<p> The objective of this doctoral dissertation is to develop a model to predict the phototoxicity of petroleum and petroleum components to aquatic organisms. Petroleum contains polycyclic aromatic hydrocarbons (PAHs), alkylated PAHs and heterocyclic PAHs some of which absorb light in the ultraviolet light (UV) and visible (VIS) regions. The result is increased photo-enhanced toxicity, by a factor of two to greater than 1000 in the presence of light.</p><p> The PAHs in petroleum differ in their properties, such as octanol-water partitioning coefficients and molar absorption spectra, and each may exhibit phototoxicity. It is inefficient and impractical to conduct toxicity tests on all the chemicals and all the organisms of concern. Even if the testing was undertaken, it is not clear how to interpret the results and use them for phototoxic risk assessments where light conditions and time of exposure vary. Accordingly, there has been a considerable effort expended to develop models to predict the phototoxicity of PAHs to the aquatic organisms. In each of the previous modeling frameworks various combination of the underlying factors in phototoxicity were incorporated to varying degrees. However, no model included all elements in a unified modeling framework such that the model can be applicable to all PAHs, PAH mixtures, organisms, and light exposure conditions.</p><p> In this dissertation, a phototoxic target lipid model (PTLM) is developed to predict phototoxicity of single PAHs measured either as median lethal concentration (LC50) at a fixed duration of exposure or median lethal time (LT50) at a fixed concentration. The model accounts for differences in the physical and chemical properties of PAHs and test species sensitivities, as well as variations in light characteristics, such as length of exposure, and the light source irradiance spectrum and intensity. The PTLM is based on the narcotic target lipid model (NTLM) of PAHs. Both models rely on the assumption that mortality occurs when the toxicant concentration in the target lipid of the organism reaches a threshold concentration. The model is calibrated using 333 observations of LC50s and LT50s for 20 individual PAHs, 15 test species, and various UV light exposure conditions and times ranging from 1 hour to 100 hours. The LC50 concentrations range from less than 0.1 to greater that 10⁴ &mu;g/L. The model has two fitting parameters that are shown to be constant across PAHs and organisms. The compound specific parameters incorporated in the PTLM are the octanol-water partition coefficient and molar absorption coefficient. The critical target lipid body burden is the only organism specific parameter. The root mean square error (RMSE) of prediction for log(LC50) and log(LT50) are 0.473 and 0.382, respectively. Other phototoxic components of petroleum include alkylated PAHs (APAHs) and benzothiophenes. The PTLM is validated by predicting the observed phototoxic LT50 and LC50 of those chemicals exposed to four different species under different light conditions with RMSE = 0.478. The results support the PTLM capability to predict the phototoxicity of single PAHs for organisms with a wide range of sensitivity and for various light exposure conditions. </p><p> Modeling the phototoxicity of mixtures is accomplished by using the toxic unit (TU) approach and TU additivity. The model is validated by predicting the phototoxicity of the binary and ternary mixtures of three PAHs, pyrene, anthracene, and fluoranthene exposed to <i>Americamysis bahia</i> and <i>Menidia beryllina</i>. The comparison between the observed and predicted phototoxicity for the mixtures results in RMSE = 0.274.</p><p> The PTLM is applied to predict petroleum phototoxicity of the water accommodated fraction for three field collected oil samples, MASS (neat oil), CTC (moderately weathered oil), and Juniper (heavily weathered oil) exposed to four aquatic species indigenous to the Gulf of Mexico, <i>M. beryllina</i>, <i> A. bahia</i>, <i>Cyprinodon variegatus</i>, and <i>Fundulus grandis</i> using natural or simulated solar radiation. For cases in which no phototoxicity was observed, the PTLM predictions are correct in over 70% of the cases (10 out of 14 predictions). When toxicity was observed the RMSE = 0.321.</p>

