Resources

Dai, H., Dong, Z. & Jiang, L. Directional liquid dynamics of interfaces with superwettability. Sci. Adv. 6, eabb5528 (2020).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Chaudhury, M. K. & Whitesides, G. M. How to make water run uphill. Science 256, 1539–1541 (1992).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Kwon, G. et al. Visible light guided manipulation of liquid wettability on photoresponsive surfaces. Nat. Commun. 8, 14968 (2017).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Liu, M., Wang, S. & Jiang, L. Nature-inspired superwettability systems. Nat. Rev. Mater. 2, 17036 (2017).Article 
ADS 
CAS 

Google Scholar 
Chu, K. H., Xiao, R. & Wang, E. N. Uni-directional liquid spreading on asymmetric nanostructured surfaces. Nat. Mater. 9, 413–417 (2010).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Kota, A. K., Kwon, G., Choi, W., Mabry, J. M. & Tuteja, A. Hygro-responsive membranes for effective oil–water separation. Nat. Commun. 3, 1025 (2012).Article 
ADS 
PubMed 

Google Scholar 
Zhang, G. et al. Processing supramolecular framework for free interconvertible liquid separation. Nat. Commun. 11, 425 (2020).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Wang, B., Liang, W., Guo, Z. & Liu, W. Biomimetic super-lyophobic and super-lyophilic materials applied for oil/water separation: a new strategy beyond nature. Chem. Soc. Rev. 44, 336–361 (2015).Article 
PubMed 

Google Scholar 
Jiang, Y. et al. Crystal structural and mechanism of a calcium-gated potassium channel. Nature 417, 523–526 (2002).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Liu, Z., Wang, W., Xie, R., Ju, X. J. & Chu, L. Y. Stimuli-responsive smart gating membranes. Chem. Soc. Rev. 45, 460–475 (2016).Article 
CAS 
PubMed 

Google Scholar 
Hou, X. Smart gating multi-scale pore/channel-based membranes. Adv. Mater. 28, 7049–7064 (2016).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Qu, R. et al. Aminoazobenzene@Ag modified meshes with large extent photo-response: towards reversible oil/water removal from oil/water mixtures. Chem. Sci. 10, 4089–4096 (2019).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Qu, R. et al. Photothermally induced in situ double emulsion separation by a carbon nanotube/poly(Nisopropylacrylamide) modified membrane with superwetting properties. J. Mater. Chem. A 8, 7677–7686 (2020).Article 
CAS 

Google Scholar 
Hu, L. et al. Photothermal-responsive single-walled carbon nanotube-based ultrathin membranes for on/off switchable separation of oil-in-water nanoemulsions. ACS Nano 9, 4835–4842 (2015).Article 
CAS 
PubMed 

Google Scholar 
Cheng, B. et al. Development of smart poly(vinylidene fluoride)-graft-poly(acrylic acid) tree-like nanofiber membrane for pH-responsive oil/water separation. J. Membr. Sci. 534, 1–8 (2017).Article 
CAS 

Google Scholar 
Zhang, L., Zhang, Z. & Wang, P. Smart surfaces with switchable superoleophilicity and superoleophobicity in aqueous media: toward controllable oil/water separation. NPG Asia Mater. 4, e8 (2012).Article 

Google Scholar 
Li, J. J., Zhou, Y. N. & Luo, Z. H. Smart fiber membrane for pH-induced oil/water separation. ACS Appl. Mater. Inter. 7, 19643–19650 (2015).Article 
CAS 

Google Scholar 
Kwon, G. et al. On-demand separation of oil-water mixtures. Adv. Mater. 24, 3666 (2012).Article 
CAS 
PubMed 

Google Scholar 
Liu, Y., Zhao, L., Lin, J. & Yang, S. Electrodeposited surfaces with reversibly switching interfacial properties. Sci. Adv. 5, eaax0380 (2019).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Zhang, W. et al. Thermo-driven controllable emulsion separation by a polymer-decorated membrane with switchable wettability. Angew. Chem. Int. Ed. 57, 5740 (2018).Article 
CAS 

Google Scholar 
Ou, R., Wei, J., Jiang, L., Simon, G. P. & Wang, H. Robust thermos-responsive polymer composite membrane with switchable superhydrophilicity and superhydrophobicity for efficient oil-water separation. Environ. Sci. Technol. 50, 906–914 (2016).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Rana, D. & Matsuura, T. Surface modifications for antifouling membranes. Chem. Rev. 110, 2448–2471 (2010).Article 
CAS 
PubMed 

Google Scholar 
Dutta, K. & De, S. Smart responsive materials for water purification: an overview. J. Mater. Chem. A 5, 22095–22112 (2017).Article 
CAS 

Google Scholar 
Dong, L. & Zhao, Y. CO2-switchable membranes: structures, functions, and separation applications in aqueous medium. J. Mater. Chem. A 8, 16738–16746 (2020).Article 
CAS 

Google Scholar 
Cunningham, M. F. & Jessop, P. G. Carbon dioxide-switchable polymers: where are the future opportunities? Macromolecules 52, 6801–6816 (2019).Article 
ADS 
CAS 

Google Scholar 
Zhang, Q., Lei, L. & Zhu, S. Gas-responsive polymers. ACS Macro Lett. 6, 515–522 (2017).Article 
CAS 
PubMed 

Google Scholar 
Liu, H., Lin, S., Feng, Y. & Theato, P. CO2-responsive polymer materials. Polym. Chem. 8, 12–23 (2017).Article 

Google Scholar 
Lin, S. J., Shang, J. J. & Theato, P. Facile fabrication of CO2‑responsive nanofibers from photo-cross-linked poly(pentafluorophenyl acrylate) nanofibers. ACS Macro Lett. 7, 431–436 (2018).Article 
CAS 
PubMed 

Google Scholar 
Lin, S. J. & Theato, P. CO2-responsive polymers. Macromol. Rapid Commun. 34, 1118–1133 (2013).Article 
CAS 
PubMed 

Google Scholar 
Yan, Q. & Zhao, Y. Block copolymer self-assembly controlled by the “green” gas stimulus of carbon dioxide. Chem. Commun. 50, 11631–11641 (2014).Article 
CAS 

Google Scholar 
Yan, Q. & Zhao, Y. CO2‑stimulated diversiform deformations of polymer assemblies. J. Am. Chem. Soc. 135, 16300–16303 (2013).Article 
CAS 
PubMed 

Google Scholar 
Darabi, A., Jessop, P. G. & Cunningham, M. F. CO2-responsive polymeric materials: synthesis, self-assembly, and functional applications. Chem. Soc. Rev. 45, 4391–4436 (2016).Article 
CAS 
PubMed 

Google Scholar 
Che, H. et al. CO2-responsive nanofibrous membranes with switchable oil/water wettability. Angew. Chem. Int. Ed. 54, 8934–8938 (2015).Article 
ADS 
CAS 

Google Scholar 
Lei, L., Zhang, Q., Shi, S. & Zhu, S. Highly porous poly(high internal phase emulsion) membranes with “open-cell” structure and CO2‑switchable wettability used for controlled oil/water separation. Langmuir 33, 11936–11944 (2017).Article 
CAS 
PubMed 

Google Scholar 
Mo, J., Sha, J., Li, D., Li, Z. & Chen, Y. Fluid release pressure for nanochannels: the Young-Laplace equation using the effective contact angle. Nanoscale 11, 8408–8415 (2019).Article 
CAS 
PubMed 

Google Scholar 
Seveno, D., Blake, T. D. & Coninck, J. Young’s equation at the nanoscale. Phys. Rev. Lett. 111, 096101 (2013).Article 
ADS 
PubMed 

Google Scholar 
Yang, Z., He, C., Suia, H., He, L. & Li, X. Recent advances of CO2-responsive materials in separations. J. CO2 Util. 30, 79–99 (2019).Article 
CAS 

Google Scholar 
Tauhardt, L. et al. Zwitterionic poly(2-oxazoline)s as promising candidates for blood contacting applications. Polym. Chem. 5, 5751 (2014).Article 
CAS 

Google Scholar 
Zhang, X. et al. Janus poly(vinylidene fluoride)-graft-(TiO2 nanoparticles and PFDS) membranes with loose architecture and asymmetric wettability for efficient switchable separation of surfactant-stabilized oil/water emulsions. J. Membr. Sci. 640, 119837 (2021).Article 
CAS 

Google Scholar 
Feng, X. & Jiang, L. Design and creation of superwetting/antiwetting surfaces. Adv. Mater. 18, 3063–3078 (2006).Article 
CAS 

Google Scholar 
Tao, M., Xue, L., Liu, F. & Jiang, L. An intelligent superwetting PVDF membrane showing switchable transport performance for oil/water separation. Adv. Mater. 26, 2943–2948 (2014).Article 
CAS 
PubMed 

Google Scholar 
Li, X. et al. Universal and tunable liquid-liquid separation by nanoparticle-embedded gating membranes based on a self-defined interfacial parameter. Nat. Commun. 12, 80 (2021).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Peng, B. et al. Cellulose-based materials in wastewater treatment of petroleum industry. Green. Energy Environ. 5, 37–49 (2020).Article 

Google Scholar 
Huang, K. et al. Cation-controlled wetting properties of vermiculite membranes and its promise for fouling resistant oil-water separation. Nat. Commun. 11, 1097 (2020).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Haase, M. F. et al. Multifunctional nanocomposite hollow fiber membranes by solvent transfer induced phase separation. Nat. Commun. 8, 1234 (2017).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
J. Zhang, L. Liu, Y. Si, J. Yu, B. Ding. Electrospun nanofibrous membranes: an effective arsenal for the purification of emulsified oily wastewater. Adv. Funct. Mater. 30, 2002192 (2020).Kim, S., Kim, K., Jun, G. & Hwang, W. Wood-nanotechnology-based membrane for the efficient purification of oil-in-water emulsions. ACS Nano 14, 17233–17240 (2020).Article 
CAS 
PubMed 

Google Scholar 
Kralchevsky, P. A. & Nagayama, K. Capillary interactions between particles bound to interfaces, liquid films and biomembranes. Adv. Colloid Interfacace Sci. 85, 145–192 (2000).Article 
CAS 

Google Scholar 
Dehkordi, T. F., Shirin-Abadi, A. R., Karimipour, K. & Mahdavian, A. R. CO2-, electric potential-, and photo-switchable-hydrophilicity membrane (x-SHM) as an efficient color-changeable tool for oil/water separation. Polymer 212, 123250 (2021).Article 
CAS 

Google Scholar 
Huang, X., Mutlu, H. & Theato, P. A CO2-gated anodic aluminum oxide based nanocomposite membrane for de-emulsification. Nanoscale 12, 21316–21324 (2020).Article 
CAS 
PubMed 

Google Scholar 
Shirin-Abadi, A. R., Gorji, M., Rezaee, S., Jessop, P. G. & Cunningham, M. F. CO2-Switchable-hydrophilicity membrane (CO2-SHM) triggered by electric potential: faster switching time along with efficient oil/water separation. Chem. Commun. 54, 8478–8481 (2018).Article 

Google Scholar 
Abraham, S., Kumaranab, S. K. & Montemagno, C. D. Gas-switchable carbon nanotube/polymer hybrid membrane for separation of oil-in-water emulsions. RSC Adv. 7, 39465–39470 (2017).Article 
ADS 
CAS 

Google Scholar 
Liu, Y. et al. Separate reclamation of oil and surfactant from oil-in-water emulsion with a CO2-responsive material. Environ. Sci. Technol. 56, 9651–9660 (2022).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Zhang, Q. et al. CO2‑Switchable membranes prepared by immobilization of CO2‑breathing microgels. ACS Appl. Mater. Inter. 9, 44146–44151 (2017).Article 
CAS 

Google Scholar 
Kung, C. H., Zahiri, B., Sow, P. K. & Mérida, W. On-demand oil-water separation via low-voltage wettability switching of core-shell structures on copper substrates. Appl. Surf. Sci. 444, 15–27 (2018).Article 
ADS 
CAS 

Google Scholar 
Du, L., Quan, X., Fan, X., Chen, S. & Yu, H. Electro-responsive carbon membranes with reversible superhydrophobicity/superhydrophilicity switch for efficient oil/water separation. Sep. Purif. Technol. 210, 891–899 (2019).Article 
CAS 

Google Scholar 
Wu, J. et al. A 3D smart wood membrane with high flux and efficiency for separation of stabilized oil/water emulsions. J. Hazard. Mater. 441, 129900 (2023).Article 
CAS 
PubMed 

Google Scholar 
Yang, C. et al. Facile fabrication of durable mesh with reversible photo-responsive wettability for smart oil/water separation. Prog. Org. Coat. 160, 106520 (2021).Article 
CAS 

Google Scholar 
Chen, Z. et al. Smart light responsive polypropylene membrane switching reversibly between hydrophobicity and hydrophilicity for oily water separation. J. Membr. Sci. 638, 119704 (2021).Article 
CAS 

Google Scholar 
Li, J. J., Zhu, L. T. & Luo, Z. H. Electrospun fibrous membrane with enhanced swithchable oil/water wettability for oily water separation. Chem. Eng. J. 287, 474–481 (2016).Article 
CAS 

Google Scholar 
Wang, Y. et al. Temperature-responsive nanofibers for controllable oil/water separation. RSC Adv. 5, 51078–51085 (2015).Article 
ADS 
CAS 

Google Scholar 
Ding, Y. et al. One-step fabrication of a micro/nanosphere-coordinated dual stimulus-responsive nanofibrous membrane for intelligent antifouling and ultrahigh permeability of viscous water-in-oil emulsions. ACS Appl. Mater. Inter. 13, 27635–27644 (2021).Article 
CAS 

Google Scholar 
Xiang, Y., Shen, J., Wang, Y., Liu, F. & Xue, L. A pH-responsive PVDF membrane with superwetting properties for the separation of oil and water. RSC Adv. 5, 23530–23539 (2015).Article 
ADS 
CAS 

Google Scholar 
Dou, Y. L. et al. Dual-responsive polyacrylonitrile-based electrospun membrane for controllable oil-water separation. J. Hazard. Mater. 438, 129565 (2022).Article 
CAS 
PubMed 

Google Scholar 
Li, J. J., Zhou, Y. N. & Luo, Z. H. Mussel-inspired V-shaped copolymer coating for intelligent oil/water separation. Chem. Eng. J. 322, 693–701 (2017).Article 
CAS 

Google Scholar 
Zhou, Y. N., Li, J. J. & Lu, Z. H. Toward efficient water/oil separation material: effect of copolymer composition on pH-responsive wettability and separation performance. AIChE J. 62, 1758–1770 (2016).Article 
CAS 

Google Scholar 
Xu, Z. et al. Fluorine-free superhydrophobic coatings with pH-induced wettability transition for controllable oil−water separation. ACS Appl. Mater. Inter. 8, 5661–5667 (2016).Article 
CAS 

Google Scholar 
Dang, Z., Liu, L., Li, Y., Xiang, Y. & Guo, G. In situ and ex situ pH-responsive coatings with switchable wettability for controllable oil/water separation. ACS Appl. Mater. Inter. 8, 31281–31288 (2016).Article 
CAS 

Google Scholar 
Cai, Y. et al. A smart membrane with antifouling capability and switchable oil wettability for high-efficiency oil/water emulsions separation. J. Membr. Sci. 555, 69–77 (2018).Article 
CAS 

Google Scholar 
Zhang, Z. et al. A reusable, biomass-derived, and pH-responsive collagen fiber based oil absorbent material for effective separation of oil-in-water emulsions. Colloid Surf. A 633, 127906 (2022).Article 
CAS 

