ANALYSIS AND SIMULATION OF ENERGY USE AND COST AT A MUNICIPAL WASTEWATER TREATMENT PLANT

The cost of electricity, a major operating cost of municipal wastewater treatment plants, is related to influent flow rate, power price, and power load. With knowledge of inflow and price patterns, plant operators can manage processes to reduce electricity costs. Records of influent flow, power price, and load are evaluated for Blue Plains Advanced Wastewater Treatment Plant. Diurnal and seasonal trends are analyzed. Power usage is broken down among treatment processes. A simulation model of influent pumping, a large power user, is developed. It predicts pump discharge and power usage based on wet-well level. Individual pump characteristics are tested in the plant. The model accurately simulates plant inflow and power use for two pumping stations [R2 = 0.68, 0.93 (inflow), R2 =0.94, 0.91(power)]. Wet-well stage-storage relationship is estimated from data. Time-varying wet-well level is added to the model. A synthetic example demonstrates application in managing pumps to reduce electricity cost.

Changes in the community structure of urban and rural forest patches in Baltimore from 1998 to 2015

Urban forests are often highly fragmented with many exotic species. Altered disturbance regimes and environmental pollutants influence urban forest vegetation. One of the best ways to understand the impacts of land-use on forest composition is through long-term research. In 1998, the Baltimore Ecosystem Study established eight forest plots to investigate the impacts of urbanization on natural ecosystems. Four plots were located in urban forest patches and four were located in rural forests. In 2015, I revisited these plots to measure abundances and quantify change in forest composition, diversity, and structure. Sapling, shrub, and seedling abundance were reduced in the rural plots. Alpha diversity and turnover was lower in the rural plots. Beta diversity was reduced in the rural plots. The structure of the urban plots was mostly unchanged, except for a highly reduced sapling layer. Beta diversity in the urban plots was consistent across surveys due to high species turnover.

Identification and assessment of potential wind energy project sites in the State of Maryland

Gemstone Team Renewables

Characterization and analysis of the exogenous application of selected phytohormones on C. reinhardtii metabolism

Gemstone Team Genes to Fuels

Lifetime and distribution of ozone and related pollutants in the eastern United States

Most major cities in the eastern United States have air quality deemed unhealthy by the EPA under a set of regulations known as the National Ambient Air Quality Standards (NAAQS). The worst air quality in Maryland is measured in Edgewood, MD, a small community located along the Chesapeake Bay and generally downwind of Baltimore during hot, summertime days. Direct measurements and numerical simulations were used to investigate how meteorology and chemistry conspire to create adverse levels of photochemical smog especially at this coastal location. Ozone (O3) and oxidized reactive nitrogen (NOy), a family of ozone precursors, were measured over the Chesapeake Bay during a ten day experiment in July 2011 to better understand the formation of ozone over the Bay and its impact on coastal communities such as Edgewood. Ozone over the Bay during the afternoon was 10% to 20% higher than the closest upwind ground sites. A combination of complex boundary layer dynamics, deposition rates, and unaccounted marine emissions play an integral role in the regional maximum of ozone over the Bay. The CAMx regional air quality model was assessed and enhanced through comparison with data from NASA’s 2011 DISCOVER-AQ field campaign. Comparisons show a model overestimate of NOy by +86.2% and a model underestimate of formaldehyde (HCHO) by –28.3%. I present a revised model framework that better captures these observations and the response of ozone to reductions of precursor emissions. Incremental controls on electricity generating stations will produce greater benefits for surface ozone while additional controls on mobile sources may yield less benefit because cars emit less pollution than expected. Model results also indicate that as ozone concentrations improve with decreasing anthropogenic emissions, the photochemical lifetime of tropospheric ozone increases. The lifetime of ozone lengthens because the two primary gas-phase sinks for odd oxygen (Ox ≈ NO2 + O3) – attack by hydroperoxyl radicals (HO2) on ozone and formation of nitrate – weaken with decreasing pollutant emissions. This unintended consequence of air quality regulation causes pollutants to persist longer in the atmosphere, and indicates that pollutant transport between states and countries will likely play a greater role in the future.

