京都大学 / 新制・課程博士 / 博士(地球環境学) / 甲第24153号 / 地環博第231号 / 新制||地環||44(附属図書館) / 京都大学大学院地球環境学舎地球環境学専攻 / (主査)教授 梶井 克純, 教授 高野 裕久, 准教授 田中 周平 / 学位規則第4条第1項該当 / Doctor of Global Environmental Studies / Kyoto University / DFAM

Background: Air pollution has been associated with adverse health effects for all-cause and specific respiratory morbidity and mortality outcomes. Acute exacerbations of COPD (AE-COPD) accelerate the decline in pulmonary function and are associated with greater mortality, morbidity, health care utilization, and reduced quality of life. Since the 1970 Clean Air Act was implemented, important reductions in air pollution have been achieved, but no safe threshold has been identified. Objectives: The study was planned to evaluate associations between exposure to ambient concentrations of five criteria air pollutants (CO, SO2/, NO2/, ozone, PM2.5/) in Philadelphia, Pennsylvania, and visits to Temple University Hospital for AE-COPD, from January 1, 2005 through March 31, 2007. To identify subgroups with greater susceptibility to air pollution, associations were examined according to age, gender, race, residence, and antibiotic prescription. Methods: Average daily air pollutant concentrations were obtained from the EPA's Air Quality Services Data Mart. Air pollutant exposures were evaluated for the day of the visit (lag0), one and two days preceding the visit (lag1 and lag2), and the average concentration over three days (lag012). Poisson regression provided rate ratios (RRs) to estimate associations between air pollution exposures and AE-COPD hospital visits. Results: Of 1546 hospital visits for AE-COPD, 43% were from persons 65 years or older, 50% of each gender, and 90% from Philadelphia. In single pollutant models, increased RRs were present at all lags for NO2/ (e.g., RR = 2.27 [95%CI: 1.52, 3.38] at lag012) and SO2/ (e.g., RR = 1.70 [95%CI: 1.38, 2.08] at lag012). For PM2.5/, the direct effect was present only during the winter at lag1, lag2, and lag012 (RR = 1.79 [95%CI: 1.08, 2.96]). Inverse associations were present for ozone at all lags (e.g., RR = 0.64 [95%CI: 0.53, 0.76] at lag012). Compared to the cohort as a whole, those ≥ 65 years of age were at greater risk of an AE-COPD hospital visit associated with PM2.5/ and CO at lag012, with NO2/ and SO2/ at lag0 and lag012, but there was no difference in ozone effect. Conclusions: Primary gaseous air pollution exposures (SO2/, CO, NO2/) were associated with increased AE-COPD hospital visits among COPD patients at Temple University Hospital. The effects of SO2/, CO, NO2/, and PM2.5 were greater for the subgroup ≥ 65 years of age compared to the cohort as a whole. Inverse associations with ozone were consistent across subgroups. These results suggest that air quality during the study period was insufficient to protect the health of COPD patients, especially those ≥ 65 years old. Further study is needed to understand generalizability to other populations and to evaluate lower ranges of exposure from current levels of air pollution. / Public Health

