-1921. The SO-NAO eigenvector (1) successfully discriminates between the 5-10 years preceding a famine and the other years, (2) predicts eight of ten major famines, and (3) correctly identifies fifty out of eighty events (63%) of food availability decline leading up to major famines.
The second study investigates the impact of the NAO, PDO, SO, and AMO on 63 British Isle famines between AD 1049 and 1914 attributed to climate causes in historical texts. Stepwise Regression Analysis demonstrates that the 5-year lagged NAO is the primary teleconnective influence on famine patterns; it successfully discriminates 73.8% of weather-related famines in the British Isles from 1049 to 1914.
The final study identifies the aggregated influence of the NAO, SO, PDO, and SASM on 70 Indian famines from AD 1049 to 1955. PCA results in a NAO-SOI vector and SASM vector that predicts famine conditions with a positive NAO and negative SO, distinct from the secondary SASM influence. The NAO-famine relationship is consistently the strongest; 181 of 220 (82%) of all famines occurred during positive NAO years.
Ultimately, the causes of famine are complex and involve many factors including societal and climatic. This dissertation demonstrates that climate teleconnections impact famine patterns and often the aggregates of multiple climate variables hold the most significant climatic impact. These results will increase the understanding of famine patterns and will help to better allocate resources to alleviate future famines.
Impacts of Landscape Modifications on Urban Boundary Layer Dynamics in Current and Projected Climate
The first paper is based on a systematic literature review where evidence from morphological mitigation strategies in HUDs were critically reviewed, synthesized and integrated. Metrics, measurements, and methods were extracted to examine the applicability of the different strategies, and a content synthesis identified the levels of strategy success. Collective challenges and uncertainties were interpreted to compare aspirational goals from actualities of morphological mitigation strategies.
The second paper unpacks the relationship of urban morphological attributes in influencing thermal conditions to assess latent magnitudes of heat amelioration strategies. Mindful of the challenges presented in the first study, a 92-day summer field-measurement campaign captured system dynamics of urban thermal stimuli within sub-diurnal phenomena. A composite data set of sub-hourly air temperature measurements with sub-meter morphological attributes was built, statistically analyzed, and modeled. Morphological mediation effects were found to vary hourly with different patterns under varying weather conditions in non-linear associations. Results suggest mitigation interventions be investigated and later tested on a site- use and time-use basis.
The third paper concludes with a simulation-based study to conform on the collective findings of the earlier studies. The microclimate model ENVI-met 4.4, combined with field measurements, was used to simulate the effect of rooftop shade-sails in cooling the near ground thermal environment. Results showed significant cooling effects and thus presented a novel shading approach that challenges orthodox mitigation strategies in HUDs.
The second paper considers marginal agricultural land use for bioenergy crop cultivation to meet future liquid fuels demand from cellulosic biofuels sustainably and profitably. At a wholesale fuel price of $4 gallons-of-gasoline-equivalent, 30 to 90.7 billion gallons of cellulosic biofuels can be supplied by converting 22 to 79.3 million hectares of marginal lands in the Eastern United States (U.S.). Displacing marginal croplands (9.4-13.7 million hectares) reduces stress on water resources by preserving soil moisture. This displacement is comparable to existing land use for first-generation biofuels, limiting food supply impacts. Coupled modeling reveals positive hydroclimate feedback on bioenergy crop yields that moderates the land footprint.
The third paper examines the sustainability implications of expanding use of marginal lands for corn cultivation in the Western Corn Belt, a commercially important and environmentally sensitive U.S. region. Corn cultivation on lower quality lands, which tend to overlap with marginal agricultural lands, is shown to be nearly three times more sensitive to changes in crop prices. Therefore, corn cultivation disproportionately expanded into these lands following price spikes.
Underutilized spaces can contribute towards sustainability at small and large scales in a complementary fashion. While supplying fresh produce locally and delivering other benefits in terms of energy use and public health, UA can also reduce pressures on croplands and complement non-urban food production. This complementarity can help diversify agricultural land use for meeting other goals, like supplying biofuels. However, understanding the role of market forces and economic linkages is critical to anticipate any unintended consequences due to such re-organization of land use.