DISPATCHING AND RELOCATION OF EMERGENCY VEHICLES ON FREEWAYS: THEORIES AND APPLICATIONS

Resource allocation decisions are made to serve the current emergency without knowing which future emergency will be occurring. Different ordered combinations of emergencies result in different performance outcomes. Even though future decisions can be anticipated with scenarios, previous models follow an assumption that events over a time interval are independent. This dissertation follows an assumption that events are interdependent, because speed reduction and rubbernecking due to an initial incident provoke secondary incidents. The misconception that secondary incidents are not common has resulted in overlooking a look-ahead concept. This dissertation is a pioneer in relaxing the structural assumptions of independency during the assignment of emergency vehicles. When an emergency is detected and a request arrives, an appropriate emergency vehicle is immediately dispatched. We provide tools for quantifying impacts based on fundamentals of incident occurrences through identification, prediction, and interpretation of secondary incidents. A proposed online dispatching model minimizes the cost of moving the next emergency unit, while making the response as close to optimal as possible. Using the look-ahead concept, the online model flexibly re-computes the solution, basing future decisions on present requests. We introduce various online dispatching strategies with visualization of the algorithms, and provide insights on their differences in behavior and solution quality. The experimental evidence indicates that the algorithm works well in practice. After having served a designated request, the available and/or remaining vehicles are relocated to a new base for the next emergency. System costs will be excessive if delay regarding dispatching decisions is ignored when relocating response units. This dissertation presents an integrated method with a principle of beginning with a location phase to manage initial incidents and progressing through a dispatching phase to manage the stochastic occurrence of next incidents. Previous studies used the frequency of independent incidents and ignored scenarios in which two incidents occurred within proximal regions and intervals. The proposed analytical model relaxes the structural assumptions of Poisson process (independent increments) and incorporates evolution of primary and secondary incident probabilities over time. The mathematical model overcomes several limiting assumptions of the previous models, such as no waiting-time, returning rule to original depot, and fixed depot. The temporal locations flexible with look-ahead are compared with current practice that locates units in depots based on Poisson theory. A linearization of the formulation is presented and an efficient heuristic algorithm is implemented to deal with a large-scale problem in real-time.

Development and Application of Predictive Models for Survival, Growth, and Death of Enteric Pathogens in Leafy Greens Supply Chain

Leafy greens are essential part of a healthy diet. Because of their health benefits, production and consumption of leafy greens has increased considerably in the U.S. in the last few decades. However, leafy greens are also associated with a large number of foodborne disease outbreaks in the last few years. The overall goal of this dissertation was to use the current knowledge of predictive models and available data to understand the growth, survival, and death of enteric pathogens in leafy greens at pre- and post-harvest levels. Temperature plays a major role in the growth and death of bacteria in foods. A growth-death model was developed for Salmonella and Listeria monocytogenes in leafy greens for varying temperature conditions typically encountered during supply chain. The developed growth-death models were validated using experimental dynamic time-temperature profiles available in the literature. Furthermore, these growth-death models for Salmonella and Listeria monocytogenes and a similar model for E. coli O157:H7 were used to predict the growth of these pathogens in leafy greens during transportation without temperature control. Refrigeration of leafy greens meets the purposes of increasing their shelf-life and mitigating the bacterial growth, but at the same time, storage of foods at lower temperature increases the storage cost. Nonlinear programming was used to optimize the storage temperature of leafy greens during supply chain while minimizing the storage cost and maintaining the desired levels of sensory quality and microbial safety. Most of the outbreaks associated with consumption of leafy greens contaminated with E. coli O157:H7 have occurred during July-November in the U.S. A dynamic system model consisting of subsystems and inputs (soil, irrigation, cattle, wildlife, and rainfall) simulating a farm in a major leafy greens producing area in California was developed. The model was simulated incorporating the events of planting, irrigation, harvesting, ground preparation for the new crop, contamination of soil and plants, and survival of E. coli O157:H7. The predictions of this system model are in agreement with the seasonality of outbreaks. This dissertation utilized the growth, survival, and death models of enteric pathogens in leafy greens during production and supply chain.

