Matching Items (37)
Description
Perceptions of climate variability and change reflect local concerns and the actual impacts of climate phenomena on people's lives. Perceptions are the bases of people's decisions to act, and they determine what adaptive measures will be taken. But perceptions of climate may not always be aligned with scientific observations because they are influenced by socio-economic and ecological variables. To find sustainability solutions to climate-change challenges, researchers and policy makers need to understand people's perceptions so that they can account for likely responses. Being able to anticipate responses will increase decision-makers' capacities to create policies that support effective adaptation strategies. I analyzed Mexican maize farmers' perceptions of drought variability as a proxy for their perceptions of climate variability and change. I identified the factors that contribute to the perception of changing drought frequency among farmers in the states of Chiapas, Mexico, and Sinaloa. I conducted Chi-square tests and Logit regression analyses using data from a survey of 1092 maize-producing households in the three states. Results showed that indigenous identity, receipt of credits or loans, and maize-type planted were the variables that most strongly influenced perceptions of drought frequency. The results suggest that climate-adaptation policy will need to consider the social and institutional contexts of farmers' decision-making, as well as the agronomic options for smallholders in each state.
ContributorsRodríguez, Natalia (Author) / Eakin, Hallie (Thesis advisor) / Muneepeerakul, Rachata (Thesis advisor) / Manuel-Navarrete, David (Committee member) / Arizona State University (Publisher)
Created2015
Description
The role of climate change, as measured in terms of changes in the climatology of geophysical variables (such as temperature and rainfall), on the global distribution and burden of vector-borne diseases (VBDs) remains a subject of considerable debate. This dissertation attempts to contribute to this debate via the use of mathematical (compartmental) modeling and statistical data analysis. In particular, the objective is to find suitable values and/or ranges of the climate variables considered (typically temperature and rainfall) for maximum vector abundance and consequently, maximum transmission intensity of the disease(s) they cause.
Motivated by the fact that understanding the dynamics of disease vector is crucial to understanding the transmission and control of the VBDs they cause, a novel weather-driven deterministic model for the population biology of the mosquito is formulated and rigorously analyzed. Numerical simulations, using relevant weather and entomological data for Anopheles mosquito (the vector for malaria), show that maximum mosquito abundance occurs when temperature and rainfall values lie in the range [20-25]C and [105-115] mm, respectively.
The Anopheles mosquito ecology model is extended to incorporate human dynamics. The resulting weather-driven malaria transmission model, which includes many of the key aspects of malaria (such as disease transmission by asymptomatically-infectious humans, and enhanced malaria immunity due to repeated exposure), was rigorously analyzed. The model which also incorporates the effect of diurnal temperature range (DTR) on malaria transmission dynamics shows that increasing DTR shifts the peak temperature value for malaria transmission from 29C (when DTR is 0C) to about 25C (when DTR is 15C).
Finally, the malaria model is adapted and used to study the transmission dynamics of chikungunya, dengue and Zika, three diseases co-circulating in the Americas caused by the same vector (Aedes aegypti). The resulting model, which is fitted using data from Mexico, is used to assess a few hypotheses (such as those associated with the possible impact the newly-released dengue vaccine will have on Zika) and the impact of variability in climate variables on the dynamics of the three diseases. Suitable temperature and rainfall ranges for the maximum transmission intensity of the three diseases are obtained.
Motivated by the fact that understanding the dynamics of disease vector is crucial to understanding the transmission and control of the VBDs they cause, a novel weather-driven deterministic model for the population biology of the mosquito is formulated and rigorously analyzed. Numerical simulations, using relevant weather and entomological data for Anopheles mosquito (the vector for malaria), show that maximum mosquito abundance occurs when temperature and rainfall values lie in the range [20-25]C and [105-115] mm, respectively.
The Anopheles mosquito ecology model is extended to incorporate human dynamics. The resulting weather-driven malaria transmission model, which includes many of the key aspects of malaria (such as disease transmission by asymptomatically-infectious humans, and enhanced malaria immunity due to repeated exposure), was rigorously analyzed. The model which also incorporates the effect of diurnal temperature range (DTR) on malaria transmission dynamics shows that increasing DTR shifts the peak temperature value for malaria transmission from 29C (when DTR is 0C) to about 25C (when DTR is 15C).
