Indoor air quality has become an important health concern due to the number of indoor pollutants and the realization that even minimal exposures to volatile organic compounds may produce direct or indirect adverse health outcomes. Young people are most vulnerable to these poisonous chemicals as they spend much of their times indoors at homes, schools, nurseries and in day care centers. Exposure to volatile organic compounds indoors has been related to asthma and other respiratory symptoms. The adverse effects of air pollution on respiratory health in South Durban have been described in a number of studies. In 2000, a study in the South Durban Basin at Settlers Primary School demonstrated both a high prevalence of respiratory diseases amongst schoolchildren as well as an association between ambient air pollutants and other adverse health outcomes. The South Durban Health Study subsequently undertook a health risk assessment and an epidemiological study investigating this association further on behalf of the eThekwini Municipality. The study highlighted that relatively moderate ambient concentration of N02, NO, PMIO and S02 were strongly and significantly associated with a reduction in lung function among children with persistent asthma. Moreover, attending primary school in South Durban was significantly associated with increased risk from persistent asthma when compared to schools in North Durban. METHODS The descriptive study measured the total volatile organic compound levels within selected homes and schools of asthmatic children in South and North Durban. Recommendations for reducing or mitigating indoor total volatile organic compound exposures were made. The study involved a secondary analysis of data obtained from the South Durban Health Study. The monitoring for total volatile organic compounds within homes and classrooms was undertaken using passive samplers during a 72-hour period and analyzed using a gaschromatography/ mass spectrometry method. Temperature and humidity was assessed using temperature and humidity sensors. Statistical analysis was performed using SPSS version 13. The dataset comprised 140 total volatile organic compound samples from homes and 14 from classrooms. Total volatile organic compounds were measured in microgram per cubic meter (g/m3), temperature in degrees Celsius and relative humidity in percentage of moisture. RESULTS Total volatile organic compounds with levels in households ranging from 17g/m3 to 1440g/m3 and in classrooms ranging from 48g/m3 to 5292g/m3 were measured. The mean levels detected were significantly different in homes and classrooms / Thesis (MMed.)-University of KwaZulu-Natal, Durban, 2008.

There is increasing recognition of the links between air pollution and human health. Epidemiological studies have shown that there are numerous air pollutants that are associated with indoor energy use and with the production processes of industries, and most represent some sort of health implication. However, in-depth and fundamental knowledge of the health impact relationship of most pollutants is limited. This research evaluates the socio-economic and spatial aspects of the health implications of air pollution in Richards Bay (located 200 km north of Durban), KwaZulu-Natal. The research explores community perceptions and complaints relating to human health impacts emanating from air pollution in Richards Bay. The research is informed by a multi-conceptual framework (political economy incorporating political ecology, place perspectives and environmental justice) which influenced the methods chosen in conducting the research. Standard quantitative and qualitative methods were employed in the study to generate data relating to the research objectives. The process of triangulation which is the use of multiple methods that cuts across the qualitativequantitative divide was used. The various sources of information validate and clarify data by deepening and widening an understanding of the main issues under examination. The research was implemented in various communities in Richards Bay that reflect socioeconomic differences, which contributes significantly to ascertain whether health impacts are differentially experienced by different socio-economic groups. Furthermore, the research cross-tabulated experiences, perceptions and coping strategies of different socio-economic groups in the area, especially in relation to upper, middle and lower income clusters. The spatial aspect of the research (mapping of key social and health variables) is a major contribution of this research, which draws from the field of medical geography. Information on the main residential areas was illicitied from documents providing background details on Richards Bay. A purposive sampling approach was adopted to identify the seven communities, namely, Alton, Aquadene/ Brackenham, Arboretum, Meer-en-See, Empangeni Rail, Nseleni and Umhlathuze. Simple random point sampling was