MODELING CAR OWNERSHIP, TYPE AND USAGE FOR THE STATE OF MARYLAND

Over the last few decades there has been a great increase in the number of cars in the United States. Given the importance of vehicle ownership on both transport and land-use planning and its relationship with energy consumption, the environment and health, the growth in the number of vehicles and their use has been one of the most intensely researched transport topics over many years. This thesis presents a car ownership model framework for the State of Maryland. The model has been calibrated on publicly available data (2001 and 2009 National Household Travel Survey) without the burden and the consequent cost of collecting additional data. The sample has been sufficient to correctly estimate a number of relevant socio demographic and land use variables. The model has then been applied, for demonstration purposes, to test a number of sensitivity analysis concerning changes in housing density, income, urbanization, unemployment rates and fuel price

INTEGRATED DISCRETE CONTINUOUS CHOICE MODELS: THEORY AND APPLICATIONS IN ESTIMATING HOUSEHOLD VEHICLE OWNERSHIP, TYPE AND USAGE

In the United States, transportation uses approximately 26% of the nation energy consumption, and contributes 27% to the total greenhouse gas emissions. Given the important role of private transportation, it is urgent to develop effective and innovative quantitative methodologies to support public authority decision making. Although a substantial body of the literature investigates household vehicle ownership decisions - vehicle holding, type and usage; the majority of the existing studies focuses on only one of these three decisions, is often limited to specific geographic areas and is not calibrated with the most recent travel survey data available. This dissertation proposes a modeling framework that is able to incorporate all the three decisions simultaneously, and takes into account the correlation across the discrete variable (vehicle holding) and the continuous variable (miles traveled). In this integrated discrete-continuous choice model, a multinomial probit model is used to estimate household vehicle holding decision, while a multinomial logit model is adopted to estimate the vehicle type decision. The vehicle usage decision variable is integrated with the discrete variables by adopting an unrestricted correlation pattern between the discrete and the continuous variables. Since the problem has no closed-mathematical form, I use estimation techniques based on Monte-Carlo simulations and numerical computation of multivariate normal probabilities to derive the solutions. Though a number of studies have demonstrated that unordered behavioral models outperform the ordered mechanisms for vehicle holding decisions, those comparative studies were only conducted for the discrete decisions concerning vehicle ownership. Therefore, an ordered discrete-continuous model structure is developed, in which an ordered probit replace the multinomial probit for the vehicle holding decisions. Both the unordered and ordered structures are estimated and validated on the 2009 National Household Travel Survey data. Ordered models are in general preferred to unordered models for the lower computational costs to derive the analytical solutions. However, results from operational data show that the unordered discrete-continuous models always outperform the ordered ones in terms of both statistical goodness of fit and predication capabilities. The proposed modeling framework is then applied to the entire nation and a system of national vehicle ownership models is derived. The models are calibrated using the 2009 National Household Travel Survey data, each combining four regions (Northeast, Midwest, South and West) and three area types (urban, suburban and rural). In addition, the models are applied to the 2009 American Community Survey data for six randomly selected counties/areas. The prediction results for the six counties/areas demonstrate the prediction capability of the models calibrated. The national models are valuable both for the national level (to evaluate federal policies) and small areas (that lack local household travel survey data). The results also demonstrate that the integrated discrete-continuous framework has good prediction capabilities in modeling household vehicle ownership decisions. Lastly, the dissertation estimates a discrete-continuous model for the Washington D.C. Metropolitan Area and analyzes the impact of improved bus and metro services on household ownership and use decisions in that area. The 2009 National Household Travel Survey data and the General Transit Feed Specification data are integrated, and then both spatial and temporal measurements of transit services are created on the Census Tract level. The results show that improved transit is a significant factor in household vehicle ownership choices and that the proposed methods are able to effectively predict changes in vehicle ownership and usage with respect to the transit improvements. In conclusion, the dissertation contributes to both the theoretical analysis and the practical applications of the household vehicle ownership problem. The results provide decision makers with advanced quantitative methods that are able to effectively analyze policies, aiming at promoting greener travel behavior and at mitigating energy consumption and emissions

Detection and attribution of hydrological changes in different climatic and geomorphic regions of China

