Thermo-economic and environmental optimization of a solar-driven zero-liquid discharge system for shale gas wastewater desalination

• Published in: Desalination Vol. 511; p. 115098
• Main Authors: Onishi, Viviani C., Khoshgoftar Manesh, Mohammad H., Salcedo-Díaz, Raquel, Ruiz-Femenia, Rubén, Labarta, Juan A., Caballero, José A.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.09.2021
• Subjects: High-salinity wastewater; Mechanical vapor recompression; Multiple-effect evaporation; Optimization; Renewable energy; Shale gas wastewater; Zero-liquid discharge; Shale gas wastewater; High-salinity wastewater; Mechanical vapor recompression; Zero-liquid discharge; Renewable energy; Multiple-effect evaporation; Optimization
• ISSN: 0011-9164; 1873-4464
• DOI: 10.1016/j.desal.2021.115098

Wastewater management is one of the main hurdles encountered by the shale gas industry for boosting overall process cost-effectiveness while reducing environmental impacts. In this light, this paper introduces a new multi-objective model for the thermo-economic and environmental optimization of solar-based zero-liquid discharge (ZLD) desalination systems. The solar-driven ZLD system is especially developed for desalinating high-salinity wastewaters from shale gas process. A decentralized system is proposed, encompassing a solar thermal system, a Rankine power cycle, and a multiple-effect evaporator combined with mechanical vapor recompression. The environment-friendly ZLD operation is ensured by specifying the salt concentration of brine discharges close to saturation conditions. The mathematical modelling approach is centered on a multi-objective non-linear programming (MoNLP) formulation, which is aimed at simultaneously minimizing thermo-economic and environmental objective functions. The latter objective function is quantified by the ReCiPe methodology based on life cycle assessment. The MoNLP model is implemented in GAMS software, and solved through the epsilon-constraint method. A set of trade-off Pareto-optimal solutions is presented to support decision-makers towards implementing more sustainable and cost-efficient solar-driven ZLD desalination systems. The comprehensive energy, economic and environmental analysis reveals that the innovative system significantly decreases costs and environmental impacts in shale gas wastewater operations. •New multi-objective NLP model for optimizing solar-driven ZLD desalination systems.•The system is particularly developed for high-salinity desalination applications.•The environmental impacts are quantified via the LCA-based ReCiPe methodology.•Optimal Pareto solutions reveal large reductions in environmental impacts at small increases in total costs.•The model can be used to support the decision-making process in shale gas industry.