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- All Subjects: Civil Engineering
- Genre: Academic theses
- Creators: Chong, Oswald
- Status: Published
Description
Ten regional climate models (RCMs) and atmosphere-ocean generalized model parings from the North America Regional Climate Change Assessment Program were used to estimate the shift of extreme precipitation due to climate change using present-day and future-day climate scenarios. RCMs emulate winter storms and one-day duration events at the sub-regional level. Annual maximum series were derived for each model pairing, each modeling period; and for annual and winter seasons. The reliability ensemble average (REA) method was used to qualify each RCM annual maximum series to reproduce historical records and approximate average predictions, because there are no future records. These series determined (a) shifts in extreme precipitation frequencies and magnitudes, and (b) shifts in parameters during modeling periods. The REA method demonstrated that the winter season had lower REA factors than the annual season. For the winter season the RCM pairing of the Hadley regional Model 3 and the Geophysical Fluid-Dynamics Laboratory atmospheric-land generalized model had the lowest REA factors. However, in replicating present-day climate, the pairing of the Abdus Salam International Center for Theoretical Physics' Regional Climate Model Version 3 with the Geophysical Fluid-Dynamics Laboratory atmospheric-land generalized model was superior. Shifts of extreme precipitation in the 24-hour event were measured using precipitation magnitude for each frequency in the annual maximum series, and the difference frequency curve in the generalized extreme-value-function parameters. The average trend of all RCM pairings implied no significant shift in the winter annual maximum series, however the REA-selected models showed an increase in annual-season precipitation extremes: 0.37 inches for the 100-year return period and for the winter season suggested approximately 0.57 inches for the same return period. Shifts of extreme precipitation were estimated using predictions 70 years into the future based on RCMs. Although these models do not provide climate information for the intervening 70 year period, the models provide an assertion on the behavior of future climate. The shift in extreme precipitation may be significant in the frequency distribution function, and will vary depending on each model-pairing condition. The proposed methodology addresses the many uncertainties associated with the current methodologies dealing with extreme precipitation.
ContributorsRiaño, Alejandro (Author) / Mays, Larry W. (Thesis advisor) / Vivoni, Enrique (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2013
Description
As a developing nation, China is currently faced with the challenge of providing
safe, reliable and adequate energy resources to the county's growing urban areas as well as to its expanding rural populations. To meet this demand, the country has initiated massive construction projects to expand its national energy infrastructure, particularly in the form of natural gas pipeline. The most notable of these projects is the ongoing West-East Gas Pipeline Project. This project is currently in its third phase, which will supply clean and efficient natural gas to nearly sixty million users located in the densely populated Yangtze River Delta.
Trenchless Technologies, in particular the construction method of Horizontal
Directional Drilling (HDD), have played a critical role in executing this project by
providing economical, practical and environmentally responsible ways to install buried pipeline systems. HDD has proven to be the most popular method selected to overcome challenges along the path of the pipeline, which include mountainous terrain, extensive farmland and numerous bodies of water. The Yangtze River, among other large-scale water bodies, have proven to be the most difficult obstacle for the pipeline installation as it widens and changes course numerous times along its path to the East China Sea. The purpose of this study is to examine those practices being used in China in order to compare those to those long used practices in the North American in order to understand the advantages of Chinese advancements.
Developing countries would benefit from the Chinese advancements for large-scale HDD installation. In developed areas, such as North America, studying Chinese execution may allow for new ideas to help to improve long established methods. These factors combined further solidify China's role as the global leader in trenchless technology methods and provide the opportunity for Chinese HDD contractors to contribute to the world's knowledge for best practices of the Horizontal Directional Drilling method.
safe, reliable and adequate energy resources to the county's growing urban areas as well as to its expanding rural populations. To meet this demand, the country has initiated massive construction projects to expand its national energy infrastructure, particularly in the form of natural gas pipeline. The most notable of these projects is the ongoing West-East Gas Pipeline Project. This project is currently in its third phase, which will supply clean and efficient natural gas to nearly sixty million users located in the densely populated Yangtze River Delta.
