Optimization of Desalination Systems with Detailed Water Chemistry through Integration of Reaktoro in WaterTAP

Superstructure Development, Simulation and Optimization of Desalination Systems using Aspen Custom Modeler

The growing global need for freshwater has led to greater dependency on seawater desalination. This field has often been criticized for its high energy use and environmental concerns. Various desalination methods have been developed, including membrane, thermal and hybrid systems; however, their environmental impacts differ from situation to situation. This paper puts forward a framework for the first time utilizing Artificial Intelligence (AI) to analyze to evaluate and classify the various methods of desalination technologically using vast amounts of scientific literature. With the use of Natural Language Processing (NLP), machine learning, and automated data mining, the framework captures the main operational parameters, energy consumption, and environmental consequences within over twenty years of research. The data are then subjected to AI-aided multi-criteria decision-making to evaluate each technique and classify it by its environmental sustainability. The findings prove, i.e. on the highly heterogeneous and heavily biased environmental data that AI improves the precision, efficiency, and neutrality of environmental assessments. This research provides a template and a basis for extensive automated Artificial Intelligence; it also improves the efficiency of environmental assessment and optimization of desalination systems.

Fresh water production is one of the main concerns in the new century. Population grows fast and potable water resources are decreased. In the other hand energy crises would also be another issue that must be well addressed by the politicians and also scientists. Developing desalination plant with using renewable energy (particularly solar energy) is one of the important options to overcome these concerns. Thus many researchers have been working on different desalination plants to find the best conditions and to realize the most efficient performances for different cycles. Different approaches have been used to achieve the most efficient conditions or to find the optimum operation and design conditions. Some of the researchers used parametric study approach while many other adopted different conventional optimization algorithms for these tasks. The algorithms such as gradient based algorithm, genetic algorithm, search and pattern algorithm and neural network method have been used in the field of desalination. For instance; Ophir and Lokiec (2005) described the design principles of a MED plant and various energy considerations that result in an economical MED process and plant. Kamali and Mohebbinia (2007) showed that parametric study as one of the optimization methods on thermo-hydraulic data strongly helps to increase GOR value inside MED-TVC systems. Shamel and Chung (2006) used parametric study to find the optimum condition of a Reverse Osmosis (RO) system for sea water desalination. Metaiche et al (2008) developed optimization software, Desaltop, for RO system for water desalination. They used genetic algorithm to find suitable operating parameters and also to find appropriate type of membrane. Al-Shayji (1998) used neural network method for optimization of large-scale commercial desalination plants. Djebedjian et al. (2008) used genetic algorithm for optimization of a reverse osmosis desalination system. Mussati et al. (2003) used an evolutionary algorithm for the optimization of Multi Stage Flash (MSF) system. Finding the optimum conditions is a major challenge on the desalination plant studies. The plant performance depends on several different variables and constraints that need exhausting efforts to find the optimum conditions. This chapter introduces Design of Experiment (DOE) method as a statistical tool for optimization of desalination systems. Thus two different desalination plants; Multi-Effect Desalination (MED) system and solar desalination using humidification–dehumidification cycle (SDHD) have been considered to show the ability of DOE method for optimizing such systems. These both desalination plants could use the low graded heating energy sources

Context. Water is a key molecule in star- and planet-forming regions. Recent water line observations toward several low-mass protostars suggest low water gas fractional abundances (<10−6 with respect to total hydrogen density) in the inner warm envelopes (r < 102 au). Water destruction by X-rays is thought to influence the water abundances in these regions, but the detailed chemistry, including the nature of alternative oxygen carriers, is not yet understood. Aims. Our aim is to understand the impact of X-rays on the composition of low-mass protostellar envelopes, focusing specifically on water and related oxygen-bearing species. Methods. We computed the chemical composition of two proto-typical low-mass protostellar envelopes using a 1D gas-grain chemical reaction network. We varied the X-ray luminosities of the central protostars, and thus the X-ray ionization rates in the protostellar envelopes. Results. The protostellar X-ray luminosity has a strong effect on the water gas abundances, both within and outside the H2O snowline (Tgas ~ 102 K, r ~ 102 au). Outside, the water gas abundance increases with LX, from ~10−10 for low LX to ~10−8–10−7 at LX > 1030 erg s−1. Inside, water maintains a high abundance of ~10−4 for LX ≲ 1029–1030 erg s−1, with water and CO being the dominant oxygen carriers. For LX ≳ 1030–1031 erg s−1, the water gas abundances significantly decrease just inside the water snowline (down to ~10−8–10−7) and in the innermost regions with Tgas ≳ 250 K (~10−6). For these cases, the fractional abundances of O2 and O gas reach ~10−4 within the water snowline, and they become the dominant oxygen carriers. In addition, the fractional abundances of HCO+ and CH3OH, which have been used as tracers of the water snowline, significantly increase and decrease, respectively, within the water snowline as the X-ray fluxes become larger. The fractional abundances of some other dominant molecules, such as CO2, OH, CH4, HCN, and NH3, are also affected by strong X-ray fields, especially within their own snowlines. These X-ray effects are larger in lower-density envelope models. Conclusions. X-ray-induced chemistry strongly affects the abundances of water and related molecules including O, O2, HCO+, and CH3OH, and can explain the observed low water gas abundances in the inner protostellar envelopes. In the presence of strong X-ray fields, gas-phase water molecules within the water snowline are mainly destroyed with ion-molecule reactions and X-ray-induced photodissociation. Future observations of water and related molecules (using, e.g., ALMA and ngVLA) will access the regions around protostars where such X-ray-induced chemistry is effective.

