In the current century, the most critical crises faced by human kind will likely be climate change, shortage of energy supplies, and pollution of the environment. A large variety of contaminants are susceptible to be released in the environment from households and from agricultural and industrial activities. During the last decades, physical, chemical, and biological technologies have been developed for pollution remediation and for assessing the extent of environmental contamination in water resources. Because of the large diversity of contaminants, the systematic and comprehensive analysis of elemental and compound pollutants cannot practically be conducted over an extensive network of water bodies. As a consequence, large-scale surface water monitoring programs frequently rely on biological assessment protocols based on macroinvertebrates, microalgae, or fishes, allowing to integrate the impact of many potential contaminants into single indices that are easy to interpret. However, standard bioassessment protocols are currently based on the morphological identification of representative sets of indicator organisms, which requires extensive stream sampling and laboratory observation in the laboratory and taxonomic identification. These operations are time- and personnel-consuming and require a great deal of experience. In this project, we have developed and validated an innovative water quality bioindicator based on the metagenomic analysis of the total prokaryotic microbial community in the water. Microorganisms are essential components of the aquatic ecosystem and their diversity, nature, and distribution typically reflect variations of the environmental conditions and water quality parameters. Although conventional, cultivation-based methods for microbial characterization are important in investigating the microbial communities, they are time and resources consuming. New polymerase chain reaction (PCR)-based molecular methods, such as metagenomic pyrosequencing, have the potential to quickly provide the detailed information on the microbial communities present in any environment. Advanced bioinformatics computing in connection with the resources of extensive genomic databases allow providing the detailed distribution of the microbial species present in the samples, which, in this project, was used as a fingerprint of water quality. The proposed research has been conducted using water samples collected from the Chesapeake and Ohio Canal National Historical Park (CHOH) in Maryland. Comprehensive characterization of the aquatic bacterial communities has been performed using metagenomic pyrosequencing. In parallel, a suite of relevant water quality parameters were monitored in the samples using standard methods. Using redundancy analyses (RDA), meaningful relationships were established between water characteristics and the metagenomic biomarker, showing its potential utilization as a general water quality indicator. This study provides the basis for the development of an innovative method for the fast and cost-effective assessment of water quality based on the aquatic prokaryotic microbiome. Phylogenetic analyses conducted on the metagenomic data revealed that the dominant prokaryotic phyla detected in the 19 samples are similar to the ones typically detected in freshwater environments. Microbial diversity indices showed that all 2012 samples were characterized by a low biodiversity, while 2013 samples were characterized by a higher diversity, which is likely the result of different meteorological conditions in 2012 and 2013. Clustering analysis and principal component analysis (PCA) were conducted to investigate the relationships between the relative abundance of the prokaryotic phyla and water quality parameters. The results showed that the samples collected from the same sites in different years cluster well together when compared based on the water quality parameters. On the contrary, the samples collected in 2012 made a separate group of cluster and same is true for 2013 samples when compared based on the prokaryotic phyla. These observations suggest a larger temporal variation of the microbial communities than the physico-chemical parameters of the water. PCA focusing on prokaryotic communities showed that Proteobacteria and Bacteroides phyla, including aerobic heterotrophic, fast growing bacteria – referred to as copiotrophic or 'r-type' organisms --, cluster together. On the other hand, the other phyla, including mostly anaerobic and/or autotrophic, slow growing bacteria – referred to as oligotropic or 'K-type' organisms --, form a rather distinct cluster. The dependence of the prokaryotic relative abundance on the water quality parameters for the 19 samples was then interrogated using RDA. As showed by PCA investigations, the r-type phyla cluster together and correlate with high alkalinity and conductivity. On the contrary, the K-type phyla cluster together and correlate collectively with sulfate and nitrate. As expected, the copiotrophic, fast-growing, r-type phyla also correlate with the stream samples, while the oligotrophic, slow-growing, K-type phyla correlate better with spring, cave, and mine samples. This study provides the basis for the development of an innovative method for the fast and cost-effective assessment of water quality based on the prokaryotic microbiome. / Civil Engineering

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> The photocatalytic reaction has been integrated as a developing technology for various applications such as air and water remediation, and self-cleaning surfaces. The photocatalysis is an emerging pathway of heterogeneous photocatalysis and physical chemistry. In heterogeneous photocatalysis, semiconductor compounds, mainly TiO₂, ZnO, CdS, and WO₃, have been utilized especially for water treatment and contaminant degradation. Various pollutants, such as aromatic compounds, dyes and surface active agents, can be degraded with photocatalytic techniques. Ultraviolet light and visible light are the most important sources of radiation to conduct photocatalytic reactions. </p><p> In this study, we have developed a combined method using microfluidics and photocatalysis for wastewater treatment. This technique represents a promising solution for contaminant degradation that has advantages such as continuous operation, large surface area to volume ratio, rapid response, and fine flow control. The experiment was conducted by exposing samples to UV light with methylene blue as the model pollutant and titanium dioxide (TiO₂) as the catalyst. The degradation of methylene blue was monitored with spectrophotometry. The effects of variables, such as residence time, chip thickness and intensity have been investigated. The photocatalytic degradation has been determined to be a pseudo-first-order reaction with a rate constant (0.18 <i>C</i><i>_C</i>^0.334) related to catalyst concentration. Once optimized, this system could be scaled out to process wastewater at a larger scale.</p>

