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- Genre: Doctoral Dissertation
- Genre: Interviews
- Creators: Arizona State University
- Status: Published
Description
Extreme hot-weather events have become life-threatening natural phenomena in many cities around the world, and the health impacts of excessive heat are expected to increase with climate change (Huang et al. 2011; Knowlton et al. 2007; Meehl and Tebaldi 2004; Patz 2005). Heat waves will likely have the worst health impacts in urban areas, where large numbers of vulnerable people reside and where local-scale urban heat island effects (UHI) retard and reduce nighttime cooling. This dissertation presents three empirical case studies that were conducted to advance our understanding of human vulnerability to heat in coupled human-natural systems. Using vulnerability theory as a framework, I analyzed how various social and environmental components of a system interact to exacerbate or mitigate heat impacts on human health, with the goal of contributing to the conceptualization of human vulnerability to heat. The studies: 1) compared the relationship between temperature and health outcomes in Chicago and Phoenix; 2) compared a map derived from a theoretical generic index of vulnerability to heat with a map derived from actual heat-related hospitalizations in Phoenix; and 3) used geospatial information on health data at two areal units to identify the hot spots for two heat health outcomes in Phoenix. The results show a 10-degree Celsius difference in the threshold temperatures at which heat-stress calls in Phoenix and Chicago are likely to increase drastically, and that Chicago is likely to be more sensitive to climate change than Phoenix. I also found that heat-vulnerability indices are sensitive to scale, measurement, and context, and that cities will need to incorporate place-based factors to increase the usefulness of vulnerability indices and mapping to decision making. Finally, I found that identification of geographical hot-spot of heat-related illness depends on the type of data used, scale of measurement, and normalization procedures. I recommend using multiple datasets and different approaches to spatial analysis to overcome this limitation and help decision makers develop effective intervention strategies.
ContributorsChuang, Wen-Ching (Author) / Gober, Patricia (Thesis advisor) / Boone, Christopher (Committee member) / Guhathakurta, Subhrajit (Committee member) / Ruddell, Darren (Committee member) / Arizona State University (Publisher)
Created2013
Description
The ability of Neandertals to cope with the oscillating climate of the late Pleistocene and the extent to which these climate changes affected local Neandertal habitats remain unanswered anthropological topics of considerable scientific interest. Understanding the impact of climatic instability on Neandertals is critical for reconstructing the behaviors of our closest fossil relatives and possibly identifying factors that contributed to their extinction. My work aimed to test the hypotheses that 1) cold climates stressed Neandertal populations, and 2) that global climate changes affected local Neandertal habitats. An analysis of Neandertal butchering on Cervus elaphus, Rangifer tarandus, and Capreolus capreolus skeletal material deposited during global warm and cold phases from two French sites - Pech de l'Azé IV and Roc de Marsal - was conducted to assess the impact of climate change on butchering strategies and resource extraction. Results from a statistical analysis of surface modification on all marrow yielding long bones, including the 1st phalanx, demonstrated that specimens excavated from the cold levels at each cave have more cut marks (Wald χ2= 51.33, p= <0.001) and percussion marks (Wald χ2= 4.92, p= 0.02) than specimens from the warm levels after controlling for fragment size. These results support the hypothesis that Neandertals were nutritionally stressed during glacial cycles. The hypothesis that global climates affected local habitats was tested through radiogenic strontium isotopic reconstruction of large herbivore mobility patterns (e.g., Bison, Equus, Cervus and Rangifer), because it is known that in the northern hemisphere, mammals migrate less in warm, well-vegetated environments, but more in cold, open environments. Identifying isotopic variation in mammalian fossils enables mobility patterns to be inferred, providing an indication of whether environments at Pech de l'Azé IV and Roc de Marsal tracked global climates. Results from this study indicate that Neandertal prey species within the Dordogne Valley of France did not undertake long distance round-trip migrations in glacial or interglacial cycles, maintaining the possibility that local habitats did not change in differing climatic cycles. However, because Neandertals were nutritionally stressed the most likely conclusion is that glacial cycles decreased herbivore populations, thus stressing Neandertals.