Google Scholar 
Zhang, X., Liu, C., Yang, J., Huang, X. J. & Xu, Z. K. Wettability switchable membranes for separating both oil-in-water and water-in-oil emulsions. J. Membr. Sci. 624, 118976 (2021).Article 
CAS 

Google Scholar 
Yang, W., Li, J., Zhou, P., Zhu, L. & Tang, H. Superhydrophobic copper coating: Switchable wettability, on-demand oil-water separation, and antifouling. Chem. Eng. J. 327, 849–854 (2017).Article 
CAS 

Google Scholar 
Zhai, H. et al. Crown ether modified membranes for Na+-responsive controllable emulsion separation suitable for hypersaline environments. J. Mater. Chem. A 8, 2684–2690 (2020).Article 
CAS 

Google Scholar  More

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Trahey, L. et al. Energy storage emerging: a perspective from the Joint Center for Energy Storage Research. Proc. Natl Acad. Sci. USA 117, 12550–12557 (2020).Article 

Google Scholar 
Koohi-Fayegh, S. & Rosen, M. A. A review of energy storage types, applications and recent developments. J. Energy Storage 27, 101047 (2020).Article 

Google Scholar 
Dehghani-Sanij, A. R., Tharumalingam, E., Dusseault, M. B. & Fraser, R. Study of energy storage systems and environmental challenges of batteries. Renew. Sustain. Energy Rev. 104, 192–208 (2019).Article 

Google Scholar 
Olivetti, E. A., Ceder, G., Gaustad, G. G. & Fu, X. Lithium-ion battery supply chain considerations: analysis of potential bottlenecks in critical metals. Joule 1, 229–243 (2017).Article 

Google Scholar 
Global EV Outlook (IEA, 2021); https://www.iea.org/reports/global-ev-outlook-2021.Tabelin, C. B. et al. Towards a low-carbon society: a review of lithium resource availability, challenges and innovations in mining, extraction and recycling, and future perspectives. Miner. Eng. 163, 106743 (2021).Article 

Google Scholar 
The role of Critical World Energy Outlook Special Report Minerals in Clean Energy Transitions (IEA, 2022); https://iea.blob.core.windows.net/assets/ffd2a83b-8c30-4e9d-980a-52b6d9a86fdc/TheRoleofCriticalMineralsinCleanEnergyTransitions.pdf.Xu, C. et al. Future material demand for automotive lithium-based batteries. Commun. Mater. 1, 99 (2020).Article 

Google Scholar 
Mineral Commodity Summaries. LITHIUM (USGS, 2021); https://pubs.usgs.gov/periodicals/mcs2021/mcs2021-lithium.pdf.Kesler, S. E. et al. Global lithium resources: relative importance of pegmatite, brine and other deposits. Ore Geol. Rev. 48, 55–69 (2012).Article 

Google Scholar 
Alessia, A., Alessandro, B., Maria, V. G., Carlos, V. A. & Francesca, B. Challenges for sustainable lithium supply: a critical review. J. Clean. Prod. 300, 126954 (2021).Article 

Google Scholar 
Tadesse, B., Makuei, F., Albijanic, B. & Dyer, L. The beneficiation of lithium minerals from hard rock ores: a review. Miner. Eng. 131, 170–184 (2019).Article 

Google Scholar 
Vikström, H., Davidsson, S. & Höök, M. Lithium availability and future production outlooks. Appl. Energy 110, 252–266 (2013).Article 

Google Scholar 
Sanjuan, B. et al. Major geochemical characteristics of geothermal brines from the Upper Rhine Graben granitic basement with constraints on temperature and circulation. Chem. Geol. 428, 27–47 (2016).Article 

Google Scholar 
Sanjuan, B. et al. Lithium-rich geothermal brines in Europe: an up-date about geochemical characteristics and implications for potential Li resources. Geothermics 101, 102385 (2022).Article 

Google Scholar 
Stringfellow, W. T. & Dobson, P. F. Technology for the recovery of lithium from geothermal brines. Energies 14, 6805 (2021).Article 

Google Scholar 
Dugamin, E. J. M. et al. Groundwater in sedimentary basins as potential lithium resource: a global prospective study. Sci. Rep. 11, 21091 (2021).Article 

Google Scholar 
Flexer, V., Baspineiro, C. F. & Galli, C. I. Lithium recovery from brines: a vital raw material for green energies with a potential environmental impact in its mining and processing. Sci. Total Environ. 639,, 1188–1204 (2018).Article 

Google Scholar 
Garrett, D. E. Handbook of Lithium and Natural Calcium Chloride https://doi.org/10.1016/B978-0-12-276152-2.X5035-X (2004).Article 

Google Scholar 
Mudd, G. M. Sustainable/responsible mining and ethical issues related to the Sustainable Development Goals. Geol. Soc. London, Spec. Publ. 508, 187 LP–199 (2021).Article 

Google Scholar 
Jerez, B., Garcés, I. & Torres, R. Lithium extractivism and water injustices in the Salar de Atacama, Chile: the colonial shadow of green electromobility. Polit. Geogr. 87, 102382 (2021).Article 

Google Scholar 
Alam, M. A. & Sepúlveda, R. Environmental degradation through mining for energy resources: the case of the shrinking Laguna Santa Rosa wetland in the Atacama Region of Chile. Energy Geosci. 3, 182–190 (2022).Article 

Google Scholar 
Hailes, O. Lithium in international law: trade, investment, and the pursuit of supply chain justice. J. Int. Econ. Law 25, 148–170 (2022).Article 

Google Scholar 
Bustos-Gallardo, B., Bridge, G. & Prieto, M. Harvesting lithium: water, brine and the industrial dynamics of production in the Salar de Atacama. Geoforum 119, 177–189 (2021).Article 

Google Scholar 
Agusdinata, D. B., Liu, W., Eakin, H. & Romero, H. Socio-environmental impacts of lithium mineral extraction: towards a research agenda. Environ. Res. Lett. 13, 123001 (2018).Article 

Google Scholar 
Liu, W. & Agusdinata, D. B. Interdependencies of lithium mining and communities sustainability in Salar de Atacama, Chile. J. Clean. Prod. 260, 120838 (2020).Article 

Google Scholar 
Ellingsen, L. A. W., Singh, B. & Strømman, A. H. The size and range effect: lifecycle greenhouse gas emissions of electric vehicles. Environ. Res. Lett. 11, 054010 (2016).Article 

Google Scholar 
Ambrose, H. & Kendall, A. Understanding the future of lithium: part 2, temporally and spatially resolved life-cycle assessment modeling. J. Ind. Ecol. 24, 90–100 (2020).Article 

Google Scholar 
Porzio, J. & Scown, C. D. Life-cycle assessment considerations for batteries and battery materials. Adv. Energy Mater. 11, 2100771 (2021).Article 

Google Scholar 
Pell, R. et al. Towards sustainable extraction of technology materials through integrated approaches. Nat. Rev. Earth Environ. 2, 665–679 (2021).Article 

Google Scholar 
Stamp, A., Lang, D. J. & Wäger, P. A. Environmental impacts of a transition toward e-mobility: the present and future role of lithium carbonate production. J. Clean. Prod. 23, 104–112 (2012).Article 

Google Scholar 
Ejeian, M., Grant, A., Shon, H. K. & Razmjou, A. Is lithium brine water? Desalination 518, 115169 (2021). Discussion of why brine water should be considered in environmental assessments.Article 

Google Scholar 
Marazuela, M. A., Vázquez-Suñé, E., Ayora, C. & García-Gil, A. Towards more sustainable brine extraction in salt flats: learning from the Salar de Atacama. Sci. Total. Environ. 703, 135605 (2020). Conceptual hydrogeological modelling, calibrated with field data, proposing clever strategies to minimize water impacts during brine pumping.Article 

Google Scholar 
Marazuela, M. A., Vázquez-Suñé, E., Ayora, C., García-Gil, A. & Palma, T. Hydrodynamics of salt flat basins: the Salar de Atacama example. Sci. Total. Environ. 651, 668–683 (2019).Article 

Google Scholar 
Marazuela, M. A., Vázquez-Suñé, E., Ayora, C., García-Gil, A. & Palma, T. The effect of brine pumping on the natural hydrodynamics of the Salar de Atacama: the damping capacity of salt flats. Sci. Total. Environ. 654, 1118–1131 (2019).Article 

Google Scholar 
Houston, J., Butcher, A., Ehren, P., Evans, K. & Godfrey, L. The evaluation of brine prospects and the requirement for modifications to filing standards. Econ. Geol. 106, 1125–1239 (2011). Conceptual hydrogeological modelling about brine pumping and freshwater recharge.Article 

Google Scholar 
Liu, W., Agusdinata, D. B. & Myint, S. W. Spatiotemporal patterns of lithium mining and environmental degradation in the Atacama Salt Flat, Chile. Int. J. Appl. Earth Obs. Geoinf. 80, 145–156 (2019). Pioneering publication with solid data highlighting the environmental impacts related to lithium mining from continental brines.
Google Scholar 
Gutierrez, J. S. et al. Climate change and lithium mining influence flamingo abundance in the Lithium Triangle. Proc. R. Soc. B Biol. Sci. 289, 20212388 (2022).Article 

Google Scholar 
Marazuela, M. A. et al. 3D mapping, hydrodynamics and modelling of the freshwater-brine mixing zone in salt flats similar to the Salar de Atacama (Chile). J. Hydrol. 561, 223–235 (2018).Article 

Google Scholar 
Rosen, M. R. The importance of groundwater in playas: a review of playa classifications and the sedimentology and hydrology of playas. in Paleoclimate and Basin Evolution of Playa Systems Vol. 289 (ed. Rosen, M. R.) (Geological Society of America, 1994).Currey, D. R. & Sack, D. Hemiarid Lake Basins: Hydrographic Patterns BT — Geomorphology of Desert Environments (eds Parsons, A. J. & Abrahams, A. D.) 471–487 (Springer Netherlands, 2009). https://doi.org/10.1007/978-1-4020-5719-9_15.Marconi, P., Arengo, F. & Clark, A. The arid Andean plateau waterscapes and the Lithium Triangle: flamingos as flagships for conservation of high-altitude wetlands under pressure from mining development. Wetl. Ecol. Manag. https://doi.org/10.1007/s11273-022-09872-6 (2022).Article 

Google Scholar 
Gajardo, G. & Redón, S. Andean hypersaline lakes in the Atacama Desert, northern Chile: between lithium exploitation and unique biodiversity conservation. Conserv. Sci. Pract. 1, e94 (2019).
Google Scholar 
Boualleg, M. & Burdet, F. A. P. Method of preparing an adsorbent material shaped in the absence of binder and method of extracting lithium from saline solutions using said material. US patent WO/097202 Al. (2015).Chen, S., Zhang, Q., Andrews-Speed, P. & Mclellan, B. Quantitative assessment of the environmental risks of geothermal energy: a review. J. Environ. Manage. 276, 111287 (2020).Article 

Google Scholar 
Megalooikonomou, K. G., Parolai, S. & Pittore, M. Toward performance-driven seismic risk monitoring for geothermal platforms: development of ad hoc fragility curves. Geotherm. Energy 6, 8 (2018).Article 

Google Scholar 
Bosia, C., Mouchot, J., Ravier, G., Seibel, O. & Genter, A. Evolution of brine geochemical composition during operation of EGS geothermal plants (Alsace, France). In Proc. 46th Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, February 15–17, 2021 SGP-TR-218 (2021).Tyszer, M., Tomaszewska, B. & Kabay, N. Desalination of geothermal wastewaters by membrane processes: strategies for environmentally friendly use of retentate streams. Desalination 520, 115330 (2021).Article 

Google Scholar 
Chagnes, A. & Światowska, J. Lithium Process Chemistry: Resources, Extraction, Batteries and Recycling (Elsevier, 2015).Khalil, A., Mohammed, S., Hashaikeh, R. & Hilal, N. Lithium recovery from brine: recent developments and challenges. Desalination 528, 115611 (2022).Article 

Google Scholar 
Meng, Z. et al. Highly flexible interconnected Li+ ion-sieve porous hydrogels with self-regulating nanonetwork structure for marine lithium recovery. Chem. Eng. J. 445, 136780 (2022).Article 

Google Scholar 
Marthi, R. & Smith, Y. R. Application and limitations of a H2TiO3 — diatomaceous earth composite synthesized from titania slag as a selective lithium adsorbent. Sep. Purif. Technol. 254, 117580 (2021).Article 

Google Scholar 
Li, X. et al. Amorphous TiO2-derived large-capacity lithium ion sieve for lithium recovery. Chem. Eng. Technol. 43, 1784–1791 (2020).Article 

Google Scholar 
Zhou, Z. et al. Recovery of lithium from salt-lake brines using solvent extraction with TBP as extractant and FeCl3 as co-extraction agent. Hydrometallurgy 191, 105244 (2020).Article 

Google Scholar 
Song, J., Huang, T., Qiu, H., Li, X. M. & He, T. Recovery of lithium from salt lake brine of high Mg/Li ratio using Na[FeCl4 ∗ 2TBP] as extractant: thermodynamics, kinetics and processes. Hydrometallurgy 173, 63–70 (2017).Article 

Google Scholar 
Li, R. et al. Novel ionic liquid as co-extractant for selective extraction of lithium ions from salt lake brines with high Mg/Li ratio. Sep. Purif. Technol. 277, 119471 (2021).Article 

Google Scholar 
Shi, C. et al. Solvent extraction of lithium from aqueous solution using non-fluorinated functionalized ionic liquids as extraction agents. Sep. Purif. Technol. 172, 473–479 (2017).Article 

Google Scholar 
Gmar, S. & Chagnes, A. Recent advances on electrodialysis for the recovery of lithium from primary and secondary resources. Hydrometallurgy 189, 105124 (2019).Article 

Google Scholar 
Li, X. et al. Membrane-based technologies for lithium recovery from water lithium resources: a review. J. Memb. Sci. 591, 117317 (2019).Article 

Google Scholar 
Zhao, Z., Liu, G., Jia, H. & He, L. Sandwiched liquid-membrane electrodialysis: lithium selective recovery from salt lake brines with high Mg/Li ratio. J. Memb. Sci. 596, 117685 (2020).Article 

Google Scholar 
Li, Q. et al. Efficiently rejecting and concentrating Li+ by nanofiltration membrane under a reversed electric field. Desalination 535, 115825 (2022).Article 

Google Scholar 
Li, Y., Zhao, Y. J., Wang, H. & Wang, M. The application of nanofiltration membrane for recovering lithium from salt lake brine. Desalination 468, 114081 (2019).Article 

Google Scholar 
He, R. et al. Unprecedented Mg2+/Li+ separation using layer-by-layer based nanofiltration hollow fiber membranes. Desalination 525, 115492 (2022).Article 

Google Scholar 
Calvo, E. J. Electrochemical methods for sustainable recovery of lithium from natural brines and battery recycling. Curr. Opin. Electrochem. 15, 102–108 (2019).Article 

Google Scholar 
Battistel, A., Palagonia, M. S., Brogioli, D., La Mantia, F. & Trócoli, R. Electrochemical methods for lithium recovery: a comprehensive and critical review. Adv. Mater. 32, 1905440 (2020). Critical review about electrochemical ion pumping technologies, with suggestions about which experimental parameters need to be assessed. Not all electrochemical technologies are reviewed.Article 

Google Scholar 
Calvo, E. J. Direct lithium recovery from aqueous electrolytes with electrochemical ion pumping and lithium intercalation. ACS Omega 6, 35213–35220 (2021).Article 

Google Scholar 
He, L. et al. New insights into the application of lithium-ion battery materials: selective extraction of lithium from brines via a rocking-chair lithium-ion battery system. Glob. Chall. 2, 1700079 (2018).Article 