<p>The rapid development of nanotechnology and wider applications of engineered nanomaterials (ENMs) in the last few decades have generated concerns regarding their environmental and health risks. After release into the environment, ENMs undergo aggregation, transformation, and, for metal-based nanomaterials, dissolution processes, which together determine their fate, bioavailability and toxicity to living organisms in the ecosystems. The rates of these processes are dependent on nanomaterial characteristics as well as complex environmental factors, including natural organic matter (NOM). As a ubiquitous component of aquatic systems, NOM plays a key role in the aggregation, dissolution and transformation of metal-based nanomaterials and colloids in aquatic environments.</p><p>The goal of this dissertation work is to investigate how NOM fractions with different chemical and molecular properties affect the dissolution kinetics of metal oxide ENMs, such as zinc oxide (ZnO) and copper oxide (CuO) nanoparticles (NPs), and consequently their bioavailability to aquatic vertebrate, with Gulf killifish (Fundulus grandis) embryos as model organisms.</p><p>ZnO NPs are known to dissolve at relatively fast rates, and the rate of dissolution is influenced by water chemistry, including the presence of Zn-chelating ligands. A challenge, however, remains in quantifying the dissolution of ZnO NPs, particularly for time scales that are short enough to determine rates. This dissertation assessed the application of anodic stripping voltammetry (ASV) with a hanging mercury drop electrode to directly measure the concentration of dissolved Zn in ZnO NP suspensions, without separation of the ZnO NPs from the aqueous phase. Dissolved zinc concentration measured by ASV ([Zn]ASV) was compared with that measured by inductively coupled plasma mass spectrometry (ICP-MS) after ultracentrifugation ([Zn]ICP-MS), for four types of ZnO NPs with different coatings and primary particle diameters. For small ZnO NPs (4-5 nm), [Zn]ASV was 20% higher than [Zn]ICP-MS, suggesting that these small NPs contributed to the voltammetric measurement. For larger ZnO NPs (approximately 20 nm), [Zn]ASV was (79±19)% of [Zn]ICP-MS, despite the high concentrations of ZnO NPs in suspension, suggesting that ASV can be used to accurately measure the dissolution kinetics of ZnO NPs of this primary particle size.</p><p>Using the ASV technique to directly measure dissolved zinc concentration, we examined the effects of 16 different NOM isolates on the dissolution kinetics of ZnO NPs in buffered potassium chloride solution. The observed dissolution rate constants (kobs) and dissolved zinc concentrations at equilibrium increased linearly with NOM concentration (from 0 to 40 mg-C L-1) for Suwannee River humic acid (SRHA), Suwannee River fulvic acid and Pony Lake fulvic acid. When dissolution rates were compared for the 16 NOM isolates, kobs was positively correlated with certain properties of NOM, including specific ultraviolet absorbance (SUVA), aromatic and carbonyl carbon contents, and molecular weight. Dissolution rate constants were negatively correlated to hydrogen/carbon ratio and aliphatic carbon content. The observed correlations indicate that aromatic carbon content is a key factor in determining the rate of NOM-promoted dissolution of ZnO NPs. NOM isolates with higher SUVA were also more effective at enhancing the colloidal stability of the NPs; however, the NOM-promoted dissolution was likely due to enhanced interactions between surface metal ions and NOM rather than smaller aggregate size.</p><p>Based on the above results, we designed experiments to quantitatively link the dissolution kinetics and bioavailability of CuO NPs to Gulf killifish embryos under the influence of NOM. The CuO NPs dissolved to varying degrees and at different rates in diluted 5‰ artificial seawater buffered to different pH (6.3-7.5), with or without selected NOM isolates at various concentrations (0.1-10 mg-C L-1). NOM isolates with higher SUVA and aromatic carbon content (such as SRHA) were more effective at promoting the dissolution of CuO NPs, as with ZnO NPs, especially at higher NOM concentrations. On the other hand, the presence of NOM decreased the bioavailability of dissolved Cu ions, with the uptake rate constant negatively correlated to dissolved organic carbon concentration ([DOC]) multiplied by SUVA, a combined parameter indicative of aromatic carbon concentration in the media. When the embryos were exposed to CuO NP suspension, changes in their Cu content were due to the uptake of both dissolved Cu ions and nanoparticulate CuO. The uptake rate constant of nanoparticulate CuO was also negatively correlated to [DOC]×SUVA, in a fashion roughly proportional to changes in dissolved Cu uptake rate constant. Thus, the ratio of uptake rate constants from dissolved Cu and nanoparticulate CuO (ranging from 12 to 22, on average 17±4) were insensitive to NOM type or concentration. Instead, the relative contributions of these two Cu forms were largely determined by the percentage of CuO NP that was dissolved.</p><p>Overall, this dissertation elucidated the important role that dissolved NOM plays in affecting the environmental fate and bioavailability of soluble metal-based nanomaterials. This dissertation work identified aromatic carbon content and its indicator SUVA as key NOM properties that influence the dissolution, aggregation and biouptake kinetics of metal oxide NPs and highlighted dissolution rate as a useful functional assay for assessing the relative contributions of dissolved and nanoparticulate forms to metal bioavailability. Findings of this dissertation work will be helpful for predicting the environmental risks of engineered nanomaterials.</p> / Dissertation