used to identify the households within the communities. The number of households in each community was determined using proportionate sampling. Four hundred and seventy nine housholds (479) were interviewed which was deemed to be a statistically relevant sampling size at a 95% confidence level. The study findings indicate that the lower income areas (Nseleni, Empangeni Rail and Umhlathuze) and the middle income areas (Aquadene/ Brackenham and Arboretum) have a more youthful population with a significant number being children, while the upper income areas (Alton and Meer en See) have a more elderly population. A similar trend was also found in relation to household size. There are clearly major variations in household income and employment types in Richards Bay, linked in part to the geographical location of communities based on economic and racial groups. Lower earning respondents were located mostly in the lower status areas which were classified as predominantly African populated areas as per the historical race classification and apartheid segregated areas. More than half of the respondents indicated that industrial smoke was the cause of their present health conditions. Other stated reasons were wide ranging and therefore there was no discernible pattern that emerged in relation to the causes for poor health experienced by the affected household member. However, the data did show that more respondents living in middle/ upper income areas identified causes. Reported health conditions include allergies (30.9%), coughing (29.8%), wheezing (25.5%), chest pains (18.4%) and asthmatic bronchitis/ asthma (17.7%). With regards to health care, the findings from the study show that the economically better off communities (Alton, Aquadene/ Brackenham, Arboretum and Meer en See) used the private, more expensive health care sector while generally households in lower income areas tend to rely on public or traditional health care facilities. An interesting finding was that most respondents rate their general health status as either excellent, good (more respondents from the middle/ upper income areas than the lower income areas) or satisfactory (more respondents from Umhlathuze). A large majority of the respondents reported air pollution as the main problem that is associated with industries in Richards Bay while the health impacts of pollutants from the industries manufacturing processes was the second main cause. The areas deemed to be the most polluted were generally in or in close proximity to the industrial area or the port area. Lower income areas tendered to be most polluted, according to respondents residing in these areas or who lived in similar low income areas. The majority of respondents were found to be living in dwellings/ households made from dwellings constructed with brick and asbestos, brick and zinc, stone and other traditional materials which is indicative of housing in the poorer communities who live in informal dwellings/ households and may be a causal contributing factor of the poor health status of these communities. The participatory mapping exercise conducted during the focus group discussion revealed that participants identified the industrial areas (including the port and surrounds) as the most polluted areas. Areas outside Richards Bay were considered to be the least polluted areas. The research findings indicate that there are a complex mix of socio-economic, environmental and spatial dynamics that influence air pollution and health impacts. Thus, health issues in the context of widespread air pollution concerns are linked to social, political and environmental aspects that require urgent attention. Air pollution and health impacts remain major concerns in many parts of the world, especially in areas of high levels of industrial development such as Richards Bay. The results of this research, therefore supports the findings of other researchers who reveal that communities/ neighborhoods of lower income status are most likely to bear the brunt of negative impacts and that air pollution from indoor uses of energy, behavioral factors such as cigarette smoking and industrial processes contribute to an individual’s/ community’s quality of life. / Thesis (Ph.D.)-University of KwaZulu-Natal, Durban, 2013.