<p> The main aim of the study was to introduce new filtering techniques to better the prediction of subsurface water contaminant transport. Hybrid nudging-ensemble Kalman filter (HNEnKF) and ensemble adjustment Kalman filter were proposed in this study. EnKF with traditional nudging were gradually applied promptly in the case of the HNEnKF. Other techniques whose performance were evaluated along with HNEnKF are a numerical method, ensemble Kalman filter, and ensemble adjustment Kalman filter. In this study, the HNEnKF and the EAKF are expected to improve in robustness and convergence due to the nudging properties and the assimilation of observations with a nonlinear relation to model state variables respectively. To appraise the HNEnKF and EAKF techniques, the numerical (finite difference) method and EnKF assimilation method were used. These simulations were executed with a three-dimension subsurface contaminant transport model with a first-order decay rate parameter.</p><p> A summary of this research are outlined below: </p><p> &bull; To investigate the performance of HNEnKF and EAKF data assimilation technique in subsurface water contaminant transport modeling compared to the numerical solution and ensemble Kalman filter technique.</p><p> &bull; To apply HNEnKF and EAKF data assimilation scheme in subsurface water contaminant transport.</p>

<p> In first part of the thesis a detailed study of the particulate pollutant distribution by wind flow over a building in an urban area was performed. The accuracy of RANS-RSTM and LES turbulence models for predicted airflow over a square cylinder was first evaluated. These models are then applied for simulating wind flows over the scale-model of the Center of Excellence (CoE) Building. Comparing the simulation results with the experimental data of Kehs et al. (2009) showed that the RSTM predicted the pressure distribution on the building consistent with the measurements, but it could not capture the details of the airflow velocity field around the building. The LES simulation, however, showed good agreement with the PIV data. The LES model was then used for analyzing the particulate pollutants transport and deposition analysis. </p><p> Particle motion was modeled using a one-way coupling, Lagrangian approach. Particular attentions were given to the effect of the turbulent velocity fluctuations on particles dispersion and deposition. Instantaneous turbulent velocity fluctuations were simulated using the Langevin stochastic differential equation. The particle transport model in turbulent flows was validated by comparing the predicted deposition velocity for vertical and horizontal channel flows with the existing experimental data and numerical simulation results. Finally the particulate pollutant dispersion and deposition around the scaled CoE Building were investigated using the LES and unsteady particle tracking approach. </p><p> In addition, the size-concentration distribution of secondary organic aerosols (SOAs), as an indoor air aldehyde pollutant, was numerically modeled. The population balance equation of the SOAs was solved using the method of moments (MOM). To close the model, particle size distribution was assumed to follow a lognormal distribution, which was based on the experimental data of Chen and Hopke (2009). The nucleation of SOAs from the chemical reaction of &agr;-pinene (a common emission from indoor furniture), and ozone in the air, as well as, their Brownian coagulation and the surface growth were considered in the numerical model. The computational model was evaluated by comparison with the experimental data of Chen and Hopke (2009). </p><p> The MOM was used for modeling the distribution of the SOAs in an office space. The concentrations of SOAs in the breathing zone of an occupant in the room were evaluated for two mixed-mode ventilation systems. The simulation results showed that the pollution concentration in the ventilation system with the air outlet placed in the ceiling was smaller than the one in which the air outlet was in the floor behind the manikin model.</p>

<p> The objective of this research is to develop a simple and innovative technology that effectively lowers chemical concentrations to meet Environment Protection Agency (EPA) drinking water regulations. This study focuses on fabric inclined settling screen development for application to small community drinking water treatment systems to help them with compliance, particularly with disinfection by-products (DBPs) through enhanced solids contact. The technology developed combines fabric filters with the traditional inclined plate concept. Fabric material performance and serviceability was first checked by exposure to a drinking water treatment environment and then measuring turbidity, total dissolved organic carbon, and UV254. The study suggests a product like Pureflo (a polyester) is the more appropriate material in acidic and neutral conditions and one like Surefil (rayon/polyester blend) is the more appropriate material in basic conditions. The Pureflo product was used in bench scale systems to determine performance of the designed fabric inclined settling screen. Experiments with different coagulants, different angle, and different layers of fabric screens was conducted. A pilot scale system was set up in Vandalia, MO to test the feasibility of the fabric screen of turbidity, TOC, UV254, and TTHM removal. Results indicated that screens made from pureflo with angles from 30&deg; through 70&deg; under acidic condition have positive effects on sedimentation enhancement.</p>

