Techno-Economic Analysis of RO Desalination of Produced Water for Beneficial Reuse in California

Edalat, Arian; Hoek, Eric M.V.

doi:10.3390/w12071850

Cited by 14 publications

(4 citation statements)

References 6 publications

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“…• Soda ash softening: A 12-point uniform sample across its single-dimensional space (soda ash dose). • Recarbonation: We start with an initial set of 50 Hammersley points chosen from across the twodimensional space (soda ash and carbon dioxide dose).…”

Section: Mineral Scalingmentioning

confidence: 99%

“…Many efforts have been focused on incorporating mineral scaling models in bench-scale modules ranging from simple one-dimensional process-scale models to full computational fluid dynamic models relying on either complex mineral scaling models or simple regressions. − Some models have considered scaling limitations on RO systems, but they do not perform full treatment train optimization . Models of mineral scaling have been rarely used for the cost optimization of treatment trains at the full system scale, with some studies estimating pretreatment costs from pilot scale data, − estimating costs from operational data, , and estimating basic pretreatment design from single dimensional regression . Critically, to our knowledge, the direct incorporation of mineral scaling predictions with rigorous mathematical cost optimization of chemical dosing and RO design in conceptual, high-recovery treatment trains that surpass conventional limitations has never been demonstrated.…”

Section: Introductionmentioning

confidence: 99%

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Modeling Framework for Cost Optimization of Process-Scale Desalination Systems with Mineral Scaling and Precipitation

Amusat,

Atia,

Dudchenko

et al. 2024

ACS EST Eng.

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Cost-optimization models are powerful tools for evaluating emerging water treatment processes. However, to date, optimization models do not incorporate detailed chemical reaction phenomena, limiting the assessment of pretreatment and mineral scaling. Moreover, novel approaches for highsalinity and high-recovery desalination are typically proposed without direct quantification of pretreatment needs or mineral scaling. This work addresses a critical gap in the literature by presenting a modeling framework that includes complex water chemistry predictions with process-scale optimization. We use this approach to conduct a technoeconomic assessment on a conceptual highrecovery treatment train that includes chemical pretreatment (i.e., soda ash softening and recarbonation) and membrane-based desalination (i.e., standard and high-pressure reverse osmosis). We demonstrate how to develop and integrate accurate multidimensional surrogate models for predicting precipitation, pH, and mineral scaling tendencies. Our findings show that cost-optimal results balance the costs of pretreatment with reverse osmosis system design. Optimizing across a range of water recoveries (i.e., 50−90%) reveals multiple costoptimal schemas that vary the chemical dosing in pretreatment and the design and operation of reverse osmosis. Our results reveal that pretreatment costs can be more than double the cost of the primary desalination process at high recoveries due to the extensive pretreatment required to control scaling. This work emphasizes the importance of and provides a framework for including chemistry and mineral scaling predictions in the evaluation of emerging technologies in high-recovery desalination.

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Section: Mineral Scalingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling Framework for Cost Optimization of Process-Scale Desalination Systems with Mineral Scaling and Precipitation

Amusat,

Atia,

Dudchenko

et al. 2024

ACS EST Eng.

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“…Techno-economic feasibility studies were conducted to treat water from Placerita Canyon Oil Field by RO technology. It was found that more than 95% of TDS was removed and suggested that RO technology is viable after the incorporation of structural modifications [30]. Taniguchi et al developed a seawater reverse osmosis (SWRO) membrane, which exhibited excellent boron and TDS removal performance along with high water production.…”

Section: Reverse Osmosis Technology For Tds Removalmentioning

confidence: 99%

Total Dissolved Solids and Their Removal Techniques

Pushpalatha¹,

Sreeja²,

Karthik³

et al. 2022

IJESP

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Total dissolved solids (TDS) due to both geogenic and anthropogenic contaminations, is one of the preliminary as well as essential parameters among others to describe water quality. It includes organic and inorganic components, heavy metals, salts, other dissolved substances, and others due to indiscriminate disposal of untreated domestic and industrial effluents, urban and/or agricultural runoff which exists in the form of micro or nano level in nature. Higher TDS levels in water severely impact health and the environment. For instance, it causes gastrointestinal, cardiovascular, genotoxic, respiratory, skin, and hepatic effects in humans. High TDS level (> 500 ppm) results in excessive scaling in household appliances (e.g., pipes, heaters, and boilers) thereby reducing their efficiency. Therefore, the removal of TDS from various water matrices is taking paramount importance to minimize its impact on health and the environment. Various TDS removal technologies based on the membrane, ion, and temperature gradient are employed to treat water. In this review paper, several TDS removal technologies for instance reverse osmosis, nanofiltration, distillation, ultrafiltration, forward osmosis, precipitation, desalination, ion exchange, electrochemical techniques, electrodialysis, electrolysis, electrocoagulation, and adsorption are discussed in detail.

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“…Few recent studies show a considerable reduction in the electrical energy used by RO systems (2.8 kWh/m 3 ) due to advancements in membranes, however with a relatively poor recovery ratio. [178,179]. On the other hand, the non-payable thermal energy consumed by ADS was reported 39.8 kWh/m 3 entail with payable electrical energy consumption varies between 0.92 to 1.38 kWh/m 3 which significantly reduces the desalination cost even below 0.3 $/m 3 [30].…”

Section: Market Aspects Challenges and Future Perspectivesmentioning

confidence: 99%