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- All Subjects: Sustainability
Description
Food waste is gaining considerable attention from researchers in terms of its sources, its causes, and its potential effects on the environment, economy, and population health. To date, few instruments exist that allow researchers to measure food waste at the household level in reliable ways. This study aimed to assess the reliability of a newly developed self-assessment tool to measure household food waste, among participants living in Mexico. The survey tool consisted of 11 items which ask participants (N = 22) to estimate the amount of food per category that generally gets thrown away instead of eaten in the average week. Two tests of reliability were conducted, including Cronbach's Alpha for test-retest reliability, and Intra-class Correlation for internal reliability. Results varied across food categories evaluated by individual items. Items related to fresh fruit and bread products did not show reliability when testing for internal reliability or test-retest reliability. Fresh vegetables, meat and poultry products, meat alternative products, fish and seafood products, leftovers, and shelf stable foods were shown to be reliable when testing Cronbach's alpha and ICC. However, dairy products, eggs and frozen foods were inconclusive when testing for reliability. The study suggests future testing with larger sample sizes should be conducted to demonstrate reliability of the food waste self-assessment tool.
ContributorsLeone, Bryanna (Author) / Wharton, Christopher (Thesis advisor) / Shepard, Christina (Committee member) / Johnston, Carol (Committee member) / Arizona State University (Publisher)
Created2022
Description
Cities are facing complex problems in urban water management due to unprecedented changes in climate, natural and built environment. The shift in urban hydrology from pre-development to post-development continues to accelerate the challenges of managing excess stormwater runoff, mitigating urban flood hazards and flood damages. Physically based hydrologic-hydraulic stormwater models are a useful tool for broad subset of urban flood management including risk and hazard assessment, flood forecasting, and infrastructure adaptation decision making and planning. The existing limitations in data availability, gaps in data, and uncertainty in data preclude reliable model construction, testing, deployment, knowledge generation, effective communication of flood risks, and adaptation decision making. These challenges that affect both the science and practice motivate three chapters of this dissertation. The first study conducts diagnostic analysis of the effects of stormwater infrastructure data completeness on model’s ability to simulate flood duration, flooding flow rate; and assesses the combined effects of data gaps and model resolution to simulate flood depth, extent and volume (chapter 2). The analysis showed the significance of complete stormwater infrastructure data and high model resolution to reduce error, bias and uncertainty; this study also presented an approach for filling infrastructure data gaps using available data and design standards. The second study addresses the lack of long-term hydrological observation in urban catchment by investigating the process and benefits of leveraging novel data sources in urban flood model construction and testing (chapter 3). A proof-of-concept demonstrated the application and benefits of leveraging novel data sources for urban flood monitoring and modeling. Furthermore, it highlights the need for developing and streamlining novel data collection infrastructure. The third study applies the hydrologic-hydraulic model as an adaptation planning tool and assess the effects of uncertainty in design precipitation estimates and land use change on the optimal configuration of green infrastructure (chapter 4). Several uncertainties affect infrastructure decision making as showed by variation in optimal green infrastructure configuration under precipitation estimates and land use change. Thus, the study further highlights the need of flexible planning process in infrastructure decision making.
ContributorsShrestha, Ashish (Author) / Garcia, Margaret (Thesis advisor) / Mascaro, Giuseppe (Committee member) / Chester, Mikhail (Committee member) / Fletcher, Sarah (Committee member) / Arizona State University (Publisher)
Created2022
Description
The Water-Energy Nexus (WEN) is a concept that recognizes the interdependence of water and energy systems. The Phoenix metropolitan region (PMA) in Arizona has significant and potentially vulnerable WEN interactions. Future projections indicate that the population will increase and, with it, energy needs, while changes in future water demand are more uncertain. Climate change will also likely cause a reduction in surface water supply sources. Under these constraints, the expansion of renewable energy technology has the potential to benefit both water and energy systems and increase environmental sustainability by meeting future energy demands while lowering water use and CO2 emissions. However, the WEN synergies generated by renewables have not yet been thoroughly quantified, nor have the related costs been studied and compared to alternative options.Quantifying WEN intercations using numerical models is key to assessing renewable energy synergy. Despite recent advances, WEN models are still in their infancy, and research is needed to improve their accuracy and identify their limitations. Here, I highlight three research needs. First, most modeling efforts have been conducted for large-scale domains (e.g., states), while smaller scales, like metropolitan regions, have received less attention. Second, impacts of adopting different temporal (e.g., monthly, annual) and spatial (network granularity) resolutions on simulation accuracy have not been quantified. Third, the importance of simulating feedbacks between water and energy components has not been analyzed.