Recent and past events in the South Durban Basin (SDB) have highlighted the possible connection between perceived air pollution concerns and deteriorating health. The aim of this study is to explore how the SDB community perceives air pollution and if this can be related to some of the health problems that are experienced in these communities. The ultimate aim is to determine whether the respondents connect air pollution to specific illnesses and also how they perceive the actions used to combat air pollution and its negative health impacts. This information is gathered through a questionnaire conducted in various study areas both within and outside the SDB, then compared with demographic variables. This is done to determine if perception is related to direct industrial activity or if there are other factors influencing results. Variables such as race and level of education had little impact on the results. The results showed that areas within the SDB experience a high neighborhood satisfaction despite the current general belief of air pollution being connected to ill health. The control areas outside of the SDB support theories of gender and race and its relationship to air pollution, currently presented by researchers in the perception field. Strong associations’ do exist between general environmental satisfaction and gender. Perception of current legal enforcement is exerting a strong effect on air pollution perception formation. Vitally important is the connection of daily concrete experiences of air pollution with the lack of transparency and communication between industry and communities. It is resulting in the current perception of illness being connected to tangible air pollution. The aim is to further future studies on establishing links between health and air quality. Gaining insight from the study of public risk perceptions based on local knowledge and experience in particular places, will help shape the role of environmental policy and management response systems. / Geography / M.A. (Geography)

研究背景：顆性空氣污染物（PM₁₀）的危害作用已經為許多病學研究所證實。有學者認為，空氣動學直徑小於2.5 微米的細顆（PM₂.₅）和空氣動學直徑介於2.5 和10 微米之間的粗顆（PMc）屬於種同的污染物，應當分別測。區分粗、細顆的健康效應將為今後分別制訂有關粗、細顆的空氣質標準提供依據。同時，空氣污染物是由顆污染物和氣態污染物構成的複雜混合物，二者之間存在一定程上的合或交互作用。 / 研究目的：以每天心血管系統、呼吸系統疾病急性入院人為研究結局，區別估計顆污染物PM₁₀ 中粗、細顆的健康危害作用，并探討PM₁₀與氣態污染物（二氧化氮，NO₂；二氧化，SO₂；臭氧，O₃）的交互作用。 / 研究方法：收集香港1998 1 月至2007 12 月每天心腦血管疾病、呼吸系統疾病急性入院人，日均污染物濃，日均氣溫、相對濕等資，採用時間序分析的研究方法，應用Poisson 廣義相加模型分析顆污染物中粗、細顆的同健康效應。同時應用三個平的時間序研究模型（雙變反應面模型、合效應模型和分層模型）探討顆污染物和氣態污染物之間潛在的交互作用。 / 研究結果：研究發現，在校正PM₂.₅的影響后，PMc 對呼吸系統疾病導致的急性入院作用顯著，但對心腦血管疾病引起的急性入院則無明顯作用。在雙污染物（PMc 和PM₂.₅）模型中，空氣中每一個IQR（四分位間距）的PM[subscript c] 和PM₂.₅濃的增加將使每天急性呼吸系統疾病入院分別增加1.05% (95% CI: 0.19%, 1.91%)和1.81% (95% CI: 0.78%,2.87%)，使急性心腦血管疾病入院分別改變 -0.16% (95% CI: -1.07%,0.76%) 和1.86% (95% CI: 0.85%, 2.88%)。研究發現某種程6 的顆污染物和氣態污染物的交互作用。在NO₂ 或SO₂ 高水平（NO₂ 濃高於64.4μg/m³ 或 SO₂ 濃高於20.9μg/m³）的日子，PM₁₀ 對急性心臟疾病入院的影響高於NO₂ 或SO₂ 低、中水平的日子；而在臭氧高水平（O₃濃高於46.8μg/m³）的日子，PM₁₀ 對急性呼吸和循環系統疾病入院的作用低於O₃ 中、低水平的日子。 / 研究結：粗、細顆污染物對呼吸系統疾病的危害均作用顯著且相對獨，但對循環系統疾病的危害作用則主要體現於細顆污染物。同時，顆性污染物的健康危害可能被空氣中的氣態污染物水平所修飾：研究發現PM₁₀ 與NO₂ 或SO₂ 之間的協同作用，以及PM₁₀ 與O₃ 之間的拮抗作用。 / BACKGROUND: The adverse effects of particulate matter (PM) air pollution have been confirmed by many epidemiological studies. Fine and coarse particles should be considered as separate classes of pollutants and measured separately. Differentiating the effects of fine (PM₂.₅, particles with an aerodynamic diameter less than 2.5 microns) and coarse particles (PM[subscript c], particles with an aerodynamic diameter between 2.5 and 10 microns) would help in the future to support a PM[subscript c] standard. Meanwhile, ambient air pollution is a complex mixture of PM and gaseous pollutants. PM might interact with gaseous pollutants to affect the population health. / STUDY OBJECTIVES: To differentiate the effects of fine and coarse fractions of PM₁₀ and to explore the possible interaction between PM₁₀ and gaseous pollutants (nitrogen dioxide, NO₂; sulfur dioxide, SO₂; ozone, O₃) on emergency hospital admissions for cardio-respiratory diseases in Hong Kong. / METHODS: This is a time series study. Daily counts of emergency hospital admissions for cardio-respiratory diseases, daily mean air pollution concentrations and weather conditions were collected from January 1998 to December 2007 in Hong Kong. We used generalized additive Poisson model with log link allowing overdispersion and autocorrelation to examine the differential effects of PM₂.₅ and PM[subscript c]. Three parallel time series approaches (bivariate response surface model, joint effect model and parametric stratified model) were used to explore the possible interactions between PM₁₀ and gaseous pollutants. / MAIN RESULTS: The associations between PM[subscript c] and emergency hospital admissions were statistically significant for respiratory diseases but not for circulatory diseases. In two-pollutant (PM₂.₅and PM[subscript c]) model, an interquartile range increase in the 4-day moving average (lag₀₃) concentrations of PM[subscript c] and PM₂.₅ corresponded to 1.05% (95% CI: 0.19%, 1.91%) and 1.81% (95% CI: 0.76%, 2.87%) increase of respiratory admissions, respectively. The effect estimates of PM₂.₅and PM[subscript c] remained robust when adjusting for gaseous pollutants. Meanwhile, an interquartile range increase in lag₀₁ concentrations of PM[subscript c] and PM₂.