Google Scholar 
Liu, D., Xu, W., Xiong, J., He, L. & Zhao, Z. Electrochemical system with LiMn2O4 porous electrode for lithium recovery and its kinetics. Sep. Purif. Technol. 270, 118809 (2021).Article 

Google Scholar 
Liu, D., Zhao, Z., Xu, W., Xiong, J. & He, L. A closed-loop process for selective lithium recovery from brines via electrochemical and precipitation. Desalination 519, 115302 (2021).Article 

Google Scholar 
Liu, D., Li, Z., He, L. & Zhao, Z. Facet engineered Li3PO4 for lithium recovery from brines. Desalination 514, 115186 (2021).Article 

Google Scholar 
Lai, X., Xiong, P. & Zhong, H. Extraction of lithium from brines with high Mg/Li ratio by the crystallization–precipitation method. Hydrometallurgy 192, 105252 (2020).Article 

Google Scholar 
Mendieta–George, D., Pérez–Garibay, R., Solís–Rodríguez, R., Fuentes–Aceituno, J. C. & Alvarado–Gómez, A. Study of the direct production of lithium phosphate with pure synthetic solutions and membrane electrolysis. Miner. Eng. 185, 107713 (2022).Article 

Google Scholar 
Cerda, A. et al. Recovering water from lithium-rich brines by a fractionation process based on membrane distillation–crystallization. J. Water Process. Eng 41, 102063 (2021). Membrane distillation-based DLE proposal to recover freshwater during brine concentration from high-salinity brines.Article 

Google Scholar 
Quist-Jensen, C. A., Ali, A., Mondal, S., Macedonio, F. & Drioli, E. A study of membrane distillation and crystallization for lithium recovery from high-concentrated aqueous solutions. J. Memb. Sci. 505, 167–173 (2016).Article 

Google Scholar 
Zhou, G. et al. Progress in electrochemical lithium ion pumping for lithium recovery. J. Energy Chem. 59, 431–445 (2021).Article 

Google Scholar 
Xu, P. et al. Materials for lithium recovery from salt lake brine. J. Mater. Sci. 56, 16–63 (2021).Article 

Google Scholar 
Wang, J. et al. Electrochemical technologies for lithium recovery from liquid resources: a review. Renew. Sustain. Energy Rev. 154, 111813 (2022).Article 

Google Scholar 
Sun, Y., Wang, Q., Wang, Y., Yun, R. & Xiang, X. Recent advances in magnesium/lithium separation and lithium extraction technologies from salt lake brine. Sep. Purif. Technol. 256, 117807 (2021).Article 

Google Scholar 
Nie, X.-Y., Sun, S.-Y., Sun, Z., Song, X. & Yu, J.-G. Ion-fractionation of lithium ions from magnesium ions by electrodialysis using monovalent selective ion-exchange membranes. Desalination 403, 128–135 (2017).Article 

Google Scholar 
Ding, D., Yaroshchuk, A. & Bruening, M. L. Electrodialysis through nafion membranes coated with polyelectrolyte multilayers yields >99% pure monovalent ions at high recoveries. J. Memb. Sci. 647, 120294 (2022).Article 

Google Scholar 
Li, Q. et al. Ultrahigh-efficient separation of Mg2+/Li+ using an in-situ reconstructed positively charged nanofiltration membrane under an electric field. J. Memb. Sci. 641, 119880 (2022).Article 

Google Scholar 
Qiu, Y. et al. Integration of selectrodialysis and selectrodialysis with bipolar membrane to salt lake treatment for the production of lithium hydroxide. Desalination 465, 1–12 (2019).Article 

Google Scholar 
Palagonia, M. S., Brogioli, D. & La Mantia, F. Lithium recovery from diluted brine by means of electrochemical ion exchange in a flow-through-electrodes cell. Desalination 475, 114192 (2020).Article 

Google Scholar 
Palagonia, M. S., Brogioli, D. & Mantia, F. L. Effect of current density and mass loading on the performance of a flow-through electrodes cell for lithium recovery. J. Electrochem. Soc. 166, E286–E292 (2019).Article 

Google Scholar 
Guo, Z.-Y. et al. Prefractionation of LiCl from concentrated seawater/salt lake brines by electrodialysis with monovalent selective ion exchange membranes. J. Clean. Prod. 193, 338–350 (2018).Article 

Google Scholar 
Zhao, L.-M. et al. Separating and recovering lithium from brines using selective-electrodialysis: sensitivity to temperature. Chem. Eng. Res. Des. 140, 116–127 (2018).Article 

Google Scholar 
Sharma, P. P. et al. Sulfonated poly (ether ether ketone) composite cation exchange membrane for selective recovery of lithium by electrodialysis. Desalination 496, 114755 (2020).Article 

Google Scholar 
Chen, Q.-B. et al. Development of recovering lithium from brines by selective-electrodialysis: effect of coexisting cations on the migration of lithium. J. Memb. Sci. 548, 408–420 (2018).Article 

Google Scholar 
Díaz Nieto, C. H. & Flexer, V. Is it possible to recover lithium compounds from complex brines employing electromembrane processes exclusively? Curr. Opin. Electrochem. 35, 101087 (2022).Article 

Google Scholar 
Li, X. et al. Highly selective separation of lithium with hierarchical porous lithium-ion sieve microsphere derived from MXene. Desalination 537, 115847 (2022).Article 

Google Scholar 
Parker SS, et al. Potential lithium extraction in the United States: environmental, economic, and policy implications (The Nature Conservancy, 2022); https://www.scienceforconservation.org/assets/downloads/Lithium_Report_FINAL.pdf.Arkansas Smackover Project. Standard Lithium https://www.standardlithium.com/projects/arkansas-smackover (2022).Grant, A. Re-injection enhanced production for direct lithium extraction (DLE) projects. https://www.jadecove.com/research/brinereinjection.Horne, R. N. Geothermal reinjection experience in Japan. J. Pet. Technol. 34, 495–503 (1982).Article 

Google Scholar 
Boo, C., Billinge, I. H., Chen, X., Shah, K. M. & Yin Yip, N. Zero liquid discharge of ultrahigh-salinity brines with temperature swing solvent extraction. Environ. Sci. Technol. 54, 9124–9131 (2020).Article 

Google Scholar 
Deshmukh, A. et al. Thermodynamics of solvent-driven water extraction from hypersaline brines using dimethyl ether. Chem. Eng. J. 434, 134391 (2022).Article 

Google Scholar 
Panagopoulos, A. Brine management (saline water & wastewater effluents): sustainable utilization and resource recovery strategy through minimal and zero liquid discharge (MLD & ZLD) desalination systems. Chem. Eng. Process. Process Intensif. 176, 108944 (2022).Article 

Google Scholar 
Al-Ghouti, M. A., Al-Kaabi, M. A., Ashfaq, M. Y. & Da’na, D. A. Produced water characteristics, treatment and reuse: a review. J. Water Process Eng. 28, 222–239 (2019).Article 

Google Scholar 
Samuel, O. et al. Oilfield-produced water treatment using conventional and membrane-based technologies for beneficial reuse: a critical review. J. Environ. Manag. 308, 114556 (2022).Article 

Google Scholar 
Arena, J. T. et al. Management and dewatering of brines extracted from geologic carbon storage sites. Int. J. Greenh. Gas Control 63, 194–214 (2017).Article 

Google Scholar 
Ogden, D. D. & Trembly, J. P. Desalination of hypersaline brines via Joule-heating: experimental investigations and comparison of results to existing models. Desalination 424, 149–158 (2017).Article 

Google Scholar 
Kaplan, R., Mamrosh, D., Salih, H. H. & Dastgheib, S. A. Assessment of desalination technologies for treatment of a highly saline brine from a potential CO2 storage site. Desalination 404, 87–101 (2017).Article 

Google Scholar 
Baspineiro, C. F., Franco, J. & Flexer, V. Potential water recovery during lithium mining from high salinity brines. Sci. Total Environ. 720, 137523 (2020).Article 

Google Scholar 
Sustainable production. SQM https://www.sqmlithium.com/en/nosotros/produccion-sustentable/ (2022).Sustainability Report (Orocobre, 2021); https://www.orocobre.com/wp/?mdocs-file=7259.Grant, A. From Catamarca to Qinghai: the Commercial Scale Direct Lithium Extraction Operations. Jadecove https://www.jadecove.com/research/fromcatamarcatoqinghai (2020).Sustainability report (Livent, 2021); https://livent.com/wp-content/uploads/2022/07/Livent_2021SustainabilityReport-English.pdf.Park, S. H. et al. Lithium recovery from artificial brine using energy-efficient membrane distillation and nanofiltration. J. Memb. Sci. 598, 117683 (2020). Pioneering DLE proposal to recover freshwater during brine concentration via nanofiltration followed by membrane distillation.Article 

Google Scholar 
Pramanik, B. K., Asif, M. B., Kentish, S., Nghiem, L. D. & Hai, F. I. Lithium enrichment from a simulated salt lake brine using an integrated nanofiltration-membrane distillation process. J. Environ. Chem. Eng. 7, 103395 (2019).Article 

Google Scholar 
Ko, C.-C. et al. Performance of ceramic membrane in vacuum membrane distillation and in vacuum membrane crystallization. Desalination 440, 48–58 (2018).Article 

Google Scholar 
Baspineiro, C. F., Franco, J. & Flexer, V. Performance of a double-slope solar still for the concentration of lithium rich brines with concomitant fresh water recovery. Sci. Total. Environ. 791, 148192 (2021).Article 

Google Scholar 
Ling, Z. et al. Desalination and Li+ enrichment via formation of cyclopentane hydrate. Sep. Purif. Technol. 231, 115921 (2020).Article 

Google Scholar 
Niu, J. et al. An electrically switched ion exchange system with self-electrical-energy recuperation for efficient and selective LiCl separation from brine lakes. Sep. Purif. Technol. 274, 118995 (2021).Article 

Google Scholar 
Nie, X.-Y., Sun, S.-Y., Song, X. & Yu, J.-G. Further investigation into lithium recovery from salt lake brines with different feed characteristics by electrodialysis. J. Memb. Sci. 530, 185–191 (2017).Article 

Google Scholar 
Jiang, C., Wang, Y., Wang, Q., Feng, H. & Xu, T. Production of lithium hydroxide from lake brines through electro-electrodialysis with bipolar membranes (EEDBM). Ind. Eng. Chem. Res. 53, 6103–6112 (2014).Article 

Google Scholar 
Díaz Nieto, C. H., Rabaey, K. & Flexer, V. Membrane electrolysis for the removal of Na+ from brines for the subsequent recovery of lithium salts. Sep. Purif. Technol. 252, 117410 (2020).Article 

Google Scholar 
Díaz Nieto, C. H. et al. Membrane electrolysis for the removal of Mg2+ and Ca2+ from lithium rich brines. Water Res. 154, 117–124 (2019).Article 

Google Scholar 
Ji, P.-Y. et al. Effect of coexisting ions on recovering lithium from high Mg2+/Li+ ratio brines by selective-electrodialysis. Sep. Purif. Technol. 207, 1–11 (2018).Article 

Google Scholar 
Lee, D.-H. et al. Selective lithium recovery from aqueous solution using a modified membrane capacitive deionization system. Hydrometallurgy 173, 283–288 (2017).Article 

Google Scholar 
Díaz Nieto, C. H., Kortsarz, J. A., Vera, M. L. & Flexer, V. Effect of temperature, current density and mass transport during the electrolytic removal of magnesium ions from lithium rich brines. Desalination 529, 115652 (2022).Article 

Google Scholar 
Li, X. et al. Taming wettability of lithium ion sieve via different TiO2 precursors for effective Li recovery from aqueous lithium resources. Chem. Eng. J. 392, 123731 (2020).Article 

Google Scholar 
Sun, J. et al. Preparation of high hydrophilic H2TiO3 ion sieve for lithium recovery from liquid lithium resources. Chem. Eng. J. 453, 139485 (2023).Article 

Google Scholar 
Qian, F. et al. Trace doping by fluoride and sulfur to enhance adsorption capacity of manganese oxides for lithium recovery. Mater. Des. 194, 108867 (2020).Article 

Google Scholar 
Taghvaei, N., Taghvaei, E. & Askari, M. Synthesis of anodized TiO2 nanotube arrays as ion sieve for lithium extraction. ChemistrySelect 5, 10339–10345 (2020).Article 

Google Scholar 
Qian, F. et al. Highly lithium adsorption capacities of H1.6Mn1.6O4 ion-sieve by ordered array structure. ChemistrySelect 4, 10157–10163 (2019).Article 

Google Scholar 
Sarmiento, N. et al. A solar irradiation GIS as decision support tool for the Province of Salta, Argentina. Renew. Energy 132, 68–80 (2019).Article 

Google Scholar 
Dellicompagni, P., Franco, J. & Flexer, V. CO2 emission reduction by integrating concentrating solar power into lithium mining. Energy Fuels 35, 15879–15893 (2021).Article 

Google Scholar 
Zavahir, S. et al. A review on lithium recovery using electrochemical capturing systems. Desalination 500, 114883 (2021).Article 

Google Scholar 
Joo, H. et al. Pilot-scale demonstration of an electrochemical system for lithium recovery from the desalination concentrate. Environ. Sci. Water Res. Technol. 6, 290–295 (2020). Pilot-scale demonstration of processing 6 tonnes of brine daily using electrochemical ion pumping.Article 

Google Scholar 
Song, J. F., Nghiem, L. D., Li, X.-M. & He, T. Lithium extraction from Chinese salt-lake brines: opportunities, challenges, and future outlook. Environ. Sci. Water Res. Technol. 3, 593–597 (2017). Thorough review of pilot-scale projects for lithium mining from brines in China.Article 

Google Scholar 
Yu, C. et al. Bio-inspired fabrication of ester-functionalized imprinted composite membrane for rapid and high-efficient recovery of lithium ion from seawater. J. Colloid Interf. Sci. 572, 340–353 (2020).Article 

Google Scholar 
Lu, J. et al. Multilayered ion-imprinted membranes with high selectivity towards Li+ based on the synergistic effect of 12-crown-4 and polyether sulfone. Appl. Surf. Sci. 427, 931–941 (2018).Article 

Google Scholar 
Ryu, T. et al. Lithium recovery system using electrostatic field assistance. Hydrometallurgy 151, 78–83 (2015).Article 

Google Scholar 
Sun, Y., Wang, Y., Liu, Y. & Xiang, X. Highly efficient lithium extraction from brine with a high sodium content by adsorption-coupled electrochemical technology. ACS Sustain. Chem. Eng. 9, 11022–11031 (2021).Article 

Google Scholar 
Torres, W. R., Díaz Nieto, C. H., Prévoteau, A., Rabaey, K. & Flexer, V. Lithium carbonate recovery from brines using membrane electrolysis. J. Memb. Sci. 615, 118416 (2020). A DLE methodology with three consecutive electromembrane processes for the sequential recovery of magnesium, calcium and sodium by-products, together with lithium carbonate and concomitant fresh-water production in a circular economy framework.Article 

Google Scholar 
Du, X. et al. A novel electroactive λ-MnO2/PPy/PSS core–shell nanorod coated electrode for selective recovery of lithium ions at low concentration. J. Mater. Chem. A 4, 13989–13996 (2016).Article 

Google Scholar 
Luo, G. et al. Electrochemical lithium ions pump for lithium recovery from brine by using a surface stability Al2O3–ZrO2 coated LiMn2O4 electrode. J. Energy Chem. 69, 244–252 (2022).Article 

Google Scholar 
Oyarce, E., Roa, K., Boulett, A., Salazar-Marconi, P. & Sánchez, J. Removal of lithium ions from aqueous solutions by an ultrafiltration membrane coupled to soluble functional polymer. Sep. Purif. Technol. 288, 120715 (2022).Article 