Increasing levels of air pollution are prompting researchers to develop more reliable air pollution modeling approaches in order to protect the public and the environment from toxic contaminants and airborne pathogens. Although land use regression has long been used to assess exposure to air pollution, researchers are increasingly using machine learning algorithms to quantify the concentration of harmful pollutants—for this study black carbon (BC) and particle number (PN). Additionally, researchers are moving away from using fixed-site data in favor of using mobile monitoring data in a variety of locations to develop hourly empirical models of particulate air pollution. This study uses secondary data describing BC and PN pollutant levels, which are obtained from roads that bikers share in the more rural location of Blacksburg (VA). Machine learning (ML) algorithms are then built to develop accurate and reliable short-term empirical prediction models. Different pre-processing methods for the mobile monitoring data and various input variables are tested to assess how ML can be used effectively in this process. Three types of time-average models are developed (daytime, hourly average, and one second models). Various combinations of spatial and temporal input variables are used in the short-term models. The impact of adding more spatiotemporal variables (e.g., emissions) to machine learning models to improve model performance is assessed in the short-term models. Incorporating spatial and temporal autocorrelation is intended to develop more sophisticated validation approaches for identifying ML performance patterns—the goal of which is to predict concentration levels more accurately in comparison to using raw data without data reprocessing. The results show that the model developed using refined disaggregated data is able to detect the spatial distribution of the pollutant concentration at equivalent levels as the smoothed data models, although the latter display fewer errors. The performance of the short-term model including all variables is equivalent to the model omitting emissions. The ML results are compared to earlier stepwise regression model results, suggesting that ML has the ability to improve both long-term and short-term model accuracy. Our findings indicate that ML demonstrates higher predictive capacity in comparison to stepwise regression. The results from this study may be useful in enhancing the performance of ML through the incorporation of different data preprocessing tasks, as well as showing how different input variables contribute to the ML modeling process. The findings from this study could be used toward the development of environmental/eco-friendly routes that would decrease the risk for exposure to harmful vehicle-related emissions. / Doctor of Philosophy / Air pollution is a major environmental threat to human health, claiming the lives of millions of people each year, primarily as a result of fine particulate matter entering the respiratory system. As such, it is important to develop reliable and accurate air pollution modeling approaches in order to protect the public and the environment from toxic contaminants and pathogens in the air. Although an approach known as land use regression has long been used to assess exposure to air pollution, researchers are increasingly using machine learning (ML) algorithms to quantify the concentration of harmful pollutants—for this study black carbon and particle number, which is a generic assessment that captures a number of known airborne hazards. Additionally, researchers are moving away from using fixed-site data in favor of using mobile monitoring data in a variety of locations to develop hourly empirical models of particulate air pollution. In this study, machine learning algorithms are developed using secondary data collected from roads that bikers share, which are representative of pollution levels of particle number and black carbon in the more rural location of Blacksburg (VA), in order to develop accurate and reliable short-term empirical prediction models. Different pre-processing methods of the mobile monitoring data and various input variables are tested to assess how machine learning can be efficiently used in this process. Our findings indicate that machine learning demonstrates higher predictive capacity in comparison to stepwise regression. The results from this study are expected to be useful in enhancing the performance of machine learning through the incorporation of different data preprocessing tasks, as well as how different input variables contribute to the machine learning modeling process. The findings from this study could assist transportation planners and other stakeholders better assess pollution risks for bike riders and pedestrians. As such, this study's findings could be used toward the development of environmental/eco-friendly routes that would decrease the risk for exposure to harmful vehicle-related emissions.

This case study documents the entire indoor air quality (IAQ) problem experienced by the students, faculty and staff of Cowgill Hall on the campus of Virginia Polytechnic Institute and State University from August 1987 to August 1988, recommends a general IAQ solution process and makes several specific suggestions to prevent the reoccurrence of the problem in Cowgill Hall. Background information on Cowgill Hall and the indoor air quality issue are also provided. This document is addressed to students of architecture, engineering and related disciplines. It emphasizes the growing importance and possible repercussions of their design decisions on the total environment; both in and out of doors. / Master of Science

The efficacy of indoor environment evaluation is, in part, a function of the reliability and validity of the different measures used. This thesis presents results of a study, conducted in a building without known problems, which compares the reliability and validity of sensory comfort components from three well-known survey questionnaires. A review of literature reveals that sensory comfort theory draws upon many disciplines including, hedonics, psychometrics, and olfaction theory. The fundamental domains thermal, air quality, lighting, and acoustics and their dimensions are identified. The conceptual model integrates these theories underlying human response to sensory comfort. The research questions involved in the selection of survey questionnaires are explored by examining sixteen indoor environment survey questionnaires. A meta-evaluation reveals that these questionnaires have three major functions, proactive, reactive, and re-evaluative studies. Finally, the methods used to analyze survey questionnaires for reliability and validity are examined. An analysis of variance shows that the order in which questions were presented did not affect responses. The reliability of the measures tested ranged from poor to good. Examination of content and face validity by expert and untrained judges demonstrates inconsistencies in common or accepted meanings of the measures considered in evaluating the indoor environment. Analysis of construct validity indicates that not all survey questionnaire variables were categorized under their expected dimensions. Contrary to advice found in the literature, this thesis suggests that the practice of combining items from different questionnaires is problematic. Finally, in buildings with known problems we can expect a relatively high degree of reliability and validity. However, the utility of such questionnaires in inventorying and assessing buildings without known problems will prove to be questionable. / Master of Urban and Regional Planning