₅was associated with -0.16% (95% CI: -1.07%, 0.76%) and 1.86% (95% CI: 0.85%, 2.88%) change of circulatory admissions, respectively. Some interactions between PM₁₀ and gaseous pollutants were found. The effects of PM₁₀ on circulatory hospitalizations were greatest during the days when NO₂ or SO₂ concentrations were high (the 3rd tertile, NO₂>64.4 or SO₂>20.9μg/m³). The effects of PM₁₀ on both respiratory and circulatory admissions were greatest during the days when O₃ concentrations were in low to medium levels (<=46.8μg/m³). / CONCLUSION: We found PM[subscript c] to be associated with emergency hospital admissions for respiratory diseases independent of the effect of PM₂.₅, but not for circulatory diseases in Hong Kong. The effects of PM₁₀ on cardio-respiratory hospital admissions were modified by gaseous pollutants. There were synergetic interactions between PM₁₀ and NO₂ or SO₂ on cardiac hospitalizations and antagonistic interactions between PM₁₀ and ozone on cardio-respiratory hospitalizations. These findings provide supportive evidence for a future PM[subscript c] regulation and contribute to the development of a multipollutant air quality management. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Qiu, Hong = 顆粒污染物對人群健康的短期效應 : 時間序列研究 / 邱宏. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 122-137). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Qiu, Hong = Ke li wu ran wu dui ren qun jian kang de duan qi xiao ying : shi jian xu lie yan jiu / Qiu Hong. / Abstract (English) --- p.v / Abstract (Chinese) --- p.viii / List of Contents --- p.x / List of Tables --- p.xiv / List of Figures --- p.xvi / List of Abbreviation --- p.xviii / Acknowledgements --- p.xix / Chapter Chapter 1 --- Introduction --- p.1 / Chapter Chapter 2 --- Literature Review --- p.5 / Chapter 2.1. --- Review on the differential health effects of fine and coarse particles --- p.5 / Chapter 2.1.1 --- A brief description of particulate matter air pollution --- p.5 / Chapter 2.1.2 --- The objective of this part of literature review --- p.7 / Chapter 2.1.3 --- Methods --- p.8 / Chapter 2.1.3.1 --- Inclusion and exclusion criteria of studies/papers --- p.8 / Chapter 2.1.3.2 --- Search terms and keywords --- p.9 / Chapter 2.1.3.3 --- Information abstracted --- p.9 / Chapter 2.1.4 --- Results --- p.10 / Chapter 2.1.4.1 --- Short-term effects of PM₂.₅and PM[subscript c] on mortality --- p.10 / Chapter 2.1.4.2 --- Short-term effects of PM₂.₅and PM[subscript c] on morbidity --- p.14 / Chapter 2.1.4.3 --- Biological mechanisms underlying the differential effects of PM₂.₅and PM[subscript c] --- p.18 / Chapter 2.1.5 --- Conclusion remarks --- p.19 / Chapter 2.1.5.1 --- Health effects of PM₂.₅and PM[subscript c] on mortality --- p.19 / Chapter 2.1.5.2 --- Health effects of PM₂.₅and PM[subscript c] on morbidity --- p.20 / Chapter 2.2. --- Review on the joint effects/interactions of particulate matter and gaseous pollutants --- p.21 / Chapter 2.2.1 --- Concept of Interaction --- p.21 / Chapter 2.2.2 --- The objective of this part of literature review --- p.21 / Chapter 2.2.3 --- Methods --- p.22 / Chapter 2.2.3.1 --- Search terms and key words --- p.22 / Chapter 2.2.3.2 --- Information abstract --- p.22 / Chapter 2.2.4 --- Results --- p.23 / Chapter 2.2.4.1 --- Studies on the interaction between particulate matter and gaseous pollutants --- p.23 / Chapter 2.2.4.1.1 --- Studies on the interaction between PM₁₀ and NO₂ --- p.23 / Chapter 2.2.4.1.2 --- Studies on the interaction between PM₁₀ and O₃ --- p.24 / Chapter 2.2.4.1.3 --- Studies on the interaction between PM and SO₂ --- p.26 / Chapter 2.2.4.1.4 --- Modifiers identified through multicity study --- p.30 / Chapter 2.2.4.2 --- Methodology used to detect interaction in time series studies --- p.33 / Chapter 2.2.4.2.1 --- Nonparametric bivariable response surface model --- p.33 / Chapter 2.2.4.2.2 --- Non-stratification interaction model --- p.34 / Chapter 2.2.4.2.3 --- Parametric stratified model --- p.34 / Chapter 2.2.4.2.4 --- Time series classification and regression tree (CART) model --- p.35 / Chapter 2.2.4.3 --- Biological mechanisms of interaction between pollutants --- p.36 / Chapter 2.2.5 --- Conclusion remarks --- p.38 / Chapter Chapter 3 --- Differential health effects of fine and coarse particles --- p.39 / Chapter 3.1 --- Objectives --- p.39 / Chapter 3.2 --- Materials and Methods --- p.39 / Chapter 3.2.1 --- Data on particulate pollutants and meteorology variables --- p.39 / Chapter 3.2.2 --- Data on emergency hospital admissions for cardio-respiratory diseases --- p.40 / Chapter 3.2.3 --- Statistical models --- p.42 / Chapter 3.2.3.1 --- Core model set up --- p.42 / Chapter 3.2.3.2 --- Single-pollutant and two-pollutant models --- p.44 / Chapter 3.2.3.3 --- Concentration-response relationship --- p.45 / Chapter 3.2.3.4 --- Sensitivity analysis --- p.46 / Chapter 3.3 --- Results --- p.47 / Chapter 3.3.1 --- Location of Tsuen Wan station, Tsuen Wan region --- p.47 / Chapter 3.3.2 --- Air pollution concentrations and meteorological factors --- p.47 / Chapter 3.3.3 --- Emergency hospital admissions for cardio-respiratory diseases --- p.50 / Chapter 3.3.4 --- Regression results and Sensitivity analysis --- p.51 / Chapter 3.3.4.1 --- Effects of coarse