Explicitly incorporating the effects of chemical phenomena such as chemical pretreatment and mineral scaling during the design of treatment systems is critical; however, the complexity of these phenomena and limitations on data have historically hindered the incorporation of detailed water chemistry into the modeling and optimization of water desalination systems. Thus, while qualitative assessments and experimental studies on chemical pretreatment and scaling are abundant in the literature, very little has been done to assess the technoeconomic implications of different chemical pretreatment alternatives within the context of end-to-end water treatment train optimization. In this work, we begin to address this challenge by exploring the impact of pH control during pretreatment on the cost and operation of a high-recovery desalination train. We compare three pH control methods used in water treatment (H2SO4, HCl, and CO2) and assess their impact on the operation of a desalination plant for brackish water and seawater. Our results show that the impact of the acid choice on the cost can vary widely depending on the water source, with CO2 found to be up to 11% and 49% more expensive than HCl in the seawater and brackish cases, respectively. We also find that the acid chemistry can significantly influence upstream processes, with use of H2SO4 requiring more calcium removal in the softening step to prevent gypsum scaling in HPRO system. Our work highlights why incorporating water chemistry information is critical when evaluating the key cost and operational drivers for high-recovery desalination treatment trains.

Water chemistry of tundra lakes in the periglacial zone of the Bellsund Fiord (Svalbard) in the summer of 2013

Groundwater quality assessment study was conducted in Wera Dijo, Southern Ethiopia. The study's objective is to understand water chemistry suitability for domestic and irrigation activities. In the study area, only regional hydrochemistry work has been done; hence this study focused on the detailed water chemistry of the study area. Twenty-eight shallow and deep water samples were collected, and major physical and chemical parameters were studied. The important hydrochemical facies of water present throughout this region are Ca–Mg–HCO3, Ca–Mg–SO4 and Na–HCO3–Cl. Except for fluoride, sodium, and potassium ion, the levels of major cation and anion were found to be below the World Health Organization's allowable limits for drinking purposes in the majority of the study area. The fluoride ion in groundwater exceeded the highest allowable amount of 1.5 mg/L for drinking water in fifteen of the samples. The sodium percentage, permeability index, sodium absorption ratio and The United States Salinity Laboratory (USSL) categorization were used to evaluate the water in this study location for irrigation purposes. Based on several water quality parameters overall, the research area water chemistry was suitable for drinking, agricultural activity and industrial use.

Water chemistry analysis of an industrial selective flocculation dispersion hematite ore concentrator plant

<p>Baseflow is fed by groundwater to a large fraction. Estimating water quantity and quality from groundwater stores is essential for water management. However, there are few datasets available that contain detailed water chemistry analysis on high spatial resolution across multiple headwater catchments in (high) Alpine environments. This information is essential to analyze mixing processes on catchment scale from distinct landscape features.</p><p>We use two data sets: i) water chemistry analysis snapshot sampling campaigns in 7 headwater streams during low‑flow periods across Switzerland, and ii) a detailed chemical screening (every 25 m) in one selected catchment during baseflow, including electric conductivity and temperature. Major ions, stable isotopes, TOC, DOC, trace elements were analyzed for some of the samples (> 80). These data reveal the chemical fingerprint of the contributing groundwater sources. The chemical composition of these contributing sources to baseflow is largely influenced by weathering products depended on lithology and geomorphology. Using maximum likelihood calculations, we define the ion composition and the isotopic signature of the potential major endmembers (up to three), based on the mixed samples along the main stem.</p><p>The proposed methodology allows to i) reduce uncertainty of the endmembers, and ii) quantify the relative contribution of different lithology and geomorphological features to streamflow and shows iii) which spatial scale of input information is needed to analyze mixing processes from various groundwater sources. Our results show how the contribution of different lithologies, along with topography and geomorphological features, varies spatially throughout Alpine headwater catchments.</p>