There is evidence that landslides occurred along the White Bluffs in south-central Washington State both within the last 11,000 years and the last several hundred years. Modern, active landslide activity along the bluffs began in the late 1960s. Over the last century, this area of the Columbia River Basin has been converted from rangeland and dryland farming to irrigated agriculture, with water provided to the area via an extensive network of canals and laterals. The most prominent and controversial landslide along the White Bluffs lies above Locke Island. Movement of the slide into the Columbia River has forced the river to shift its flow, eroding the banks of Locke Island and its cultural resources. Water is often implicated as a cause of slope failure. Of particular relevance to understanding the hydrological context for initial failure and longer-term stability of Locke Island landslide are the subsurface recharge and groundwater fluxes at the landslide toe. The influences of land use change and climate fluctuations on the subsurface system, and the relative importance of these factors, has been examined using statistical analysis and a numerical modeling framework. Results from wavelet analysis of an approximately 2000 year Palmer Drought Severity Index dataset indicate that low frequency drought and pluvial cycles, at multidecadal to centennial timescales, are persistent features of regional climate in the Columbia River Basin, which may be linked to solar insolation. Results from a two-dimensional variably saturated finite element model indicate that discharge at the toe of Locke Island landslide is governed by changes to the regional groundwater system. Increases in recharge from irrigation and from a wetter climate can increase regional groundwater flow by raising water levels and increasing the discharge rate from the system. Large fluctuations in river stage can increase discharge at the landslide toe more than regional increases in recharge; these increases, however, tend to be short-lived. Regional recharge to the groundwater system is likely the largest influence on achieving and maintaining a state of equilibrium along the White Bluffs.

The environment, health, and safety properties of thorium-uranium-based (âthoriumâ) fuel cycles are estimated and compared to those of analogous uranium-plutonium-based (âuraniumâ) fuel cycle options using a structured assessment methodology. Thorium resource recovery as a measure of environmental sustainability is described in terms of resource availability, chemical processing requirements, and radiological impacts. Results indicate that near-term thorium recovery will occur as a by-product of mining for other commodities, particularly titanium, and could satisfy even the most intensive nuclear demand for thorium six times over. Chemical flowsheet and radiological process analyses show greater, but not insurmountable, impacts for thorium recovery compared to uranium recovery. Four fuel cycle options are compared: a modified-open uranium option, a modified-open thorium option, a closed uranium option, and a closed thorium option. The options are compared on the bases of resource sustainability, waste management (both low- and high-level waste), and occupational radiological impacts. At steady-state, occupational doses somewhat favor the closed thorium option while low-level waste slightly favors the closed uranium option, although uncertainties are significant. The high-level waste properties favor the closed options (especially with thorium), but uranium options produce slightly less I-129 and may present less risk in a repository environment. Resource requirements are much lower for the closed options and are relatively similar between thorium and uranium. In addition to the steady-state results, several potential transition pathways are considered for closed uranium and thorium end-states. For dose, low-level waste, and fission products contributing to repository risk, the differences among transition impacts largely reflect the steady-state differences. However, the high-level waste properties show the opposite result in transition (strongly favoring uranium, whereas thorium is strongly favored at steady-state), since used present-day uranium fuel is disposed in transitions to purely thorium-based options. Resource consumption was the only metric was strongly influenced by specific transition pathways, favoring the most rapid transitions regardless of whether thorium or uranium was used.