ContributorsHodgkins, Jamie Melichar (Author) / Marean, Curtis W (Thesis advisor) / Reed, Kaye E (Thesis advisor) / Knudson, Kelly J. (Committee member) / Spencer, Lillian M (Committee member) / Arizona State University (Publisher)
Created2012
Description
The numerical climate models have provided scientists, policy makers and the general public, crucial information for climate projections since mid-20th century. An international effort to compare and validate the simulations of all major climate models is organized by the Coupled Model Intercomparison Project (CMIP), which has gone through several phases since 1995 with CMIP5 being the state of the art. In parallel, an organized effort to consolidate all observational data in the past century culminates in the creation of several "reanalysis" datasets that are considered the closest representation of the true observation. This study compared the climate variability and trend in the climate model simulations and observations on the timescales ranging from interannual to centennial. The analysis focused on the dynamic climate quantity of zonal-mean zonal wind and global atmospheric angular momentum (AAM), and incorporated multiple datasets from reanalysis and the most recent CMIP3 and CMIP5 archives. For the observation, the validation of AAM by the length-of-day (LOD) and the intercomparison of AAM revealed a good agreement among reanalyses on the interannual and the decadal-to-interdecadal timescales, respectively. But the most significant discrepancies among them are in the long-term mean and long-term trend. For the simulations, the CMIP5 models produced a significantly smaller bias and a narrower ensemble spread of the climatology and trend in the 20th century for AAM compared to CMIP3, while CMIP3 and CMIP5 simulations consistently produced a positive trend for the 20th and 21st century. Both CMIP3 and CMIP5 models produced a wide range of the magnitudes of decadal and interdecadal variability of wind component of AAM (MR) compared to observation. The ensemble means of CMIP3 and CMIP5 are not statistically distinguishable for either the 20th- or 21st-century runs. The in-house atmospheric general circulation model (AGCM) simulations forced by the sea surface temperature (SST) taken from the CMIP5 simulations as lower boundary conditions were carried out. The zonal wind and MR in the CMIP5 simulations are well simulated in the AGCM simulations. This confirmed SST as an important mediator in regulating the global atmospheric changes due to GHG effect.
ContributorsPaek, Houk (Author) / Huang, Huei-Ping (Thesis advisor) / Adrian, Ronald (Committee member) / Wang, Zhihua (Committee member) / Anderson, James (Committee member) / Herrmann, Marcus (Committee member) / Arizona State University (Publisher)
Created2013
Description
Global climate change (GCC) is among the most important issues of the 21st century. Adaptation to and mitigation of climate change are some of the salient local and regional challenges scientists, decision makers, and the general public face today and will be in the near future. However, designed adaptation and mitigation strategies do not guarantee success in coping with global climate change. Despite the robust and convincing body for anthropogenic global climate change research and science there is still a significant gap between the recommendations provided by the scientific community and the actual actions by the public and policy makers. In order to design, implement, and generate sufficient public support for policies and planning interventions at the national and international level, it is necessary to have a good understanding of the public's perceptions regarding GCC. Based on survey research in nine countries, the purpose of this study is two-fold: First, to understand the nature of public perceptions of global climate change in different countries; and secondly to identi-fy perception factors which have a significant impact on the public's willingness to sup-port GCC policies or commit to behavioral changes to reduce GHG emissions. Factors such as trust in GCC information which need to be considered in future climate change communication efforts are also dealt with in this dissertation. This study has identified several aspects that need to be considered in future communication programs. GCC is characterized by high uncertainties, unfamiliar risks, and other characteristics of hazards which make personal connections, responsibility and engagement difficult. Communication efforts need to acknowledge these obstacles, build up trust and motivate the public to be more engaged in reducing GCC by emphasizing the multiple benefits of many policies outside of just reducing GCC. Levels of skepticism among the public towards the reality of GCC as well as the trustworthiness and sufficien-cy of the scientific findings varies by country. Thus, communicators need to be aware of their audience in order to decide how educational their program needs to be.