Grafts were made using 2-0 rootstock and scion from 12 ortets of eastern white pine (Pinus strobus L.) growing at the Radford Army Ammunition Plant (RAAP). The 12 ortets represented 4 symptom severity classes (3 ortets/class) ranging from trees with > 25% of their crowns exhibiting necrotic tipburn (Class I) to those with healthy crowns (Class IV). Grafts were made in spring 1976 and ramets were grown in a greenhouse drawing charcoal filtered air. Each treatment was performed twice, on separate days for a total of 10 ramets/clone/ treatment. Five ramets/clone were used in each 6 hour treatment. The current years growth was 7-10 weeks old when treated. The treatments were as follows: 1) 0₃-10 pphm, 2) 0₃-30 pphm, 3) NO₂-10 pphm, 4) NO₂-30 pphm, 5) 0₃-10+NO₂ -10 pphm, 6) 0₃-10+NO₂ -30 pphm, 7) no pollutant. The fumigation chamber was a modified open-top field chamber located indoors. Environmental conditions during the 14 treatments averaged: 26 C, 64% RH, and 16 Klux. The ramets were evaluated prior to fumigation and then 2, 7, and 14 days thereafter for visible symptoms. The overall injury was generally light with only 11% of the clone treatment combinations exhibiting injury on > 25% of the needle fascicles. Clones I-1 and I-2 were the most sensitive clones while clones III-1, IV-2 and to a lesser degree clones III-3 and IV-1 were tolerant. These results agree with field ratings of eastern white pine sensitivity at the RAAP and provide the first step in the development of an air pollution bioindicator system at the installation. / Master of Science

Most existing environmental chambers cannot simulate dynamically changing environmental conditions. Hence there is a need for a dynamically controlled artificial environment for plant studies. This project demonstrates the control of temperature, humidity and SO₂ concentration in a Continuous Stirred Tank Reactor (CSTR) system using feedback control through a computer. An IBM-PC was connected to the measuring instrumentation and control equipment through a data acquisition and control system. Temperature and humidity were controlled by an ON-OFF control scheme. Sulfur dioxide concentration was controlled by means of a modified proportional derivative control algorithm. The system is capable of achieving a wide range of temperatures (7°C to 40°C), humidities (30% to 97%), and SO₂ concentrations. Temperature is maintained within ±0.5°C of the desired value and humidity is controlled within ±4% of the desired value. Sulfur dioxide concentration is kept within ±10% of the desired concentration. It was found that as humidity increases, the supply rate of SO₂ must be increased to maintain a given concentration. Software response time is slow. This causes time lags in the modification of the controlled parameters to achieve desired values. The heating and cooling characteristics of the system can be improved by better insulation of the chamber walls. The system demonstrates that computerized feedback control is practical for application to controlling environmental parameters in a fumigation chamber. / Master of Science