Finally, the malaria model is adapted and used to study the transmission dynamics of chikungunya, dengue and Zika, three diseases co-circulating in the Americas caused by the same vector (Aedes aegypti). The resulting model, which is fitted using data from Mexico, is used to assess a few hypotheses (such as those associated with the possible impact the newly-released dengue vaccine will have on Zika) and the impact of variability in climate variables on the dynamics of the three diseases. Suitable temperature and rainfall ranges for the maximum transmission intensity of the three diseases are obtained.
ContributorsOkuneye, Kamaldeen O (Author) / Gumel, Abba B (Thesis advisor) / Kuang, Yang (Committee member) / Smith, Hal (Committee member) / Thieme, Horst (Committee member) / Nagy, John (Committee member) / Arizona State University (Publisher)
Created2018
Description
The most recent decision of the 2012 Conference of the Parties (CoP) to the United Nations Framework Convention on Climate Change (UNFCCC) recognizes that in order to create climate policies that respond to the different needs of men and women a more balanced representation of women from developed and developing countries is needed. National Adaptation Programmes of Action (NAPAs) provide a process for Least Developed Countries (LDCs) to “identify priority activities that respond to their urgent and immediate needs to respond to impending threats from climate change.” Since 1997, the United Nations has agreed to gender mainstreaming- a globally accepted strategy for promoting gender equality by ensuring that gender perspectives and attention to the goal of gender equality are central to all activities in the all UN systems.
Due to the gender division of labor climate change will affect men and women differently. Policies and programs that do not take into account the needs and capacities of both men and women will fail to be effective and may worsen preexisting conditions that historically favor men. My research investigates the UN’s commitment towards gender mainstreaming. More specifically my objective is to understand how and to what extent the NAPAs from 49 countries integrate a gender dimension into their national climate adaptation policy. For the purpose of this research, I consider three interrelated issues: whether gender-specific needs and vulnerabilities were identified by the NAPA; if these needs and vulnerabilities were addressed by proposed adaptation projects; and in what forms women participated in the formulation of the NAPA. The scope of this research begins with an overview assessment of 49 NAPAs followed by a comparative assessment of NAPAs from four countries- Afghanistan, Bangladesh, Maldives, and Niger, and an in-depth analysis of Nepal’s NAPA, which incorporates field study. Nepal was chosen as a focus country due to its identification as being both inclusive and gender sensitive.
The method of inquiry consists of both quantitative and qualitative analysis, utilizing the quantitative measures of HDI and GII and the qualitative methods of content analysis and case study. The findings suggest that the response to the gender dimensions of climate change found in adaptation policies vary widely among the LDCs and the level of response is dependent upon social, cultural, economic, and political contexts within each LDC. Additionally, I find that gender mainstreaming techniques have not been fully integrated into the NAPA policy and processes, and have not been effective at promoting gender equality through adaptation strategies. Recommendations are provided in order to help mainstream gender in NAPAs as they continue to be developed, revised, and implemented.
Due to the gender division of labor climate change will affect men and women differently. Policies and programs that do not take into account the needs and capacities of both men and women will fail to be effective and may worsen preexisting conditions that historically favor men. My research investigates the UN’s commitment towards gender mainstreaming. More specifically my objective is to understand how and to what extent the NAPAs from 49 countries integrate a gender dimension into their national climate adaptation policy. For the purpose of this research, I consider three interrelated issues: whether gender-specific needs and vulnerabilities were identified by the NAPA; if these needs and vulnerabilities were addressed by proposed adaptation projects; and in what forms women participated in the formulation of the NAPA. The scope of this research begins with an overview assessment of 49 NAPAs followed by a comparative assessment of NAPAs from four countries- Afghanistan, Bangladesh, Maldives, and Niger, and an in-depth analysis of Nepal’s NAPA, which incorporates field study. Nepal was chosen as a focus country due to its identification as being both inclusive and gender sensitive.
The method of inquiry consists of both quantitative and qualitative analysis, utilizing the quantitative measures of HDI and GII and the qualitative methods of content analysis and case study. The findings suggest that the response to the gender dimensions of climate change found in adaptation policies vary widely among the LDCs and the level of response is dependent upon social, cultural, economic, and political contexts within each LDC. Additionally, I find that gender mainstreaming techniques have not been fully integrated into the NAPA policy and processes, and have not been effective at promoting gender equality through adaptation strategies. Recommendations are provided in order to help mainstream gender in NAPAs as they continue to be developed, revised, and implemented.
