Kin-Fai Ho. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references (leaves [61-66]). / Abstracts in English and Chinese. / Contents / ACKNOWLEDGMENT / ABSTRACT / Chapter CHAPTER 1 --- INTRODUCTION / Chapter 1.1 --- Air Pollution in Hong Kong / Chapter 1.2 --- Brief introduction of Particulate Matter / Chapter 1.2.1 --- Total suspended particulates / Chapter 1.2.2 --- Respirable suspended particulates / Chapter 1.2.3 --- PM2.5 / Chapter 1.3 --- Lead in Air Particulate and its Harmful Effects on Human / Chapter 1.4 --- Air Sampling / Chapter 1.5 --- Sample Treatment / Chapter 1.5.1 --- Acid digestion method / Chapter 1.5.2 --- Slurry sampling method / Chapter 1.5.3 --- Comparison between acid digestion and slurry sampling method / Chapter 1.5.4 --- Chemical modification / Chapter CHAPTER 2 --- EXPERIMENTAL / Chapter 2.1 --- Apparatus / Chapter 2.2 --- Instrumental analysis / Chapter 2.2.1 --- Electrothermal atomic absorption spectrometry / Chapter 2.2.2 --- Background correction by the Zeeman effect / Chapter 2.3 --- Reagents / Chapter 2.4 --- Procedure / Chapter 2.4.1 --- Collection of air sample / Chapter 2.4.2 --- Treatment of sample collected on filter / Chapter 2.4.2.1 --- Digestion Procedure / Chapter 2.4.2.2 --- Procedure for Slurry Preparation / Chapter 2.4.3 --- Temperature program employed / Chapter 2.4.4 --- Sample introduction / Chapter 2.4.5 --- Determination of Lead in PM 2.5 by Acid Digestion Method / Chapter 2.4.6 --- Determination of Lead in PM 2.5 by Developed Method / Chapter 2.4.7 --- Study of particle size and suspension behavior of PM 2.5 in solvent / Chapter CHAPTER 3 --- RESULTS AND DISCUSSION / Chapter 3.1 --- Choice of filter for air sampling / Chapter 3.2 --- Choice of Solvents for Suspension of Air Particulates / Chapter 3.3 --- Ultrasonic agitation / Chapter 3.4 --- Effect of the sonication time / Chapter 3.5 --- Particle size and Effect of stabilization agents / Chapter 3.6 --- Effect of acid predigestion of the slurry sample / Chapter 3.7 --- Chemical Modification / Chapter 3.7.1 --- Use palladium as chemical modifier / Chapter 3.7.2 --- Amount of chemical modifier / Chapter 3.7.3 --- Effect of nitric acid / Chapter 3.8 --- Optimization of the graphite furnace temperature / Chapter 3.9 --- Effect of using platform / Chapter 3.10 --- Sample injection volume / Chapter 3.11 --- Recovery study of Lead in PM2.5 / Chapter 3.12 --- The limit of detection and precision of the developed method / Chapter CHAPTER 4 --- CONCLUSION / APPENDIX / REFERENCES

Congested traffic corridors in dense urban areas are key contributors to the degradation of urban air quality. While waiting at bus stops, transit patrons may be exposed to greater amounts of vehicle-based pollution, including particulate matter, due to their proximity to the roadway. Current guidelines for the location and design of bus stops do not take into account air quality or exposure considerations. This thesis provides a unique contribution to roadside air quality studies and presents an innovative method for the consideration of bus shelter placement. Exposure to roadside pollutants is estimated for transit riders waiting at three-sided bus stop shelters that either: 1) face roadway traffic, or 2) face away from roadway traffic. Shelters were instrumented with particulate matter monitoring equipment, sonic anemometers for wind speed and direction, and vehicle counters capable of categorizing vehicles by length. Temperature and relative humidity were gathered from a nearby monitoring station. Data were collected for two different days at three shelters during both the morning and afternoon peak periods for a total of eleven data periods. Bus shelter orientation is found to significantly affect concentration of four sizes of particulate matter: ultrafine particles, PM1, PM2.5, and PM10. Shelters with an opening oriented towards the roadway were observed to have significantly higher concentrations inside the shelter than outside the shelter. In contrast, shelters oriented away from the roadway were observed to have significantly lower concentrations inside the shelter than outside the shelter. The differences in average particulate matter concentrations are statistically significant across all four sizes of particulate matter studied. Additional correlation and linear regression investigation reveals interactions between particulate concentrations and built environment characteristics, vehicle flow, and weather conditions. Temperature and relative humidity played a large role in the diurnal variation of average concentration levels. In all instances, particulate concentrations were greater during the morning period, often substantially so. Particulate concentrations are shown to vary based on both wind speed and direction. Vehicle flow is correlated with particulate levels, though significance is not consistent. Lagged vehicle flow is demonstrated to be more consistently significant. Regression analysis suggests weather factors such as wind, temperature, and relative humidity explain roughly 70% of particulate variation, while vehicle flow explains less than 6%.

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

Indiana University-Purdue University Indianapolis (IUPUI) / This paper presents a novel approach of particulate material (soot) measurement in a Diesel particulate filter using Electrical Capacitance Tomography. Modern Diesel Engines are equipped with Diesel Particulate Filters (DPF), as well as on-board technologies to evaluate the status of DPF because complete knowledge of DPF soot loading is very critical for robust efficient operation of the engine exhaust after treatment system. Emission regulations imposed upon all internal combustion engines including Diesel engines on gaseous as well as particulates (soot) emissions by Environment Regulatory Agencies. In course of time, soot will be deposited inside the DPFs which tend to clog the filter and hence generate a back pressure in the exhaust system, negatively impacting the fuel efficiency. To remove the soot build-up, regeneration of the DPF must be done as an engine exhaust after treatment process at pre-determined time intervals. Passive regeneration use exhaust heat and catalyst to burn the deposited soot but active regeneration use external energy in such as injection of diesel into an upstream DOC to burn the soot. Since the regeneration process consume fuel, a robust and efficient operation based on accurate knowledge of the particulate matter deposit (or soot load)becomes essential in order to keep the fuel consumption at a minimum. In this paper, we propose a sensing method for a DPF that can accurately measure in-situ soot load using Electrical Capacitance Tomography (ECT). Simulation results show that the proposed method offers an effective way to accurately estimate the soot load in DPF. The proposed method is expected to have a profound impact in improving overall PM filtering efficiency (and thereby fuel efficiency), and durability of a Diesel Particulate Filter (DPF) through appropriate closed loop regeneration operation.