My dissertation addresses how engineers, scientists, and bureaucrats generated knowledge about pollution, crafted an institution for environmental protection, and constructed a collective identity for themselves. I show an important shift in regulators\' priorities, from stringent health-based standards to flexible technology-based ones through the development of end-of-pipeline pollution control devices, which contributed to the emergence of economic incentives and voluntary management programs. Drawing on findings from archival documents, published sources, and oral history interviews, I examine the first decade of the EPA amid constant organizational changes that shaped the technological and managerial character of environmental policy in the United States. Exploring the EPA\'s internal research and development processes and their relationship with scientific and engineering communities sheds light on how the new fields of environmental engineering and policy were co-produced in the 1970s. I argue that two competing approaches for environmental management, a community health approach and a control technology approach, developed from EPA\'s responses to bureaucratic, geographical, and epistemic challenges. I focus on researchers and managers from the Office of Research and Development at Research Triangle Park, North Carolina, as they were engaged in (1) controversy about integrated aerometry and epidemiology research intended to correlate air pollution and health, (2) intra-agency debate about the government\'s responsibility for introducing catalytic converters for tailpipe emissions reduction and responding to the potential environmental and social consequences, and (3) inter-agency activities for the demonstration of scrubbers for smokestack emissions and further application of the control technology approach in energy-related environmental problems. My principal conceptual contribution is "regulatory engineering." I define regulatory engineering as an approach to sociotechnical problems in which engineering practices are incorporated into regulatory and organizational changes, which in turn influences technical knowledge and identity formation. As EPA activities became closely associated with energy and economic issues toward the end of the 1970s, I argue that engineers took the initiative in demonstrating and evaluating control technologies for pollution abatement and energy development, scientists carefully studied environmental and health effects of these technologies, and regulators set up pollution standards and attainment deadlines accordingly. Studying the co-production of knowledge, institution, and identity through the lens of regulatory engineering helps us to understand technoscientific and managerial aspects of environmental governance beyond the 1970s EPA where technical feasibility considerations, economic incentives, and cooperative management expanded into legislation and regulation. / Ph. D.

Exposure to ground-level ozone (O₃), which forms secondarily in the atmosphere, intensifies the risk of respiratory and cardiovascular diseases. Effective mitigation strategies require understanding the spatiotemporal variability of O₃ precursors, including nitrogen oxides (NOx) and volatile organic compounds (VOCs), as well as O₃ formation photochemistry. This thesis examines the concentrations of trace gases closely related to O₃ production, specifically nitrogen dioxide (NO₂, the dominant component of NOx) and formaldehyde (HCHO, a proxy for VOC reactivity), as well as photochemical conditions. I investigate how these factors differ on high-O₃ days, change diurnally, and respond to the temporal resolution of anthropogenic emissions. The focus is on the summer of 2018 due to the availability of trace gas retrievals from the TROPOspheric Monitoring Instrument (TROPOMI) and in situ measurements from field campaigns. I first investigate New York City (NYC) and the Baltimore/Washington D.C. area, where high O₃ levels frequently occur in summer. On high-O₃ days (when the maximum daily 8-hour average (MDA8) O₃ exceeds 70 ppb), tropospheric vertical column densities (VCDTrop) of HCHO and NO₂ increase in urban centers. The HCHO/NO2 VCDTrop ratio, proposed as an indicator of local surface O₃ production sensitivity to its precursors, generally rises due to a more pronounced increase in HCHO VCDTrop. This suggests a shift toward a more NOx-sensitive O₃ production regime that could enhance the effectiveness of NOx controls on the highest O₃ days. As retrievals of tropospheric trace gases from Low Earth Orbit (LEO) satellites like TROPOMI are limited to one overpass per day (early afternoon), I then analyze spatial variability in HCHO and NO₂ concentration diurnal patterns and connect changes in column densities with surface concentrations. Diurnal HCHO patterns indicate the impact of temperature-dependent VOC emissions, while a bimodal surface NO₂ pattern reflects diurnal patterns of local anthropogenic NOx emissions and boundary layer dynamics. Column concentration peaks generally occur about four hours after surface concentration peaks (morning for NO2 and midday for HCHO), highlighting the challenge of relating column densities to health-related surface concentrations. I also explore how the temporal resolution of anthropogenic emissions influences air pollution levels and diurnal variations. Surface NOx and O3 concentrations show different spatial patterns of change when switching from daily mean to hourly varying nitric oxide emissions. In urban areas of both the western and eastern CONUS, adding hourly NO emissions increases daytime emissions, leading to O₃ decreases, indicating NOx-saturated O₃ chemistry. In the western CONUS, monthly mean surface NO₂ increases, while in the eastern CONUS, characterized by shorter NO₂ lifetimes, NO₂ decreases. These sensitivities highlight the importance of accounting for diurnal changes when inferring emissions from concentrations. This thesis advances our understanding of O₃-NOx-VOC air pollution by exploring variations in both surface and column conditions across urban-rural gradients. It integrates in situ measurements, space-based observations, and modeling techniques and assesses advanced modeling tools for future applications. These findings support the future applications of geostationary satellite retrievals for continuous trace gas observation throughout daylight hours, supplementing the once-a-day LEO satellite data used in this thesis, with implications such as aiding source attribution and targeting cost-effective control measures for O₃ mitigation.

