A Decision-making Framework for Hybrid Resource Recovery Oriented Wastewater Systems

Water shortage, water contamination, and the emerging challenges in sustainable water resources management (e.g., the likely impacts of climate change and population growth) necessitate adopting a reverse logistics approach, which is the process of moving wastewater from its typical final destination back to the water supply chain for reuse purposes. This practice not only reduces the negative impacts of wastewater on the environment, but also provides an alternative to withdrawal from natural water resources, forming a closed-loop water supply chain. However, the design of such a supply chain requires an appropriate sustainability assessment, which simultaneously accounts for economic, environmental, and social dimensions. The overall aim of this work was therefore to contribute to the literature by evaluating the impacts of water reclamation and reuse according to the triple-bottom-line sustainability indicators (i.e., economic, environmental, and social) and to develop frameworks and mathematical models to help decision-makers, stakeholders, and officials with the design of sustainable water reclamation and reuse systems. The applicability of the developed frameworks and models was examined using real case studies and hypothetical scenario analyses. This enactment also revealed the tradeoffs and thresholds associated with the design of sustainable water reclamation and reuse systems. To conquer the mentioned goal, the research was conducted in three major sections. The first part of the research was outlined to design possible scenarios for water reuse based on water reuse guidelines and evaluate the different types of end-use based on the three major dimensions of sustainability (i.e., economic, environmental and social aspects), simultaneously. The different reuse types considered include unrestricted urban reuse, agricultural reuse, indirect potable reuse (IPR), direct potable reuse (DPR), distributed unrestricted urban reuse, as well as some degree of decentralization of treatment plants for distributed unrestricted urban reuse. The tradeoff investigation and decision-making framework were demonstrated in a case study and a regret-based model was adopted as the support tool for multi-criteria decision-making. This study revealed that although increasing the degree of treatment for water reuse required implementation of advanced treatment options and it increased the implementation, operation, and maintenance (O&M) costs of the design, it increased the value of resource recovery significantly, such that it can offset the capital and O&M costs associated with the treatment and distribution for DPR. Improving the reclaimed water quality also reduced the environmental footprint (eutrophication) to almost 50% for DPR compared to the other reuse scenarios. This study revealed that the distance between the water reclamation facility and the end use plays a significant role in economic and environmental (carbon footprint) indicators. In the second part of this research, a multi-objective optimization model was developed to minimize the costs and environmental footprint (greenhouse gas emissions), and maximize social benefits (value of resource recovery) of the water reclamation systems by locating the treatment facility, allocating treatment capacity, selecting treatment technology, and allocating customers (final reclaimed water users). The expansion of the water reclamation system in Hillsborough County, Florida was evaluated to illustrate the use of the model. The impacts of population density and topography (elevation variation) of the water service area on the model outputs were also investigated. Although the centralization of treatment facilities takes advantage of the economies of scale, the results revealed that simultaneous consideration of economic and environmental indicators favored decentralization of treatment facilities in the study area. This was mainly due to the significant decrease in water transfer requirements, especially in less populous areas. Moreover, the results revealed that contribution of population density to the optimal degree of decentralization of treatment facilities was significant. In the last part of this work, hypothetical scenarios for a water service area were generated to evaluate the impacts of external variables on the design of water reclamation and reuse systems. Although the conducted sensitivity analyses in the previous sections revealed the tradeoffs and thresholds associated with the design of water reclamation systems, the concept of a hypothetical study helped with the elimination of case-specific factors and local conditions that could possibly influenced the outcomes. These factors, which were specific to the case studies (e.g., the location of candidate sites for implementation of water reclamation facilities and special population distribution patters) made barriers to the conclusions and hurdled the interpretation of findings. Two major factors, which were found to be significant among the factors influencing the design of water systems (i.e., elevation variation and population density), were selected for the evaluation. Accordingly, three different topographies (i.e., flat region, medium elevation variation, and hilly) and three types of population density (i.e., low, medium, and high) were considered for the design of hypothetical cases and the previous model developed in the second section was modified and used to evaluate the impacts. The results revealed that although decentralization of water reclamation facilities decreases the costs and environmental impacts associated with water transfer phase (i.e., wastewater collection and reclaimed water distribution), there were tradeoffs between the impacts of decentralization of treatment plants and the benefits from economies of scale for treatment. The results showed that when the population density is high and there is moderate to high elevation variations in the water service area, decentralization of treatment facilities is the beneficiary option. However, if the population density is low, economies of scale for treatment becomes more influential and lower degrees of decentralization of treatment facilities is preferred