particulate matter on emergency hospital admissions for respiratory diseases --- p.51 / Chapter 3.3.4.2 --- Differential effects of fine and coarse particles on emergency hospital admissions for cardiovascular diseases --- p.56 / Chapter 3.4 --- Discussion --- p.61 / Chapter 3.4.1 --- Main findings of this study --- p.61 / Chapter 3.4.2 --- Compared with findings from the literature --- p.62 / Chapter 3.4.3 --- Exposure windows selection and possible misclassification --- p.64 / Chapter 3.4.4 --- Sensitivity analyses of main findings --- p.65 / Chapter 3.4.5 --- Biological mechanisms of the differential effects of fine and coarse particles --- p.67 / Chapter 3.4.6 --- Limitations of this study --- p.68 / Chapter 3.5 --- Conclusion and recommendations --- p.69 / Chapter Chapter 4 --- Joint effects/Interactions of PM₁₀ and gaseous pollutants --- p.70 / Chapter 4.1 --- Objectives --- p.70 / Chapter 4.2 --- Materials and Methods --- p.70 / Chapter 4.2.1 --- Data on air pollution and meteorology variables --- p.70 / Chapter 4.2.2 --- Data on emergency hospital admissions for cardio-respiratory diseases --- p.71 / Chapter 4.2.3 --- Statistical models --- p.72 / Chapter 4.2.3.1 --- Core model set up --- p.72 / Chapter 4.2.3.2 --- Three parallel time series models --- p.73 / Chapter 4.3 --- Results --- p.76 / Chapter 4.3.1 --- Air pollution concentrations and meteorological factors --- p.76 / Chapter 4.3.2 --- Emergency hospital admissions for cardio-respiratory diseases --- p.79 / Chapter 4.3.3 --- Results from single-pollutant model --- p.81 / Chapter 4.3.3.1 --- Pollution effects on emergency hospital admissions for respiratory diseases --- p.81 / Chapter 4.3.3.2 --- Pollution effects on emergency hospital admissions for circulatory diseases --- p.83 / Chapter 4.3.4 --- Joint effects/Interactions between PM₁₀ and NO₂ on cardio-respiratory hospitalizations --- p.85 / Chapter 4.3.5 --- Joint effects/Interactions between PM₁₀ and O₃ on cardio-respiratory hospitalizations --- p.91 / Chapter 4.3.6 --- Joint effects/Interactions between PM₁₀ and SO₂ on cardio-respiratory hospitalizations --- p.96 / Chapter 4.4 --- Discussion --- p.102 / Chapter 4.4.1 --- Main findings --- p.102 / Chapter 4.4.1.1 --- Effect estimates compared with previous Hong Kong studies --- p.102 / Chapter 4.4.1.2 --- Interactions between particulate matter and gaseous pollutants --- p.103 / Chapter 4.4.1.2.1 --- Interactions between PM₁₀ and NO₂ on cardiac hospitalizations --- p.103 / Chapter 4.4.1.2.2 --- Interactions between PM₁₀ and O₃ on cardio-respiratory hospitalizations --- p.109 / Chapter 4.4.1.2.3 --- Interactions between PM₁₀ and SO₂ on cardiac hospitalizations --- p.113 / Chapter 4.4.2 --- Strengths and limitations of this study --- p.116 / Chapter 4.5 --- Conclusion and recommendations --- p.119 / Chapter Chapter 5 --- Concluding remarks --- p.120 / References List --- p.122 / Chapter Appendix --- Relevant Publications and Submitted/Drafted Papers --- p.138

Thesis (MTech (Environmental Health))--Cape Peninsula University of Technology, 2019. / Background: A recent review on the effects of ambient air pollution on human health in sub-Saharan Africa, specifically calls for an urgent need for more epidemiological studies in developing countries due to a lack of data in these countries. Air pollution information on exposure is important for understanding and addressing its public health impact in developing countries. In many African countries, the spatial distribution of air pollutants has not been quantified even though air pollution is a global public health risk. The main goal of the study was to quantify and compare the seasonal spatial variation of household air pollution in the 4 Western Cape neighbourhoods. Methods: Weekly indoor and outdoor measurements of Particulate Matter (PM2.5), Sulphur dioxide (SO2), Ozone (O3), Carbon monoxide (CO) and Nitrogen dioxide (NO2) were conducted at 127 households in four informal settlement areas (Khayelitsha, Marconi-Beam, Masiphumulele and Oudtshoorn) during one month each in summer and winter. PM2.5 measurements were conducted using Mesa Labs GK2.05 (KTL) cyclone with the GilAir Plus Air Sampling Pump, Gases were measured using Passam passive samplers. Statistical analyses were performed using Stata V12. Simple linear regression was used to evaluate the relationship between continuous exposure levels and the respective predictor variables. These include distance to major roads, bus routes, open grills and waste burning sites. Results: The highest average weekly outdoor PM2.5 and NO2 concentrations for summer were recorded in Milnerton (8.76 µg/m3 and 16.32 µg/m3 respectively). However, the highest average concentrations during winter for PM2.5 were recorded in Oudtshoorn (PM2.5: 16.07 µg/m3), whilst the highest NO2, was recorded in Khayelitsha (NO2: 35.69 µg/m3). SO2 levels were consistently low during both seasons. Noordhoek generally recorded the lowest average levels