Applying Nanofiltration to Decrease Energy Consumption and Sensitivity toward Feed Composition Fluctuations in Salt Production
Abstract
:1. Introduction
2. Experimental
2.1. Batch-Mode Nanofiltration
2.2. Scaling Risk Analysis
2.3. Plant Modeling
- Calculate the composition of the feed water using ‘Ziemowit-650’ and the required variation in Cl−/Mg2+/Ca2+/SO42− concentration (from −10% to +10%), change the Na+ concentration to ensure the electroneutrality condition is preserved;
- If nanofiltration is included, calculate the permeate composition assuming the ion rejection coefficient obtained in batch-mode experiments, permeate recovery of 74.3%, and the ionic composition obtained in Step 2. Calculate the NF energy consumption [23], assuming 1 m3 of feed, 74.3% permeate recovery, and 40 bar operating pressure;
- Using mass balance equations, calculate the composition of the process streams in the evaporator step, assuming the final Cl− concentration in the concentrate as 176 kg/m3 [23] and 1 m3 of ‘Ziemowit-650’ or 0.743 m3 of NF permeate as evaporator feed;
- Knowing the amount of water that must be evaporated, calculate the energy consumption in the evaporator, assuming a specific energy consumption of 44 kWh/m3 of distillate. This is the empirical value of the electric energy consumption of the vapor compression unit, part of the ZOD technology implemented in the Czerwionka-Leszczyny salt production plant. While it should be possible to decrease the energy consumption of the evaporator by applying modern more efficient technology or by utilizing waste heat where available, we have chosen to stick to the current industrial practice and decided that redesigning the thermal part of the technology is beyond the scope of this paper;
- Minimize the error function of the crystallizer using the mass balance equations. The amount of evaporated water, crystallized salt, and gypsum are independent variables, while the maximum chloride concentration after crystallization (200 g/dm3), the value of the gypsum solubility product (4.302 × 10−6), and the maximum concentration of bivalent cations as their respective chlorides in the post-crystallization lyes (8% w/w) are the boundary conditions;
- Calculate the energy consumption of the crystallizer, assuming the specific energy consumption of 66 kWh/m3 of the distillate.
2.4. Economic Model
3. Results and Discussion
3.1. Batch-Mode Nanofiltration
3.2. Scaling Risk Assessment
3.3. Plant Modeling
3.4. Economic Assessment
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
References
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Cl− [g/dm3] | Ca2+ [g/dm3] | Mg2+ [g/dm3] | SO42− [g/dm3] | Na+ [g/dm3] | Ba [mg/dm3] | Sr [mg/dm3] |
---|---|---|---|---|---|---|
48.91 | 1.92 | 2.07 | 2.85 | 26.88 | <0.1 | 53.8 |
Parameter | Value |
---|---|
Polymer | Proprietary PA TFC |
Approx. molecular weight cut-off | 300–500 Da |
MgSO4 rejection (test conditions: 2000 ppm MgSO4 solution at 7.6 bar operating pressure, 25 °C) | 97% |
NaCl rejection (test conditions: 2000 ppm NaCl solution at 7.6 bar operating pressure, 25 °C) | 20% |
Maximum operating pressure at temperature lower than 35 °C | 41.37 bar |
Parameter | Value |
---|---|
Plant capacity | 128 m3/h |
Interest rate | 6% |
Chemical Engineering Plant Cost Index (CEPCI) | 576.7 |
Depreciation of civil costs | 30 years |
Depreciation of mechanical/electrical costs | 15 years |
Depreciation of membrane costs | 5 years |
Cost of a single membrane module | 1000 EUR |
Plant availability | 94% |
Electric energy cost | 0.06 EUR/kWh |