Google Scholar 
Han, H. J., Qu, W., Zhang, Y. L., Lu, H. D. & Zhang, C. L. Enhanced performance of Li+ adsorption for H1.6Mn1.6O4 ion-sieves modified by Co doping and micro array morphology. Ceram. Int. 47, 21777–21784 (2021).Article 

Google Scholar 
Zhu, X. et al. Study on adsorption extraction process of lithium ion from West Taijinar brine by shaped titanium-based lithium ion sieves. Sep. Purif. Technol. 274, 119099 (2021).Article 

Google Scholar 
Meng, Z. et al. Highly flexible interconnected Li+ion-sieve porous hydrogels with self-regulating nanonetwork structure for marine lithium recovery. Chem. Eng. J. 445, 136780 (2022).Article 

Google Scholar 
Xiong, J., Zhao, Z., Liu, D. & He, L. Direct lithium extraction from raw brine by chemical redox method with LiFePO4/FePO4 materials. Sep. Purif. Technol. 290, 120789 (2022).Article 

Google Scholar 
Vera, M. L. et al. A strategy to avoid solid formation within the reactor during magnesium and calcium electrolytic removal from lithium-rich brines. J. Solid State Electrochem. https://doi.org/10.1007/s10008-022-05219-6 (2022).Article 

Google Scholar 
Lide, D. R. CRC Handbook of Chemistry and Physics (CRC Press. Boca Raton, 2005).Neumann, J. et al. Recycling of lithium-ion batteries — current state of the art, circular economy, and next generation recycling. Adv. Energy Mater. 12, 2102917 (2022).Article 

Google Scholar 
Amici, J. et al. A roadmap for transforming research to invent the batteries of the future designed within the European large scale research initiative BATTERY 2030+. Adv. Energy Mater. 12, 2102785 (2022).Article 

Google Scholar 
Graedel, T. E. et al. What do we know about metal recycling rates? J. Ind. Ecol. 15, 355–366 (2011).Article 

Google Scholar 
Kinnunen, P. H.-M. & Kaksonen, A. H. Towards circular economy in mining: opportunities and bottlenecks for tailings valorization. J. Clean. Prod. 228, 153–160 (2019).Article 

Google Scholar 
Falagán, C., Grail, B. M. & Johnson, D. B. New approaches for extracting and recovering metals from mine tailings. Miner. Eng. 106, 71–78 (2017).Article 

Google Scholar 
Nwaila, G. T. et al. Valorisation of mine waste — part I: characteristics of, and sampling methodology for, consolidated mineralised tailings by using Witwatersrand gold mines (South Africa) as an example. J. Environ. Manage. 295, 113013 (2021).Article 

Google Scholar 
Singh, S., Sukla, L. B. & Goyal, S. K. Mine waste & circular economy. Mater. Today Proc. 30, 332–339 (2020).Article 

Google Scholar 
Purnell, P., Velenturf, A. P. M. & Marshall, R. New Governance for Circular Economy: Policy, Regulation and Market Contexts for Resource Recovery from Waste. (eds. Macaskie, L. E. et al.) Ch. 16 (Royal Society of Chemistry, 2019).Velenturf, A. P. M. et al. Circular economy and the matter of integrated resources. Sci. Total Environ. 689, 963–969 (2019).Article 

Google Scholar 
Yang, Y. et al. Research advances in magnesium and magnesium alloys worldwide in 2020. J. Magnes. Alloy. 9, 705–747 (2021).Article 

Google Scholar 
Løvik, A. N., Hagelüken, C. & Wäger, P. Improving supply security of critical metals: current developments and research in the EU. Sustain. Mater. Technol. 15, 9–18 (2018).
Google Scholar 
Potash. Albemarle https://www.albemarle.com/businesses/lithium/products/pot-ash (2023).Production processes. SQM https://www.sqm.com/en/acerca-de-sqm/recursos-naturales/proceso-de-produccion/ (2018).Thiel, G. P. & Lienhard V, J. H. Treating produced water from hydraulic fracturing: composition effects on scale formation and desalination system selection. Desalination 346, 54–69 (2014).Article 

Google Scholar 
Shaffer, D. L. et al. Desalination and reuse of high-salinity shale gas produced water: drivers, technologies, and future directions. Environ. Sci. Technol. 47, 9569–9583 (2013).Article 

Google Scholar 
Ogunbiyi, O. et al. Sustainable brine management from the perspectives of water, energy and mineral recovery: a comprehensive review. Desalination 513, 115055 (2021).Article 

Google Scholar 
Kumar, A. et al. Metals recovery from seawater desalination brines: technologies, opportunities, and challenges. ACS Sustain. Chem. Eng. 9, 7704–7712 (2021).Article 

Google Scholar 
Snæbjörnsdóttir, S. Ó. et al. Carbon dioxide storage through mineral carbonation. Nat. Rev. Earth Environ. 1, 90–102 (2020).Article 

Google Scholar 
Saccò, M. et al. Salt to conserve: a review on the ecology and preservation of hypersaline ecosystems. Biol. Rev. 96, 2828–2850 (2021).Article 

Google Scholar 
Chiappero, M. F., Vaieretti, M. V. & Izquierdo, A. E. A baseline soil survey of two peatlands associated with a lithium-rich salt flat in the argentine puna: physico-chemical characteristics, carbon storage and biota. Mires Peat 27, 16 (2021).
Google Scholar 
Batanero, G. L. et al. Flamingos and drought as drivers of nutrients and microbial dynamics in a saline lake. Sci. Rep. 7, 12173 (2017).Article 

Google Scholar 
Avila-Arias, H., Nies, L. F., Gray, M. B. & Turco, R. F. Impacts of molybdenum-, nickel-, and lithium-oxide nanomaterials on soil activity and microbial community structure. Sci. Total. Environ. 652, 202–211 (2019).Article 

Google Scholar 
Robinson, B. H., Yalamanchali, R., Reiser, R. & Dickinson, N. M. Lithium as an emerging environmental contaminant: mobility in the soil–plant system. Chemosphere 197, 1–6 (2018).Article 

Google Scholar 
Bolan, N. et al. From mine to mind and mobiles — lithium contamination and its risk management. Environ. Pollut. 290, 118067 (2021).Article 

Google Scholar 
Shokri-Kuehni, S. M. S., Norouzi Rad, M., Webb, C. & Shokri, N. Impact of type of salt and ambient conditions on saline water evaporation from porous media. Adv. Water Resour. 105, 154–161 (2017).Article 

Google Scholar 
Obaya, M., López, A. & Pascuini, P. Curb your enthusiasm. Challenges to the development of lithium-based linkages in Argentina. Resour. Policy 70, 101912 (2021).Article 

Google Scholar 
Risacher, F., Alonso, H. & Salazar, C. The origin of brines and salts in Chilean salars: a hydrochemical review. Earth-Sci. Rev. 63, 249–293 (2003).Article 

Google Scholar 
Corenthal, L. G., Boutt, D. F., Hynek, S. A. & Munk, L. A. Regional groundwater flow and accumulation of a massive evaporite deposit at the margin of the Chilean Altiplano. Geophys. Res. Lett. 43, 8017–8025 (2016).Article 

Google Scholar 
Vásquez, C., Ortiz, C., Suárez, F. & Muñoz, J. F. Modeling flow and reactive transport to explain mineral zoning in the Atacama salt flat aquifer, Chile. J. Hydrol. 490, 114–125 (2013).Article 

Google Scholar  More

Chasing Icebergs: How Frozen Freshwater Can Save the Planet Matthew H. Birkhold Viking (2023)The flavour of chilled Svalbarði-brand water, melted from an iceberg just 1,000 kilometres from the North Pole, is described by the company as “like catching snowflakes on the tongue”. Bottled in Longyearbyen, a tiny metropolis in Norway’s Svalbard archipelago, Svalbarði water is airlifted to luxury locales in London, Sydney, Florida and Macau. “Taste the Arctic to Save the Arctic,” its website croons, promoting the supposed carbon neutrality of the water, which sells online for €99.95 (US$107) for a 750-millilitre bottle.That price is far out of reach for most of the world’s people, including the one in four who lack safe drinking water. In Chasing Icebergs, Matthew Birkhold, a scholar of law, culture and the humanities, considers whether it’s possible to slake the world’s thirst with the two-thirds of global fresh water that is locked away in ice caps and glaciers — “stuck at the poles in gigantic fortresses of ice”, in his words.Some are already at it — and not just epicureans quaffing Svalbarði. In Newfoundland, Canada, Birkhold interviews “iceberg cowboy” Ed Kean, who wrangles bergs from the frigid sea, selling the water to cosmetics companies and breweries. In Qaanaaq, Greenland’s northernmost town, Birkhold notes, the public water supply includes filtered and treated iceberg melt.
Towing icebergs to arid regions to reduce water scarcity
There’s more where that came from. By one estimate, some 2,300 cubic kilometres of ice breaks off from Antarctica every year. More than 100,000 Arctic and Antarctic icebergs melt into the ocean annually, according to a 2022 United Nations report. A relatively small, 113-million-tonne iceberg, says Birkhold, could be towed from Antarctica to Cape Town, South Africa, to supply 20% of the city’s water needs for a year. What’s not to like?Quite a lot, perhaps. “To write this book, I have talked to dozens of scientists,” Birkhold writes. “They are uniformly dubious.” Palaeoclimatologist Ellen Mosley-Thompson has led nine expeditions to Antarctica and six to Greenland to extract ice cores. “Make sure you write that I am skeptical of iceberg towing,” she instructs him.Less sceptical is master mariner Nick Sloane, the brains behind the Cape Town plan. Using satellite data to find the best berg, his “team of glaciologists, engineers and oceanographers” plans to catch it in a giant net and pull it by tugboat into the mighty Antarctic Circumpolar Current, and thence into the north-flowing Benguela Current towards South Africa.

Icebergs are sometimes towed to prevent damage to oil platforms.Credit: Greg Locke/Reuters

Sloane has estimated the cost at a cool $100 million, plus an extra $50 million or so to melt the ice and funnel the fresh water to land, if the iceberg hasn’t melted into the sea or fallen apart en route. In various interviews, Cape Town officials have expressed themselves as less than enthused.Sloane’s plans have yet to materialize. Meanwhile, POLEWATER, a Berlin-based company, has been working for almost a decade on a similar plan — to haul frozen fresh water to the western coast of Africa and the Caribbean, where the company intends to give it away to those in dire need. It, too, will use satellites to locate suitable bergs, but once it has relocated them, it plans to pump meltwater from pools on top into easily transportable gigantic bags.Then there’s the UAE Iceberg Project, the dream of Emirati inventor Abdulla Alshehhi to import an Antarctic iceberg to the Fujairah coast of the United Arab Emirates. An animated promotion features penguins and polar bears — species hailing from opposite poles — posing dolefully on the iceberg. Alshehhi has said that “it will be cheaper to bring in these icebergs” than to desalinate seawater — a common technique in the Middle East.
World’s largest ice sheet threatened by warm water surge
Desalination provides at least 35 trillion litres of drinking water globally every year. Birkhold notes that it is prohibitively expensive in many places. It also relies on fossil fuels for energy, and pollutes the ocean with excess salt. But he offers limited information on other, perhaps more effective, alternatives to iceberg towing, such as recycling municipal wastewater or tapping brackish water for crop irrigation. He offers no data on more esoteric sources of water, such as fog harvesting, used by remote communities in Chile, Morocco and South Africa. Nor does he address initiatives to reduce water waste or increase efficiency of use.Birkhold speculates that if iceberg harvesting succeeds, it might not remain the province of quixotic entrepreneurs — bigger, water-hungry enterprises might muscle in with their “deep coffers and profit-driven approach”. The race is largely unregulated: few national laws address iceberg use, and no international agreements clarify who can capture and sell these freshwater resources. If they are to be exploited fairly, the author concludes, “we need to decide who gets to use icebergs — and how and how many — in a way that is just and equitable”.Birkhold is engagingly honest about potential pitfalls. But if the enterprise could succeed, enormous quantities of fresh water that would otherwise melt into the ocean could be delivered to parched regions. Kudos to the author for diving in — whether or not it is ever realized.

