Mitigation of Greenhouse Gas Emissions from Urban Environmental Infrastructures

The world’s population will increase to 9.4 billion people by 2050 and 70% of whom will be living in urban areas. Such urbanization with population growth and industrial development demands in turn create a need for the planning, design, and construction of environmental infrastuctures (e.g., water and wastewater treatment plants: WTPs and WWTPs). The environmental infrastructures are essential to provide cities and towns with water supply, waste disposal, and pollution control services. During the operation of WTPs and WWTPs, massive amount of energy, fuels, and chemicals are consumed. Therefore, they could be major contributors to urban greenhouse gas (GHG) emissions (i.e., 17% of GHGs are generated from water and sewer sector in urban area). To make cities resilient and sustainable, the emission of GHGs from WTPs and WWTPs should be estimated as accurately as possible and effective mangement plans should be set up as soon as possible. A comprehensive model was developed to quantitatively estimate on-site and off-site GHGs generated from WTPs and WWTPs. The model was applied to an advanced WTP (treating 200,000 m³/d of raw water with micro-filtration membrane) and a hybrid WWTP (treating 5,500 m³/d of municipal wastewater with five-stage Bardenpho processes). The overall on-site and off-site GHG emissions from the advanced WTP and hybrid WWTP were 0.193 and 2.337 kgCO2e/d*m3. The major source of GHG generation in the advanced WTP was off-site GHG emissions (98.6%: production of chemicals consumed for on-site use and electricity consumed for unit-process operation). On the other hand, on-site GHG emissions related to biochemical reactions (64%) was the main GHG source of the hybrid WWTP. Reducing electricity consumption in advanced WTPs could be the best option for generating less GHG emissions and acquiring better water quality. Various options (CO2 capture and conversion to other useful materials, recovery and reused of CH4, and operation of WWTPs at optimal conditions) could significanlty reduce the total amount of GHG emissions in hybrid WWTPs. The results could be applied to the development of green and sustainable technology, leading to a change in paradigm of urban environmental infrastructure

Binary data on radiation-related brain damage prenatally exposed and statistical threshold model

Exposure to ionizing radiation has been testified to have harmful effects on the developing human brain, particularly in the highly vulnerable period of 8-15 weeks after ovulation as an incereased frequency of severe mental retardation. However, the distribution of cases of severe mental retardation suggests a threshold in the low dose region. Data are composed of a binary (1,0) for mentally retarded or normal individuals. The statistical approaches with a threshold are conceivable for a simple, odds, logistic and Gompertz regression models. Estimation of threshold and 100(1-α)% confidence limits are derived from the maximum likelihood technique based on a profile approach

n-3 and n-6 Polyunsaturated Fatty Acids and Vitamin D related to Subclinical Atherosclerois in the ERA-Jump Study

Cardiovascular disease is of public health significance due to its highest rates of mortality. Atherosclerotic cardiovascular events can often result in fatal or disabling non-fatal events. More than half of CHD fatal events do not show earlier symptoms. Early identification of subclinical atherosclerosis and establishment of preventive control are important to reduce CHD mortality and morbidity. The present study aimed to examine: 1) whether n-6 fatty acids are inversely associated with plasminogen activator inhibitor-1 (PAI-1) and fibrinogen; 2) whether vitamin D deficiency is associated with subclinical atherosclerosis; and 3) whether Japanese men have lower incidence or progression of CAC than Caucasian men, and further if marine n-3 fatty acids are inversely associated with incidence or progression of CAC. To test these aims, the Electron-Beam Tomography, Risk Factor Assessment among Japanese and U.S. Men in Post-World War II Birth Cohort (ERA-JUMP) study was utilized.The findings were: 1) in a population-based cross-sectional-sample of 915 men aged 40-49, serum n-6 fatty acids were inversely and significantly associated with PAI-1 but not with fibrinogen; 2) in 295 middle-aged men of a population-based cross-sectional sample, Japanese men showed lower levels of serum vitamin D, despite their habitual fish intake as a major dietary intake, than Caucasian or Japanese-American men. Further, vitamin D deficiency was not associated with subclinical atherosclerosis as measured by intima-media thickness (IMT) and CAC, except for significant associations on IMT in a univariate model among Caucasian men, and on CAC in both univariate and multivariate models among Japanese-American men; and 3) in the follow-up study of 472 men, Japanese men had a significantly lower incidence and progression of CAC than Caucasian men. Japanese men showed significant risk reduction on incident CAC associated with marine n-3 PUFA. However, Japanese and Caucasian men showed no significant associations of marine n-3 PUFA on the progression of CAC. Future studies to examine the causal associations as well as underlying mechanisms are warranted. From the public health importance, these findings extend our understanding of n-3 and n-6 polyunsaturated fatty acids and vitamin D related to subclinical atherosclerosis as well as help to establish public health guidelines

