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.

页岩气行业在提高整体工艺成本效益同时减少对环境的影响方面，废水管理是主要障碍之一。有鉴于此，本文介绍了一种新的多目标模型，用于基于太阳能的零液体排放（ZLD）脱盐系统的热经济和环境优化。太阳能驱动的ZLD系统专为页岩气工艺中的高盐度废水脱盐而开发。提出了一种分散式系统，该系统包括太阳能热系统，朗肯动力循环以及与机械蒸汽再压缩相结合的多效蒸发器。通过指定接近饱和条件的盐水排放的盐浓度，可以确保环境友好的ZLD操作。数学建模方法以多目标非线性规划（MoNLP）公式为中心，该公式旨在同时最小化热经济和环境目标函数。后一种目标函数通过ReCiPe方法基于生命周期评估进行量化。MoNLP模型在GAMS软件中实现，并通过epsilon-constraint方法求解。提出了一系列折衷的帕累托最优解决方案，以支持决策者实施更具可持续性和成本效益的太阳能驱动的ZLD海水淡化系统。全面的能源，经济和环境分析表明，该创新系统显着降低了页岩气废水运营中的成本和环境影响。旨在同时最小化热经济和环境目标功能。后一种目标函数通过ReCiPe方法基于生命周期评估进行量化。MoNLP模型在GAMS软件中实现，并通过epsilon-constraint方法求解。提出了一系列折衷的帕累托最优解决方案，以支持决策者实施更具可持续性和成本效益的太阳能驱动的ZLD海水淡化系统。全面的能源，经济和环境分析表明，该创新系统显着降低了页岩气废水运营中的成本和环境影响。旨在同时最小化热经济和环境目标功能。后一种目标函数通过ReCiPe方法基于生命周期评估进行量化。MoNLP模型在GAMS软件中实现，并通过epsilon-constraint方法求解。提出了一系列折衷的帕累托最优解决方案，以支持决策者实施更具可持续性和成本效益的太阳能驱动的ZLD海水淡化系统。全面的能源，经济和环境分析表明，该创新系统显着降低了页岩气废水运营中的成本和环境影响。MoNLP模型在GAMS软件中实现，并通过epsilon-constraint方法求解。提出了一系列折衷的帕累托最优解决方案，以支持决策者实施更具可持续性和成本效益的太阳能驱动的ZLD海水淡化系统。全面的能源，经济和环境分析表明，该创新系统显着降低了页岩气废水运营中的成本和环境影响。MoNLP模型在GAMS软件中实现，并通过epsilon-constraint方法求解。提出了一系列折衷的帕累托最优解决方案，以支持决策者实施更具可持续性和成本效益的太阳能驱动的ZLD海水淡化系统。全面的能源，经济和环境分析表明，该创新系统显着降低了页岩气废水运营中的成本和环境影响。