Competing Interests
The author declares no competing interests. More

Study design and hypothesesThe encouragement of the Chinese central government to local governments to adopt the PPP model through the top-down procedure and build and operate WTI has created favourable external policy circumstances for the development of wastewater treatment PPP projects. However, the acceptance of the PPP model by both local governments and private capital is rooted in the positive effect of it on improving the UWTE. In China there is no completely private-owned WTI before. Compared to the original government monopoly on the construction and operation of the WTI, the introduction of private capital participation is equipped with conditions to improve the UWTE. The participation of private capital can donate sufficient funds, scientific management experience, and advanced technology to the construction and operation of the regional, quasi-natural monopoly, and public welfare WTI21, which are key elements that determine the UWTE. Furthermore, the urban wastewater treatment field was in a state of no market competition before the introduction of private capital, and the government’s early monopoly ensured that private capital could obtain both economic benefits and performance with exclusive agency rights after joining. Meanwhile, the government would conduct a performance assessment of the quality of wastewater treatment during construction and operation, and private capitals whose wastewater treatment efficiency failed to meet the requirements would be barred from obtaining performance benefits40. Therefore, private capital is inherently incentivised to ensure the UWTE and minimise profit loss. Most of the private capital involved in the construction and operation of WTI in China comes from state-owned enterprises, partly due to the remarkable cooperation between the local government and state-owned enterprises at the beginning of the market economy reform41. This is convenient for both sides in reducing the cost of supervising due to information asymmetry in the principal-agent relationship and to facilitate the unique advantages of state-owned capital to undertake social responsibility. Therefore, Hypothesis 1 is proposed:UWTE is high in prefecture-level cities that have introduced the PPP model compared to prefecture-level cities that have not adopted the PPP model for the construction and operation of WTI.The return mechanism is related to the risk sharing of the costs of WTI construction and operation. Part of the purpose of introducing private capital is to share the cost risk of the government’s monopoly on the construction and operation of infrastructure by exchanging the government’s appropriate concession of operating revenue42; however, excessive cost and risk sharing reduces the probability of private capital participation in the construction and operation of infrastructure43. In China, the return mechanisms of the public–private WTI include user payment, government payment, and feasibility gap subsidy, of which the cost risks of construction and operation under the first two return mechanisms are primarily borne unilaterally by the private capital and the government, respectively44, whereas the cost risks of construction and operation under the latter are borne by the government to fill the gap of user payment39. Accordingly, Hypothesis 2 is proposed:The return mechanism of the feasibility gap subsidy has a greater impact on improving the UWTE than the mechanisms of user payment and government payment.The way to choose private capital to cooperate with the government is related to the efficiency of the construction and operation of the WTI. Private capital selected through competitive procurement usually exhibits sufficient funds, scientific management experience, and innovative technology45. Cooperation between the government and this type of private partner helps obtain the optimal construction and operation plan at the lowest cost. The adoption of competitive procurement can improve efficiency while saving transaction costs, especially for infrastructures with large capital scale and long term and complicated operational systems, such as urban wastewater treatment38. In China, the competitive procurement mechanism of PPPs for WTI includes public bidding, competitive negotiation, invitational bidding, and competitive consultation, whereas the non-competitive procurement mechanism mainly refers to single-source procurement46. In accordance with this, Hypothesis 3 is proposed:The competitive procurement mechanism has a greater impact on improving the UWTE than the single-source procurement mechanism.The PPP is ultimately a contract between the principal and the agent that specifies how risks are shared and how benefits are distributed40. Construction and operation of WTI under the PPP model usually require long-term contracts. This means that contracts are often incomplete, and the allocation of remaining control rights has a significant impact on the incentives for private capital parties to participate. Existing research suggests that the greater the remaining control the private capital receives, the stronger their incentive to participate in the construction and operation of infrastructure, and the more they pursue innovation and efficiency47. The remaining control right is related to the manner in which the infrastructure is operated48. In China, PPPs for WTI operate through outsourcing (e.g. Operation and Maintenance [OM], Management Contract [MC], and Build-Transfer [BT]), franchising (e.g. Build-Operate-Transfer [BOT], Build-Own-Operate-Transfer [BOOT], Transfer-Operate-Transfer [TOT], and Rehabilitate-Operate-Transfer [ROT]), and privatisation (e.g. Build-Own-Operate [BOO] and Buy-Build-Operate [BBO]). Therefore, Hypothesis 4 is proposed:Privatised operations have a greater impact on improving UWTE than outsourcing and franchising.Promotion after demonstration has long been a feature of public policy formulation and implementation by the Chinese government, and this is also true for the construction and operation of wastewater treatment PPP projects. Selecting a portion of these projects for demonstration can facilitate pre-judgement of the issues encountered in the construction and operation of infrastructure and improve efficiency49. The demonstration of WTI is prioritised for various government policies and funding support and is subject to stringent monitoring by the government50. Therefore, to obtain priority support from the government, WTIs that have not entered the demonstration have greater motivation to perform higher quality wastewater treatment. In this case, Hypothesis 5 is proposed:Wastewater treatment PPP projects that have not yet entered the demonstration have a UWTE higher than those that have been in the demonstration.Quantifying the UWTE using DEAIn order to measure the efficiency represented by the capacity to increase output at a given input, two methods have been proposed. One is the estimation method based on parameters. The common method is stochastic frontier analysis (SFA). The other is based on the nonparametric estimation method, and the DEA is the most widely used. Although SFA can consider the influence of random factors on output, it needs to determine the specific form of production frontier as the condition when measuring efficiency. This means that if the pre-set production function form is inconsistent with the reality, the efficiency of the measure is not accurate. In contrast, the advantage of DEA is that there is no need to presuppose a specific production function form. It is based on a number of input and output indicators, using the method of linear programming, with the data envelope frontier as the comparison base, the decision making unit (DMU) of the same type of relative evaluation to determine the efficiency. In addition, DEA can also give the improvement space of each DMU in terms of input and output, which is convenient to give optimisation suggestions. Thus, DEA is widely used to assess the efficiency of public services, the environment, and natural resources fields51. With different settings of comparative DMUs, DEA can be divided into the CCR model, which assumes that the comparative DMUs meet the condition of constant returns to scale, and the BCC model, which assumes that the comparative DMUs meet the condition of variable returns to scale, and Shephard distance function introduced to distinguish pure technical efficiency from scale efficiency and determine whether the DMU production is optimal. Most studies have concluded that the BCC model is more consistent with the reality of production52; therefore, it is widely accepted and adopted compared to the CCR model. In this study, DEA based on the BCC model was used to measure the UWTE. The length of the urban wastewater network and the daily treatment capacity of urban wastewater treatment plants are established as input indicators, and the total amount of urban wastewater treatment is established as the output indicator53. The efficiency for each DMU is measured by solving the following linear programming of the BCC model, shown in Eq. (1):$$begin{array}{l}max theta \ s.t.mathop {sum }limits_{i = 1}^{283} lambda _i cdot lwn_i le lwn_{i_0}\ mathop {sum }limits_{i = 1}^{283} lambda _i cdot dtc_i le dtc_{i_0}\ mathop {sum }limits_{i = 1}^{283} lambda _i cdot tawt_i le theta tawt_{i_0}\ lambda _i ge 0\ mathop {sum }limits_{i = 1}^{283} lambda _i = 1end{array}$$
(1)
where subscript θ denotes the evaluated DMU. lwni and dtci represent the inputs, i.e. length of the wastewater network and the daily treatment capacity of urban wastewater treatment plants in prefecture-level city i, respectively, and the output is tawti, the total amount of wastewater treatment of each prefecture-level city. is a λ vector of intensity variable, and θ represents the efficiency score based on the input-output calculation. This is the UWTE to be calculated in this study.Causal linking the PPPs to the UWTE using DEA-Tobit regression modelThe DEA-Tobit regression model was used to empirically test the causal relationship between the PPPs and the UWTE. It is meaningful to use DEA to measure the UWTE, because the measured relative efficiency can be used to evaluate the capacity of urban wastewater treatment, and make it possible to compare the capacity of urban wastewater treatment between prefecture-level cities, and also creates conditions for finding the factors affecting the UWTE. As the range of UWTE measured by DEA is between 0 and 1, it does not obey the normal distribution and violates the classical assumption of ordinary least squares estimation. Therefore, in order to avoid the bias caused by OLS estimation, the restricted dependent variable model, also known as the Tobit regression model, is usually adopted in previous studies. The regression model which combines DEA and the Tobit regression model is also called the DEA-Tobit regression model. This study employs a DEA-Tobit regression model based on panel data, shown in Eq. (2).$$uwte_{it} = beta _0 + beta _1 cdot PPP_{it} + X^prime cdot gamma + varepsilon _{it}$$
(2)
where uwte denotes the efficiency of urban wastewater treatment. PPP denotes the degree of development of urban wastewater treatment PPP projects, which is measured in three calibres by determining the presence or absence of wastewater treatment PPP projects, the number of wastewater treatment PPP projects, and the investment amount of wastewater treatment PPP projects. X′ denotes other main control variables that potentially affect UWTE including population density, urbanisation rate, GDP per capita, industrialisation rate, openness, and green innovations. i and t represent prefecture-level city and year, respectively. β0 and εit denote the intercept term and the random disturbance term, respectively. β1 and γ are both parameters to be estimated, and β1 is significantly positive, indicating that the PPP model has a significant positive effect on the UWTE. Because the DEA-Tobit regression model with panel data does not have consistent and unbiased parameter estimates obtained under the fixed effects, the random effects estimation method is used in this study, referring to the parameter estimation recommendations presented by Liu et al.54Measurements of dependent, explanatory and control variablesThe dependent variable in this study is the UWTE. As mentioned above, we use DEA based on the BCC model to measure the UWTE. The closer the value of UWTE is to 1, the higher the efficiency is; the closer it is to 0, the lower the efficiency is.The degree of PPP development is the key explanatory variable of this study. It can be measured in various ways. The most common approach is determining the presence or absence of PPP projects, the number of PPP projects, and the investment amount of PPP projects31,33. To assess the impact of PPP on the UWTE in a comprehensive and reliable manner, this study uses all three metrics simultaneously.The endogeneity of mutual causation must be addressed when investigating the causal relationship between PPPs and the UWTE. This is because prefecture-level cities that use PPP models to build and operate WTI may consider wastewater treatment to be important, for example, the promotion of local government officials is closely related to the quality of public services in their jurisdictions during their tenure. To obtain a higher promotion probability, these prefecture-level cities focus on the efficiency of urban public services, including wastewater treatment, and the higher UWTE determines their willingness to adopt PPPs. Therefore, this study uses instrumental variables to eliminate the endogeneity problem in the regression analysis.Exogenous and correlation conditions are required for suitable instrumental variables. Waste treatment PPP development measured by determining the presence or absence and the number of waste treatment PPP projects is an instrumental variable for the degree of wastewater treatment PPP projects. This is because waste treatment and wastewater treatment are both urban environmental protection infrastructures. Furthermore, prefecture-level cities that consider wastewater treatment are highly likely to consider waste treatment, which are highly correlated. The PPP development for waste treatment does not directly affect the UWTE. Furthermore, the mean number of wastewater PPP projects in neighbouring prefecture-level cities in the prefecture-level city’s province was an instrumental variable for wastewater treatment PPP projects there. This is because, on the one hand, local government officials proactively follow the practices of other neighbouring prefecture-level cities in the province55. Assuming that other neighbouring prefecture-level cities in the province are inclined to promote wastewater treatment PPP projects, the prefecture-level city is highly likely to adopt a PPP model for the construction and operation of WTI. However, the mean number of wastewater treatment PPP projects in other neighbouring prefecture-level cities in the province will not directly affect UWTE in the prefecture-level city.Control variables: based on IPAT theory56, population density, urbanisation rate, GDP per capita, industrialisation rate, openness, and green innovations were selected in this study to measure the influence of three dimensions of population, wealth, and technology on the UWTE. The population density is measured as the urban population divided by the urban area. The higher the population density, the greater the need for an urban wastewater treatment capacity. The urbanisation rate is calculated as the share of urban population in the total population of the prefecture-level city. The higher the urbanisation rate, the higher the population in urban areas and the higher the demand for urban wastewater treatment capacity. Meanwhile, the urban population produces relatively more wastewater.GDP per capita is measured as GDP divided by population. The higher the GDP per capita, the higher the level of economic development of the prefecture-level city, and the more the government can regulate urban wastewater35, thus affecting the UWTE. The industrialisation rate is obtained by calculating the ratio of the output value of the secondary industry to GDP. The higher the industrialisation rate, the greater the demand for urban water resources, and more wastewater discharges are generated2, which affects the UWTE. Openness is measured by the proportion of imports and exports to GDP. The higher the openness, the more likely it is to attract companies with advanced environmental technologies57, reducing the amount of wastewater discharged from the prefecture-level city’s production sector. The ‘pollution heaven’ hypothesis may attract additional pollution discharge enterprises to the prefecture-level city58, affecting the prefecture-level city’s UWTE. Green innovations are measured using the number of green patents for wastewater treatment. Green patents for wastewater treatment are obtained from the Green List of International Patent Classification provided by the World Intellectual Property Organization (WIPO). If there are green patents for wastewater treatment, the reduction of wastewater discharge from enterprises is more likely, and thus the UWTE is improved59. This study considers the logarithm of the number of green patents for wastewater treatment to avoid the influence of data heteroscedasticity on the regression estimation results.DataThe research sample in this study comprised 1303 wastewater treatment PPP projects in 283 prefecture-level cities in China from 2014 to 2019, excluding Hong Kong, Macao, and Taiwan. To estimate the impact of PPPs on the UWTE, we needed data on the length of urban wastewater network, daily treatment capacity of urban wastewater treatment plants, total amount of urban wastewater treatment, wastewater treatment PPP projects, population density, urbanisation rate, GDP per capita, industrialisation rate, openness, and green innovations. Data on the length of the urban wastewater network, the daily treatment capacity of urban wastewater treatment plants, and the total amount of urban wastewater treatment were obtained from the China Urban Construction Statistical Yearbook 2014–201960. The PPP data were obtained from the Ministry of Finance’s Public–Private Partnerships Center61 and were captured by python technology. Data on population density, urbanisation rate, GDP per capita, industrialisation rate, and openness were obtained from China City Statistical Yearbook 2015–202062, and data on green patents were obtained from China National Intellectual Property Administration63. Supplementary Table 1 presents the descriptive statistics of the main variables, and Supplementary Fig. 1 reports the UWTE of 283 prefecture-level cities in China from 2014 to 2019. More