Trenchless Technologies, in particular the construction method of Horizontal
Directional Drilling (HDD), have played a critical role in executing this project by
providing economical, practical and environmentally responsible ways to install buried pipeline systems. HDD has proven to be the most popular method selected to overcome challenges along the path of the pipeline, which include mountainous terrain, extensive farmland and numerous bodies of water. The Yangtze River, among other large-scale water bodies, have proven to be the most difficult obstacle for the pipeline installation as it widens and changes course numerous times along its path to the East China Sea. The purpose of this study is to examine those practices being used in China in order to compare those to those long used practices in the North American in order to understand the advantages of Chinese advancements.
Developing countries would benefit from the Chinese advancements for large-scale HDD installation. In developed areas, such as North America, studying Chinese execution may allow for new ideas to help to improve long established methods. These factors combined further solidify China's role as the global leader in trenchless technology methods and provide the opportunity for Chinese HDD contractors to contribute to the world's knowledge for best practices of the Horizontal Directional Drilling method.
ContributorsCarlin, Maureen Cassin (Author) / Ariaratnam, Samuel T (Thesis advisor) / Chong, Oswald (Committee member) / Bearup, Wylie (Committee member) / Arizona State University (Publisher)
Created2014
Description
Given the importance of buildings as major consumers of resources worldwide, several organizations are working avidly to ensure the negative impacts of buildings are minimized. The U.S. Green Building Council's (USGBC) Leadership in Energy and Environmental Design (LEED) rating system is one such effort to recognize buildings that are designed to achieve a superior performance in several areas including energy consumption and indoor environmental quality (IEQ). The primary objectives of this study are to investigate the performance of LEED certified facilities in terms of energy consumption and occupant satisfaction with IEQ, and introduce a framework to assess the performance of LEED certified buildings.
This thesis attempts to achieve the research objectives by examining the LEED certified buildings on the Arizona State University (ASU) campus in Tempe, AZ, from two complementary perspectives: the Macro-level and the Micro-level. Heating, cooling, and electricity data were collected from the LEED-certified buildings on campus, and their energy use intensity was calculated in order to investigate the buildings' actual energy performance. Additionally, IEQ occupant satisfaction surveys were used to investigate users' satisfaction with the space layout, space furniture, thermal comfort, indoor air quality, lighting level, acoustic quality, water efficiency, cleanliness and maintenance of the facilities they occupy.
From a Macro-level perspective, the results suggest ASU LEED buildings consume less energy than regional counterparts, and exhibit higher occupant satisfaction than national counterparts. The occupant satisfaction results are in line with the literature on LEED buildings, whereas the energy results contribute to the inconclusive body of knowledge on energy performance improvements linked to LEED certification. From a Micro-level perspective, data analysis suggest an inconsistency between the LEED points earned for the Energy & Atmosphere and IEQ categories, on one hand, and the respective levels of energy consumption and occupant satisfaction on the other hand. Accordingly, this study showcases the variation in the performance results when approached from different perspectives. This contribution highlights the need to consider the Macro-level and Micro-level assessments in tandem, and assess LEED building performance from these two distinct but complementary perspectives in order to develop a more comprehensive understanding of the actual building performance.
This thesis attempts to achieve the research objectives by examining the LEED certified buildings on the Arizona State University (ASU) campus in Tempe, AZ, from two complementary perspectives: the Macro-level and the Micro-level. Heating, cooling, and electricity data were collected from the LEED-certified buildings on campus, and their energy use intensity was calculated in order to investigate the buildings' actual energy performance. Additionally, IEQ occupant satisfaction surveys were used to investigate users' satisfaction with the space layout, space furniture, thermal comfort, indoor air quality, lighting level, acoustic quality, water efficiency, cleanliness and maintenance of the facilities they occupy.