Through large-scale hydrological simulation, understanding the impact of different climatic and geomorphic conditions on hydrological variables is valuable for water and land management. However, the related study is still a challenge due to strong environmental diversity in large scale region. The physically-based, national-scale hydrological model in China was developed and validated, which considered the spatial heterogeneity of climatic and geomorphic conditions. Using the model, hydrological differences during the period 1956–2020 in 21 representative basins located in nine climatic zones and four geomorphic regions were quantified. Results showed that: 1) mean annual precipitation was strongly positively correlated with mean actual evapotranspiration, and both increased gradually from north to south. Interestingly, as annual precipitation increases, precipitation tended to be more evenly distributed. In recent decades, the northern river basins have been warming and drying, while the Heihe River basin and the cold northeast regions were under climatic warming and wetting; 2) the spatial distribution of streamflow was consistent with precipitation, but their trends were different. In cold regions affected by frozen soil, the streamflow tended to increase. On the contrary, the basins located in the Warm Temperate Zone with intense human activities and fragile ecosystem had a significant decrease in natural streamflow. As for the streamflow components, the frozen soil and karst structures contributed to the increase of the baseflow index (BFI); 3) The streamflow increase or reduction in 86% of the basins was dominated by climate change, as the contribution rate varied from 51.4% to 95.7%. Affected by the Grain to Green Programme, the streamflow of the Weihe River basin reduced significantly while the BFI increased. However, the reduction of forest, grassland and wetland areas dominated streamflow increase in the Huaihe, and Hulan River basins, and the rates were 65.3% and 66.1%, respectively

Association between Metabolic Score for Visceral Fat and the risk of hypertension in different ethnic groups: a prospective cohort study in Southwest China

ObjectiveVisceral adipose tissue assessment holds significant importance in hypertension prevention. This study aimed to explore the association between the Metabolic Score for Visceral Fat (METS-VF), a new indicator based on laboratory and anthropometry measures, and hypertension risk and to further investigate the association between the METS-VF and the risk of hypertension in different ethnic groups.MethodsIn this study, a total of 9,280 people from 48 townships in 12 districts (counties) of Guizhou Province were selected for the survey using a multistage cluster random sampling method, and 5,127 cases were finally included in the analysis after excluding those with missing relevant data, losing visits, dying at follow-up, those who suffered from hypertension at baseline, and those whose information on the outcome of hypertension was not clear. Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) between METS-VF and incident hypertension, and an accelerated failure time (AFT) model was applied to analyze the association between METS-VF and the onset time of hypertension.ResultsThe total person-years (PYs) of the 5,127 subjects were 36,188.52 years, and the median follow-up time was 6.64 years. During follow-up, 1,127 patients were newly diagnosed with hypertension, and the incidence density was 31.14/1,000 PYs. After adjusting for multivariables, compared with the METS-VF first (Q1), the third (Q3) and fourth (Q4) groups of the METS-VF increased by 29.9% and 61.5%, respectively (HR = 1.299 [1.061, 1.590] and 1.615 [1.280, 2.036]). The risk of hypertension increased with higher METS-VF values (HR = 1.323 [1.167, 1.500], ptrend < 0.001). In the Han Chinese population, Q2 and Q3 increased the risk of hypertension (HR = 1.459 [1.111, 1.917], 1.999 [1.417, 2.718]), and the onset of hypertension was advanced by 0.653 (β = −0.653 (−0.930, −0.375]) years for per 1 unit increase in METS-VF. However, these associations were not found in ethnic minorities.ConclusionMETS-VF was significantly positively associated with the risk of hypertension, and the association was different among ethnic groups

Measuring transit service impacts on vehicle ownership and use

In this paper we measure the impact of public transportation on household vehicle ownership and use. Advanced econometric models are estimated on household travel survey data and on geographic data. In particular, data from the 2009 US National Household Travel Survey is merged with geographic information obtained from the General Transit Feed Specification source. The integration of variables specific to the spatial and temporal coverage of the transit service allows the analysis of different policy scenarios. Results obtained for the Washington DC Metropolitan Area indicate that enhanced transit services reduce the number of private vehicles and vehicle miles traveled. Effects are more marked when bus services are improved and on car use. The study is important for all Metropolitan Regions that are dealing with the problem of congestion, high levels of greenhouse gas emissions and that are planning to invest in more efficient and accessible public transportation services