Overview of paper search outcomeA general overview of the 231 general water consumption-related and 48 framework analysis scientific publications reviewed in this study (Fig. 3) shows that the number of papers published per year from the general water consumption-related set has been increasing, particularly since the early 2000s. Peaks of more than 10 papers per year in this category emerge since 2011, with a maximum peak of 34 papers recorded in 2018. This increasing trend in time can be attributed to the increasing development of smart metering studies, which have been increasingly allowing detailed household water demand/consumption and behavioral analysis20,47. As a selected subset of the general water consumption-related papers set, the number of framework analysis papers has also increased in the last decade, compared to the ’80s and ’90s, constituting up to 5 papers per year. The final set of papers includes small-case studies comprising only a few units (11 individual households are considered as a minimum in48), as well as large-scale studies comprising several thousands of households (e.g., more than 8000 individual households are considered in49), or entire communities/towns50.Fig. 3: Temporal development of the literature on the determinants of household water consumption.The yearly count of the 231 general water consumption-related (blue) and 48 framework analysis (orange) scientific publications reviewed in this study is represented for the last forty years.Full size imageFigure 4 shows the locations of the studies from the framework analysis set, with larger blue dots indicating more studies. The geographical distribution of the reviewed studies indicates that the interest in the determinants of water use is worldwide. Prominent interest emerges in particular areas, such as the US west coast, the east coast of Australia, and the Mediterranean area in Europe, perhaps reflecting the combination of areas more prone to drought and/or having the higher economic capacity to undertake water use related research.Fig. 4: Geographical locations of the 48 framework analysis papers.The location of the 48 framework analysis papers reviewed in this study is represented with blue markers. Marker size is proportional to the amount of studies in a specific location.Full size imageDeterminant representation by classFrom the analysis of the 48 framework analysis papers, we identified a range of heterogeneous determinants and quantified different combinations of determinant classes, namely observable, latent, and external (see Determinant classification). Figure 5 shows an overview of the representation for the different classes of determinants over the 48 analyzed papers. Observable determinants were the most popular (47 total studies, i.e., 98% representation), with latent and external having lower representation of 52% and 56%, respectively. The values represented in the figure confirm our hypotheses that observable determinants are more common in literature than latent determinants, due to their availability in public databases, either at the household level or at coarser spatial sub-urban scales (e.g., census data collected at the block group-level, such as those used in49). The slightly higher representation of external determinants, compared to latent determinants, is also as expected due to the widespread availability of weather records (e.g., temperature, rainfall) from national or international environmental agencies. While there is no full consensus in the literature on the effect of weather or price variables on water consumption51,52,53, the high degree of representation of external determinants demonstrates that they are considered in more than half of the studies.Fig. 5: Venn diagram of household water consumption determinants representation.The representation of different classes of determinants (observable, latent, and external) in the 48 reviewed framework analysis papers is represented with coloured circles. Intersections are also visualized. The size of each circle and the numerical labels indicate the number of studies in which each combination of determinant classes appeared.Full size imageIt is worth observing that multiple classes of determinants are simultaneously analyzed in most of the reviewed studies, with fewer than 20% analyzing observable variables alone. Further, almost every time external or latent variables are considered, they appear in combination with observable variables. Only one study specifically focused on analyzing the motivations for using and conserving water based on only latent determinants42, while no studies exclusively considered external variables. In contrast, nearly 30% of the studies included both observable and external variables, approximately 23% of the studies considered latent and external variables simultaneously, and 27% of the studies included all three types of determinant classes.The high representation of observable determinants (Fig. 5) suggests that observable variables are widespread in the literature on modelling and forecasting of household water consumption. The prevalence of this class of determinants seems also to confirm the findings from previous studies, which demonstrated that meteorological variables have a greater influence on medium-term prediction and urban/suburban scales, but socio-demographics become more relevant when household-scale and short-term water demand models are developed54,55.Individual determinant representation, impact, and effortTo facilitate interpretation of the numerical values we obtained for the three determinant assessment criteria (i.e., representation, impact, and effort) we defined some regions of interest for each criterion based on thresholds (see the regions labelled as low/high/very high in Fig. 6). We selected the threshold values used to delimit the above regions of interest based on visual inspection of the empirical distribution of the representation, impact, and effort values. This simplification is carried out to facilitate the inference of general qualitative conclusions, while accounting for the low number of papers and, at the same time, high number of determinants. As a result, representation values above/below 30% are considered high/low. Impact values below 75% are considered low, values between 75% and 90% are considered high, and values above 90% are considered very high. Effort rate values above/below 8 are considered high/low.Fig. 6: Individual analysis of representation, impact, and effort.The three criteria to perform determinant analysis, i.e., representation (top), impact (middle), and effort rate (bottom) are associated with individual determinants. Observable determinant class is shown in green, latent class in blue, and external in orange. Shaded background indicates different levels of intensity for each analysis criterion. See Tables 1–3 for determinant acronyms definition (the determinants included in the categories marked as “Other” in the tables are not represented for better clarity).Full size imageFrom the resulting data visualized in Fig. 6, we can infer the following insights about determinant representation, impact, and effort. First, the determinants with the highest representation (top plot in Fig. 6) were household income ( > 70%), family size ( > 60%), and age ( > 45%). As already suggested by the outcomes of class representation (Fig. 5), all the above determinants with high representation are observable. One exception is the awareness determinant, which is the only non-observable determinant we found with high representation. The majority of the other determinants had a representation rate of 10% to 30%.Second, the number of determinants with a high or very high impact (middle plot in Fig. 6) is much larger than the number of determinants with high representation. It must be noted that a high impact does not necessarily mean that a determinant was found to have a high influence on water consumption, but rather that it was found to have some influence on water consumption in many publications. Interestingly, some determinants from all classes achieve high or very high levels of impact. Observable determinants with very high impact include socio-demographic information (number of occupants), house characteristics (house age, value), and outdoor characteristics (garden size, and presence of rainwater tanks). While these latter attributes related to gardens ranked among those with the highest impact, garden composition was found to have one of the lowest impact rates across the analyzed studies. Also, the observable determinants related to the education level of occupants was found to have low impact. A latent variable that emerges as very important (GARD_C) is also related to garden characteristics, but, rather than representing any physical variable, it accounts for the psychological value given by occupants’ attitudes and habits towards gardening. Finally, all external variables were found to have high or very high impact, with rainfall and water price emerging as the two with impact above 90%.The bottom plot of Fig. 6 shows that there was a wide variability in the effort rate for each individual determinant. Data on most of the observable determinants can be generally gathered with low effort, but some (e.g., appliance inventory and irrigation system) require house visits, and thus require high effort. In turn, all latent variables display an effort rate higher than 6, and three out of four are classified as high-effort. Conversely, data on all external determinants can be retrieved with low effort, as they are usually available from national agencies (weather data) and water utilities (water price). Obtaining information on higher effort determinants likely requires getting in contact with individual householders, via phone/online surveys, or house visits.Overall, the results reported in Fig. 6 suggest that there are trade-offs between representation, impact, and effort. In the next section, we perform a joint analysis of the three criteria and their trade-off to infer the implications of the outcomes of this study for researchers and practitioners.Trade-off analysis and implications for researchers and practitionersFigure 7 shows the interaction between the representation, impact, and effort criteria. The distribution of blue and orange points in the figure demonstrates that there are different trade-offs among the three criteria. Each trade-off can have a different set of implications to derive recommendations for researchers and also practitioners. We identified the three groups of determinants marked with (A), (B), and (C) to illustrate the different needs of research and practice. Group A is characterized by high impact, high representation, and low effort. Determinants in this group include household family size, occupants’ age, and occupants’ income. This group of well-studied determinants with proven impact might be particularly interesting for practitioners aiming to gather knowledge on household water consumption with budget constraints. Group (B), which includes, among others, information on the household irrigation system, appliance efficiency, and occupant gender, is characterized by medium-to-high impact, but low representation, and a range of low to high effort. While this group might not be very appealing for practitioners due to low representation, researchers might be interested in focusing on these determinants to increase their representation and, thus, validate or contrast the limited findings on these determinants that appear in the literature. Finally, Group C refers to determinants with low representation and, compared to those in groups A and B, lower impact. As they also might require high gathering efforts, these determinants should be treated with caution until more research is performed to prove their potential impact on a larger sample of studies.Fig. 7: Trade-off analysis of determinant representation, impact, and effort.Impact (x-axis) vs Representation (y-axis) vs Effort (color) of each determinant. Each point refers to a specific determinant. See Tables 1–3 for determinant acronyms definition. The determinants classified as “High effort” are those with an effort value larger than 8.0, vice-versa for the “Low effort” determinants. Determinants are organized in three groups: Group A – high impact, high representation, and low effort; Group B – medium-to-high impact, low representation, and mixed low and high effort; Group C – low representation, low impact, mixed effort.Full size imageAccounting for similar trade-offs across the entire sample of determinants that we have identified from the review of the literature enables determinant-specific recommendations to be derived for practitioners and researchers. In the last step of this review and determinant classification effort we thus develop a trade-off analysis framework that considers different combinations of representation, effort, and impact to formulate such recommendations. In keeping with the goal of this study, our trade-off analysis aims at identifying groups of determinants that have proven cost-effective impact via extensive research and, thus, can be recommended for use in practice, compared with groups of determinants that require more research to address open questions related to representation, impact, and effort. The proposed trade-off analysis framework includes four main recommendation categories:UIn this category, we include determinants characterized by high representation, high/very high impact, and low effort. We consider these determinants as determinants that practitioners can “definitely use” (U), as they have been extensively researched and have been shown to have an impact in most cases, while being affordable. For the same reasons, higher levels of research priority should be devoted to less explored determinants, while these can serve as references. The determinants included in box (A) in Fig. 7 belong to this group.IR-UCIn this category, we classify those determinants characterized by low representation, high/very high impact, and low effort. Given their promising, but not extensively proven, impact, and overall affordability, further research on these determinants should be prioritized to increase their representation (IR). We consider these determinants as determinants that practitioners can “use with caution” (UC), as they have not been extensively researched, but at the same time might have high impact at low-cost. The determinants included in box (B) in Fig. 7 and classified as low effort (blue color) belong to this group.LE/IR-UCIn this category, we include determinants characterized by generally low representation, high/very high impact, and high effort. Similarly to the previous category, we believe that practitioners can use these determinants “with caution” (UC), as they have not been extensively researched and require high effort for data collection, but at the same time might have high/very high impact. Given their promising, but not extensively proven, impact, and high cost, further research on these determinants should be prioritized, primarily to lower the effort (LE) needed to collect them and, thus, facilitate their consideration in more studies (increased representation – IR). The determinants included in box (B) in Fig. 7 and classified as high effort (orange color) belong to this group.IR/LE/AI-NPIn this category, we include determinants characterized by low representation, low impact, and mainly high effort. Given the limited knowledge on these determinants, we suggest that these determinants are “not prioritized” (NP) for use by practitioners unless further research demonstrates that the effort required to collect these determinants is worth the benefit of considering them. Further research should then aim at increasing their representation (IR), lowering the effort needed to obtain data on these determinants (LE), and further assessing their impact (AI) to acquire better knowledge on their actual value. The determinants included in box (C) in Fig. 7 belong to this group.Summary information on the above categories is reported in Table 5. Based on the proposed trade-off analysis framework and the threshold values defined in Fig. 6, we associated each of the different determinants identified in the framework analysis papers with a level of recommendation (see Fig. 8). Some relevant insights for researchers and practitioners emerge. First, only observable determinants are classified as “U”. At present, there are some socio-demographic determinants (i.e., number of occupants, income level, and occupant age) that can be reliably used by practitioners in most cases to model household water consumption and can be easily and affordably retrieved.Table 5 Framework for trade-off analysis, based on representation, impact, and effort.Full size tableFig. 8: Household water consumption determinant classification and associated recommendations for practitioners and researchers based on individual determinants.Each household water consumption determinant identified in the framework analysis papers is associated with a level of recommendation. Determinants are classified according to the three defined classes (columns), i.e., observable, latent, and external. Four levels of recommendation (rows) are formulated for practitioners and researchers. They are sorted in decreasing order of representation and proven impact in research, as well as confidence for use in practical applications. Confidence for use in practical applications decreases going from green (“U” level of recommendation) to orange (“IR/LE/AI-NP” level of recommendation).Full size imageSecond, all external variables (i.e., average rainfall, temperature, and water price) are classified as IR-UC. Consequently, they have a proven impact, but have been used sporadically in connection with household water consumption (while they have been used more often at larger, urban scales), thus results might be case-specific and further research is needed to assess their impact on a larger number of studies.Third, a mix of observable and latent external variables deserves further research to lower effort (e.g., by improving technology/data gathering practices or identifying lower-effort proxies for the same type of information) and increase representation. These variables are either observable determinants, the collection of which requires significant effort and house visits/calls to occupants (e.g., to build an inventory of appliance efficiency or storing information on irrigation systems), or latent variables the impact of which is still not proven due to low representation. The increasing availability of high-resolution metering and behavioral studies fostered by smart metering development is likely to contribute more knowledge on these determinants and more complete guidelines for use by practitioners in the coming years7,17,20.Fourth, we would like to stress that the recommendation “Do not favor adoption until further research” for the determinants classified as IR/LE/AI-NP does not mean that they should not be considered in future applications or no research should be done on them. Conversely, we recognize that many existing studies are based on limited data or data with coarser spatio-temporal resolutions, thus conclusive statements on the impact of such determinants would require further validation. Since large uncertainty about their impact remains, more studies are actually needed to increase the representation of these determinants and increase the statistical significance and generality of their impact assessment. Joint research that also includes other determinants with higher levels of representation could be beneficial to discover more information on the determinants in this group and better understand whether practitioners should eventually include one/more of these determinants in their analysis. Further research could be also developed to assess the degree to which these determinants are correlated with others, and hence redundant, and to which extent these and other determinants can relate to particular characteristics of water consumption (e.g., demand peaks, end use components).Finally, some of the determinants that we recommend to use with caution (UC) in practice, and that should be prioritized for research, might become determinants to definitely use (U) in the future. Two limitations currently prevent us to recommend “definitely use” for these determinants, i.e., generally low representation and high effort for data collection. Low representation indicates that the determinant has not been well-studied in the literature. Hence it might not be generalizable to a wide range of locations. To address the disadvantages of low representation, the following is recommended for practitioners:

Check the literature and if there are studies with similar context (location/climate/application) to the practitioners’ required application, and the impact of the determinant is high, then the determinant could be considered for use.

Continue to monitor the literature, to see if new studies appear using that determinant.

The other limitation, high effort, means that in the reviewed past studies it has been costly for practitioners to collect some of the required determinants. With the advent and widespread use of new technologies, the effort required to collect some of the required high-effort determinants may be substantially reduced. Lowering the effort related to some high-impact, yet also high-effort, determinants (see, e.g., those indicated with orange color in Group B in Fig. 7) would have a two-fold benefit. The direct reduction of the costs required to collect information on those determinants will also enable wider consideration of these determinants in a larger number of studies, thus increasing their representation. As technology enhances the capture of such determinants, there is an opportunity to revisit past studies/datasets and increase the representation of these determinants, which might then transition to determinant group A in in Fig. 7. To address the current limitations and disadvantages of high effort, the following is recommended for practitioners:

Monitor the use of emerging technologies that provide an opportunity to lower the cost required to collect the determinant. For example, there is an opportunity for analysis of high resolution satellite maps/photos to provide automated estimates of observable determinants such as garden size (GSZE) over large number of households, which would lower the cost substantially56. Similarly, latent determinants such as water consumption awareness (AWARE_C) could be based on the uptake of user-friendly smart metering and phone apps on water consumption if they were widely available17,57.

Evaluate overall costs vs benefits based on preliminary experiments on small sample data (to evaluate benefits while avoiding high costs), and consider the use of lower cost proxy data for the “high effort” determinant.

These recommendations provide some guidance for practitioners to handle determinants classified as “use with caution”.Limitations and future researchThis work provides evidence and a quantitative framework for the analysis of household water consumption determinants, yet several limitations and questions remain for further research. First, alternative formulations of determinant representations, impact, and effort could lead to different results. This also stands for the subjective thresholds we adopted to distinguish between high and low representation, impact, and effort. Such thresholds and criteria formulation could be changed based on needs and subjective judgement.Second, in this review we focused on the analysis of individual determinants of household water consumption. However, some determinants could be correlated, present redundant information, or be accounted for in alternative ways to build models for forecasting water demand (e.g., rainfall amount versus rainfall occurrence53). Input feature engineering, variable redundancy, and data accuracy can substantially affect the performance of water demand models. Future studies focused on comparative analysis of alternative determinant formulations and inter-links/dependencies among different determinants can help define non-redundant determinant sets to train models of water demand and recommendations for variable pre-processing.Third, the findings of this study are consistent with previous review papers that identified both observable and latent variables as the most important with respect to domestic water consumption58. Yet, other meta-analyses and review studies found partly contradictory results. Differently from our study26, found that the most important determinants of water use behaviour are related to individual opportunities and motivations, gender, income, and education level. In turn59, formulated a model that accounted for a wide range of variables including demographics, dwelling characteristics, household composition, conservation intention, trust, perceptions, habits, and perceived behavioral control. It must be noted that the above studies do not consider household water consumption per se as we do here, but relate potential determinants of water consumption also to individual consumption or behavior changes (i.e., changes in water consumption over time). Future, potentially contrasting, studies could then expand the scope of this work and relax the exclusion criteria we adopted here to achieve more inclusive comparative analyses that investigate the effect of different determinants in relation to quantified intervals of total household water consumption, and other heterogeneous aspects of domestic water demand, including statistics on end use components (e.g., flow rate, duration, or frequency of individual appliances)60 and temporal changes of water consumption levels due to external stressors such as droughts, or demand management interventions39,49, for example.Fourth, the set of framework analysis papers includes case studies primarily located in the United States, Australia, and Europe (see Fig. 4). Geographical coverage is thus skewed. There is a need for more studies from other geographical regions (including countries with low-income economies) in order to obtain a more balanced picture and consolidate/expand the results obtained so far.Finally, recent works have highlighted that urban and household water demands have been modelled at different spatial and temporal resolutions47. The choice of the temporal and spatial resolution of interest is determined both by data availability and the specific modelling and management purpose. Multi-scale studies combining different levels of spatial and temporal aggregation of water demands and potential determinants would further advance our analysis and contextualize specific recommendations for data collection and processing at the different spatial and temporal scales of interest. More

Goh, P. S., Matsuura, T., Ismail, A. F. & Ng, B. C. The water-energy nexus: solutions towards energy-efficient desalination. Energy Technol. 5, 1136–1155 (2017).Article 

Google Scholar 
Jia, C., Yan, P., Liu, P. & Li, Z. Energy industrial water withdrawal under different energy development scenarios: a multi-regional approach and a case study of China. Renew. Sust. Energ. Rev. 135, 110224 (2021).Article 

Google Scholar 
Damkjaer, S. & Taylor, R. The measurement of water scarcity: defining a meaningful indicator. Ambio 46, 513–531 (2017).Article 

Google Scholar 
Venugopal, K. & Dharmalingam, S. Utilization of bipolar membrane electrodialysis for salt water treatment. Water Environ. Res. 85, 663–670 (2013).Article 
CAS 

Google Scholar 
Camacho, L. et al. Advances in membrane distillation for water desalination and purification applications. Water 5, 94–196 (2013).Article 

Google Scholar 
Cingolani, D., Eusebi, A. L. & Battistoni, P. Osmosis process for leachate treatment in industrial platform: economic and performances evaluations to zero liquid discharge. J. Environ. Manag. 203, 782–790 (2017).Article 
CAS 

Google Scholar 
Shahzad, M. W., Burhan, M., Ang, L. & Ng, K. C. in Emerging Technologies for Sustainable Desalination Handbook (ed. Gude, V. G.) Ch. 1 (Elsevier Science, 2018)Feria-Díaz, J. J., López-Méndez, M. C., Rodríguez-Miranda, J. P., Sandoval-Herazo, L. C. & Correa-Mahecha, F. Commercial thermal technologies for desalination of water from renewable energies: a state of the art review. Processes 9, 262 (2021).Article 