From a Macro-level perspective, the results suggest ASU LEED buildings consume less energy than regional counterparts, and exhibit higher occupant satisfaction than national counterparts. The occupant satisfaction results are in line with the literature on LEED buildings, whereas the energy results contribute to the inconclusive body of knowledge on energy performance improvements linked to LEED certification. From a Micro-level perspective, data analysis suggest an inconsistency between the LEED points earned for the Energy & Atmosphere and IEQ categories, on one hand, and the respective levels of energy consumption and occupant satisfaction on the other hand. Accordingly, this study showcases the variation in the performance results when approached from different perspectives. This contribution highlights the need to consider the Macro-level and Micro-level assessments in tandem, and assess LEED building performance from these two distinct but complementary perspectives in order to develop a more comprehensive understanding of the actual building performance.
ContributorsChokor, Abbas (Author) / El Asmar, Mounir (Thesis advisor) / Chong, Oswald (Committee member) / Parrish, Kristen (Committee member) / Arizona State University (Publisher)
Created2015
Description
The Colorado River Basin (CRB) is the primary source of water in the
southwestern United States. A key step to reduce the uncertainty of future streamflow
projections in the CRB is to evaluate the performance of historical simulations of General
Circulation Models (GCMs). In this study, this challenge is addressed by evaluating the
ability of nineteen GCMs from the Coupled Model Intercomparison Project Phase Five
(CMIP5) and four nested Regional Climate Models (RCMs) in reproducing the statistical
properties of the hydrologic cycle and temperature in the CRB. To capture the transition
from snow-dominated to semiarid regions, analyses are conducted by spatially averaging
the climate variables in four nested sub-basins. Most models overestimate the mean
annual precipitation (P) and underestimate the mean annual temperature (T) at all
locations. While a group of models capture the mean annual runoff at all sub-basins with
different strengths of the hydrological cycle, another set of models overestimate the mean
annual runoff, due to a weak cycle in the evaporation channel. An abrupt increase in the
mean annual T in observed and most of the simulated time series (~0.8 °C) is detected at
all locations despite the lack of any statistically significant monotonic trends for both P
and T. While all models simulate the seasonality of T quite well, the phasing of the
seasonal cycle of P is fairly reproduced in just the upper, snow-dominated sub-basin.
Model performances degrade in the larger sub-basins that include semiarid areas, because
several GCMs are not able to capture the effect of the North American monsoon. Finally,
the relative performances of the climate models in reproducing the climatologies of P and
T are quantified to support future impact studies in the basin.
southwestern United States. A key step to reduce the uncertainty of future streamflow
projections in the CRB is to evaluate the performance of historical simulations of General
Circulation Models (GCMs). In this study, this challenge is addressed by evaluating the
ability of nineteen GCMs from the Coupled Model Intercomparison Project Phase Five
(CMIP5) and four nested Regional Climate Models (RCMs) in reproducing the statistical
properties of the hydrologic cycle and temperature in the CRB. To capture the transition
from snow-dominated to semiarid regions, analyses are conducted by spatially averaging
the climate variables in four nested sub-basins. Most models overestimate the mean
annual precipitation (P) and underestimate the mean annual temperature (T) at all
locations. While a group of models capture the mean annual runoff at all sub-basins with
different strengths of the hydrological cycle, another set of models overestimate the mean
annual runoff, due to a weak cycle in the evaporation channel. An abrupt increase in the
mean annual T in observed and most of the simulated time series (~0.8 °C) is detected at
all locations despite the lack of any statistically significant monotonic trends for both P
and T. While all models simulate the seasonality of T quite well, the phasing of the
seasonal cycle of P is fairly reproduced in just the upper, snow-dominated sub-basin.
Model performances degrade in the larger sub-basins that include semiarid areas, because
several GCMs are not able to capture the effect of the North American monsoon. Finally,
the relative performances of the climate models in reproducing the climatologies of P and
T are quantified to support future impact studies in the basin.