This dissertation fills these major research gaps by focusing on long-term water allocations and energy dispatch in the metropolitan region of Phoenix. An energy model is developed using the Low Emissions Analysis Platform (LEAP) platform and is subsequently coupled with a water management model based on the Water Evaluation and Planning (WEAP) platform. Analyses are conducted to quantify (1) the value of adopting coupled models instead of single models that are externally coupled, and (2) the accuracy of simulations based on different temporal resolutions of supply and demand and spatial granularity of the water and energy networks. The WEAP-LEAP integrated model is then employed under future climate scenarios to quantify the potential of renewable energy technologies to develop synergies between the PMA's water and energy systems.
ContributorsMounir, Adil (Author) / Mascaro, Giuseppe (Thesis advisor) / White, Dave (Committee member) / Garcia, Margaret (Committee member) / Xu, Tianfang (Committee member) / Chester, Mikhail (Committee member) / Arizona State University (Publisher)
Created2022
Description
A large amount of research associates the lack of fruit and vegetable consumption and the intake of animal-based foods with poor health outcomes. Making shifts towards a plant-focused diet could benefit the health of individuals. Individuals who show the highest long-term adherence to the avoidance of animal-based foods are those who value animal welfare. PURPOSE: The primary purpose of this study is to explore the validity of a novel animal food frequency questionnaire (AFFQ) in relation to dietary animal food intake using 3-day dietary food logs and measuring potential renal acid load (PRAL). PRAL is the amount of acid that is produced by the body after digesting food. Fruits and vegetables produce a lower acid load, which is reflective of positive health outcomes. A secondary aim of this study is to explore the relation between AFFQ scores and measures of empathy. METHODS: Participants complete a 10-minute survey including the AFFQ and the BES-A. The Basic Scale of Empathy for adults will be viewed based on the 2 factor and 3 factor analysis assessing: Affective empathy, Cognitive empathy, Emotional contagion, and Emotional Disconnection. The AFFQ will be scored and correlated with the 3-day food log and PRAL to explore validity of the new AFFQ scale. Secondarily, the AFFQ will be scored and correlated with the BES-A to explore an association. RESULTS: The null hypotheses H01 and H02 were rejected. H01 showed that AFFQ correlates significantly with percentage of dietary protein coming from animal- based products (r=.676, p=.016). H02 showed AFFQ has a significant correlation to PRAL (r=.831, p<.001). PRAL and the percentage of protein in the diet coming from animal-based products have a significant correlation (r=.725, p=.008). The null hypothesis H03 was accepted with AFFQ and BES-A 2 factor and 3 factor’s correlations showing (r= -.412, p=.183) and (r= -.307, p=.332). CONCLUSION: The AFFQ was able to reflect differences in frequency of animal-based food intake among the convenience sample. The AFFQ and individuals’ food choices were not related to their empathy levels.
ContributorsAlpine, Evajean May (Author) / Wharton, Christopher (Thesis advisor) / Lehmann, Jessica (Committee member) / Johnston, Carol (Committee member) / Arizona State University (Publisher)
Created2021
Description
Most American children consume less than the recommend amount of fruits and vegetables (F&V), 74% and 84%, respectively. Eating too few F&V in childhood is associated with increased risk of cardiovascular disease, hypertension, respiratory symptoms, and some cancers later in life. Adequate F&V consumption favorably impacts antioxidant status, gut flora, mood, and cognitive functioning. Nutrients such as vitamin C and fiber are only naturally occurring in plant foods. For many children, school lunches are an important source of F&V. This pilot study assessed the feasibility of providing condiments to increase children’s consumption of salad bar F&V in an elementary school cafeteria at lunchtime. The trial site was a single Title 1 elementary school in a large, urban district in the greater Phoenix metropolitan area. Taste tests were conducted on three convenience samples of children in grades 3 – 7, aged 8 – 12 years (n=57) to identify the most popular condiment flavors. The five highest rated flavors were made available daily at a “flavor station” in the school’s lunchroom for three consecutive weeks during the Fall 2018 semester. Descriptive and inferential statistics were used to analyze data. A cost analysis was conducted for capital outlays related to the flavor station. School employee perceptions of F&V and the flavor station were assessed via posttest online surveys. Peanut butter was rated the best tasting condiment by children and was the only condiment that increased in popularity throughout the intervention. Overall, daily F&V consumption increased 17 g per child. There was a linear increase in F&V consumption during the study (r=0.986; P=0.014). As a proportion of the total F&V selected, F&V waste decreased by nearly 3%. The average daily cost of providing the flavor station was $0.09 per student. Sixty-five percent of school staff felt that the flavor station should continue at their school. Peanut butter is an affordable, nutrient-dense food that accommodates the USDA Food and Nutrition Service meal patterns and nutrition standards, and thus, is a viable strategy for increasing F&V consumption and decreasing F&V waste. The results herein inform the development of future interventions to improve the palatability of F&V for children.