ContributorsHagen, Bjoern (Author) / Pijawka, David (Thesis advisor) / Brazel, Anthony (Committee member) / Chhetri, Netra (Committee member) / Guhathakurta, Subhrajit (Committee member) / Arizona State University (Publisher)
Created2013
Description
This research addresses human adaptive decisions made at the Pleistocene-Holocene transition - the transition from the Last Glacial Maximum (LGM) to the climate regime in which humankind now lives - in the Mediterranean region of southeast Spain. Although on a geological time scale the Pleistocene-Holocene transition is the latest in a series of widespread environmental transformations due to glacial-interglacial cycles, it is the only one for which we have a record of the response by modern humans. Mediterranean Spain lay outside the refugium areas of late Pleistocene Europe, in which advancing ice sheets limited the land available for subsistence and caused relative demographic packing of hunter-gatherers. Therefore, the archaeological records of Mediterranean Spain contain more generally applicable states of the Pleistocene-Holocene transition, making it a natural laboratory for research on human adaptation to an environmental transformation. Foragers in Mediterranean Spain appear to have primarily adapted to macroclimatic change by extending their social networks to access new subsistence resources and by changing the mix of traditional relationships. Comparing faunal records from two cave sites near the Mediterranean coast with Geographic Information System (GIS) reconstructions of the coastal littoral plain from the LGM to the Holocene indicates the loss of the large ungulate species (mainly Bos primigenius and Equus) at one site coincided with the associated littoral disappearing due to sea level rise in the late Upper Paleolithic. Farther north, where portions of the associated littoral remained due to a larger initial mass and a more favorable topography, the species represented in the faunal record were constant through time. Social boundary defense definitions of territory require arranging social relationships in order to access even this lightly populated new hunting area on the interior plain. That the values of the least-cost-paths fit the parameters of two models equating varying degrees of social alliance with direct travel distances also helps support the hypothesis that foragers in Mediterranean Spain adapted to the consequences of macroclimatic change by extending their social networks to gain access to new subsistence resources Keeping these relationships stable and reliable was a mitigating factor in the mobility patterns of foragers during this period from direct travel to more distant down-the-line exchange. Information about changing conditions and new circumstances flowed along these same networks of social relationships. The consequences of climate-induced environmental changes are already a concern in the world, and human decisions in regard to future conditions are built upon past precedents. As the response to environmental risk centers on increasing the resilience of vulnerable smallholders, archaeology has an opportunity to apply its long-term perspective in the search for answers
ContributorsSchmich, Steven A (Author) / Clark, Geoffrey A. (Thesis advisor) / Barton, Michael (Thesis advisor) / Bearat, Hamdallah (Committee member) / Jochim, Michael A. (Committee member) / Arizona State University (Publisher)
Created2013
Description
The implications of a changing climate have a profound impact on human life, society, and policy making. The need for accurate climate prediction becomes increasingly important as we better understand these implications. Currently, the most widely used climate prediction relies on the synthesis of climate model simulations organized by the Coupled Model Intercomparison Project (CMIP); these simulations are ensemble-averaged to construct projections for the 21st century climate. However, a significant degree of bias and variability in the model simulations for the 20th century climate is well-known at both global and regional scales. Based on that insight, this study provides an alternative approach for constructing climate projections that incorporates knowledge of model bias. This approach is demonstrated to be a viable alternative which can be easily implemented by water resource managers for potentially more accurate projections. Tests of the new approach are provided on a global scale with an emphasis on semiarid regional studies for their particular vulnerability to water resource changes, using both the former CMIP Phase 3 (CMIP3) and current Phase 5 (CMIP5) model archives. This investigation is accompanied by a detailed analysis of the dynamical processes and water budget to understand the behaviors and sources of model biases. Sensitivity studies of selected CMIP5 models are also performed with an atmospheric component model by testing the relationship between climate change forcings and model simulated response. The information derived from each study is used to determine the progressive quality of coupled climate models in simulating the global water cycle by rigorously investigating sources of model bias related to the moisture budget. As such, the conclusions of this project are highly relevant to model development and potentially may be used to further improve climate projections.