ContributorsGautam, Jenita (Author) / Mascaro, Giuseppe (Thesis advisor) / Vivoni, Enrique (Committee member) / Wang, Zhihua (Committee member) / Arizona State University (Publisher)
Created2018
Description
The United States building sector was the most significant carbon emission contributor (over 40%). The United States government is trying to decrease carbon emissions by enacting policies, but emissions increased by approximately 7 percent in the U.S. between 1990 and 2013. To reduce emissions, investigating the factors affecting carbon emissions should be a priority. Therefore, in this dissertation, this research examine the relationship between carbon emissions and the factors affecting them from macro and micro perspectives. From a macroscopic perspective, the relationship between carbon dioxide, energy resource consumption, energy prices, GDP (gross domestic product), waste generation, and recycling waste generation in the building and waste sectors has been verified. From a microscopic perspective, the impact of non-permanent electric appliances and stationary and non-stationary occupancy has been investigated. To verify the relationships, various kinds of statistical and data mining techniques were applied, such as the Granger causality test, linear and logarithmic correlation, and regression method. The results show that natural gas and electricity prices are higher than others, as coal impacts their consumption, and electricity and coal consumption were found to cause significant carbon emissions. Also, waste generation and recycling significantly increase and decrease emissions from the waste sector, respectively. Moreover, non-permanent appliances such as desktop computers and monitors consume a lot of electricity, and significant energy saving potential has been shown. Lastly, a linear relationship exists between buildings’ electricity use and total occupancy, but no significant relationship exists between occupancy and thermal loads, such as cooling and heating loads. These findings will potentially provide policymakers with a better understanding of and insights into carbon emission manipulation in the building sector.
ContributorsLee, Seungtaek (Author) / Chong, Oswald (Thesis advisor) / Sullivan, Kenneth (Committee member) / Tang, Pingbo (Committee member) / Arizona State University (Publisher)
Created2018
Description
The increasingly recurrent extraordinary flood events in the metropolitan area of Monterrey, Mexico have led to significant stakeholder interest in understanding the hydrologic response of the Santa Catarina watershed to extreme events. This study analyzes a flood mitigation strategy proposed by stakeholders through a participatory workshop and are assessed using two hydrological models: The Hydrological Modeling System (HEC-HMS) and the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS).
The stakeholder-derived flood mitigation strategy consists of placing new hydraulic infrastructure in addition to the current flood controls in the basin. This is done by simulating three scenarios: (1) evaluate the impact of the current structure, (2) implementing a large dam similar to the Rompepicos dam and (3) the inclusion of three small detention dams. These mitigation strategies are assessed in the context of a major flood event caused by the landfall of Hurricane Alex in July 2010 through a consistent application of the two modeling tools. To do so, spatial information on topography, soil, land cover and meteorological forcing were assembled, quality-controlled and input into each model. Calibration was performed for each model based on streamflow observations and maximum observed reservoir levels from the National Water Commission in Mexico.
Simulation analyses focuses on the differential capability of the two models in capturing the spatial variability in rainfall, topographic conditions, soil hydraulic properties and its effect on the flood response in the presence of the different flood mitigation structures. The implementation of new hydraulic infrastructure is shown to have a positive impact on mitigating the flood peak with a more favorable reduction in the peak at the outlet from the larger dam (16.5% in tRIBS and 23% in HEC-HMS) than the collective effect from the small structures (12% in tRIBS and 10% in HEC-HMS). Furthermore, flood peak mitigation depends strongly on the number and locations of the new dam sites in relation to the spatial distribution of rainfall and flood generation. Comparison of the two modeling approaches complements the analysis of available observations for the flood event and provides a framework within which to derive a multi-model approach for stakeholder-driven solutions.
The stakeholder-derived flood mitigation strategy consists of placing new hydraulic infrastructure in addition to the current flood controls in the basin. This is done by simulating three scenarios: (1) evaluate the impact of the current structure, (2) implementing a large dam similar to the Rompepicos dam and (3) the inclusion of three small detention dams. These mitigation strategies are assessed in the context of a major flood event caused by the landfall of Hurricane Alex in July 2010 through a consistent application of the two modeling tools. To do so, spatial information on topography, soil, land cover and meteorological forcing were assembled, quality-controlled and input into each model. Calibration was performed for each model based on streamflow observations and maximum observed reservoir levels from the National Water Commission in Mexico.