<p> The World Health Organization estimated in 2013 that 768 million people lack access to improved drinking water sources. Ceramic water filters have grown in popularity over the past several decades as a point-of-use treatment option to improve water quality. Water treatment reduces the health risks from disease from microbial pollution and potentially other causes. To improve filter design, a more thorough analysis is needed of the effects of the clay and organic materials used to make ceramic water filters. The research presented in this dissertation investigates the effect of four variables on ceramic water filter performance: type of organic matter, total percent volatile matter, air drying compared to oven drying at 105&deg;C, and organic matter particle size. Ceramic water filters were made using the two most common material compositions, clay and sawdust, and clay and rice husks. The moisture content, volatile matter content, and ash content of each material was measured. Ceramic discs 7.6 cm in diameter were made and fired to test for flow rate, porosity, and microbial removal efficiency. Ceramic bars were tested for flexural and impact strength. </p><p> Flow rate increased with increasing volatile matter, and therefore with porosity. The Carman-Kozeny equation was fitted to sawdust and rice husk flow rate data with an <i>R</i>² value of 0.414 and 0.970 respectively. Oven drying filters resulted in a 0.80 to 1.8 log decrease in bacterial removal. Filters produced with a mixture of 75% large (0.297&ndash;0.841 mm) and 25% small (&lt;0.297 mm) organic particles demonstrated a 68% increase in flow rate without reduction in microbial removal compared to filters made with 100% large particles. Microbial removal efficiency decreased with increasing volatile matter content, porosity, and organic matter particle diameter. The flexural and impact strength of sawdust specimens decreased with increasing volatile matter content. Flexural strength of rice husk specimens decreased with increasing volatile matter. However, impact strength of rice husk specimens increased with increasing volatile matter. The model by Li and Aubertin (2003) was fitted to sawdust and rice husk flexural strength data with an <i>R</i>² value of 0.925 and 0.935, respectively.</p><p> The results presented in this dissertation provide a range of flow rate and porosity values for sawdust and rice husk filters that can be used to predict the expected microbial removal efficiency. They compose a system of standard methods to test ceramic water filters that will allow for accurate comparison of filters made with different materials and methods.</p>

The use of biochar as a soil amendment for agricultural purposes in various cultures has been around for centuries, perhaps millennia. This study seeks to advance this practice by investigating the use of engineered biochar, by chemical impregnation, as a means of optimizing the nutrient retaining properties of soil. As a potentially major source of nutrients are found in wastewater, the biochar is also checked for its viability of pre-loading said char with nutrients, by first using it as a means to clean wastewater. First biochar (BC) is used to produce activated carbon (AC) and comparisons are made between the BC and AC in their ability to remove organics from wastewater, then the biochar is chemically modified with three chemicals, Ferrous sulfate Heptahydrate (Copperas), Calcium Chloride (Ice Bite), and Aluminum Potassium Sulfate Dodecahydrate (Alum), and tested for nutrient (orthophosphate and nitrate) sorption. The biochar failed in its unaltered form of removing organics (COD) from wastewater, actually adding COD into the solution. Only when the char was turned into activated carbon did it express the ability to remove COD. The chemically modified chars showed promise in their ability to adsorb nutrients (phosphate and nitrate) from solution (wastewater), as well as enhance the retention of said nutrients (particularly phosphate) within a sandy soil. The biochar amendments also significantly increased the water holding capacity of the sandy soil, regardless of BC type, by no less than 10%. / A Thesis submitted to the Department of Civil and Environmental Engineering in partial fulfillment of the requirements for the degree of Master of Science. / Summer Semester 2018. / July 12, 2018. / Includes bibliographical references. / Hafiz Ahmad, Professor Directing Thesis; Gang Chen, Committee Member; Youneng Tang, Committee Member.

The biological degradation of selenate to elemental selenium and recovery of valuable selenium nanoparticles has been extensively studied and reported by researchers throughout literature. The major challenges in degradation and recovery processes are the reduction of high concentration of selenium oxyanions and effective separation of bacterial cells and sludge from these economically beneficial elemental selenium nanoparticles. This study seeks to investigate the efficacy of a novel combination system comprising a biological reactor, a separating chamber and a tangential-flow ultrafiltration module (TFU). The biological reactor was investigated for its ability to reduce selenate at high loading rates. The separating chamber containing the inclined bacterium-nanoparticle separator was investigated for its ability to separate bacteria from nanoparticles. The TFU was investigated for its ability to induce a water-bacterium-nanoparticles separation even at high selenate loading rates. The reactor system worked in synergism to remove high concentration of selenate from wastewater and simultaneously recover the valuable elemental selenium nanoparticles thereby eliminating the additional use of chemicals or post-treatment operations. / A Thesis submitted to the Department of Civil and Environmental Engineering in partial fulfillment of the requirements for the degree of Master of Science. / Fall Semester 2018. / November 26, 2018. / Includes bibliographical references. / Youneng Tang, Professor Directing Thesis; Gang Chen, Committee Member; Clayton Clark, Committee Member.