ContributorsScholtz, Cameron (Author) / Johnston, Carol (Thesis advisor) / Alexon, Christy (Committee member) / Hooker, Steven (Committee member) / Schwake, David (Committee member) / Swan, Pamela (Committee member) / Wharton, Christopher (Christopher Mack), 1977- (Committee member) / Arizona State University (Publisher)
Created2019
Description
Vegetative filter strips (VFS) are an effective methodology used for storm water management particularly for large urban parking lots. An optimization model for the design of vegetative filter strips that minimizes the amount of land required for stormwater management using the VFS is developed in this study. The resulting optimization model is based upon the kinematic wave equation for overland sheet flow along with equations defining the cumulative infiltration and infiltration rate.
In addition to the stormwater management function, Vegetative filter strips (VFS) are effective mechanisms for control of sediment flow and soil erosion from agricultural and urban lands. Erosion is a major problem associated with areas subjected to high runoffs or steep slopes across the globe. In order to effect economy in the design of grass filter strips as a mechanism for sediment control & stormwater management, an optimization model is required that minimizes the land requirements for the VFS. The optimization model presented in this study includes an intricate system of equations including the equations defining the sheet flow on the paved and grassed area combined with the equations defining the sediment transport over the vegetative filter strip using a non-linear programming optimization model. In this study, the optimization model has been applied using a sensitivity analysis of parameters such as different soil types, rainfall characteristics etc., performed to validate the model
In addition to the stormwater management function, Vegetative filter strips (VFS) are effective mechanisms for control of sediment flow and soil erosion from agricultural and urban lands. Erosion is a major problem associated with areas subjected to high runoffs or steep slopes across the globe. In order to effect economy in the design of grass filter strips as a mechanism for sediment control & stormwater management, an optimization model is required that minimizes the land requirements for the VFS. The optimization model presented in this study includes an intricate system of equations including the equations defining the sheet flow on the paved and grassed area combined with the equations defining the sediment transport over the vegetative filter strip using a non-linear programming optimization model. In this study, the optimization model has been applied using a sensitivity analysis of parameters such as different soil types, rainfall characteristics etc., performed to validate the model
ContributorsKhatavkar, Puneet N (Author) / Mays, Larry W. (Thesis advisor) / Fox, Peter (Committee member) / Wang, Zhihua (Committee member) / Mascaro, Giuseppe (Committee member) / Arizona State University (Publisher)
Created2015
Description
The combination of rapid urban growth and climate change places stringent constraints on multisector sustainability of cities. Green infrastructure provides a great potential for mitigating anthropogenic-induced urban environmental problems; nevertheless, studies at city and regional scales are inhibited by the deficiency in modelling the complex transport coupled water and energy inside urban canopies. This dissertation is devoted to incorporating hydrological processes and urban green infrastructure into an integrated atmosphere-urban modelling system, with the goal to improve the reliability and predictability of existing numerical tools. Based on the enhanced numerical tool, the effects of urban green infrastructure on environmental sustainability of cities are examined.
Findings indicate that the deployment of green roofs will cool the urban environment in daytime and warm it at night, via evapotranspiration and soil insulation. At the annual scale, green roofs are effective in decreasing building energy demands for both summer cooling and winter heating. For cities in arid and semiarid environments, an optimal trade-off between water and energy resources can be achieved via innovative design of smart urban irrigation schemes, enabled by meticulous analysis of the water-energy nexus. Using water-saving plants alleviates water shortage induced by population growth, but comes at the price of an exacerbated urban thermal environment. Realizing the potential water buffering capacity of urban green infrastructure is crucial for the long-term water sustainability and subsequently multisector sustainability of cities. Environmental performance of urban green infrastructure is determined by land-atmosphere interactions, geographic and meteorological conditions, and hence it is recommended that analysis should be conducted on a city-by-city basis before actual implementation of green infrastructure.
