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Brine and bittern waste streams are classified as a byproduct of seawater desalination operations, as well as many inorganic industries. As such, many of those industries are challenged to develop and implement sustainable, cost-effective strategies for managing water usage and wastewater discharge. As a result, zero liquid discharge goals have garnered a lot of interest for the purpose of enhancing strategies for wastewater handling. Zero liquid discharge may be achieved using a number of methods, including technologies through which industrial wastewater is reduced to dry solids/salts. This would mostly involve wastewater processing to brine water quality, using standard brine-producing wastewater treatment methods, followed by conventional zero liquid discharge techniques, which in turn transform brine wastewater to salts/bitterns. Salt sludge and bittern waste from zero liquid discharge processing have no adverse effects on the environment. Moreover, many techniques allow for the recovery of extra-purified water streams, as a result of wastewater-to-brine processing, and/or brine-to-salt processing. Recovered water streams may be directly reused, or even utilized to enhance the quality of other wastewater streams before reuse. Since compliance with stringent industrial wastewater regulations is through zero liquid discharge applications, this work discusses the incorporation of zero liquid discharge processing options onto interplant water network synthesis problems. Accounting for the presence of both central and distributed zero liquid discharge processing schemes enables the identification of cost-optimal interplant water networks, when stringent wastewater discharge requirements are imposed. This paper focuses on a specific class of water integration problems, which involve brine management. A case study is used to illustrate the proposed approach and to highlight the importance of accounting for zero liquid discharge considerations, to develop grassroots designs for interplant water networks. For a given industrial city layout, four different scenarios have been carried out, and each case was associated with certain wastewater discharge requirements. As a result, differing optimal interplant water network designs have been attained for each of the cases, which have been investigated.

Unconventional shale gas production in the United States has been largely improved due to the development of hydraulic fracturing technology and is projected to rapidly grow in the coming years. However, the acquisition of freshwater and management of flowback and produced (FP) water associated with hydraulic fracturing operation are two of the greatest challenges in shale gas development, especially in arid regions. For efficient and sustainable water management, a better understanding of freshwater consumption and FP water production for shale gas wells is necessary to appropriately expand and upgrade the existing water network and shale gas network. To achieve this, we first collected water-use volume and monthly FP water production volume data for shale gas wells drilled in the Eagle Ford and Marcellus shale regions. Next, after integrating the data from multiple database sources, the water recovery ratio was calculated as the ratio of cumulative FP water volume to water-use volume and used as a metric to characterize the wells in these two shale regions. Then, we analyzed the obtained water recovery ratio data according to the location and production history to study the spatiotemporal variations across multiple counties and time periods. It shows that around 30% of the collected wells drilled in the Eagle Ford region have the water recovery ratio greater than 1; however, only 1% of the collected wells drilled in the Marcellus region have the water recovery ratio greater than 1. Besides, the water recovery ratios vary significantly across the counties in each shale region. To demonstrate how different water recovery ratio may affect shale gas development, a shale gas supply chain network (SGSCN) optimization model from the literature was utilized to perform two case studies in the Marcellus region. The optimal results suggest that different configurations of SGSCN are required for economically desirable and practically feasible management of shale gas wells with different water recovery ratios.

Eco-industrial parks provide a platform for the application of industrial symbiosis where the synergistic network of companies reuse portions of their by-products to reduce disposed waste, reduce environmental emissions, and improve plant efficiency. However, designing a complex network of material and energy exchanges between companies in an industrial park while satisfying multiple conflicting objectives require a systematic design methodology. In addition, strategic decision-making in an eco-industrial park involves the selection of prospective companies (i.e., support tenants), which complement the existing companies (i.e., anchor tenants). In this study, a fuzzy mixed-integer non-linear programming model is proposed to select prospective support tenants in an eco-industrial park while satisfying the product demand, minimizing the environmental footprint of the eco-industrial park, and also maximizing the annualized profit of each company in the eco-industrial park. A hypothetical but realistic case study involving an algae-based eco-industrial park is used to demonstrate the application of the model. The results demonstrate the selection of the appropriate support tenants for the algae-based eco-industrial park together with the optimal plant configuration. Sensitivity analysis is used to assess the performance of the algae-based eco-industrial park with respect to the changes in prices of the by-products. The developed model thus aid the planners of an eco-industrial park in assessing which among the prospective support tenants would best complements an existing anchor tenant. Furthermore, the model can also identify price negotiation points between tenants for some product streams which may show sensitivity on the plant capacity of each tenant.

This paper presents an optimization formulation for designing residential water networks involving harvested rainwater and reclaimed wastewater. The design problem is posed as a multi-objective optimization formulation that seeks to balance the objectives of total annualized cost, fresh water consumption, and environmental impact. A life cycle assessment approach is undertaken for estimating the environmental impact. The seasonal dependence of the rainwater is considered in the optimization model. The design approach is applied to a case study for the city of Morelia in Mexico. The results show that significant economic, fresh water consumption, and environmental benefits can be obtained as a result of the proposed approach.