Effects of Information and Time of Use Pricing on Irish Electricity Demand and Supply

In this dissertation I quantify residential behavior response to interventions designed to reduce electricity demand at different periods of the day. In the first chapter, I examine the effect of information provision coupled with bimonthly billing, monthly billing, and in-home displays, as well as a time-of-use (TOU) pricing scheme to measure consumption over each month of the Irish Consumer Behavior Trial. I find that time-of-use pricing with real time usage information reduces electricity usage up to 8.7 percent during peak times at the start of the trial but the effect decays over the first three months and after three months the in-home display group is indistinguishable from the monthly treatment group. Monthly and bi-monthly billing treatments are not found to be statistically different from another. These findings suggest that increasing billing reports to the monthly level may be more cost effective for electricity generators who wish to decrease expenses and consumption, rather than providing in-home displays. In the following chapter, I examine the response of residential households after exposure to time of use tariffs at different hours of the day. I find that these treatments reduce electricity consumption during peak hours by almost four percent, significantly lowering demand. Within the model, I find evidence of overall conservation in electricity used. In addition, weekday peak reductions appear to carry over to the weekend when peak pricing is not present, suggesting changes in consumer habit. The final chapter of my dissertation imposes a system wide time of use plan to analyze the potential reduction in carbon emissions from load shifting based on the Ireland and Northern Single Electricity Market. I find that CO2 emissions savings are highest during the winter months when load demand is highest and dirtier power plants are scheduled to meet peak demand. TOU pricing allows for shifting in usage from peak usage to off peak usage and this shift in load can be met with cleaner and cheaper generated electricity from imports, high efficiency gas units, and hydro units.

FAMILY CHARACTERISTICS, STATE PROGRAM EFFECTIVENESS, AND REPORT OF INADEQUATE CARE AMONG FAMILIES OF YOUNG CHILDREN WITH HEARING LOSS

Approximately 1.6 per 1,000 newborns in the U.S. are born with hearing loss. Congenital hearing loss poses a risk to their speech, language, cognitive, and social-emotional development. Early detection and intervention can improve outcomes. Every state has an Early Hearing Detection and Intervention program (EHDI) to promote and track screening, audiological assessments and linkage to early intervention. However, a large percentage of children are “lost to system (LTS),” meaning that they did not receive recommended care or that it was not reported. This study used data from the 2009-2010 National Survey of Children with Special Health Care Needs and data from the 2011 EHDI Hearing Screening and Follow-Up Survey to examine how 1) family characteristics; 2) EHDI program effectiveness, as determined by LTS percentages; and 3) the family conditions of education and poverty are related to parental report of inadequate care. The sample comprised 684 children between the ages of 0 and 5 years with hearing loss. The results indicated that living in states with less effective EHDI programs was associated with an increased likelihood of not receiving early intervention services (EIS) and of reporting poor family-centered communication. Sibling classification was associated with both receipt of EIS and report of unmet need. Single mothers were less likely to report increased difficulties accessing care. Poor and less educated families, assessed separately, who lived in states with less effective EHDI programs, were more likely to report non-receipt of EIS and less likely to report unmet need as compared to similar families living in states with more effective programs. Poor families living in states with less effective programs were more likely to report less coordinated care than were poor families living in states with more effective programs. This study supports the conclusion that both family characteristics and the effectiveness of state programs affect quality of care outcomes. It appears that less effective state programs affect disadvantaged families’ service receipt report more than that of advantaged families. These findings are important because they may provide insights into the development of targeted efforts to improve the system of care for children with hearing loss.

Photochemistry and transport of tropospheric ozone and its precursors in urban and remote environments