Simulation analyses focuses on the differential capability of the two models in capturing the spatial variability in rainfall, topographic conditions, soil hydraulic properties and its effect on the flood response in the presence of the different flood mitigation structures. The implementation of new hydraulic infrastructure is shown to have a positive impact on mitigating the flood peak with a more favorable reduction in the peak at the outlet from the larger dam (16.5% in tRIBS and 23% in HEC-HMS) than the collective effect from the small structures (12% in tRIBS and 10% in HEC-HMS). Furthermore, flood peak mitigation depends strongly on the number and locations of the new dam sites in relation to the spatial distribution of rainfall and flood generation. Comparison of the two modeling approaches complements the analysis of available observations for the flood event and provides a framework within which to derive a multi-model approach for stakeholder-driven solutions.
ContributorsCázares Rodríguez, Jorge E (Author) / Vivoni, Enrique (Thesis advisor) / Wang, Zhihua (Committee member) / Mays, Larry W. (Committee member) / Arizona State University (Publisher)
Created2016
Description
Resilient acquisition of timely, detailed job site information plays a pivotal role in maintaining the productivity and safety of construction projects that have busy schedules, dynamic workspaces, and unexpected events. In the field, construction information acquisition often involves three types of activities including sensor-based inspection, manual inspection, and communication. Human interventions play critical roles in these three types of field information acquisition activities. A resilient information acquisition system is needed for safer and more productive construction. The use of various automation technologies could help improve human performance by proactively providing the needed knowledge of using equipment, improve the situation awareness in multi-person collaborations, and reduce the mental workload of operators and inspectors.
Unfortunately, limited studies consider human factors in automation techniques for construction field information acquisition. Fully utilization of the automation techniques requires a systematical synthesis of the interactions between human, tasks, and construction workspace to reduce the complexity of information acquisition tasks so that human can finish these tasks with reliability. Overall, such a synthesis of human factors in field data collection and analysis is paving the path towards “Human-Centered Automation” (HCA) in construction management. HCA could form a computational framework that supports resilient field data collection considering human factors and unexpected events on dynamic job sites.
This dissertation presented an HCA framework for resilient construction field information acquisition and results of examining three HCA approaches that support three use cases of construction field data collection and analysis. The first HCA approach is an automated data collection planning method that can assist 3D laser scan planning of construction inspectors to achieve comprehensive and efficient data collection. The second HCA approach is a Bayesian model-based approach that automatically aggregates the common sense of people from the internet to identify job site risks from a large number of job site pictures. The third HCA approach is an automatic communication protocol optimization approach that maximizes the team situation awareness of construction workers and leads to the early detection of workflow delays and critical path changes. Data collection and simulation experiments extensively validate these three HCA approaches.
Unfortunately, limited studies consider human factors in automation techniques for construction field information acquisition. Fully utilization of the automation techniques requires a systematical synthesis of the interactions between human, tasks, and construction workspace to reduce the complexity of information acquisition tasks so that human can finish these tasks with reliability. Overall, such a synthesis of human factors in field data collection and analysis is paving the path towards “Human-Centered Automation” (HCA) in construction management. HCA could form a computational framework that supports resilient field data collection considering human factors and unexpected events on dynamic job sites.
This dissertation presented an HCA framework for resilient construction field information acquisition and results of examining three HCA approaches that support three use cases of construction field data collection and analysis. The first HCA approach is an automated data collection planning method that can assist 3D laser scan planning of construction inspectors to achieve comprehensive and efficient data collection. The second HCA approach is a Bayesian model-based approach that automatically aggregates the common sense of people from the internet to identify job site risks from a large number of job site pictures. The third HCA approach is an automatic communication protocol optimization approach that maximizes the team situation awareness of construction workers and leads to the early detection of workflow delays and critical path changes. Data collection and simulation experiments extensively validate these three HCA approaches.