Since the Industrial Revolution, human society has rapidly developed and flourished. Meanwhile, some interconnected side effects, particularly in realms of water, energy, food and environment, are tackling the sustainability of society. These grand challenges are intricately interconnected, underscoring the importance of addressing these problems through the lens of the water-energy-environment (WEE) nexus, which emphasizes the interlinkages between these sectors. For instance, the unprecedented scale of CO₂ has accumulated in the atmosphere, and it has accelerated global warming and the chained environmental problems, such as droughts and floods. This insecurity for water resources has encouraged water recycling. At the same time, a new class of anthropogenic contaminants, including pharmaceutical and personal care products (PPCP), heavy metals, herbicides or pesticides, and per-fluoroalkyl substances (PFAS), have been accumulated in natural water bodies. These contaminants are called emerging contaminants, and these can potentially cause severe problems in ecology and human health. Thus, this thesis aimed to tackle these multifaceted issues by investigating the interfacial chemistries between the natural or engineered solids and aqueous phases, particularly in the context of in-situ carbon mineralization and water remediation.To mitigate climate change, we should not only reduce CO₂ emissions but also remove the previously emitted CO₂ from the air. In-situ carbon mineralization is a critical technology to meet the agenda of carbon dioxide removal from the air (CDR) as the potential capacity and offer a thermodynamically downhill reaction to store CO₂ permanently in solid form. During the in-situ carbon mineralization, water plays a pivotal role in the interactions at Rock-H₂O-CO₂ interfaces. However, the kinetics and mechanisms of interfacial reactions in the mineral-aqueous phases with various compositions still need to be fully understood. Additionally, in-situ carbon mineralization demands substantial water usage; therefore, addressing water security become imperative. However, during the water usage and recycling process, the accumulation of ions, including heavy metals, and the spreading of organic pollutants can intensify the concerns about water security. Thus, this thesis’s objectives are to focus on a fundamental understanding of reaction kinetics and mechanisms occurring at the interested interfaces to address these challenges. At the mineral-aqueous phase for in-situ carbon mineralization, the effect of parameters, such as temperature, pH, and mineralogy has been assessed for mineral dissolution in the aqueous phase, and both basalt and peridotite were investigated. Related to the dissolution kinetics, this thesis discussed the frameworks for determining the dissolution rate, which can affect our understanding of experimental results. The dissolution studies exploring the effect of various parameters related to the in-situ carbon mineralization provided valuable insights into the reactivity of feedstock and morphological alterations that can be utilized for reactive-transportation modeling. Also, the experiment results may suggest the system boundary to engineer the geological CO₂ storage process. Also, carbonation behaviors were studied in terms of direct carbonation and nucleation. For the direct carbonation, olivine mineral and peridotite rock retrieved from a potential CO₂ storage site were tested, and the effects of parameters including pH, additives, and temperature were discussed. During the in-situ carbon mineralization, dissolved cations and dissolved CO₂ can be nucleated and precipitated on the different types of mineral surfaces. Therefore, this study investigated the interfacial interactions with different types of mineral surfaces and containing ions in the aqueous phase. These studies provide the fundamental understanding of the thermodynamics and kinetics of carbonation during in-situ carbon mineralization. Lastly, this study explored the kinetics and mechanisms of adsorption at adsorbent–emerging contaminant containing fluid interfaces in regard to water remediation and recycling. In this study, biochar from waste streams and MOFs with different modifications were used for the strategical development of adsorbents, while spectroscopic analysis methods were adopted to elucidate the mechanisms. Also, the effect of coexisting ions or reusability was discussed. Further, the results and insights from this investigation can be utilized for developing future generations of adsorbents and designing the remediation process. Consequently, through understanding the various regimes of interfaces, this study may contribute to the advancement of strategic approaches for addressing the complex challenges within the WEE nexus, particularly related to sustainable in-situ carbon mineralization.