for all pollutants. Winter average weekly concentrations were generally higher than the levels recorded in summer for all pollutants. In a sub-sample of indoor and outdoor measurements, the results were comparable for PM2.5, NO2 and CO. However, the results of Ozone (O3) showed relatively higher (~10 times) outdoor compared to indoor levels. Linear regression modelling results revealed that significant predictors of elevated exposure to PM2.5 were proximity to construction activities and open grills. Analysis demonstrated a clear dose-response relationship with distance, with open grills within 1000m associated with a 0.33 µg/m3 increase in PM2.5 to 6.77 µg/m3 at a distance of 25 meters. Results from the linear regression modelling revealed that significant predictors of exposure to NO2 were proximity to rapid transport bus stops, bus routes, taxi routes and major routes. Distance to rapid transport bus stops demonstrated an increase in NO2 between 0.09 µg/m3 (at 1km) to 2.16 µg/m3 (at 50m) during summer. A similar pattern was observed for taxi routes and bus routes displaying an increase of 6.26 μg/m3and 6.82 μg/m3 respectively within the proximity of 1000 meters. / MAUERBERGER Foundation Scholarship

Background: This dissertation comprises research conducted on two distinct projects. Project I focuses on the connection between household air pollution (HAP) from cooking with biomass fuels and blood pressure (BP); this research is situated in the context of a large randomized trial of a cookstove intervention in Ghana, West Africa. The setting of Project II, meanwhile, is the residential environment of New York City, where we explore temperature and humidity conditions in homes and relate these conditions to summertime heat wave risk and to the survival and transmission of respiratory viruses in the winter. Although these projects are quite distinct, each relates to the complex relationship between climate change and health. Reducing HAP to improve health (the focus of Project I) will simultaneously reduce climate change through a reduction in emissions of short-lived climate pollutants into the atmosphere. Meanwhile, furthering our understanding of heat and humidity levels inside urban residences (the focus of Project II) is crucial to our ability to protect health in light of projections for a changing climate. Domestic activities associated with heating, cooling, and cooking are thus very relevant both to human health and to climate change mitigation and adaptation. Objectives and Methods: Our overall objective for Project I was to investigate exposure- response relationships between HAP and BP in a cohort of pregnant women taking part in the Ghana Randomized Air Pollution and Health Study (GRAPHS). We first explored this association in a cross-sectional study (Chapter 1), in which we used 72-hour personal monitoring to ascertain levels of exposure among the GRAPHS women to carbon monoxide (CO), one of the pollutants emitted by traditional wood-fed cooking fires. These exposure data were collected at enrollment into the GRAPHS study, prior to the initiation of cooking with improved cookstoves. We investigated the association between these “baseline” CO exposure levels and the women’s blood pressure at enrollment into GRAPHS. A limitation of this study was that BP was only measured once. We followed this with a second study of 44 women drawn from the same cohort (Chapter 2), for whom we designed BP protocols using 24-hour ambulatory blood pressure monitoring (ABPM), the current gold standard for clinical diagnosis of hypertension. As we were not aware of any prior research in Africa that had employed ABPM, we also designed a parallel BP protocol using home blood pressure monitoring (HBPM) equipment for comparison with ABPM. The use of ABPM with concurrent personal CO monitoring enabled us to investigate hourly associations between CO exposure and changes in BP. We also evaluated BP in these women both before and after the cookstove intervention; this allowed us to investigate whether any changes in BP were associated with switching to an improved cookstove. Our objectives for Project II were to understand the distribution of temperature and humidity conditions in a range of New York City homes during the summer and winter seasons, to evaluate the impact of structural and behavioral factors (e.g. building size, use of air conditioning, and use of humidifiers) on these conditions, and to build models that could help predict indoor conditions from more readily available outdoor measurements. We conducted this research in two ways. We first analyzed a set of indoor temperature and humidity measurements that were collected in 285 New York City apartments during portions of summers 2003-2011 and used these data to simulate indoor conditions during two heat wave scenarios, one of which was more moderate and the other of which was more extreme (Chapter 3). Second, we designed and conducted a