The efficient use of water worldwide is of overriding importance due to its vital role in life. Recently, several countries have suffered water scarcity mainly due to population increase and problems associated to climate change such as the change in the precipitation patterns in the world. In this project, a mathematical programming model for the efficient and sustainable use of water under parametric uncertainty is proposed. The model considers rainwater harvesting (which includes catchment, storage and distribution) as alternative water source; it also considers sustainability aspects from the economic and environmental points of view, maximizing the revenue from the sales of water minus the cost of production and treatment, while maintaining desirable levels of water in the natural reservoirs. The uncertainty is a result of the change in the precipitation patterns. The proposed model is applied to a case study for the city of Morelia, Michoacan in Mexico, considering a time horizon of 5 years. Results show the optimal schedule for water storage and distribution to different sectors of the society (public, agricultural and industrial users). It was found that the use of alternative water sources such as harvested rainwater, along with an appropriate planning schedule of storage and distribution might help reduce the pressure over natural reservoirs even under conditions of uncertainty in the precipitation, while satisfying the water demands in a city.

This paper presents an optimization approach to the development of macroscopic networks for water integration within industrial cities. The methodology considers various strategies for industrial wastewater reuse amongst different processing facilities that operate within the city. Two different scenarios for the placement of intermediate water treatment interceptors are considered: (1) on-site ‘decentralized’ water treatment within each plant, and (2) off-site ‘centralized’ water treatment that can be shared amongst a cluster of existing industrial plants. The overall objective is to develop cost-efficient water networks that can attain effective interplant water integration scenarios, whilst considerably reducing freshwater consumption and wastewater discharge where appropriate. The optimization model has been formulated as a Mixed Integer Non-Linear Program (MINLP), and accounts for pressure drops associated with piping across all individual source-interceptor-sink allocations. Additionally, a representation that accounts for constrained water transport was adopted, in which designated corridor regions within an industrial city are utilized for the planning of economical pipeline networks that achieve desirable water allocation strategies. In doing so, shortest routing options were obtained between water sources, sinks, and treatment interceptors, according to a given industrial city layout. A case study that considers various different scenarios in terms of contaminant information and piping connectivity is presented to illustrate the proposed approach.

This paper presents a generic approach for the synthesis of heat integrated resource conservation networks (HIRCNs) of the fixed flow rate problem, where process sources linked directly to process sinks without any prior mixing. The mixed integer non-linear program (MINLP) formulation complemented by floating pinch concept was developed to determine the optimum fresh material resources as well as hot and cold energy utilities. The proposed approach is applicable for both concentration- and property-based direct reuse/recycle system with variable operating parameters (i.e. flow rates, temperatures and properties). Three literature case studies are solved to illustrate the proposed approach.

Biorefineries appear to be a viable solution to replace traditional fossil fuel refineries, but their implementation requires the exploration of several aspects, including feedstock selection, processing routes, products, harvesting sites, processing and markets, as well as numerous other sustainability criteria. The optimal solution to these problems is not immediately obvious. Therefore, this study presents an optimization model to design and plan sustainable biorefinery supply chains that considers numerous relevant issues. These issues include the multiple available biomass feedstocks at various harvesting sites, the availability and seasonality of biomass resources, different potential geographical locations for processing plants that produce multiple products using diverse production technologies, economies of scale for the production technologies, demands and prices of multiple products in each market, locations of storage facilities and a number of transportation modes between the supply chain components. Sustainability considerations are incorporated into the proposed model by including simultaneous economic, environmental and social performance data in the evaluation of the supply chain designs. The problem was formulated as a multi-objective, multi-period, mixed-integer linear program that seeks to maximize the profit of the supply chain, minimize its environmental impact and maximize the number of jobs generated by its implementation. The environmental impact was measured by the Eco-indicator99 according to the life-cycle assessment technique, and the social objective was quantified by the number of jobs generated. The Pareto-optimal solutions were obtained using the e-constraint method. To illustrate the capabilities of the proposed multi-site system model, a case study was presented that addresses the optimal design and planning of a biorefinery supply chain to fulfill the expected ethanol and biodiesel demands in Mexico. The results indicate that cost-effective and sustainable solutions can be obtained that satisfy Mexican demand by choosing feedstocks that are available year-round and do not significantly adversely impact the environment. Furthermore, the number of jobs generated by implementing the biorefinery supply chain would have a significant social impact.

This paper presents a new general mathematical programming model for the optimal retrofit of material conservation networks considering recycle, reuse and regeneration schemes (notice that most of the previously reported methods only have considered the synthesis case, and nowadays it is very important to have strategies for the retrofit of water networks because several existing water network are functioned under suboptimal conditions because these were synthesized using inefficient approaches or because the process and environmental constraints have changed). The model considers the reconfiguration of existing networks to satisfy stricter process and environmental constraints considering the repiping for the network, the reuse of the existing treatment units, the modification for the capacity and performance of the existing units and the installation of new treatment units to reduce the overall operating cost through the reduction of the use of fresh sources. The objective function accounts for the minimization of the total annual cost associated to the retrofit process. This retrofit process involves simultaneously economic (because the reduction of the fresh sources costs) and environmental (because the reduction of the waste streams discharged to the environment and with a better quality) improvements. The applicability of the proposed model is proved through a set of example problems addressed, where no numerical complications were observed. In addition, the proposed approach is general and it can be applied to any specific case with the information required.