Selective flocculation and dispersion processes rely on differences in the surface chemistry of fine mineral particles (<25>ìm) to allow for the concentration of specific minerals from an ore body. The effectiveness of selective flocculation and dispersion processes for the concentration of hematite (Fe2O3) ore are strongly dependent on the ionic content of the process water. The goal of this research was to analyze the ionic content of an operating selective flocculation and dispersion type hematite ore concentrator and determine how carbon dioxide affects the filtration of the final product. A detailed water chemistry analysis of the entire process was determined to show concentration profiles throughout the process. This information was used to explain process phenomena and promote future research into this subject. A subsequent laboratory study was conducted to show how carbon dioxide affects filtration rate and relate this effect to the zeta potential of the constituents of the concentrated hematite ore.

Supercritical water (SCW) has attracted increasing attention after the Generation IV International Forum selected the supercritical water-cooled reactor (SCWR) as one of six concepts for further investigation. The reference design for the SCWR calls for an operating pressure of 25 MPa and a core outlet temperature as high as 625 °C. Tritium is of special interest in these proposed systems, because of the appreciable quantities that would be produced. Regarding the water chemistry in SCWR systems, there is however a complete lack of information on the radiolysis of SCW by tritium β-particles. Because direct measurement of the chemistry under such extreme conditions of high temperature, pressure, and mixed neutron and β/γ radiation fields is difficult, chemical models and computer simulations are important for predicting the detailed radiation chemistry of the cooling water in a SCWR core and the impact on materials. In this study, Monte Carlo simulations were used to predict the yields (or G-values) for the primary species e−aq, H˙, H2, ˙OH, and H2O2 formed from the radiolysis of deaerated SCW (H2O) by the low-energy β-electrons (∼18.6 keV maximum) of tritium at 400 °C as a function of water density in the range of ∼0.15–0.6 g cm−3 (∼24–56 MPa). The objective was to elucidate the (time-dependent) mechanisms involved in the self-radiolysis of tritiated water under supercritical conditions. Calculated yields were compared with data obtained for low-"linear energy transfer" (LET) radiation (such as 60Co γ-rays or high-energy electrons) and fast neutrons. Our simulations revealed that there was a strong resemblance between the density dependences of the different yields for the radiolysis of SCW with tritium β− particles and fast neutrons, corroborating very well with a model of tritium β radiolysis mainly driven by the chemical action of "short tracks" of high local LET. As for the effect of density on the various yields, there was an increased "cage" escape of free radicals at low-density SCW. In contrast, these density effects acted in the opposite sense in the high-density liquid-like region where the caged free radical products were forced to remain as colliding neighbors and recombine, thereby increasing the molecular yields. Finally, the occurrence of the reaction of H˙ atoms with water in the homogeneous chemical stage was found to play a critical role in the formation yields of H2 and ˙OH at 400 °C. Recent work has recognized the potential importance of this reaction above 200 °C, but its rate constant is still not well known.

Back to the basics – Estimating the sensitivity of freshwater to acidification using traditional approaches

There is a tremendous diversity in wetland types and wetland vegetation in the United States, caused primarily by regional, geologic, topographic, and climatic differences. Wetland hydrology, a primary driving force influencing wetland ecology, development, and persistence, is as yet poorly understood. The interaction between groundwater and surface water and the discharge–recharge relationships in wetlands affect water quality and nutrient budgets as well as vegetative composition. Hydrologic considerations necessary for an improved understanding of wetland ecology include detailed water budgets, water chemistry, water regime, and boundary conditions. Wetland values are often based on perceived wetland functions. These hydrologic functions include (i) flood storage and flood-peak desynchronization, (ii) recharge and discharge, (iii) base flow and estuarine water balance, and (iv) water-quality regulation. Expanded research and basic data collection focussed on wetland hydrology and its relation to wetland ecology are needed to identify and quantify the hydrologic functions of wetlands.