new study in which temperature and humidity were monitored in a set of 40 NYC apartments between 2013 and 2015 (Chapters 4-6). This second study enabled us extend our research into the winter season, and also to explore how factors such as air conditioning and humidifier use impacted indoor temperature and humidity. We also investigated relationships between the monitored conditions, self-reported perceptions of the indoor environment, and symptoms that were experienced among household members. Results: In the cross-sectional analysis of CO and BP in the GRAPHS cohort (Chapter 1), we found a significant positive association between CO exposure and diastolic blood pressure (DBP): on average, each 1 ppm increase in exposure to CO was associated with 0.43 mmHg higher DBP [0.01, 0.86]. A non-significant positive trend was also observed for systolic blood pressure (SBP). In our study of the acute relationship between CO exposure and BP (Chapter 2), we determined that peak CO exposure (defined as above the 90th percentile of the exposure distribution, or an average of 4.1ppm) in the two hours prior to BP measurement was associated with elevations in hourly systolic BP (4.3 mmHg [95% CI: 1.1, 7.4]) and diastolic BP (4.5 mmHg [95% CI: 1.9, 7.2]), as compared to BP following lower CO exposures. We also observed a non-significant trend toward lower BP following initiation of cooking with an improved cookstove. Lastly, we demonstrated that ABPM was a feasible and well-tolerated tool for BP assessment in a rural West African setting. For Project II in New York City, we first determined that there was a great deal of variability in indoor summer heat index (HI) between homes in association with similar outdoor conditions, and that this variability increased with increasing outdoor heat (Chapter 3). Our simulation of a moderate heat wave led us to conclude that the hottest 5% of the homes would reach peak indoor heat index (HI) values of 39°C. In a more extreme heat wave simulation, HI in the hottest 5% of homes reached a peak of 41oC and did not drop below 34oC for the entire nine- day simulated heat wave period. Our second indoor monitoring study yielded the following findings: in the summer season (Chapter 4), we found significant differences in indoor temperature and heat index according to the type of air conditioning (AC) in the home. Homes with central AC were the coolest, followed by homes with ductless AC, window AC, and no AC. Apartments on the top floor of a building were significantly hotter than other apartments regardless of the presence of AC. During the winter season (Chapter 5), median vapor pressure in our sample of apartments was 6.5mb. Comparing humidity levels in the apartments to a threshold of 10mb vapor pressure that has been proposed as protective against influenza virus transmission, levels of absolute humidity in the homes remained below this threshold for 86% of the winter: a total of over three months. Residential use of humidifiers was not associated with higher indoor humidity levels. Larger building size (above 100 units) was significantly associated with lower humidity, while the presence of a radiator heating system was non-significantly associated with higher humidity. Lastly, perceptions of indoor temperature and measured temperature were significantly associated in both the summer and the winter (Chapter 6), while sleep quality was inversely related to measured indoor temperature in the summer season only. Reports of heat- stress symptoms were associated with perceived, but not measured, temperature in the summer season. Conclusions: The work presented in this dissertation adds to a growing body of evidence on the importance of exposures in the domestic environment to health and well-being. The research reported here on household air pollution in Ghana documents an exposure-response relationship between air pollution from cookstoves and elevations in blood pressure, on both a chronic and an acute basis. As elevated BP is a known risk factor for cardiovascular disease (CVD), our research provides support for a plausible factor linking HAP exposure to CVD. Meanwhile, our research on temperature and humidity in New York City residences provides concrete data to supplement the very slim literature to date documenting these conditions in the home environment, where Americans spend over half their time. We conclude, first, that AC may not be fully protective against summertime heat risk, and second, that the levels of humidity we observed in residential environments are consistent with levels that have been shown to promote enhanced survival and transmission of respiratory viruses in experimental settings. We suggest that interventions that can reduce exposure to household air pollution and excess indoor heat can also mitigate climate change, and that with thoughtful planning we can improve health at the same time as we foster resiliency in the face of a changing climate.

