<p> Waste disposal has always been one of the challenging aspects of human life mostly in populated areas. In every urban region, various factors can impact both amount and composition of the generated waste, and these factors might depend on a series of parameters. Therefore, developing a predictive model for waste generation has always been challenging. We believe that one main problem that city planners and policymakers face is a lack of an accurate yet easy-to-use predictive model for the waste production of a given municipality. It would be vital for them, especially during business downturns, to access a reliable predictive model that can be employed in planning resources and allocating budget. However, most developed models are complicated and extensive. The objective of this research is to study the trend of solid waste generation in Philadelphia with respect to business cycle indicators, population growth, current policies and environmental awareness, and to develop a satisfactory predictive model for waste generation. </p><p> Three predictive models were developed using time series analysis, stationary and nonstationary multiple linear regressions. The nonstationary OLS model was just used for comparison purposes and does not have any modeling value. Among the other two developed predictive models, the multiple linear regression model with stationary variables yielded the most accurate predictions for both total and municipal solid waste generation of Philadelphia. Despite its unsatisfactory statistics (R-square, p-value, and F-value), stationary OLS model could predict Philadelphia&rsquo;s waste generation with a low level of approximately 9% error. Although time series modeling demonstrated a less successful prediction comparing to the stationary OLS model (25% error for total solid waste, and 10.7% error for municipal waste predictions), it would be a more reliable method based on its model statistics. The common variable used in all three developed models which made our modeling different from the Streets Department&rsquo;s estimations was unemployment rate. Including an economic factor such as unemployment rate in modeling the waste generation could be helpful especially during economic downturns, in which economic factors can dominate the effects of population growth on waste generation. </p><p> A prediction of waste generation may not only help waste management sector in landfill and waste-to-energy facilities planning but it also provides the basis for a good estimation of its future environmental impacts. In future, we are hoping to predict related environmental trends such as greenhouse gas emissions using our predictive model.</p>

Extraction, production, utilization and disposal of material resources have been undertaken continuously for much of human histories. Unavoidably, all of these activities have disturbed our environment, and subsequently have been harmful to humans and ecosystems in this and future generations. Due to time lag associated with both environment impact and the effects of measures taken to reduce this impact, existing approaches (i.e. monitoring and reacting) do not give sufficiently rapid feedback for effective environmental management. With regard to the complexity and concern related to environment-health chain effects, there is currently no environmental tool or approach that can provide comprehensive information and indicators covering all major environment and health themes, to enable decision makers to make informed judgements about regional policies and plans, relating to the sustainable use and disposal of material resources. Consequently, there is a need for developing a new approach by taking account of a multidisciplinary concept used in this thesis. Substance Flow Analysis (SFA) has been mainly applied in order to provide input information for Health Risk Assessment (HRA). The SFA approach provides the quantity of the substance that is transported (flows) and stored in the system (stock), and of which sub-system, flow, and process is the greatest concern. The HRA approach provides estimates of human health risk associated with site, activity and facility. An environmental fate and transport model is another key knowledge area incorporated into the HRA process. An integrating method of SFA, environmental fate and transport, and HRA is developed and illustrated by a case study of cadmium in Australia. This thesis shows that this new integration of existing stand-alone methods can provide holistic information and useful indicators covering all significant economic activities, environment, flows, and health risk assessment for selected substances. This enables better decision making on the use and disposal of substances at a range of levels in the economy, from corporations to regions and nations.

Previous literature on the Environmental Kuznets Curve has focused extensively on why or why not such a relationship is observed given specific scenarios. More recent literature has shifted attention towards factors that may explain differences in the distribution or threshold of the curve. The purpose of this paper is to determine why we witness different cutoff points for environmental improvement given the same dependent variable. For this analysis, the relationship between CO2 emissions and GDP growth is observed in the United States and the BRIC countries (Brazil, Russia, India and China) from 1981-2006. The results suggest that the standard for environmental improvement is lower for the BRIC countries compared with the United States. Factors that explain this are FDI inflow, share of production from different industries, share of energy from different sources, and overall incentives.

Thesis (M. Sc.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 107-116).