Experimental and Simulation Studies of Imidazolium Chloride Ionic Liquids with Different Alkyl Chain Lengths for Viscosity Reductions in Heavy Crude Oil: The Effect on Asphaltene Dispersion

Heavy crude oil poses challenges in terms of extraction and transportation due to its high viscosity. In the pursuit of effective methods to reduce viscosity in heavy crude oil, this study investigates the potential of imidazolium chloride ionic liquids with varying alkyl chain lengths as viscosity reducers. The experimental results demonstrate that the addition of 1-dodecyl-3-methylimidazole chloride ([C12-MIM]Cl) leads to a maximum viscosity reduction of 49.87%. Solubility parameters were calculated based on characterization of the average molecular structure of the asphaltenes. The viscosity reduction effect is enhanced when the solubility parameter of the ionic liquid closely matches that of the asphaltene. The initial asphaltene deposition point of heavy crude oil is increased from 63% to 68% with the addition of 150 mg/L [C12-MIM]Cl. Furthermore, the average particle size of asphaltene deposits decreases from 79.35 μm to 48.54 μm. The viscosity of heavy crude oil is influenced by the aggregation of asphaltenes. The ability of ionic liquids, especially those with longer alkyl chains, to disperse asphaltene molecules and reduce viscosity has been confirmed through molecular dynamics and quantum mechanical simulations

Changes in Annual, Seasonal and Monthly Climate and Its Impacts on Runoff in the Hutuo River Basin, China

Much attention has focused on the effects of precipitation (P) and temperature (T) changes on runoff (R); however, the impacts of other climatic factors need to be studied further. Moreover, the monthly and seasonal scale also need to be investigated. In this paper, we investigated the characteristics of changes in annual, seasonal, and monthly hydroclimatic variables, including R, P, T, sunshine duration (SD), relative humidity (RH), and wind speed (WS), between 1956 and 2015 in the Hutuo River basin (HTRB) using the nonparametric Mann-Kendall test, the cumulative anomaly test and the Precipitation-Runoff double cumulative curve method. Additionally, we assessed the contributions of climatic factors to changes in R in the HTRB between 1956 and 2015 using the climate elasticity method. The results indicated that significant downward trends were found for both annual and seasonal R, SD, RH, and WS. In contrast, there was a nonsignificant decrease in annual P; specifically, P significantly increased in spring and winter, but P insignificantly decreased in summer and autumn. Annual and seasonal T increased significantly. The annual R showed an abrupt change in 1979; thus, the entire study period from 1956 to 2015 was divided into two periods: the baseline period (i.e., 1956–1978) and the change period (i.e., 1979–2015). The elasticities in the climatic factors were calculated using the climate elasticity method, and the elasticity values of P, T, SD, RH, and WS were 1.84, −1.07, −2.79, 1.73, and −0.45, respectively. Increasing T was the main cause of the decline in R, and decreasing SD had a large negative contribution to the decline in R in the HTRB. This study will help researchers understand the interactions between climate change and hydrological processes at the basin scale and promote water resource management and watershed planning

Decomposing the Driving Factors of Water Use in China

Based on the national input–output table, a comparable price non-competitive input–output table was compiled for 2002, 2007, and 2012. The influence factors of price and product imports were removed from the table. Furthermore, a water-use input–output table was constructed based on the links between the economic system and water resources management. With the multi-factor structural decomposition analysis (SDA) model developed in this paper, the driving forces of water use were decomposed into 18 factors, and quantitative effect results were obtained. Total water use in China increased by 3.9% from 2002 to 2007 and by 5.4% from 2007 to 2012 with the combined effects of multiple factors. For example, the increase in economic scale raised water use by 46.6% and 45.5%, respectively. Advancement in agricultural technology (production and water-saving technologies) reduced water use by 14.9% and 19.8%, respectively. Reducing the proportion of thermal/nuclear power and increasing the price of electricity have water use-reducing effects. Changes in the mode of development considerably reduced water use by 9.5% and 5.3%, respectively. Water-use management should focus on factors that have great influence on water use and show high water-use sensitivity