<p> Minimizing coastal wetland loss is a high priority in coastal areas throughout the world. Commonly used protection methods are costly, and may have negative impacts on the surrounding areas. The Wave Suppression and Sediment Collection (WSSC) system is an alternative shoreline protection structure. Primary goals of this study are to evaluate the sediment collection performance of three WSSC units under different sand conditions, to determine the performance characteristics of the units in terms of energy coefficients, and to validate a Computational Fluid Dynamic (CFD) model to determine the parameters governing wave attenuation. Sand collection results showed the units collected a minimum of 25% more fine sand than coarse, and that collection was affected by pipe size and row location. A mass transfer model was developed to predict the collection rate of sands based on wave and sand characteristics. The model fit experimental data well, with R2 values over 0.84 for three units and two different sands. A mass transfer coefficient alpha (a) was used within the model to compare the actual sand collection to the predicted amount. Resulting alpha values showed that sediment collection efficiency is governed by open area and pipe location within the devices. Performance characterization showed the WSSC units have wave reflections of 0.45 to 0.80, wave transmissions ranging from 0.10 to 0.40, and wave energy dissipation between 0.50 and 0.90, depending upon the unit and wave conditions. The WSSC units reflect more wave energy and transmit less energy compared to other breakwaters. The CFD model was validated using experimental velocity measurements. Statistical tests showed model velocities were not significantly different from experimental data. Units were modeled parametrically using CFD. Results indicated that wave reduction could be increased by decreasing pipe diameter, reducing the face slope, or increasing the number of rows.</p>

<p> Ordered Mesoporous Carbons (OMCs) with well-controlled pore structure and narrow pore size distribution demonstrated great potential as highly functional adsorbents. The pore size and surface chemistry of OMCs were considered two of the most important factors that affect the adsorption capacity of organic compounds. The objective of this study is to optimize the structure of OMCs for resorcinol adsorption by changing the pore size and oxygen content using computational approach. New rhombic OMC models with varied pore size and oxygen content were constructed using Materials Visualizer module. The specific surface area, total pore volume, small angle X-ray diffraction patterns, and resorcinol adsorption capacity results were calculated by Forcite and sorption module in Materials Studio package. The simulation results were validated by the experimental data. Experimentally, the OMCs were synthesized using sucrose as carbon precursor by hard-template method. The tunable pore size (4nm to 15nm) and oxygen content of the OMCs are obtained by adjusting the amount of boric acid as a pore-expanding reagent. The experimental results, such as BET surface area, X-ray power diffraction patterns, and adsorption capacity of resorcinol, were compared with the simulation results. The optimal pore size of OMC for resorcinol removal was found to be 6 nm. The simulation results confirmed that oxygen containing functional group was an important factor for adsorption on OMCs. The improvement of adsorption capacity was not so significant comparing with the influence of specific surface area, since the adsorption process was a more of a physical process rather than a process with chemical interaction.</p>

<p> With the pollution of freshwater sources and the continual increase in freshwater demand due to rapid industrialization and population explosion, the globe is facing an eminent danger of scarcity of freshwater. One way to increase the water supply beyond the hydrological cycle is to reuse and recycle the waste water by developing an onsite recycling/reclamation technology. Such a bench-scale treatment technology was developed to treat the cooling tower blowdown water (CTBW) from the cooling towers of California State University, Long Beach (CSULB). The CTBW was treated by using electrodialysis. </p><p> The main objective of this project was to bring down the level of total dissolved solids (TDS) of the CTBW to lower than 230 mg/L which is equivalent to the TDS level of tap water provided by the Long Beach Water Department. The secondary objective was to regenerate the hydrochloric acid using the waste ions. Two differently configured electrodialysis cells (onechambered and two-chambered cell) were used and their treatment efficiencies were compared. The one-chambered cell successfully reduced the TDS level by upto 48% for three samples tested in the setup. The two-chambered cell achieved the TDS reduction up to 93.4% for the four samples tested in the setup. The study was successful in regenerating 1.42 mol/L concentration of hydrochloric acid. An economic and water savings analysis was also performed. Calculations showed that by implementing this technology, it is possible to save 10,362,564.76 L/year which translates to $10,813.13 in economic savings. The total annual savings were estimated to be $12,984.01. The payback period for the investment in this study was 50 months, thus a profit of $15,949.48 is expected by the end of the equipment life of the setup.</p><p>