Developing whole-system cost assessment and infrastructure optimisation models for the wastewater sector in Japan and the UK

A critical role of the wastewater industry is the timely and efficient provision of crucial infrastructure (Lofrano & Brown, 2010; Drinan & Spellman, 2013; Tchobanoglous & Leverenz, 2013). However, changes in operating environment characteristics during the long lifetime of assets can make it challenging to maintain the long-term efficiency of a wastewater system (WWS) (Maurer, 2009). This issue likely influences many aspects of the service’s performance. However, we specifically focus this research on economic performance, which still also impact other performance pillars (Lozano, 2008; Larsen et al., 2019; UNICEF & WHO, 2019). Therefore, we aim at exploring the real factors that would significantly impact the economics of the different parts of the system during its lifetime.

A WWS consists of two main sub-systems which work together to provide wastewater treatment service (Drinan & Spellman, 2013; Wei, 2013). These include the wastewater transportation/collection part, in which a network of pipelines and pumps is used to transfer the flow of wastewater from different sources such as households, business and industrial units; and the Wastewater Treatment Plants (WWTPs), at which a sequence of treatment processes are conducted to finally discharge effluents safely into water bodies (Drinan, 2001). However, the characteristics of these facilities are mutually dependent and involve costs interactions. Economies of scale observed in treatment might be offset by the high costs of collection network resulting in a financially inefficient WWS. Therefore, to ensure the maintenance of a cost-effective service for a long term, this inherent complexity should be addressed when the economic performance of current systems is assessed or when planning for infrastructure developments/transitions. In both cases, effective decision-support tools that can provide accurate insights or/and foresights are crucial to support relevant stakeholders with the thorough knowledge to make rational decisions (Bhattacharyya et al., 1995; Brunner & Starkl, 2012; Roefs et al., 2016).

Accordingly, this research focuses on two main goals. These goals are fundamentally triggered by the inherent complexity of such a network industry. Firstly, the development of cost assessment models for a WWS at a whole-system level is essential to account for costs interactions when evaluating the overall cost behaviour of existing systems. Specifically, our aim in this research is to understand the cost drivers not only within the internal environment of the subsystems, but also in the external/remote environment surrounding the system, the subsystems’ characteristics, and the associated cost behaviour. To achieve this goal, it is therefore crucial to explore costs driving factors from a holistic view. Secondly, the other topic we focus on is related to exploring the optimal wastewater infrastructure paradigm when looking for improvement on service provision through the conduction of vital transitions on existing infrastructures. Given that the decisions related to infrastructural transitions can be major and risky as they are future courses of actions, knowledge-based scenario-panning tools that can be used in the strategic planning stage are beneficial for comparing the feasibility of different alternatives before the actual changes are made on ground. Therefore, the other goals of this PhD research are to develop effective methods which should allow us to explore the viability of certain transitions seeking improvements for existing infrastructures.