ContributorsAnagnostou, Sotiria (Author) / Chhetri, Netra (Thesis advisor) / Hackett, Edward (Committee member) / Hibner-Koblitz, Ann (Committee member) / Arizona State University (Publisher)
Created2015
Description
The Global Change Assessment Model (GCAM) is an integrated assessment tool for exploring consequences and responses to global change. However, the current iteration of GCAM relies on NetCDF file outputs which need to be exported for visualization and analysis purposes. Such a requirement limits the uptake of this modeling platform for analysts that may wish to explore future scenarios. This work has focused on a web-based geovisual analytics interface for GCAM. Challenges of this work include enabling both domain expert and model experts to be able to functionally explore the model. Furthermore, scenario analysis has been widely applied in climate science to understand the impact of climate change on the future human environment. The inter-comparison of scenario analysis remains a big challenge in both the climate science and visualization communities. In a close collaboration with the Global Change Assessment Model team, I developed the first visual analytics interface for GCAM with a series of interactive functions to help users understand the simulated impact of climate change on sectors of the global economy, and at the same time allow them to explore inter comparison of scenario analysis with GCAM models. This tool implements a hierarchical clustering approach to allow inter-comparison and similarity analysis among multiple scenarios over space, time, and multiple attributes through a set of coordinated multiple views. After working with this tool, the scientists from the GCAM team agree that the geovisual analytics tool can facilitate scenario exploration and enable scientific insight gaining process into scenario comparison. To demonstrate my work, I present two case studies, one of them explores the potential impact that the China south-north water transportation project in the Yangtze River basin will have on projected water demands. The other case study using GCAM models demonstrates how the impact of spatial variations and scales on similarity analysis of climate scenarios varies at world, continental, and country scales.
ContributorsChang, Zheng (Author) / Maciejewski, Ross (Thesis advisor) / Sarjoughian, Hessam S. (Committee member) / White, Dave (Committee member) / Luo, Wei (Committee member) / Arizona State University (Publisher)
Created2015
Description
Energy use within urban building stocks is continuing to increase globally as populations expand and access to electricity improves. This projected increase in demand could require deployment of new generation capacity, but there is potential to offset some of this demand through modification of the buildings themselves. Building stocks are quasi-permanent infrastructures which have enduring influence on urban energy consumption, and research is needed to understand: 1) how development patterns constrain energy use decisions and 2) how cities can achieve energy and environmental goals given the constraints of the stock. This requires a thorough evaluation of both the growth of the stock and as well as the spatial distribution of use throughout the city. In this dissertation, a case study in Los Angeles County, California (LAC) is used to quantify urban growth, forecast future energy use under climate change, and to make recommendations for mitigating energy consumption increases. A reproducible methodological framework is included for application to other urban areas.
In LAC, residential electricity demand could increase as much as 55-68% between 2020 and 2060, and building technology lock-in has constricted the options for mitigating energy demand, as major changes to the building stock itself are not possible, as only a small portion of the stock is turned over every year. Aggressive and timely efficiency upgrades to residential appliances and building thermal shells can significantly offset the projected increases, potentially avoiding installation of new generation capacity, but regulations on new construction will likely be ineffectual due to the long residence time of the stock (60+ years and increasing). These findings can be extrapolated to other U.S. cities where the majority of urban expansion has already occurred, such as the older cities on the eastern coast. U.S. population is projected to increase 40% by 2060, with growth occurring in the warmer southern and western regions. In these growing cities, improving new construction buildings can help offset electricity demand increases before the city reaches the lock-in phase.
In LAC, residential electricity demand could increase as much as 55-68% between 2020 and 2060, and building technology lock-in has constricted the options for mitigating energy demand, as major changes to the building stock itself are not possible, as only a small portion of the stock is turned over every year. Aggressive and timely efficiency upgrades to residential appliances and building thermal shells can significantly offset the projected increases, potentially avoiding installation of new generation capacity, but regulations on new construction will likely be ineffectual due to the long residence time of the stock (60+ years and increasing). These findings can be extrapolated to other U.S. cities where the majority of urban expansion has already occurred, such as the older cities on the eastern coast. U.S. population is projected to increase 40% by 2060, with growth occurring in the warmer southern and western regions. In these growing cities, improving new construction buildings can help offset electricity demand increases before the city reaches the lock-in phase.