Google Scholar 
Ahmad, N. A., Goh, P. S., Yogarathinam, L. T., Zulhairun, A. K. & Ismail, A. F. Current advances in membrane technologies for produced water desalination. Desalination 493, 114643 (2020).Article 
CAS 

Google Scholar 
Errico, M. et al. Membrane assisted reactive distillation for bioethanol purification. Chem. Eng. Process 157, 108110 (2020).Article 
CAS 

Google Scholar 
Saren, S., Mitra, S., Miyazaki, T., Ng, K. C. & Thu, K. A novel hybrid adsorption heat transformer – multi-effect distillation (AHT-MED) system for improved performance and waste heat upgrade. Appl. Energy 305, 117744 (2022).Article 

Google Scholar 
Son, H. S., Shahzad, M. W., Ghaffour, N. & Ng, K. C. Pilot studies on synergetic impacts of energy utilization in hybrid desalination system: multi-effect distillation and adsorption cycle (MED-AD). Desalination 477, 114266 (2020).Shahzad, M. W., Burhan, M. & Ng, K. C. A standard primary energy approach for comparing desalination processes. NPJ Clean. Water 2, 1–7 (2019).Article 
CAS 

Google Scholar 
Zheng, X., Chen, D., Wang, Q. & Zhang, Z. Seawater desalination in China: retrospect and prospect. Chem. Eng. J. 242, 404–413 (2014).Article 
CAS 

Google Scholar 
Werber, J. R., Osuji, C. O. & Elimelech, M. Materials for next-generation desalination and water purification membranes. Nat. Rev. Mater. 1, 1–15 (2016).Article 

Google Scholar 
Mahmoud, K. A., Mansoor, B., Mansour, A. & Khraisheh, M. Functional graphene nanosheets: the next generation membranes for water desalination. Desalination 356, 208–225 (2015).Article 
CAS 

Google Scholar 
Homaeigohar, S. & Elbahri, M. Graphene membranes for water desalination. NPG Asia Mater. 9, e427–e427 (2017).Article 
CAS 

Google Scholar 
Li, X. et al. Enhancement of interfacial solar vapor generation by environmental energy. Joule 2, 1331–1338 (2018).Article 
CAS 

Google Scholar 
Brongersma, M. L., Halas, N. J. & Nordlander, P. Plasmon-induced hot carrier science and technology. Nat. Nanotechnol. 10, 25–34 (2015).Article 
CAS 

Google Scholar 
Ni, G. et al. Volumetric solar heating of nanofluids for direct vapor generation. Nano Energy 17, 290–301 (2015).Article 
CAS 

Google Scholar 
Wang, X., Ou, G., Wang, N. & Wu, H. Graphene-based recyclable photo-absorbers for high-efficiency seawater desalination. ACS Appl. Mater. Interfaces 8, 9194–9199 (2016).Article 
CAS 

Google Scholar 
Ghasemi, H. et al. Solar steam generation by heat localization. Nat. Commun. 5, 4449 (2014).Article 
CAS 

Google Scholar 
Han, X. et al. Intensifying heat using MOF‐isolated graphene for solar‐driven seawater desalination at 98% solar‐to‐thermal efficiency. Adv. Funct. Mater. 31, 2008904 (2021).Article 
CAS 

Google Scholar 
Luo, X. et al. The energy efficiency of interfacial solar desalination. Appl. Energy 302, 117581 (2021).Article 

Google Scholar 
Mahian, O., Kianifar, A., Kalogirou, S. A., Pop, I. & Wongwises, S. A review of the applications of nanofluids in solar energy. Int. J. Heat. Mass Transf. 57, 582–594 (2013).Article 
CAS 

Google Scholar 
Ni, G. et al. Steam generation under one sun enabled by a floating structure with thermal concentration. Nat. Energy 1, 1–7 (2016).Article 

Google Scholar 
Panchal, H., Patel, P., Patel, N. & Thakkar, H. Performance analysis of solar still with different energy-absorbing materials. Int. J. Ambient. Energy 38, 224–228 (2015).Article 

Google Scholar 
Li, S.-F., Liu, Z.-H., Shao, Z.-X., Xiao, H.-S. & Xia, N. Performance study on a passive solar seawater desalination system using multi-effect heat recovery. Appl. Energy 213, 343–352 (2018).Article 

Google Scholar 
Yin, Z. et al. Extremely black vertically aligned carbon nanotube arrays for solar steam generation. ACS Appl. Mater. Interfaces 9, 28596–28603 (2017).Article 
CAS 

Google Scholar 
Wang, Z. et al. A wood–polypyrrole composite as a photothermal conversion device for solar evaporation enhancement. J. Mater. Chem. A 7, 20706–20712 (2019).Article 
CAS 

Google Scholar 
Ghim, D., Jiang, Q., Cao, S., Singamaneni, S. & Jun, Y.-S. Mechanically interlocked 1T/2H phases of MoS2 nanosheets for solar thermal water purification. Nano Energy 53, 949–957 (2018).Article 
CAS 

Google Scholar 
Ito, Y. et al. Multifunctional porous graphene for high-efficiency steam generation by heat localization. Adv. Mater. 27, 4302–4307 (2015).Article 
CAS 

Google Scholar 
Li, T., Fang, Q., Xi, X., Chen, Y. & Liu, F. Ultra-robust carbon fibers for multi-media purification via solar-evaporation. J. Mater. Chem. A 7, 586–593 (2019).Article 
CAS 

Google Scholar 
Liu, H. et al. Narrow bandgap semiconductor decorated wood membrane for high-efficiency solar-assisted water purification. J. Mater. Chem. A 6, 18839–18846 (2018).Article 
CAS 

Google Scholar 
Wang, G. et al. Reusable reduced graphene oxide based double-layer system modified by polyethylenimine for solar steam generation. Carbon 114, 117–124 (2017).Article 
CAS 

Google Scholar 
Yang, Y. et al. Two-dimensional flexible bilayer janus membrane for advanced photothermal water desalination. ACS Energy Lett. 3, 1165–1171 (2018).Article 
CAS 

Google Scholar 
Wang, Y., Wu, X., Yang, X., Owens, G. & Xu, H. Reversing heat conduction loss: extracting energy from bulk water to enhance solar steam generation. Nano Energy 78, 105269 (2020).Article 
CAS 

Google Scholar 
Zhu, M. et al. Plasmonic wood for high-efficiency solar steam generation. Adv. Energy Mater. 8, 1701028 (2018).Article 

Google Scholar 
Gong, F. et al. Scalable, eco-friendly and ultrafast solar steam generators based on one-step melamine-derived carbon sponges toward water purification. Nano Energy 58, 322–330 (2019).Article 
CAS 

Google Scholar 
Kong, Y. et al. Self-floating maize straw/graphene aerogel synthesis based on microbubble and ice crystal templates for efficient solar-driven interfacial water evaporation. J. Mater. Chem. A 8, 24734–24742 (2020).Article 
CAS 

Google Scholar 
Wang, M., Wang, P., Zhang, J., Li, C. & Jin, Y. A ternary Pt/Au/TiO2 -decorated plasmonic wood carbon for high-efficiency interfacial solar steam generation and photodegradation of tetracycline. ChemSusChem 12, 467–472 (2019).Article 
CAS 

Google Scholar 
Li, T. et al. Scalable and highly efficient mesoporous wood-based solar steam generation device: localized heat, rapid water transport. Adv. Funct. Mater. 28, 1707134 (2018).Article 

Google Scholar 
Liu, K. K. et al. Wood-graphene oxide composite for highly efficient solar steam generation and desalination. ACS Appl. Mater. Interfaces 9, 7675–7681 (2017).Article 
CAS 

Google Scholar 
Zou, Y. et al. Boosting solar steam generation by photothermal enhanced polydopamine/wood composites. Polymer 217, 123464 (2021).Article 
CAS 

Google Scholar 
Li, Y. et al. 3D-printed, all-in-one evaporator for high-efficiency solar steam generation under 1 Sun illumination. Adv. Mater. 29, 1700981 (2017).Article 

Google Scholar 
Hong, S. et al. Nature-inspired, 3D origami solar steam generator toward near full utilization of solar energy. ACS Appl. Mater. Interfaces 10, 28517–28524 (2018).Article 
CAS 

Google Scholar 
Zhang, L., Li, R., Tang, B. & Wang, P. Solar-thermal conversion and thermal energy storage of graphene foam-based composites. Nanoscale 8, 14600–14607 (2016).Article 
CAS 

Google Scholar 
Tu, C. et al. A 3D-structured sustainable solar-driven steam generator using super-black nylon flocking materials. Small 15, e1902070 (2019).Article 

Google Scholar 
Pham, T. T. et al. Durable, scalable and affordable iron (III) based coconut husk photothermal material for highly efficient solar steam generation. Desalination 518, 115280 (2021).Article 
CAS 

Google Scholar 
Shao, B. et al. A general method for selectively coating photothermal materials on 3D porous substrate surfaces towards cost-effective and highly efficient solar steam generation. J. Mater. Chem. A 8, 24703–24709 (2020).Article 
CAS 

Google Scholar 
Yuan, B. et al. A low‐cost 3D spherical evaporator with unique surface topology and inner structure for solar water evaporation‐assisted dye wastewater treatment. Adv. Sustain. Syst. 5, 2000245 (2020).Article 

Google Scholar 
Xu, Y. et al. Origami system for efficient solar driven distillation in emergency water supply. Chem. Eng. J. 356, 869–876 (2019).Article 
CAS 

Google Scholar 
Kim, K., Yu, S., Kang, S.-Y., Ryu, S.-T. & Jang, J.-H. Three-dimensional solar steam generation device with additional non-photothermal evaporation. Desalination 469, 114091 (2019).Article 
CAS 

Google Scholar 
Shi, Y. et al. A 3D photothermal structure toward improved energy efficiency in solar steam generation. Joule 2, 1171–1186 (2018).Article 
CAS 

Google Scholar 
Sui, Y., Hao, D., Guo, Y., Cai, Z. & Xu, B. A flowerlike sponge coated with carbon black nanoparticles for enhanced solar vapor generation. J. Mater. Sci. 55, 298–308 (2019).Article 

Google Scholar 
Cao, N. et al. A self-regenerating air-laid paper wrapped ASA 3D cone-shaped Janus evaporator for efficient and stable solar desalination. Chem. Eng. J. 397, 125522 (2020).Article 
CAS 

Google Scholar 
Wang, Y. et al. Improved light-harvesting and thermal management for efficient solar-driven water evaporation using 3D photothermal cones. J. Mater. Chem. A 6, 9874–9881 (2018).Article 
CAS 

Google Scholar 
Liu, H. et al. Conformal microfluidic-blow-spun 3D photothermal catalytic spherical evaporator for omnidirectional enhanced solar steam generation and CO2 reduction. Adv. Sci. 8, e2101232 (2021).Article 

Google Scholar 
Gong, Y. et al. Towards suppressing dielectric loss of GO/PVDF nanocomposites with TA-Fe coordination complexes as an interface layer. J. Mater. Sci. Technol. 34, 2415–2423 (2018).Article 
CAS 

Google Scholar 
Mehrkhah, R., Goharshadi, E. K. & Mohammadi, M. Highly efficient solar desalination and wastewater treatment by economical wood-based double-layer photoabsorbers. J. Ind. Eng. Chem. 101, 334–347 (2021).Article 
CAS 

Google Scholar 
Kuang, Y. et al. A high-performance self-regenerating solar evaporator for continuous water desalination. Adv. Mater. 31, e1900498 (2019).Article 

Google Scholar 
Guan, H., Cheng, Z. & Wang, X. Highly compressible wood sponges with a spring-like lamellar structure as effective and reusable oil absorbents. ACS Nano 12, 10365–10373 (2018).Article 
CAS 

Google Scholar 
Ghafurian, M. M. et al. Enhanced solar desalination by delignified wood coated with bimetallic Fe/Pd nanoparticles. Desalination 493, 114657 (2020).Article 
CAS 

Google Scholar 
Sahiner, N., Butun Sengel, S. & Yildiz, M. A facile preparation of donut-like supramolecular tannic acid-Fe(III) composite as biomaterials with magnetic, conductive, and antioxidant properties. J. Coord. Chem. 70, 3619–3632 (2017).Article 
CAS 

Google Scholar 
Huang, Y., Lin, Q., Yu, Y. & Yu, W. Functionalization of wood fibers based on immobilization of tannic acid and in situ complexation of Fe (II) ions. Appl. Surf. Sci. 510, 145436 (2020).Article 
CAS 

Google Scholar 
Song, L., Zhang, X.-F., Wang, Z., Zheng, T. & Yao, J. Fe3O4/polyvinyl alcohol decorated delignified wood evaporator for continuous solar steam generation. Desalination 507, 115024 (2021).Article 
CAS 

Google Scholar 
Li, X. et al. Graphene oxide-based efficient and scalable solar desalination under one sun with a confined 2D water path. Proc. Natl Acad. Sci. 113, 13953–13958 (2016).Article 
CAS 

Google Scholar 
Li, X. Q. et al. Three-dimensional artificial transpiration for efficient solar waste-water treatment. Natl Sci. Rev. 5, 70–77 (2018).Article 
CAS 

Google Scholar 
Ma, M., Dong, S., Hussain, M. & Zhou, W. Effects of addition of condensed tannin on the structure and properties of silk fibroin film. Polym. Int. 66, 151–159 (2017).Article 
CAS 

Google Scholar 
Jiang, P. et al. Synthesis of flame-retardant, bactericidal, and color-adjusting wood fibers with metal phenolic networks. Ind. Crops Prod. 170, 113796 (2021).Article 
CAS 

Google Scholar 
Song, J. et al. Processing bulk natural wood into a high-performance structural material. Nature 554, 224–228 (2018).Article 
CAS 

Google Scholar  More

Afolalu, S. A., Ikumapayi, O. M., Ogedengbe, T. S., Kazeem, R. A. & Ogundipe, A. T. Waste pollution, wastewater and effluent treatment methods – an overview. Mater. Today Proc. 62, 3282–3288 (2022).Article 
CAS 

Google Scholar 
Jamwal, P. & Shirin, S. Impact of microbial activity on the performance of planted and unplanted wetland at laboratory scale. Water Pract. Technol. 16, 472–489 (2021).Article 

Google Scholar 
Wang, J. et al. A review on microorganisms in constructed wetlands for typical pollutant removal: species, function, and diversity. Front. Microbiol. 13, 845725 (2022).Article 

Google Scholar 
Shruthi, R. & Shivashankara, G. P. Effect of HRT and seasons on the performance of pilot-scale horizontal subsurface flow constructed wetland to treat rural wastewater. Water Pract. Technol. 17, 445–455 (2022).Article 

Google Scholar 
Arden, S. & Ma, X. Constructed wetlands for greywater recycle and reuse: a review. Sci. Total Environ. 630, 587–599 (2018).Article 
CAS 

Google Scholar 
Ali, M., Rousseau, D. P. L. & Ahmed, S. A full-scale comparison of two hybrid constructed wetlands treating domestic wastewater in Pakistan. J. Environ. Manag. 210, 349–358 (2018).Article 
CAS 

Google Scholar 
Corbella, C. & Puigagut, J. Improving domestic wastewater treatment efficiency with constructed wetland microbial fuel cells: Influence of anode material and external resistance. Sci. Total Environ. 631–632, 1406–1414 (2018).Article 

Google Scholar 
Rajan, R. J., Sudarsan, J. S. & Nithiyanantham, S. Microbial population dynamics in constructed wetlands: Review of recent advancements for wastewater treatment. Environ. Eng. Res. 24, 181–190 (2019).Article 