The goal of this dissertation was to examine transport of gas-phase contaminants and the processes causing nonideal transport. With one exception, all experimental work was performed with synthetic porous media (glass beads). I performed experiments with methane, trichloroethene, benzene, and toluene. Transport experiments for gas-phase contaminants in dry homogeneous and heterogeneous porous media were performed to study dispersion of gases during transport. Axial diffusion was found to be a primary contributor to dispersion at gas velocities < 20 cm min⁻¹. Conversely, mechanical mixing was the main contributor to total dispersion at gas velocities > 50 cm min⁻¹. Dispersion of gas-phase contaminants during transport through dry heterogeneous (macroporous) medium was caused by three processes: axial diffusion, which was predominant at gas velocity < 20 cm min⁻¹ and negligible at gas velocity > 100 cm min⁻¹; mechanical mixing, predominant at gas velocities ranging from 30 to 120 cm min⁻¹; and diffusion between macropore and micropore domains, the main contribution to total dispersion at gas velocities above 160 cm min⁻¹. The latter process was responsible for rate-limited transport of gas-phase contaminants (methane, trichloroethene, benzene) through heterogeneous porous medium causing increased dispersion, early breakthrough, and tailing of breakthrough curves. Transport of gas-phase contaminants through the unsaturated heterogeneous porous medium showed a similar trends. The presence of heterogeneity and immobile water caused nonequilibrium transport of methane and trichloroethene. Predictions of breakthrough curves, which fit the experimental data well, were estimated independently and demonstrated that diffusion between macropore and micropore domains have a more pronounced effect on transport nonequilibrium than diffusion in immobile water. Retention of gas-phase contaminants in the unsaturated porous media was also examined. Solid-phase sorption of gas-phase contaminants was minimal and thus not responsible for delay during the transport. The major contribution to total retention was due to accumulation at the gas-water interface. For example, 62-73% and 30-50% total trichloroethene mass was retained at the interface during transport through the glass beads and aquifer material, respectively. Accumulation of benzene at the interface contributed to total benzene retention by 53-61% of total mass.

A prevailing problem in applied hydrology is the estimation of runoff from ungaged small watersheds and drainge basins. In this study, arid and semiarid regions were Grouped according to their climatic, geomorphologic, and soil characteristics, disregarding their geographic position. Eighty watersheds were used in this study from three countries: U.S., Brazil, and Australia. Twenty-two climatic, geomorphologic and soil variables were used for the delineation of homogeneous Groups in the cluster analysis, and two major Groups were defined. The results suggest that homogeneous Groups can be delimited independently of their geographic position. Cluster analysis and Andrews' plot were used for regionalization of the watersheds. The variables used for development of the models for each Group were selected by stepwise multiple regression analysis. The Andrews' plot further examination reinforce the statement that hydrologically similar watersheds are independent of their geographic position. In a preliminary study 60 watersheds were used to determine the most important variables. For Group I, the stepwise multiple regression analysis reduced the available 21 independent variables to three variables: rainfall, soil permeability index, and temperature. For Group II, only two variables were statistically significant (rainfall and watershed form factor). Once the most significant variables were selected, 20 additional watersheds with data were also included in the final study. Upon evaluation of the regression statistics, Group II responded better than Group I. The equations were: UNFORMATTED EQUATION FOLLOWS: Group I "Dry" Q = -68.476 + 0.0784 P + 4.131Temp -3.950Slpr n = 29 R² = 70% SE = 11.16 mm/yr Group II "Wet" Q = 1.29*10⁻¹¹* P⁴·⁴¹* Rf⁻⁰·⁰⁹³ n = 37 R² = 79% SE = 30.52 mm/yr UNFORMATTED EQUATION ENDS Computed annual runoff values for Group II showed a good agreement with observed values, suggesting that the developed equation is good for prediction of the annual runoff water yield. In contrast, predicted values for the Group I showed poor agreement with the observed values, suggesting that the model should be treated with caution.

<p> Simulated oil spills were created in <i>S. alterniflora</i> sediment-water microcosms to determine the effects of applied crude oil on <i> S. alterniflora</i> during two 90-day studies. In the first experiment, oil dosage was varied at 0-250 mg crude oil/g wet soil to determine the lethal dosage level. In the second experiment, oil type, dosage, and soil type were varied to determine the effects of oil under multiple scales of resolution. A light, medium, and heavy crude oil at dosages ranging from 0-150 mg crude oil/g wet soil were used in addition to an oiled and non-oiled soil. Following the completion of the 90-day experiment, several key findings were observed: (1) The lethal dosage limit was reached at 250 mg crude oil/g wet soil during the first experiment but not the second, by design; (2) At initial dosages of 10 and 50 mg crude oil/g wet soil, the oiled soil (acclimated for 4 months) was more influential in decreasing cumulative biomass growth rates compared to oil applied at the oil-water interface; (3) At the heaviest dosages applied as a simulated oil slick, concentrations of 150 mg crude oil/g wet soil, evapotranspiration rates were negatively affected by the oil (significant at p=0.05 in a one-tailed t-test); (4) Light, heavy, and then medium crude oil showed the lowest biomass growths, in that order, indicating that light crude oil was the most toxic in these microcosm experiments with <i> S. alterniflora;</i> (5) The 10 mg oil/g wet soil out-performed the 0 mg oil/g wet soil in transpiration and biomass growth.</p>