Findings indicate that the deployment of green roofs will cool the urban environment in daytime and warm it at night, via evapotranspiration and soil insulation. At the annual scale, green roofs are effective in decreasing building energy demands for both summer cooling and winter heating. For cities in arid and semiarid environments, an optimal trade-off between water and energy resources can be achieved via innovative design of smart urban irrigation schemes, enabled by meticulous analysis of the water-energy nexus. Using water-saving plants alleviates water shortage induced by population growth, but comes at the price of an exacerbated urban thermal environment. Realizing the potential water buffering capacity of urban green infrastructure is crucial for the long-term water sustainability and subsequently multisector sustainability of cities. Environmental performance of urban green infrastructure is determined by land-atmosphere interactions, geographic and meteorological conditions, and hence it is recommended that analysis should be conducted on a city-by-city basis before actual implementation of green infrastructure.
ContributorsYang, Jiachuan (Author) / Wang, Zhihua (Thesis advisor) / Kaloush, Kamil (Committee member) / Myint, Soe (Committee member) / Huang, Huei-Ping (Committee member) / Mascaro, Giuseppe (Committee member) / Arizona State University (Publisher)
Created2016
Description
The world has been continuously urbanized and is currently accommodating more than half of the human population. Despite that cities cover only less than 3% of the Earth’s land surface area, they emerged as hotspots of anthropogenic activities. The drastic land use changes, complex three-dimensional urban terrain, and anthropogenic heat emissions alter the transport of mass, heat, and momentum, especially within the urban canopy layer. As a result, cities are confronting numerous environmental challenges such as exacerbated heat stress, frequent air pollution episodes, degraded water quality, increased energy consumption and water use, etc. Green infrastructure, in particular, the use of trees, has been proved as an effective means to improve urban environmental quality in existing research. However, quantitative evaluations of the efficacy of urban trees in regulating air quality and thermal environment are impeded by the limited temporal and spatial scales in field measurements and the deficiency in numerical models.
This dissertation aims to advance the simulation of realistic functions of urban trees in both microscale and mesoscale numerical models, and to systematically evaluate the cooling capacity of urban trees under thermal extremes. A coupled large-eddy simulation–Lagrangian stochastic modeling framework is developed for the complex urban environment and is used to evaluate the impact of urban trees on traffic-emitted pollutants. Results show that the model is robust for capturing the dispersion of urban air pollutants and how strategically implemented urban trees can reduce vehicle-emitted pollution. To evaluate the impact of urban trees on the thermal environment, the radiative shading effect of trees are incorporated into the integrated Weather Research and Forecasting model. The mesoscale model is used to simulate shade trees over the contiguous United States, suggesting how the efficacy of urban trees depends on geographical and climatic conditions. The cooling capacity of urban trees and its response to thermal extremes are then quantified for major metropolitans in the United States based on remotely sensed data. It is found the nonlinear temperature dependence of the cooling capacity remarkably resembles the thermodynamic liquid-water–vapor equilibrium. The findings in this dissertation are informative to evaluating and implementing urban trees, and green infrastructure in large, as an important urban planning strategy to cope with emergent global environmental changes.
This dissertation aims to advance the simulation of realistic functions of urban trees in both microscale and mesoscale numerical models, and to systematically evaluate the cooling capacity of urban trees under thermal extremes. A coupled large-eddy simulation–Lagrangian stochastic modeling framework is developed for the complex urban environment and is used to evaluate the impact of urban trees on traffic-emitted pollutants. Results show that the model is robust for capturing the dispersion of urban air pollutants and how strategically implemented urban trees can reduce vehicle-emitted pollution. To evaluate the impact of urban trees on the thermal environment, the radiative shading effect of trees are incorporated into the integrated Weather Research and Forecasting model. The mesoscale model is used to simulate shade trees over the contiguous United States, suggesting how the efficacy of urban trees depends on geographical and climatic conditions. The cooling capacity of urban trees and its response to thermal extremes are then quantified for major metropolitans in the United States based on remotely sensed data. It is found the nonlinear temperature dependence of the cooling capacity remarkably resembles the thermodynamic liquid-water–vapor equilibrium. The findings in this dissertation are informative to evaluating and implementing urban trees, and green infrastructure in large, as an important urban planning strategy to cope with emergent global environmental changes.
ContributorsWang, Chenghao (Author) / Wang, Zhihua (Thesis advisor) / Myint, Soe W. (Committee member) / Huang, Huei-Ping (Committee member) / Mascaro, Giuseppe (Committee member) / Arizona State University (Publisher)
Created2019