Understanding how multiphase processes affect the iron-containing aerosol cycle is key to predict ocean biogeochemistry changes and hence the feedback effects on climate. For this work, the EC-Earth Earth system model in its climate-chemistry configuration is used to simulate the global atmospheric oxalate (OXL), sulfate (SO42−), and iron (Fe) cycles, after incorporating a comprehensive representation of the multiphase chemistry in cloud droplets and aerosol water. The model considers a detailed gas-phase chemistry scheme, all major aerosol components, and the partitioning of gases in aerosol and atmospheric water phases. The dissolution of Fe-containing aerosols accounts kinetically for the solution’s acidity, oxalic acid, and irradiation. Aerosol acidity is explicitly calculated in the model, both for accumulation and coarse modes, accounting for thermodynamic processes involving inorganic and crustal species from sea salt and dust. Simulations for present-day conditions (2000–2014) have been carried out with both EC-Earth and the atmospheric composition component of the model in standalone mode driven by meteorological fields from ECMWF’s ERA-Interim reanalysis. The calculated global budgets are presented and the links between the 1) aqueous-phase processes, 2) aerosol dissolution, and 3) atmospheric composition, are demonstrated and quantified. The model results are supported by comparison to available observations. We obtain an average global OXL net chemical production of 12.61 ± 0.06 Tg yr−1 in EC-Earth, with glyoxal being by far the most important precursor of oxalic acid. In comparison to the ERA-Interim simulation, differences in atmospheric dynamics as well as the simulated weaker oxidizing capacity in EC-Earth result overall in a ~30 % lower OXL source. On the other hand, the more explicit representation of the aqueous-phase chemistry in EC-Earth compared to the previous versions of the model leads to an overall ~20 % higher sulfate production, but still well correlated with atmospheric observations. The total Fe dissolution rate in EC-Earth is calculated at 0.806 ± 0.014 Tg Fe yr−1 and is added to the primary dissolved Fe (DFe) sources from dust and combustion aerosols in the model (0.072 ± 0.001 Tg Fe yr−1). The simulated DFe concentrations show a satisfactory comparison with available observations, indicating an atmospheric burden of ∼0.007 Tg Fe, and overall resulting in an atmospheric deposition flux into the global ocean of 0.376 ± 0.005 Tg Fe yr−1, well within the range reported in the literature. All in all, this work is a first step towards the development of EC-Earth into an Earth System Model with fully interactive bioavailable atmospheric Fe inputs to the marine biogeochemistry component of the model.

Understanding how multiphase processes affect the iron-containing aerosol cycle is key to predict ocean biogeochemistry changes and hence the feedback effects on climate. For this work, the EC-Earth Earth system model in its climate-chemistry configuration is used to simulate the global atmospheric oxalate (OXL), sulfate (SO42−), and iron (Fe) cycles, after incorporating a comprehensive representation of the multiphase chemistry in cloud droplets and aerosol water. The model considers a detailed gas-phase chemistry scheme, all major aerosol components, and the partitioning of gases in aerosol and atmospheric water phases. The dissolution of Fe-containing aerosols accounts kinetically for the solution’s acidity, oxalic acid, and irradiation. Aerosol acidity is explicitly calculated in the model, both for accumulation and coarse modes, accounting for thermodynamic processes involving inorganic and crustal species from sea salt and dust. Simulations for present-day conditions (2000–2014) have been carried out with both EC-Earth and the atmospheric composition component of the model in standalone mode driven by meteorological fields from ECMWF’s ERA-Interim reanalysis. The calculated global budgets are presented and the links between the 1) aqueous-phase processes, 2) aerosol dissolution, and 3) atmospheric composition, are demonstrated and quantified. The model results are supported by comparison to available observations. We obtain an average global OXL net chemical production of 12.61 ± 0.06 Tg yr−1 in EC-Earth, with glyoxal being by far the most important precursor of oxalic acid. In comparison to the ERA-Interim simulation, differences in atmospheric dynamics as well as the simulated weaker oxidizing capacity in EC-Earth result overall in a ~30 % lower OXL source. On the other hand, the more explicit representation of the aqueous-phase chemistry in EC-Earth compared to the previous versions of the model leads to an overall ~20 % higher sulfate production, but still well correlated with atmospheric observations. The total Fe dissolution rate in EC-Earth is calculated at 0.806 ± 0.014 Tg Fe yr−1 and is added to the primary dissolved Fe (DFe) sources from dust and combustion aerosols in the model (0.072 ± 0.001 Tg Fe yr−1). The simulated DFe concentrations show a satisfactory comparison with available observations, indicating an atmospheric burden of ∼0.007 Tg Fe, and overall resulting in an atmospheric deposition flux into the global ocean of 0.376 ± 0.005 Tg Fe yr−1, well within the range reported in the literature. All in all, this work is a first step towards the development of EC-Earth into an Earth System Model with fully interactive bioavailable atmospheric Fe inputs to the marine biogeochemistry component of the model.