Energy efficiency | 80% |
Chemicals cost | 0.023 EUR/m3 of NF permeate |
Sample | Permeate Recovery [%] | Concentration [g/dm3] | |||
---|---|---|---|---|---|
Cl− | Ca2+ | Mg2+ | SO42− | ||
Permeate 1 | 10 | 37.57 | 0.28 | 0.27 | - |
Permeate 2 | 20 | 39.34 | 0.20 | 0.19 | - |
Permeate 3 | 31.3 | 40.05 | 0.36 | 0.12 | - |
Permeate 4 | 40 | 45.36 | 0.40 | 0.17 | - |
Permeate 5 | 50 | 45.01 | 0.48 | 0.19 | - |
Permeate 6 | 60 | 47.14 | 0.68 | 0.27 | - |
Permeate 7 | 70 | 50.32 | 1.04 | 0.39 | - |
Permeate 8 | 74.3 | 52.45 | 1.04 | 0.83 | - |
Retentate | 74.3 | 70.88 | 6.41 | 6.81 | 10.25 |
Averaged permeate | 44.65 | 0.56 | 0.30 | 0.099 |
Species | Formula | Saturation Index (SI) | Saturation Level [%] |
---|---|---|---|
Anhydrite | CaSO4 | 0.42 | 263 |
Barite | BaSO4 | 0.54 | 347 |
Bischofite | MgCl2·6H2O | −5.36 | 0 |
Bloedite | Na2Mg(SO4)2·4H2O | −3.69 | 0 |
Brucite | Mg(OH)2 | −11.96 | 0 |
Celestite | SrSO4 | 0.37 | 234 |
Epsomite | MgSO4·7H2O | −1.87 | 1 |
Glauberite | Na2Ca(SO4)2 | −0.9 | 13 |
Gypsum | CaSO4·2H2O | 0.7 | 501 |
H2O(g) | H2O | −1.54 | 3 |
Halite | NaCl | −1.34 | 5 |
Hexahydrite | MgSO4·6H2O | −2.11 | 1 |
Kieserite | MgSO4·H2O | −3.23 | 0 |
Labile S | Na4Ca(SO4)3·2H2O | −3.08 | 0 |
Leonhardite | MgSO4·4H2O | −2.72 | 0 |
Magnesium chloride dihydrate | MgCl2·2H2O | −15.18 | 0 |
Magnesium chloride tetrahydrate | MgCl2·4H2O | −7.67 | 0 |
Mirabilite | Na2SO4·10H2O | −1.55 | 3 |
Pentahydrite | MgSO4·5H2O | −2.36 | 0 |
Portlandite | Ca(OH)2 | −18.01 | 0 |
Thenardite | Na2SO4 | −2.13 | 1 |
Parameter | ZOD Technology | ZOD Technology with NF Pretreatment | |
---|---|---|---|
Energy consumption [kWh/t of salt produced] | Nanofiltration | 0 | 37 |
Evaporator | 769 | 522 | |
Crystallizer | 254 | 232 | |
Total | 1023 | 791 | |
Mass of salt produced salt [kg/m3 of coal mine water] | 41.31 | 46.77 | |
Gypsum mass produced by crystallizer [kg/m3 of coal mine water] | 4.850 | 0.111 | |
Salt recovery [%] | 51.3 | 58.0 | |
Volume of postcrystallisation lyes [m3/m3 of coal mine water] | 0.119 | 0.024 | |
Volume of NF retentate [m3/m3 of coal mine water] | 0 | 0.257 |
Parameter | ZOD Technology | ZOD Technology with NF Pretreatment |
---|---|---|
Mass of salt produced [t/y] | 46,320 * | 52,442 * |
Electric energy costs [EUR/y] | 2,843,122 | 2,488,897 |
Income from selling salt [EUR/y] | 6,067,920 | 6,869,902 |
CAPEX of NF [EUR] | 0 | 3,646,294 |
NF chemicals costs [EUR/y] | 0 | 21,694 |
NF maintenance costs [EUR/y] | 0 | 72,926 |
NF other costs excluding energy [EUR/y] | 0 | 145,852 |
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Turek, M.; Mitko, K.; Skóra, P. Applying Nanofiltration to Decrease Energy Consumption and Sensitivity toward Feed Composition Fluctuations in Salt Production. Membranes 2024, 14, 103. https://doi.org/10.3390/membranes14050103
Turek M, Mitko K, Skóra P. Applying Nanofiltration to Decrease Energy Consumption and Sensitivity toward Feed Composition Fluctuations in Salt Production. Membranes. 2024; 14(5):103. https://doi.org/10.3390/membranes14050103
Chicago/Turabian StyleTurek, Marian, Krzysztof Mitko, and Paweł Skóra. 2024. "Applying Nanofiltration to Decrease Energy Consumption and Sensitivity toward Feed Composition Fluctuations in Salt Production" Membranes 14, no. 5: 103. https://doi.org/10.3390/membranes14050103
APA StyleTurek, M., Mitko, K., & Skóra, P. (2024). Applying Nanofiltration to Decrease Energy Consumption and Sensitivity toward Feed Composition Fluctuations in Salt Production. Membranes, 14(5), 103. https://doi.org/10.3390/membranes14050103