Groundwater remediation is conducted in polluted sites to remove contaminants and to restore ground water quality. After remediation goals are achieved, long-term groundwater monitoring (LTM) that can span decades is required to assess the concentration of residual contaminants and to avoid the risk of human health and environment. On large remediation sites, the cost for maintaining a LTM network, collecting samples, conducting water quality lab analysis can be a significant, persistent and growing financial burden for the private entities and government agencies who are responsible for environmental remediation projects. LTM network optimization offers an opportunity to improve the cost-effectiveness of the LTM effort while meeting data accuracy requirements. The optimization includes identifying the redundancy in the monitoring network, and recommending changes to protect against potential impacts to the public and the environment. This study develops a variant ant colony optimization (VACO) method, using ordinary kriging (OK) or inverse distance weighting (IDW) for data interpolation, to identify optimal LTM networks that minimize the cost of LTM by reducing the number of monitoring locations with minimum overall data loss. ACO is a global stochastic search method inspired by the collective problem-solving ability of a colony of ants as they search for the most efficient routes from their nests to food sources. The performance of ACO variant (VACO) developed in this study is evaluated separately in two test cases. In the first case, VACO is used to solve a simplified traveling sales person problem. In the second case, both enumeration method and VACO are employed for optimization of a synthetic long term monitoring network of 73 wells generated from a groundwater transport simulation model. The two sets of test show that the VACO performs well for optimization problems. The VACO is finally adopted for the optimization of a long term monitoring network of 30 wells in Logistic Center, Washington, with the data interpolation methods of inverse distance weighing, ordinary kriging, and modified inverse distance weighing which is developed in this study. The optimization results are analyzed and group of ideal redundant wells identified. The conclusion of this study is summarized at the end, and future work is suggested. / A Dissertation submitted to the Department of Civil and Environmental Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Fall Semester 2017. / November 17, 2017. / ant cology optimization, convergence, ground water long term monitoring network, iteration, spatial optimization, swarm intelligence / Includes bibliographical references. / Gang Chen, Professor Co-Directing Dissertation; Ming Ye, Professor Co-Directing Dissertation; Xiaoqiang Wang, University Representative; Amy Chan Hilton, Committee Member; Wenrui Huang, Committee Member; Youneng Tang, Committee Member.

This dissertation research represents one of the first attempts to investigate the structural and functional microbial ecology of methanol, ethanol and glycerol fostered denitrification. The overarching goal of this research was to elucidate the link between the structure and function of denitrifying microbial populations grown on different carbon sources. Specific objectives were to: 1) diagnose bacteria specifically assimilating methanol and ethanol and determine denitrification kinetics induced by the two carbon sources; 2) investigate factors leading to nitrous oxide (N2O) and nitric oxide (NO) emissions from methanol and ethanol feeding denitrification reactors; 3) characterize glycerol assimilating populations that perform suspended- and biofilm-growth denitrification; 4) examine the potential of using alcohol dehydrogenase gene as a biomarker for methanol and glycerol induced denitrification activity; 5) evaluate the impact of different carbon sources (methanol and ethanol) on the transcript and proteome of a model facultative methylotroph, Methyloversatilis universalis FAM5. First, the technique of DNA stable isotope probing and quantitative polymerase chain reaction were adapted to diagnose and track methylotrophic denitrifying bacteria in activated sludge. Methanol assimilating populations in the methanol fed denitrifying sequencing batch reactor (SBR) were Methyloversatilis spp. and Hyphomicrobium spp. related species. Upon switching to ethanol, only Methyloversatilis spp. was sustained pointing to their metabolic versatility at least with respect to carbon assimilation. This study represents one of the first investigations of the existence and utilization of facultative methylotrophy in activated sludge. Second, the potential of N2O and NO emitted from methanol and ethanol fed denitrifying SBRs was studied during different transient shocks, including organic carbon limitation, nitrite inhibition and oxygen inhibition. Organic carbon limitation and exposure to nitrite did not result in statistically significant emissions over the control. However, statistically higher N2O emissions were observed during exposure to oxygen on the ethanol fed biomass and coincided with sustained denitrification activity in the presence of oxygen. Therefore, the results suggest that the dosage of ethanol to anoxic zones needs to be strictly controlled to minimize N2O emissions in the downstream aerobic zones. Third, the structure-function analysis of denitrification was extended to glycerol (the main component of biodiesel waste and a potential replacement for methanol) in both suspended and biofilm phases of a hybrid integrated fixed-film bioreactor. During long-term operation on glycerol, the biofilm community had a higher phylogenetic diversity (dominated by Comamonas spp., Bradyrhizobium spp., and