ContributorsBaker, Noel C (Author) / Huang, Huei-Ping (Thesis advisor) / Trimble, Steve (Committee member) / Anderson, James (Committee member) / Clarke, Amanda (Committee member) / Calhoun, Ronald (Committee member) / Arizona State University (Publisher)
Created2013
Description
Investments in climate science come with an expectation of social benefit. Science policy--decision processes through which individuals and organizations support, manage, and evaluate research--plays an important role in determining those outcomes. Yet the details of how climate science policy actually works have received very little attention amid academic and policy-focused discussions of climate science. This dissertation examines climate science policy with particular attention to how it supports "public values" that justify research investments. It is widely recognized funding for climate science in the US has advanced knowledge considerably in recent decades but failed to produce useful information for decision makers. In Chapter 2, I use a methodological approach known as Public Value Mapping (PVM) to investigate this failure of the science policy system. My results show that science funding institutions have been ineffective at guiding climate science toward desired outcomes because of problematic, but common assumptions about the links between science and societal benefit. The remaining chapters look more closely at the implications of these tacit assumptions, which are held by individuals, and embedded in the organizations that implement climate science policy. Chapter 3 examines the notion that prediction is essential to climate science. Wide acceptance of the "prediction imperative" limits the scope of climate science policy. Chapter 4 examines the interplay of values and assumptions in two recently established organizations in Australia, each supporting research on climate change adaptation. In Chapter 5 I document a widespread assumption in the climate science literature that agreement among multiple models should bolster confidence in their results. This can only be correct if the models are independent of one another. Climate scientists have not demonstrated this to be true, nor have they offered a plausible framework for doing so. This dissertation adds an important dimension to our understanding of how climate science knowledge is produced, while offering constructive and practical recommendations to science policy decision makers working in government programs that fund climate science. Insight from these chapters suggests that an explicit and reflexive focus on values in science policy can be helpful to organizations pursuing science policy innovation.
ContributorsMeyer, Ryan McLaren (Author) / Sarewitz, Daniel (Thesis advisor) / David, Guston (Committee member) / Andrew, Hamilton (Committee member) / Clark, Miller (Committee member) / Roger, Pielke Jr (Committee member) / Arizona State University (Publisher)
Created2010
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
This study uses the Weather Research and Forecasting (WRF) model to simulate and predict the changes in local climate attributed to the urbanization for five desert cities. The simulations are performed in the fashion of climate downscaling, constrained by the surface boundary conditions generated from high resolution land-use maps. For each city, the land-use maps of 1985 and 2010 from Landsat satellite observation, and a projected land-use map for 2030, are used to represent the past, present, and future. An additional set of simulations for Las Vegas, the largest of the five cities, uses the NLCD 1992 and 2006 land-use maps and an idealized historical land-use map with no urban coverage for 1900.
The study finds that urbanization in Las Vegas produces a classic urban heat island (UHI) at night but a minor cooling during the day. A further analysis of the surface energy balance shows that the decrease in surface Albedo and increase effective emissivity play an important role in shaping the local climate change over urban areas. The emerging urban structures slow down the diurnal wind circulation over the city due to an increased effective surface roughness. This leads to a secondary modification of temperature due to the interaction between the mechanical and thermodynamic effects of urbanization.
The simulations for the five desert cities for 1985 and 2010 further confirm a common pattern of the climatic effect of urbanization with significant nighttime warming and moderate daytime cooling. This effect is confined to the urban area and is not sensitive to the size of the city or the detail of land cover in the surrounding areas. The pattern of nighttime warming and daytime cooling remains robust in the simulations for the future climate of the five cities using the projected 2030 land-use maps. Inter-city differences among the five urban areas are discussed.
The study finds that urbanization in Las Vegas produces a classic urban heat island (UHI) at night but a minor cooling during the day. A further analysis of the surface energy balance shows that the decrease in surface Albedo and increase effective emissivity play an important role in shaping the local climate change over urban areas. The emerging urban structures slow down the diurnal wind circulation over the city due to an increased effective surface roughness. This leads to a secondary modification of temperature due to the interaction between the mechanical and thermodynamic effects of urbanization.
The simulations for the five desert cities for 1985 and 2010 further confirm a common pattern of the climatic effect of urbanization with significant nighttime warming and moderate daytime cooling. This effect is confined to the urban area and is not sensitive to the size of the city or the detail of land cover in the surrounding areas. The pattern of nighttime warming and daytime cooling remains robust in the simulations for the future climate of the five cities using the projected 2030 land-use maps. Inter-city differences among the five urban areas are discussed.
ContributorsKamal, Samy (Author) / Huang, Huei-Ping (Thesis advisor) / Anderson, James (Thesis advisor) / Herrmann, Marcus (Committee member) / Calhoun, Ronald (Committee member) / Myint, Soe (Committee member) / Arizona State University (Publisher)
Created2015
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