Google Scholar 
Karajić, M. et al. Microbial activity in a pilot-scale, subsurface flow, sand-gravel constructed wetland inoculated with halotolerant microorganisms. Afr. J. Biotechnol. 11, 15020–15029 (2012).
Google Scholar 
Lee, C., Fletcher, T. D. & Sun, G. Nitrogen removal in constructed wetland systems. Eng. Life Sci. 9, 11–22 (2009).Article 
CAS 

Google Scholar 
Hijosa-Valsero, M. et al. Removal of antibiotics from urban wastewater by constructed wetland optimization. Chemosphere 83, 713–719 (2011).Article 
CAS 

Google Scholar 
Takavakoglou, V., Pana, E. & Skalkos, D. Constructed Wetlands as nature-based solutions in the post-COVID agri-food supply chain: challenges and opportunities. Sustain 14, 3145 (2022).Article 
CAS 

Google Scholar 
Si, Z. et al. Mechanism and performance of trace metal removal by continuous-flow constructed wetlands coupled with a micro-electric field. Water Res. 164, 114937 (2019).Article 
CAS 

Google Scholar 
Syranidou, E. et al. Responses of the endophytic bacterial communities of juncus acutus to pollution with metals, emerging organic pollutants and to bioaugmentation with indigenous strains. Front. Plant Sci. 9, 1526 (2018).Article 

Google Scholar 
Vassallo, A. et al. Temporal evolution of bacterial endophytes associated to the roots of phragmites australis exploited in phytodepuration of wastewater. Front. Microbiol. 11, 1652 (2020).Article 

Google Scholar 
Mukherjee, K. & Pal, S. Hydrological and landscape dynamics of floodplain wetlands of the Diara region, Eastern India. Ecol. Indic. 121, 106961 (2021).Article 

Google Scholar 
Bera, T. et al. Pollution assessment and mapping of potentially toxic elements (PTE) distribution in urban wastewater fed natural wetland, Kolkata, India. Environ. Sci. Pollut. Res. 29, 67801–67820 (2022).Article 
CAS 

Google Scholar 
Polz, M. F. & Cordero, O. X. Bacterial evolution: genomics of metabolic trade-offs. Nat. Microbiol. 1, 16181 (2016).Article 
CAS 

Google Scholar 
Dai, T. et al. Nutrient supply controls the linkage between species abundance and ecological interactions in marine bacterial communities. Nat. Commun. 13, 175 (2022).Article 
CAS 

Google Scholar 
Gandhi, S. R., Korolev, K. S. & Gore, J. Cooperation mitigates diversity loss in a spatially expanding microbial population. Proc. Natl Acad. Sci. USA 116, 23582–23587 (2019).Article 
CAS 

Google Scholar 
Jin, D. et al. Bacterial communities and potential waterborne pathogens within the typical urban surface waters. Sci. Rep. 8, 1–9 (2018).Article 

Google Scholar 
Furman, O. et al. Stochasticity constrained by deterministic effects of diet and age drive rumen microbiome assembly dynamics. Nat. Commun. 11, 1–13 (2020).Article 

Google Scholar 
Lew, S., Glińska-Lewczuk, K. & Lew, M. The effects of environmental parameters on the microbial activity in peat-bog lakes. PLoS ONE 14, 1–18 (2019).Article 

Google Scholar 
Zheng, F. et al. Comparison and interpretation of freshwater bacterial structure and interactions with organic to nutrient imbalances in restored wetlands. Front. Microbiol. 13, 946537 (2022).Article 

Google Scholar 
Tardy, V. et al. Stability of soil microbial structure and activity depends on microbial diversity. Environ. Microbiol. Rep. 6, 173–183 (2014).Article 
CAS 

Google Scholar 
Coyte, K. Z., Schluter, J. & Foster, K. R. The ecology of the microbiome: Networks, competition, and stability. Science 350, 663–666 (2015).Article 
CAS 

Google Scholar 
Elder, F. C. T. et al. Stereoselective metabolism of chloramphenicol by bacteria isolated from wastewater, and the importance of stereochemistry in environmental risk assessments for antibiotics. Water Res. 217, 118415 (2022).Article 
CAS 

Google Scholar 
Lopeman, R. C., Harrison, J., Desai, M. & Cox, J. A. G. Mycobacterium abscessus: environmental bacterium turned clinical nightmare. Microorganisms 7, 90 (2019).Article 
CAS 

Google Scholar 
Zhao, J. et al. Production, purification and biochemical characterisation of a novel lipase from a newly identified lipolytic bacterium Staphylococcus caprae NCU S6. J. Enzyme Inhib. Med. Chem. 36, 248–256 (2021).Article 

Google Scholar 
Syed, A. et al. Heavy metals induced modulations in growth, physiology, cellular viability, and biofilm formation of an identified bacterial isolate. ACS Omega 6, 25076–25088 (2021).Article 
CAS 

Google Scholar 
Delgado-Blas, J. F. et al. Population genomics and antimicrobial resistance dynamics of Escherichia coli in wastewater and river environments. Commun. Biol. 4, 1–13 (2021).Article 

Google Scholar 
Kemper, K., De Goeje, P. L. & Peeper, D. S. Phenotype switching: tumor cell plasticity as a resistance mechanism and target for therapy. Cancer Res. 74, 5937–5942 (2014).Article 
CAS 

Google Scholar 
NCCLS. Performance standards for antimicrobial disk and dilution susceptibility tests for bacteria isolated from animals. in Approved standard-second edition NCCLS document M31-A3 (ed. Wayne, P.) vol. 28 (National Committee for Clinical Laboratory Standards, 2002).CLSI. Performance standards for antimicrobial susceptibility testing; Twenty-Fifth informational supplement. in CLSI document M100-S25 (ed. Wayne, P.) (Clinical and Laboratory Standards Institute, 2015).Davies, J. & Dorothy, D. Origins and evolution of antibiotic resistance. Microbiol. Mol. Biol. Rev. 74, 417–433 (2010).Article 
CAS 

Google Scholar 
Davies, J. Inactivation of antibiotics and the dissemination of resistance genes. Science 264, 375–382 (1994).Article 
CAS 

Google Scholar 
Li, D. et al. Antibiotic resistance characteristics of environmental bacteria from an oxytetracycline production wastewater treatment plant and the receiving river. Appl. Environ. Microbiol. 76, 3444–3451 (2010).Article 
CAS 

Google Scholar 
Rizzo, L. et al. Urban wastewater treatment plants as hotspots for antibiotic resistant bacteria and genes spread into the environment: a review. Sci. Total Environ. 447, 345–360 (2013).Article 
CAS 

Google Scholar 
Balcazar, J. L. Bacteriophages as vehicles for antibiotic resistance genes in the environment. PLoS Pathog. 10, 1–4 (2014).Article 

Google Scholar 
von Wintersdorff, C. J. H. et al. Dissemination of antimicrobial resistance in microbial ecosystems through horizontal gene transfer. Front. Microbiol. 7, 1–10 (2016).
Google Scholar 
Al-Sarawi, H. A., Najem, A. B., Lyons, B. P., Uddin, S. & Al-Sarawi, M. A. Antimicrobial resistance in Escherichia coli isolated from marine sediment samples from Kuwait Bay. Sustain 14, 1–11 (2022).
Google Scholar 
Tejedor-Junco, M. T., Díaz, V. C., González-Martín, M. & Tuya, F. Presence of microplastics and antimicrobial-resistant bacteria in sea cucumbers under different anthropogenic influences in Gran Canaria (Canary Islands, Spain). Mar. Biol. Res. 17, 537–544 (2021).Article 

Google Scholar 
Garcias, B. et al. Extended-spectrum β-lactam resistant klebsiella pneumoniae and escherichia coli in wild European hedgehogs (Erinaceus europeus) living in populated areas. Animals 11, 2837 (2021).Article 

Google Scholar 
Gessew, G. T., Desta, A. F. & Adamu, E. High burden of multidrug resistant bacteria detected in Little Akaki River. Comp. Immunol. Microbiol. Infect. Dis. 80, 101723 (2022).Article 
CAS 

Google Scholar 
Lood, R., Ertürk, G. & Mattiasson, B. Revisiting antibiotic resistance spreading in wastewater treatment plants – Bacteriophages as a much neglected potential transmission vehicle. Front. Microbiol. 8, 1–7 (2017).Article 

Google Scholar 
Pedros-Alio, C. The rare bacterial biosphere. Ann. Rev. Mar. Sci. 4, 449–466 (2012).Article 

Google Scholar 
Lynch, M. D. J. & Neufeld, J. D. Ecology and exploration of the rare biosphere. Nat. Rev. Microbiol. 13, 217–229 (2015).Article 
CAS 

Google Scholar 
Ratzke, C., Barrere, J. & Gore, J. Strength of species interactions determines biodiversity and stability in microbial communities. Nat. Ecol. Evol. 4, 376–383 (2020).Article 

Google Scholar 
Laland, K., Matthews, B. & Feldman, M. W. An introduction to niche construction theory. Evol. Ecol. 30, 191–202 (2016).Article 

Google Scholar 
Ghoul, M. & Mitri, S. The ecology and evolution of microbial competition. Trends Microbiol. 24, 833–845 (2016).Article 
CAS 

Google Scholar 
Calatayud, J. et al. Positive associations among rare species and their persistence in ecological assemblages. Nat. Ecol. Evol. 4, 40–45 (2020).Article 

Google Scholar 
Goebel, W., Chakraborty, T. & Kreft, J. Bacterial hemolysins as virulence factors. Antonie Van Leeuwenhoek 54, 453–463 (1988).Article 
CAS 

Google Scholar 
Pandey, A., Naik, M. & Dubey, S. K. Hemolysin, protease, and EPS producing pathogenic Aeromonas hydrophila Strain An4 shows antibacterial activity against marine bacterial fish pathogens. J. Mar. Biol. 2010, 563205 (2010).Article 

Google Scholar 
Wang, Z. et al. Plastisphere enrich antibiotic resistance genes and potential pathogenic bacteria in sewage with pharmaceuticals. Sci. Total Environ. 768, 144663 (2021).Article 
CAS 

Google Scholar 
Wang, J. et al. Treatment of hospital wastewater by electron beam technology: removal of COD, pathogenic bacteria and viruses. Chemosphere 308, 136265 (2022).Article 
CAS 

Google Scholar 
Cavalini, L., Jankoski, P., Correa, A. P. F., Brandelli, A. & Da Motta, A. S. Characterization of the antimicrobial activity produced by Bacillus sp. Isolated from wetland sediment. An. Acad. Bras. Cienc. 93, 1–13 (2021).Article 

Google Scholar 
Jankoski, P. R., Correa, A. P. F., Brandelli, A. & Da Motta, A. S. Biological activity of bacteria isolated from wetland sediments collected from a conservation unit in the southern region of Brazil. An. Acad. Bras. Cienc. 93, 1–15 (2021).Article 

Google Scholar 
Seruga, P. et al. Removal of ammonia from the municipal waste treatment effuents using natural minerals. Molecules 24, 3633 (2019).Article 
CAS 

Google Scholar 
Du, Q., Liu, S., Cao, Z. & Wang, Y. Ammonia removal from aqueous solution using natural Chinese clinoptilolite. Sep. Purif. Technol. 44, 229–234 (2005).Article 
CAS 

Google Scholar 
Tamura, K., Stecher, G. & Kumar, S. MEGA11: molecular evolutionary genetics analysis version 11. Mol. Biol. Evol. 38, 3022–3027 (2021).Article 
CAS 

Google Scholar 
Saitou, N. & Nei, M. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4, 406–425 (1987).CAS 

Google Scholar 
Tamura, K., Nei, M. & Kumar, S. Prospects for inferring very large phylogenies by using the neighbor-joining method. Proc. Natl Acad. Sci. USA 101, 11030–11035 (2004).Article 
CAS 

Google Scholar 
Batoni, G., Maisetta, G. & Esin, S. Antimicrobial peptides and their interaction with biofilms of medically relevant bacteria. Biochim. Biophys. Acta 1858, 1044–1060 (2016).Article 
CAS 

Google Scholar 
Zidour, M. et al. Isolation and characterization of bacteria colonizing acartia tonsa copepod eggs and displaying antagonist effects against Vibrio anguillarum, Vibrio alginolyticus and other pathogenic strains. Front. Microbiol. 8, 1–13 (2017).Article 

Google Scholar 
Krumperman, P. H. Multiple antibiotic resistance indexing of Escherichia coli to identify high-risk sources of faecal contamination of water. Appl. Environ. Microbiol. 46, 165–170 (1983).Article 
CAS 

Google Scholar 
Paria, P. et al. Molecular characterization and genetic diversity study of Vibrio parahaemolyticus isolated from aquaculture farms in India. Aquaculture 509, 104–111 (2019).Article 
CAS 

Google Scholar 
Zheng, X. et al. Essential oils improve the survival of gnotobiotic brine shrimp (Artemia franciscana) challenged with Vibrio campbellii. Front. Immunol. 12, 693932 (2021).Article 
CAS 

Google Scholar 
Taylor, S. M., He, Y., Zhao, B. & Huang, J. Heterotrophic ammonium removal characteristics of an aerobic heterotrophic nitrifying-denitrifying bacterium, Providencia rettgeri YL. J. Environ. Sci. 21, 1336–1341 (2009).Article 
CAS 

Google Scholar 
Pereira, E. L., Borges, A. C. & da Silva, G. J. Effect of the Progressive Increase of Organic Loading Rate in an Anaerobic Sequencing Batch Reactor for Biodiesel Wastewater Treatment. Water 14, 223 (2022).Article 
CAS 

Google Scholar 
Benítez-Chao, D. F., León-Buitimea, A., Lerma-Escalera, J. A. & Morones-Ramírez, J. R. Bacteriocins: An overview of antimicrobial, toxicity, and biosafety assessment by in vivo models. Front. Microbiol 12, 630695 (2021).Simons, A., Alhanout, K. & Duval, R. E. Bacteriocins, antimicrobial peptides from bacterial origin: overview of their biology and their impact against multidrug-resistant bacteria. Microorganisms 8, 639 (2020).Garcia-Garcera, M. & Rocha, E. PC. Community diversity and habitat structure shape the repertoire of extracellular proteins in bacteria. Nat. Commun. 11, 758 (2020).Soler, P., Moreno-Mesonero, L., Zornoza, A., V. Javier Macián, & Moreno, Y. Characterization of eukaryotic microbiome and associated bacteria communities in a drinking water treatment plant. Sci. Total Environ. 797, 149070 (2021).Karri, R. R., Sahu, J. N. & Chimmiri, V. Critical review of abatement of ammonia from wastewater. J. Mol. Liq. 261, 21–31 (2018).Article 
CAS 

Google Scholar 
Royan, M. R., Solim, M. H., & Santanumurti, M. B. (2019, February). Ammonia-eliminating potential of Gracilaria sp. And zeolite: a preliminary study of the efficient ammonia eliminator in aquatic environment. In IOP Conference Series: Earth and Environmental Science (Vol. 236, No. 1, p. 012002). IOP Publishing.Liu, Y., Ngo, H. H., Guo, W., Peng, L., Wang, D. & Ni, B The roles of free ammonia (FA) in biological wastewater treatment processes: A review. Environ. Int. 123, 10–19 (2019).Article 
CAS 

Google Scholar 
Guan, T. W., Lin, Y. J., Ou, M. Y. & Chen, K. B. Isolation and diversity of sediment bacteria in the hypersaline aiding lake, China. PloS one 15, e0236006 (2020).Article 
CAS 

Google Scholar 
Nickum, J. et al. Guidelines for the use of fishes in research. FISHERIES-BETHESDA- 29 3, 26 (2004).Johansen, R., Needham, J.R., Colquhoun, D.J., Poppe, T.T. & Smith, A.J. Guidelines for health and welfare monitoring of fish used in research. Lab. Anim. 40, 323–340 (2006). More