Tessaracoccus spp.), and lower denitrification kinetics than the suspended community (dominated by Comamonas spp. and Diaphorobacter spp.). Distinct identities of glycerol assimilating populations due to the different substrate availability in the suspended and biofilm phases were shown for the first time. Fourth, carbon source-specific biomarkers of denitrification activity based on gene expression were developed. Based on short-term batch denitrification activity assays as well as long-term bioreactor operation, the applicability of alcohol dehydrogenase gene expression as quantitative descriptors of denitrification activity on methanol and glycerol in mixed cultures was demonstrated. Finally, Methyloversatilis universalis was selected as model organism to study the effects of varying electron donors (from methanol to ethanol) on its gene and protein expression profiles. Genes encoding essential enzymes that involve carbon oxidation, C1 assimilation and central metabolism were found to be differentially expressed during growth on methanol and ethanol. Several physiological and metabolic responses by M. universalis pointed to a well-defined strategy to overcome carbon limitation for surviving in engineered or natural denitrifying environments. In sum, the structural and functional ecology and the metabolism of heterotrophic denitrification on methanol, ethanol and glycerol as applicable to engineered denitrifying bioreactors was investigated in detail. From an engineering perspective, the knowledge gained can help to guide the selection and application of potential organic carbon sources for denitrification in biological nitrogen removal systems. It is expected that such judicious selection can also eventually result in better design, operation and control of engineered nitrogen removal processes and thus help attain ever more stringent nitrogen standards.

Choosing among technologies is difficult and requires a means of making comparisons across different technologies. This dissertation proposes a new methodology to make comparisons across different technologies and across different times based on a user supplied set of evaluation criteria. A simple model is developed to evaluate different technologies and to identify optimal technologies and technology pathways based on a user supplied set of evaluation criteria which allow ranking of different plants, and technology pathways, which represent different time sequences of introducing new power plant designs. This model is applied to a simple set of choices for power plant designs that invovle eight basic operation modules and a total of 96 possible power plant designs, of which 18 are physically feasible. The model also considers five unique pathways of transition over time from one type of power plant to another type. These pathways are ranked based on penalties assigned on the module level, plant level and pathway level. This dissertation studies two cases, where CO2 regulation does and does not take effect. The results show that a shorter path is favorable, and multiple changes at the same time is undesirable. The relative ranking of different pathways are different in the two cases. To find the optimal path among the entire space of solutions, we develop two combinatorial optimization algorithms. The objective function is defined as the minimum of penalties which are imposed for all deviations from an ideal or perfect system. The numerical problem of finding an optimum is solved by means of a branch-and-bound method, and a heuristic based on the label-correcting algorithm for solving the shortest-path problem. The proposed algorithms are applied to the practical examples of finding the optimal sequence of various power plant designs. The computational results show that the performance of the path-dependent shortest path algorithms depends on the structure of the problem. For average problems, the branch-and-bound algorithm is more efficient compared with the brute force search approach. In the worst case, the branch-and-bound algoirthm degenerates into the brute-force search approach. Both branch-and-bound and the brute-force search approach are exact methods. For average problems, the heuristic is more efficient than the branch-and-bound algorithm. The heuristic is not an exact method and there is no guarantee that it always finds the optimum. However, it can find a good result in a reasonable time. We use these algorithms to study technology pathways which consist of power plant designs with CO2 post-combustion capture technologies. We consider a small problem that consists of 6 designs and 14 levels of decisions, a medium problem consisting of 84 designs and 15 levels of decisions, and a big problem consisting of 492 designs and 15 decisions. We use the branch and bound algorithm for the small problem, and the heuristic for the medium and big problems. The results of small, medium and big problems show that, the best technology pathway, or the best sequence of technologies, does not agree with the sequence of best technologies of various times. By choosing a suboptimal design upfront, one can obtain a better technology pathway than the pathway with a sequence of best designs. We develop a flexible software tool that enables process modeling and optimization of complicated energy systems. The software tool models a plant in terms of basic operation modules and streams that connect the modules with material and energy flows. The software represents the beginning of new modling capability that is useful for studying individual energy systems. It introduces a new concept in comparison to traditional software tools by optimizing over entire technology pathway consisting of a time sequence of plant designs and technology choices.