Traffic is a problem across the globe, reaching perniciously into cities and communities nearly everywhere. The United States (US) has its share of traffic problems; of the ten cities with the highest traffic delay times in 2022, four were in the US. While nearly everyone living in the US has likely experienced traffic congestion of some kind, some cities are notoriously worse than others. In New York City (NYC), traffic congestion has been a problem as far back as 1913, when Fifth Avenue was so traffic-clogged it could take 40 minutes to go 23 blocks. Today, of the 25 most congested traffic corridors in the US, three are in NYC. One of these runs through the South Bronx, an environmental justice neighborhood we highlight in this dissertation. Traffic congestion is a source of air pollution (traffic-related air pollution, or TRAP) and noise, and it can result in property damage, injuries, and fatalities from collisions with other vehicles, pedestrians, or those using other forms of transportation. Both traffic congestion and TRAP have been associated with numerous negative health outcomes. For example, TRAP is associated with respiratory, cardiovascular, neurological, and pregnancy outcomes, including asthma exacerbation, incident childhood and adult asthma, reduced lung function, atherosclerosis, hypertension, stroke, myocardial infarction, cardiovascular-related mortality, cognitive decline, neurodevelopmental outcomes, pregnancy loss, term low birth weight, and small for gestational age birth. In general across the US, communities of color and higher-poverty neighborhoods face greater exposure and health burden from traffic. Throughout this dissertation, we study traffic congestion and TRAP through two lenses: (1) environmental justice; and (2) policy. Additionally, we assess the cardiovascular health impacts of TRAP. In Chapter 1, we provide background on the problem of traffic, focusing on NYC and the South Bronx. In Chapter 2, we present a case study from the South Bronx, where a new trucking-intensive warehouse was opened in 2018. In this study, we quantified the increase in vehicles and trucks following the opening of the warehouse and estimated the resulting increases in black carbon (BC) and noise. We discuss the injustice in the methods used to assess the environmental impact of the warehouse, the warehouse’s siting in a predominantly Black and Lantinx community already overburdened with trucking-intensive industries, and the desire of the community to instead use the land for a community park. In Chapter 3, we present a study quantifying how traffic congestion in NYC changed during the COVID-19 pandemic. We assess how NY on Pause, the state’s stay-at-home order, impacted traffic congestion by comparing the magnitude of traffic decreases in environmentally burdened or systematically disadvantaged neighborhoods to the magnitude of decreases in less burdened and more advantaged neighborhoods. We discuss the implications of these results for upcoming traffic policies in NYC, such as congestion pricing. In Chapter 4, we present a study evaluating diurnal changes in TRAP in NYC during NY on Pause. We discuss the implications of these results for congestion pricing, including the potential timing of TRAP decreases. In Chapter 5, we present an epidemiologic study of TRAP and myocardial infarction (MI) in New York State, identifying hazard windows of exposure in a study period where the mean nitrogen dioxide (NO₂) concentration was substantially lower than the hourly national standard. We discuss implications for the NO₂ National Ambient Air Quality Standards (NAAQS) and suggest that the current standard may be insufficient to protect population cardiovascular health. Finally, in Chapter 6, we conclude with a discussion of recommended research directions and policy considerations.