Tropospheric ozone (O3) adversely affects human health, reduces crop yields, and contributes to climate forcing. To limit these effects, the processes controlling O3 abundance as well as that of its precursor molecules must be fully characterized. Here, I examine three facets of O3 production, both in heavily polluted and remote environments. First, using in situ observations from the DISCOVER-AQ field campaign in the Baltimore/Washington region, I evaluate the emissions of the O3 precursors CO and NOx (NOx = NO + NO2) in the National Emissions Inventory (NEI). I find that CO/NOx emissions ratios derived from observations are 21% higher than those predicted by the NEI. Comparisons to output from the CMAQ model suggest that CO in the NEI is accurate within 15 ± 11%, while NOx emissions are overestimated by 51-70%, likely due to errors in mobile sources. These results imply that ambient ozone concentrations will respond more efficiently to NOx controls than current models suggest. I then investigate the source of high O3 and low H2O structures in the Tropical Western Pacific (TWP). A combination of in situ observations, satellite data, and models show that the high O3 results from photochemical production in biomass burning plumes from fires in tropical Southeast Asia and Central Africa; the low relative humidity results from large-scale descent in the tropics. Because these structures have frequently been attributed to mid-latitude pollution, biomass burning in the tropics likely contributes more to the radiative forcing of climate than previously believed. Finally, I evaluate the processes controlling formaldehyde (HCHO) in the TWP. Convective transport of near surface HCHO leads to a 33% increase in upper tropospheric HCHO mixing ratios; convection also likely increases upper tropospheric CH3OOH to ~230 pptv, enough to maintain background HCHO at ~75 pptv. The long-range transport of polluted air, with NO four times the convectively controlled background, intensifies the conversion of HO2 to OH, increasing OH by a factor of 1.4. Comparisons between the global chemistry model CAM-Chem and observations show that consistent underestimates of HCHO by CAM-Chem throughout the troposphere result from underestimates in both NO and acetaldehyde.

INTEGRATED THRESHOLD-ACTIVATED FEEDBACK MICROSYSTEM FOR REAL-TIME CHARACTERIZATION, SENSING AND TREATMENT OF BACTERIAL BIOFILMS

Biofilms are the primary cause of clinical bacterial infections and are impervious to typical amounts of antibiotics, necessitating very high doses for treatment. Therefore, it is highly desirable to develop new alternate methods of treatment that can complement or replace existing approaches using significantly lower doses of antibiotics. Current standards for studying biofilms are based on end-point studies that are invasive and destroy the biofilm during characterization. This dissertation presents the development of a novel real-time sensing and treatment technology to aid in the non-invasive characterization, monitoring and treatment of bacterial biofilms. The technology is demonstrated through the use of a high-throughput bifurcation based microfluidic reactor that enables simulation of flow conditions similar to indwelling medical devices. The integrated microsystem developed in this work incorporates the advantages of previous in vitro platforms while attempting to overcome some of their limitations. Biofilm formation is extremely sensitive to various growth parameters that cause large variability in biofilms between repeated experiments. In this work we investigate the use of microfluidic bifurcations for the reduction in biofilm growth variance. The microfluidic flow cell designed here spatially sections a single biofilm into multiple channels using microfluidic flow bifurcation. Biofilms grown in the bifurcated device were evaluated and verified for reduced biofilm growth variance using standard techniques like confocal microscopy. This uniformity in biofilm growth allows for reliable comparison and evaluation of new treatments with integrated controls on a single device. Biofilm partitioning was demonstrated using the bifurcation device by exposing three of the four channels to various treatments. We studied a novel bacterial biofilm treatment independent of traditional antibiotics using only small molecule inhibitors of bacterial quorum sensing (analogs) in combination with low electric fields. Studies using the bifurcation-based microfluidic flow cell integrated with real-time transduction methods and macro-scale end-point testing of the combination treatment showed a significant decrease in biomass compared to the untreated controls and well-known treatments such as antibiotics. To understand the possible mechanism of action of electric field-based treatments, fundamental treatment efficacy studies focusing on the effect of the energy of the applied electrical signal were performed. It was shown that the total energy and not the type of the applied electrical signal affects the effectiveness of the treatment. The linear dependence of the treatment efficacy on the applied electrical energy was also demonstrated. The integrated bifurcation-based microfluidic platform is the first microsystem that enables biofilm growth with reduced variance, as well as continuous real-time threshold-activated feedback monitoring and treatment using low electric fields. The sensors detect biofilm growth by monitoring the change in impedance across the interdigitated electrodes. Using the measured impedance change and user inputs provided through a convenient and simple graphical interface, a custom-built MATLAB control module intelligently switches the system into and out of treatment mode. Using this self-governing microsystem, in situ biofilm treatment based on the principles of the bioelectric effect was demonstrated by exposing two of the channels of the integrated bifurcation device to low doses of antibiotics.