Life-cycle energy impacts for adapting an urban water supply system to droughts

Comparative Economic and Life Cycle Analysis of Future Water Supply Mix Scenarios for Hong Kong - A Water Scarce City

Increasing urbanization and changes in climate have placed increasing stress on urban water supply systems. Policy makers have increasingly adopted alternative water supply sources, such as desalination and water reclamation to meet this challenge, however these technologies may increase the negative environmental impacts of the water supply system. These alternative sources are energy intensive, and more expensive to produce, which raises questions about their sustainability. In this study, a Life Cycle Assessment (LCA) and a economic portfolio choice model were used to determine the impacts of Hong Kong's long term water policy. The results of our study show that the current water policy will increase the carbon emissions of producing 1 m³ of freshwater by 11% to 1.65 kg CO2-Eq due to the addition of desalination. However, a fit-for-purpose water policy approach only increases emission by 4%, to 1.54 kg CO2-Eq, by instead relying on water reclamation to offset freshwater consumption. Impacts from increased energy consumption were mitigated by improved wastewater treatment, which reduced CH₄ emissions. Although, ozone layer impacts increased due to higher NOx and N₂O emissions, highlighting the need to consider emissions from wastewater treatment processes when evaluating water reclamation processes. Impacts to water prices were also minimized when reclaimed water was chosen over desalination, due to its lower unit production cost. By considering both cost and environmental impacts of such system level changes, decision makers can more accurately evaluate different water supply approaches for data-driven policymaking.

The role of climate change and decentralization in urban water services: A dynamic energy-water nexus analysis

Urban water services, including drinking water supply and wastewater treatment, are highly energy dependent, contributing to the challenges described under the water-energy nexus. Both future climate change and decentralized water system adoptions can potentially influence the energy use of the urban water services. However, the trend and the extent of such influences have not been well understood. In this study, a modeling framework was developed to quantify both the separate and the combined influences of climate change and decentralization on the life cycle energy use of the urban water cycle, using the City of Boston, MA as a testbed. Two types of household decentralized systems were considered, the greywater recycling (GWR) systems and the rainwater harvesting (RWH) systems. This modeling framework integrates empirical models based on multilinear regression analysis, hydrologic modeling, water balance models, and life cycle assessment to capture the complex interactions among centralized water services, decentralized water system adoptions, and climate parameters for cumulative energy demand (CED) assessment, considering all residential buildings in Boston. It was found that climate change alone will slightly increase the energy use of the centralized systems towards the end of the century, due to the cancelation effect amongst changes in water quality, flow rate, and space and water heating demand. When decentralization is considered alone, we found economically viable decentralized systems may not necessarily produce energy savings. In fact, RWH adoptions may increase energy use. When climate change and decentralization are combined, they will increase the water yield and cost savings of the decentralized systems, while reducing the energy use from the centralized systems. When the centralized systems are further added into the picture, the CED of the entire urban water cycle is projected to increase by 0.9% or 2.3% towards the end of the century under climate change if GWR or RWH systems are adopted by respective cost saving positive buildings.

Stochastic Approach for Optimal Positioning of Pumps As Turbines (PATs)

A generic water system consists of a series of works that allow the collection, conveyance, storage and finally the distribution of water in quantities and qualities such as to satisfy the needs of end users. In places characterized by high altitude differences between the intake works and inhabited centres, the potential energy of the water is very high. This energy is attributable to high pressures, which could compromise the functionality of the pipelines; it is therefore necessary to dissipate part of this energy. A common alternative to dissipation is the possibility of exploiting this energy by inserting a hydraulic turbine. The present study aims to evaluate the results obtained from a stochastic approach for the solution of the multi-objective optimization problem of PATs (Pumps As Turbines) in water systems. To this end, the Bayesian Monte Carlo optimisation method was chosen for the optimization of three objective functions relating to pressure, energy produced and plant costs. The case study chosen is the Net 3 literature network available in the EPANET software manual. The same problem was addressed using the NSGA-III (Nondominated Sorting Genetic Algorithm) to allow comparison of the results, since the latter is more commonly used. The two methods have different peculiarities and therefore perform better in different contexts.