ContributorsZhang, Cheng (Author) / Tang, Pingbo (Thesis advisor) / Cooke, Nancy J. (Committee member) / Chong, Oswald (Committee member) / Arizona State University (Publisher)
Created2017
Description
The performance of the Alpha Sprayed Polyurethane Foam (SPF) roofing system is perceived as not an economical option when compared to a 20-year modified bitumen roofing system. Today, the majority of roofs are being replaced, rather than newly installed. The coating manufacturer, Neogard, implemented the Alpha roofing program to identify the best contractors in the industry and to measure their roof performance. The Alpha roof system has shown consistent high performance on over 230 million square feet of surveyed roof. The author proposes to identify if the Alpha roof system is renewable, has proven performance that competes with the traditional modified roofing system, and is a more economical option by evaluating an Alpha roof system installation and the performance of a 29-year-old Alpha roof system. The Dallas Independent School District utilized the Alpha program for William Lipscomb Elementary School in 2016. Dallas Fort Worth Urethane installed the Alpha SPF roof system with high customer satisfaction ratings. This roofing installation showed the value of the Alpha roof system by saving over 20% on costs for the installation and will save approximately 69% of costs on the recoating of the roof in 20 years. The Casa View Elementary School roof system was installed with a Neogard Permathane roof system in 1987. This roof was hail tested with ten drops from 17 feet 9 inches of 1-3/4-inch steel ball (9 out of 10 passed) and four drops from 17 feet 9 inches with a 3-inch diameter steel ball (2 out of 4 passed). The analysis of the passing and failing core samples show that the thickness of the top and base Alpha SPF coating is one of the major differences in a roof passing or failing the FM-SH hail test. Over the 40-year service life, the main difference of purchasing a 61,000 square feet Alpha SPF roof versus modified bitumen roof are savings of approximately $1,067,500. Past hail tests on Alpha SPF roof systems show its cost effectiveness with high customer satisfaction (9.8 out of 10), an over 40-year service life after a $6.00/SF recoat and savings of over $1M for DISD.
ContributorsZulanas, Charles J., IV (Author) / Kashiwagi, Dean T. (Thesis advisor) / Kashiwagi, Jacob S (Thesis advisor) / Chong, Oswald (Committee member) / Arizona State University (Publisher)
Created2017
Description
Civil infrastructures undergo frequent spatial changes such as deviations between as-designed model and as-is condition, rigid body motions of the structure, and deformations of individual elements of the structure, etc. These spatial changes can occur during the design phase, the construction phase, or during the service life of a structure. Inability to accurately detect and analyze the impact of such changes may miss opportunities for early detections of pending structural integrity and stability issues. Commercial Building Information Modeling (BIM) tools could hardly track differences between as-designed and as-built conditions as they mainly focus on design changes and rely on project managers to manually update and analyze the impact of field changes on the project performance. Structural engineers collect detailed onsite data of a civil infrastructure to perform manual updates of the model for structural analysis, but such approach tends to become tedious and complicated while handling large civil infrastructures.
Previous studies started collecting detailed geometric data generated by 3D laser scanners for defect detection and geometric change analysis of structures. However, previous studies have not yet systematically examined methods for exploring the correlation between the detected geometric changes and their relation to the behaviors of the structural system. Manually checking every possible loading combination leading to the observed geometric change is tedious and sometimes error-prone. The work presented in this dissertation develops a spatial change analysis framework that utilizes spatiotemporal data collected using 3D laser scanning technology and the as-designed models of the structures to automatically detect, classify, and correlate the spatial changes of a structure. The change detection part of the developed framework is computationally efficient and can automatically detect spatial changes between as-designed model and as-built data or between two sets of as-built data collected using 3D laser scanning technology. Then a spatial change classification algorithm automatically classifies the detected spatial changes as global (rigid body motion) and local deformations (tension, compression). Finally, a change correlation technique utilizes a qualitative shape-based reasoning approach for identifying correlated deformations of structure elements connected at joints that contradicts the joint equilibrium. Those contradicting deformations can help to eliminate improbable loading combinations therefore guiding the loading path analysis of the structure.