STATISTICAL ESTIMATION METHODS IN VOLUNTEER PANEL WEB SURVEYS

Data collected through Web surveys, in general, do not adopt traditional probability-based sample designs. Therefore, the inferential techniques used for probability samples may not be guaranteed to be correct for Web surveys without adjustment, and estimates from these surveys are likely to be biased. However, research on the statistical aspect of Web surveys is lacking relative to other aspects of Web surveys. Propensity score adjustment (PSA) has been suggested as an alternative for statistically surmounting inherent problems, namely nonrandomized sample selection, in volunteer Web surveys. However, there has been a minimal amount of evidence for its applicability and performance, and the implications are not conclusive. Moreover, PSA does not take into account problems occurring from uncertain coverage of sampling frames in volunteer panel Web surveys. This study attempted to develop alternative statistical estimation methods for volunteer Web surveys and evaluate their effectiveness in adjusting biases arising from nonrandomized selection and unequal coverage in volunteer Web surveys. Specifically, the proposed adjustment used a two-step approach. First, PSA was utilized as a method to correct for nonrandomized sample selection, and secondly calibration adjustment was used for uncertain coverage of the sampling frames. The investigation found that the proposed estimation methods showed a potential for reducing the selection and coverage bias in estimates from volunteer panel Web surveys. The combined two-step adjustment not only reduced bias but also mean square errors to a greater degree than each individual adjustment. While the findings from this study may shed some light on Web survey data utilization, there are additional areas to be considered and explored. First, the proposed adjustment decreased bias but did not completely remove it. The adjusted estimates showed a larger variability than the unadjusted ones. The adjusted estimator was no longer in the linear form, but an appropriate variance estimator has not been developed yet. Finally, naively applying the variance estimator for linear statistics highly overestimated the variance, resulting in understating the efficiency of the survey estimates

The Effect of Robo-taxi User Experience on User Acceptance: Field Test Data Analysis

With the advancement of self-driving technology, the commercialization of Robo-taxi services is just a matter of time. However, there is some skepticism regarding whether such taxi services will be successfully accepted by real customers due to perceived safety-related concerns; therefore, studies focused on user experience have become more crucial. Although many studies statistically analyze user experience data obtained by surveying individuals' perceptions of Robo-taxi or indirectly through simulators, there is a lack of research that statistically analyzes data obtained directly from actual Robo-taxi service experiences. Accordingly, based on the user experience data obtained by implementing a Robo-taxi service in the downtown of Seoul and Daejeon in South Korea, this study quantitatively analyzes the effect of user experience on user acceptance through structural equation modeling and path analysis. We also obtained balanced and highly valid insights by reanalyzing meaningful causal relationships obtained through statistical models based on in-depth interview results. Results revealed that the experience of the traveling stage had the greatest effect on user acceptance, and the cutting edge of the service and apprehension of technology were emotions that had a great effect on user acceptance. Based on these findings, we suggest guidelines for the design and marketing of future Robo-taxi services