Identifying indicators of sustainable development using the global sustainability quadrant approach

Advances in information technology and global data availability have opened the door for assessments of sustainable development at a truly macro scale. It is now fairly easy to conduct a study of sustainability using the entire planet as the unit of analysis; this is precisely what this work set out to accomplish. The study began by examining some of the best known composite indicator frameworks developed to measure sustainability at the country level today. Most of these were found to value human development factors and a clean local environment, but to gravely overlook consumption of (remote) resources in relation to nature’s capacity to renew them, a basic requirement for a sustainable state. Thus, a new measuring standard is proposed, based on the Global Sustainability Quadrant approach. In a two‐dimensional plot of nations’ Human Development Index (HDI) vs. their Ecological Footprint (EF) per capita, the Sustainability Quadrant is defined by the area where both dimensions satisfy the minimum conditions of sustainable development: an HDI score above 0.8 (considered ‘high’ human development), and an EF below the fair Earth‐share of 2.063 global hectares per person. After developing methods to identify those countries that are closest to the Quadrant in the present‐day and, most importantly, those that are moving towards it over time, the study tackled the question: what indicators of performance set these countries apart? To answer this, an analysis of raw data, covering a wide array of environmental, social, economic, and governance performance metrics, was undertaken. The analysis used country rank lists for each individual metric and compared them, using the Pearson Product Moment Correlation function, to the rank lists generated by the proximity/movement relative to the Quadrant measuring methods. The analysis yielded a list of metrics which are, with a high degree of statistical significance, associated with proximity to – and movement towards – the Quadrant; most notably: Favorable for sustainable development: use of contraception, high life expectancy, high literacy rate, and urbanization. Unfavorable for sustainable development: high GDP per capita, high language diversity, high energy consumption, and high meat consumption. A momentary gain, but a burden in the long‐run: high carbon footprint and debt. These results could serve as a solid stepping stone for the development of more reliable composite index frameworks for assessing countries’ sustainability.

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR BIOFUEL FACILITY SIZE AND LOCATION AND A SIMULATION MODEL FOR DESIGN OF A BIOFUEL SUPPLY CHAIN

A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.

Development and characterization of fluorescent pH sensors based on porous silica and hydrogel support matrices

The hydrogen ion activity (pH) is a very important parameter in environment monitoring, biomedical research and other applications. Optical pH sensors have several advantages over traditional potentiometric pH measurement, such as high sensitivity, no need of constant calibration, easy for miniaturization and possibility for remote sensing. Several pH indicators has been successfully immobilized in three different solid porous materials to use as pH sensing probes. The fluorescent pH indicator fluorescein-5-isothiocyanate (FITC) was covalently bound onto the internal surface of porous silica (pore size ~10 nm) and retained its pH sensitivity. The excited state pK* a of FITC in porous silica (5.58) was slightly smaller than in solution (5.68) due to the free silanol groups (Si-OH) on the silica surface. The pH sensitive range for this probe is pH 4.5 - 7.0 with an error less than 0.1 pH units. The probe response was reproducible and stable for at least four month, stored in DI water, but exhibit a long equilibrium of up to 100 minutes. Sol-gel based pH sensors were developed with immobilization of two fluorescent pH indicators fluorescein-5-(and-6)-sulfonic acid, trisodium salt (FS) and 8-hydroxypyrene- 1,3,6-trisulfonic acid (HPTS) through physical entrapment. Prior to immobilization, the indicators were ion-paired with a common surfactant hexadecyltrimethylammonium bromide (CTAB) in order to prevent leaching. The sol-gel films were synthesized through the hydrolysis of two different precursors, ethyltriethoxysilane (ETEOS) and 3- glycidoxypropyltrimethoxysilane (GPTMS) and deposited on a quartz slide through spin coating. The pK a of the indicators immobilized in sol-gel films was much smaller than in solutions due to silanol groups on the inner surface of the sol-gel films and ammonium groups from the surrounding surfactants. Unlike in solution, the apparent pK a of the indicators in sol-gel films increased with increasing ionic strength. The equilibrium time for these sensors was within 5 minutes (with film thickness of ~470 nm). Polyethylene glycol (PEG) hydrogel was of interest for optical pH sensor development because it is highly proton permeable, transparent and easy to synthesize. pH indicators can be immobilized in hydrogel through physical entrapment and copolymerization. FS and HPTS ion-pairs were physically entrapped in hydrogel matrix synthesized via free radical initiation. For covalent immobilization, three indicators, 6,8-dihydroxypyrene-1,3- disulfonic acid (DHPDS), 2,7-dihydroxynaphthalene-3,6-disulfonic acid (DHNDS) and cresol red were first reacted with methacrylic anhydride (MA) to form methacryloylanalogs for copolymerization. These hydrogels were synthesized in aqueous solution with a redox initiation system. The thickness of the hydrogel film is controlled as ~ 0.5 cm and the porosity can be adjusted with the percentage of polyethylene glycol in the precursor solutions. The pK a of the indicators immobilized in the hydrogel both physically and covalently were higher than in solution due to the medium effect. The sensors are stable and reproducible with a short equilibrium time (less than 4 minutes). In addition, the color change of cresol red immobilized hydrogel is vivid from yellow (acidic condition) to purple (basic condition). Due to covalently binding, cresol red was not leaching out from the hydrogel, making it a good candidate of reusable "pH paper".

WATER RESOURCES, HEALTH, AND THE SUSTAINABILITY OF INTERVENTIONS TO ACHIEVE WATER AND SANITATION TARGETS OF THE MILLENNIUM DEVELOPMENT GOALS IN A CHANGING WORLD

This dissertation addresses sustainability of rapid provision of safe water and sanitation required to meet the Millennium Development Goals. Review of health-related literature and global statistics demonstrates engineers' role in achieving the MDGs. This review is followed by analyses relating to social, environmental, and health aspects of meeting MDG targets. Analysis of national indicators showed that inadequate investment, poor or nonexistent policies and governance are challenges to global sanitation coverage in addition to lack of financial resources and gender disparity. Although water availability was not found to be a challenge globally, geospatial analysis demonstrated that water availability is a potentially significant barrier for up to 46 million people living in urban areas and relying on already degraded water resources for environmental income. A daily water balance model incorporating the National Resources Conservation Services curve number method in Bolivian watersheds showed that local water stress is linked to climate change because of reduced recharge. Agricultural expansion in the region slightly exacerbates recharge reductions. Although runoff changes will range from -17% to 14%, recharge rates will decrease under all climate scenarios evaluated (-14% to -27%). Increasing sewer coverage may place stress on the readily accessible natural springs, but increased demand can be sustained if other sources of water supply are developed. This analysis provides a method for hydrological analysis in data scarce regions. Data required for the model were either obtained from publicly available data products or by conducting field work using low-cost methods feasible for local participants. Lastly, a methodology was developed to evaluate public health impacts of increased household water access resulting from domestic rainwater harvesting, incorporating knowledge of water requirements of sanitation and hygiene technologies. In 37 West African cities, domestic rainwater harvesting has the potential to reduce diarrheal disease burden by 9%, if implemented alone with 400 L storage. If implemented in conjunction with point of use treatment, this reduction could increase to 16%. The methodology will contribute to cost-effectiveness evaluations of interventions as well as evaluations of potential disease burden resulting from reduced water supply, such as reductions observed in the Bolivian communities.