Previous studies started collecting detailed geometric data generated by 3D laser scanners for defect detection and geometric change analysis of structures. However, previous studies have not yet systematically examined methods for exploring the correlation between the detected geometric changes and their relation to the behaviors of the structural system. Manually checking every possible loading combination leading to the observed geometric change is tedious and sometimes error-prone. The work presented in this dissertation develops a spatial change analysis framework that utilizes spatiotemporal data collected using 3D laser scanning technology and the as-designed models of the structures to automatically detect, classify, and correlate the spatial changes of a structure. The change detection part of the developed framework is computationally efficient and can automatically detect spatial changes between as-designed model and as-built data or between two sets of as-built data collected using 3D laser scanning technology. Then a spatial change classification algorithm automatically classifies the detected spatial changes as global (rigid body motion) and local deformations (tension, compression). Finally, a change correlation technique utilizes a qualitative shape-based reasoning approach for identifying correlated deformations of structure elements connected at joints that contradicts the joint equilibrium. Those contradicting deformations can help to eliminate improbable loading combinations therefore guiding the loading path analysis of the structure.
ContributorsKalasapudi, Vamsi Sai (Author) / Tang, Pingbo (Thesis advisor) / Chong, Oswald (Committee member) / Hjelmstad, Keith (Committee member) / Arizona State University (Publisher)
Created2017
Description
The fast pace of global urbanization makes cities the hotspots of population density and anthropogenic activities, leading to intensive emissions of heat and carbon dioxide (CO2), a primary greenhouse gas. Urban climate scientists have been actively seeking effective mitigation strategies over the past decades, aiming to improve the environmental quality for urban dwellers. Prior studies have identified the role of urban green spaces in the relief of urban heat stress. Yet little effort was devoted to quantify their contribution to local and regional CO2 budget. In fact, urban biogenic CO2 fluxes from photosynthesis and respiration are influenced by the microclimate in the built environment and are sensitive to anthropogenic disturbance. The high complexity of the urban ecosystem leads to an outstanding challenge for numerical urban models to disentangling and quantifying the interplay between heat and carbon dynamics.This dissertation aims to advance the simulation of thermal and carbon dynamics in urban land surface models, and to investigate the role of urban greening practices and urban system design in mitigating heat and CO2 emissions. The biogenic CO2 exchange in cities is parameterized by incorporating plant physiological functions into an advanced single-layer urban canopy model in the built environment. The simulation result replicates the microclimate and CO2 flux patterns measured from an eddy covariance system over a residential neighborhood in Phoenix, Arizona with satisfactory accuracy. Moreover, the model decomposes the total CO2 flux from observation and identifies the significant CO2 efflux from soil respiration. The model is then applied to quantify the impact of urban greening practices on heat and biogenic CO2 exchange over designed scenarios. The result shows the use of urban greenery is effective in mitigating both urban heat and carbon emissions, providing environmental co-benefit in cities. Furthermore, to seek the optimal urban system design in terms of thermal comfort and CO2 reduction, a multi-objective optimization algorithm is applied to the machine learning surrogates of the physical urban land surface model. There are manifest trade-offs among ameliorating diverse urban environmental indicators despite the co-benefit from urban greening. The findings of this dissertation, along with its implications on urban planning and landscaping management, would promote sustainable urban development strategies for achieving optimal environmental quality for policy makers, urban residents, and practitioners.
ContributorsLi, Peiyuan (Author) / Wang, Zhihua (Thesis advisor) / Vivoni, Enrique (Committee member) / Huang, Huei-Ping (Committee member) / Myint, Soe (Committee member) / Xu, Tianfang (Committee member) / Arizona State University (Publisher)
Created2021