ContributorsReyna, Janet Lorel (Author) / Chester, Mikhail V (Thesis advisor) / Gurney, Kevin (Committee member) / Reddy, T. Agami (Committee member) / Rey, Sergio (Committee member) / Arizona State University (Publisher)
Created2016
Description
In the United States, buildings account for 20–40% of the total energy consumption based on their operation and maintenance, which consume nearly 80% of their energy during their lifecycle. In order to reduce building energy consumption and related problems (i.e. global warming, air pollution, and energy shortages), numerous building technology programs, codes, and standards have been developed such as net-zero energy buildings, Leadership in Energy and Environmental Design (LEED), and the American Society of Heating, Refrigerating, and Air-Conditioning Engineers 90.1. However, these programs, codes, and standards are typically utilized before or during the design and construction phases. Subsequently, it is difficult to track whether buildings could still reduce energy consumption post construction. This dissertation fills the gap in knowledge of analytical methods for building energy analysis studies for LEED buildings. It also focuses on the use of green space for reducing atmospheric temperature, which contributes the most to building energy consumption. The three primary objectives of this research are to: 1) find the relationship between building energy consumption, outside atmospheric temperature, and LEED Energy and Atmosphere credits (OEP); 2) examine the use of different green space layouts for reducing the atmospheric temperature of high-rise buildings; and 3) use data mining techniques (i.e. clustering, isolation, and anomaly detection) to identify data anomalies in the energy data set and evaluate LEED Energy and Atmosphere credits based on building energy patterns. The results found that buildings with lower OEP used the highest amount of energy. LEED OEP scores tended to increase the energy saving potential of buildings, thereby reducing the need for renovation and maintenance. The results also revealed that the shade and evaporation effects of green spaces around buildings were more effective for lowering the daytime atmospheric temperature in the range of 2°C to 6.5°C. Additionally, abnormal energy consumption patterns were found in LEED buildings that used anomaly detection methodology analysis. Overall, LEED systems should be evaluated for energy performance to ensure that buildings continue to save energy after construction.
ContributorsKim, Jonghoon (Author) / Ariaratnam, Samuel T (Thesis advisor) / Chong, Oswald W (Committee member) / Bearup, Wylie K (Committee member) / Arizona State University (Publisher)
Created2016
Description
In the American Southwest, an area which already experiences a significant number of cooling degree days, anthropogenic climate change is expected to result in higher average temperatures and the increasing frequency, duration, and severity of heat waves. Climatological forecasts predict heat waves will increase by 150-840% in Los Angeles County, California and 340-1800% in Maricopa County, Arizona. Heat exposure is known to increase both morbidity and mortality and rising temperatures represent a threat to public health. As a result there has been a significant amount of research into understanding existing socio-economic vulnerabilities to extreme heat which has identified population subgroups at greater risk of adverse health outcomes. Additionally, research has shown that man-made infrastructure can mitigate or exacerbate these health risks. However, while recent socio-economic heat vulnerability research has developed geospatially explicit results, research which links it directly with infrastructure characteristics is limited. Understanding how socio-economic vulnerabilities interact with infrastructure systems is a critical component to developing climate adaptation policies and programs which efficiently and effectively mitigate health risks associated with rising temperatures.
The availability of cooled space, whether public or private, has been shown to greatly reduce health risks associated with extreme heat. However, a lack of fine-scale knowledge of which households have access to this infrastructure results in an incomplete understanding of the health risks associated with heat. This knowledge gap could result in the misallocation of resources intended to mitigate negative health impacts associated with heat exposure. Additionally, when discussing accessibility to public cooled space there are underlying questions of mobility and mode choice. In addition to captive riders, a growing emphasis on walking, biking and public transit will likely expose additional choice riders to extreme temperatures and compound existing vulnerabilities to heat.
The availability of cooled space, whether public or private, has been shown to greatly reduce health risks associated with extreme heat. However, a lack of fine-scale knowledge of which households have access to this infrastructure results in an incomplete understanding of the health risks associated with heat. This knowledge gap could result in the misallocation of resources intended to mitigate negative health impacts associated with heat exposure. Additionally, when discussing accessibility to public cooled space there are underlying questions of mobility and mode choice. In addition to captive riders, a growing emphasis on walking, biking and public transit will likely expose additional choice riders to extreme temperatures and compound existing vulnerabilities to heat.