<p> Air pollution in Beijing is becoming hard to ignore, however, there are no long-term studies examining the particle pollution such as PM 2.5 concentration. This study describes current and predicts future PM 2.5 pollution for a three-year period, 1^st January 2010 to 31^st December 2012, from the U.S. Embassy monitoring site in Chaoyang, Beijing. We calculated the 24-hour and annual PM2.5 concentrations under EPA method and using the Box-Jenkins method to build a SARIMA model (Seasonal Autoregressive Integrated Moving Average). The results showed the PM2.5 concentration decreased from 2010 to 2012. The 24-hour PM2.5 concentration was 294&mgr;g/m³, ranged from 265.2&mgr;g/m³ to 318.5&mgr;g/m³. And the annual PM2.5 concentration was 94.5&mgr;g/m³ which yearly range from 89.5&mgr;g/m³ to 99.0&mgr;g/m³ and the quarterly value from 73.1&mgr;g/m³ to 108.6&mgr;g/m³. The 24-hours and annual concentration is about 7 to 8 times higher than the US National Ambient Air Quality Standard (NAAQS). There is an urgent need for long-term studies to guide policy makers to improve the air quality in Beijing.</p>

<p> The purpose of this study was to determine community perceptions of changes in ecosystem services from the restoration of Noisette Creek saltmarsh in North Charleston, South Carolina and to explore the potential impacts of restoring Noisette Creek ecosystems on human well-being. Ecosystem services are human benefits from resources and processes that are supplied by natural ecosystems. These services have been shown to directly affect human well-being in the people using these services. Secondary data were collected at the ZCTA level to create social, economic, and health indicators to assign current levels of well-being in the study area. Three focus groups and 25 q-sorts, using 24 paired statements inspired by focus group data, were conducted to determine community perceptions of restoration and the role of Noisette Creek in influencing human well-being within the community. North Charleston in most well-being indicators scored relatively low compared to Charleston County as a whole and selected ZCTAs within the county, particularly in economic security. The focus group data showed seven main themes surrounding Noisette Creek and its restoration, the most prevalent being access to the creek, sense of community, and awareness of the condition and history of Noisette Creek. Three factors representing three discourses (awareness, ecosystem services, and community) emerged from the 25 q-sorts, all with a mix of individuals from various earned incomes and racial compositions. The general consensus using all three analyses is that the restored ecosystem services provided by Noisette Creek could lead to an overall environmental, social, and economic improvement in the area, and therefore have a positive impact on the well-being of area residents. </p>

<p> This dissertation examines whether spatial measures of health determinants and health outcomes are being used appropriately and effectively to improve the health of marginalized populations in the United States. I concentrate on three spatial measures that have received significant policy and regulatory attention in California and nationally: access to healthful foods, climate change, and housing quality. I find that measures of these health determinants have both significant limitations and unrealized potential for addressing health disparities and promoting health equity. </p><p> I define spatial triage as a process of using spatial data to screen or select place-based communities for targeted investments, policy action, and/or regulatory attention. Chapter 1 describes the historical context of spatial triage and how it relates to ongoing health equity research and policy. In Chapter 2, I evaluate spatial measures of community nutrition environments by comparing data from in-person store surveys against data from a commercial database. I find that stores in neighborhoods with higher population density or higher percentage of people of color have lower availability of healthful foods and that inaccuracies in commercial databases may produce biased measures of healthful food availability. </p><p> Chapter 3 focuses on spatial measures of climate change vulnerability. I find that currently used spatial measures of "disadvantaged communities" ignore many important factors, such as community assets, region-specific risks, and occupation-based hazards that contribute to place-based vulnerability. I draw from examples of successful actions by community-based environmental justice organizations and reframe "disadvantaged" communities as sites of solutions where innovative programs are being used to simultaneously address climate mitigation, adaptation, and equity goals. </p><p> In Chapter 4, I combine electronic health records, public housing locations, and census data to evaluate patterns of healthcare utilization and health outcomes for low-income children in San Francisco. I find that children who live in redeveloped public housing are less likely to have more than one acute care hospital visit within a year than children who live in older, traditional public housing. These results demonstrate how integrating patient-level data across hospitals and with data from other sectors can identify new types of place-based health disparities. Chapter 5 details recommendations for analytic, participatory, and cross-sector approaches to guide the development and implementation of more effective health equity research and policy.</p>