ContributorsFraser, Andrew Michael (Author) / Chester, Mikhail (Thesis advisor) / Seager, Thomas (Committee member) / Zhou, Xuesong (Committee member) / Kuby, Michael (Committee member) / Arizona State University (Publisher)
Created2016
Description
This research work uses the Weather Research and Forecasting Model to study the effect of large wind farms with an area of 900 square kilometers and a high power density of 7.58 W/m2 on regional climate. Simulations were performed with a wind farm parameterization scheme turned on in south Oregon. Control cases were also run with the parameterization scheme turned off. The primary emphasis was on offshore wind farms. Some analysis on onshore wind farms was also performed. The effects of these wind farms were studied on the vertical profiles of temperature, wind speed, and moisture as well as on temperature and on wind speed near the surface and at hub height. The effects during the day and at night were compared. Seasonal variations were also studied by performing simulations in January and in July. It was seen that wind farms produce a reduction in wind speed at hub height and that the downward propagation of this reduction in wind speed lessens as the atmosphere becomes more stable. In all the cases studied, the wind farms produced a warming effect near the surface, with greater atmospheric stability leading to higher near-surface temperatures. It was also observed that wind farms caused a drying effect below the hub height and a moistening effect above it, because they had facilitated vertical transport of moisture in the air from the lower layers of the atmosphere to the layers of the atmosphere above the wind farm.
ContributorsGeorge, Sushant (Author) / Huang, Huei-Ping (Thesis advisor) / Wang, Zhihua (Committee member) / Calhoun, Ronald (Committee member) / Arizona State University (Publisher)
Created2016
Description
Climate change poses a threat to the emotional well-being and livelihood strategies of individuals in biophysically vulnerable communities. While the biophysical effects and possibilities of climate change are well-documented, understanding the emotional impacts on individuals in these communities is an avenue of research that requires more exploration. Using an ethnographic approach, this study analyzes the emotional responses of individuals, first in three biophysically vulnerable communities in the United States, and second, in island communities. Study sites in the United States include Mobile, Alabama; Kodiak, Alaska; and Phoenix, Arizona, each of which have different vulnerabilities to the effects of climate change. Internationally, we conducted research in Viti Levu, Fiji; Nicosia, Cyprus; Wellington, New Zealand; and London, England. Using the 2014 Global Ethnohydrology Study Protocol respondents were asked about their emotional responses to the current effects of climate change, the effects of climate change on livelihoods in their area, and the effects of climate change on the younger generation. Using cross-cultural data allows for a broader understanding of emotional distress and wellbeing in response to climate change in areas with similar expected climate change outcomes, although with different levels of biophysical vulnerability, as well as understanding emotional distress and wellbeing in areas with different expected climate change outcomes, and similar levels of biophysical vulnerability. Results from this research can be used to understand possible mental health outcomes, the possibilities for political activism, and how to create mitigation strategies that resonate with local community members.
ContributorsDu Bray, Margaret V (Author) / Wutich, Amber (Thesis advisor) / BurnSilver, Shauna (Thesis advisor) / Bolin, Bob (Committee member) / Arizona State University (Publisher)
Created2017
Description
For a country like India which is highly vulnerable to climate change, the need to focus on adaptation in tandem with traditional development is immense, as the two are inextricably tied together. As a prominent actor working at the intersection of these two fields, NGOs need to be prepared for the emerging challenges of climate change. While research indicates that investments in learning can be beneficial for this purpose, there are limited studies looking into organizational learning within NGOs working on climate change adaptation. This study uses a multiple case study design to explore learning mechanisms, and trace learning over time within four development NGOs working on climate change adaptation in India. These insights could be useful for development NGOs looking to enhance their learning to meet the challenges of climate change. More broadly, this research adds to the understanding of the role of learning in climate change adaptation.
ContributorsNautiyal, Snigdha (Author) / Klinsky, Sonja (Thesis advisor) / Eakin, Hallie (Committee member) / Wang, Lili (Committee member) / Arizona State University (Publisher)
Created2017