Autonomous driving paper index

Recycled water in Queensland: building a model for the full cost of recycled class A+ water

2026-07-09

autonomous drivingperception

One-line summary

An autonomous driving research paper: Recycled water in Queensland: building a model for the full cost of recycled class A+ water.

Engineering notes

Key topics: autonomous driving, perception. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充:本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

The fact that water is a critical resource in an increasingly urbanised population was highlighted in Queensland by the prolonged 1997-2010 drought, which in South East Queensland prompted investment in significant capital infrastructure in an attempt to increase the drought resilience of water supplies. The need to consider alternative water supply sources prompted interest in recycled water from waste water treatment both to supply industry and to replace potable water. This included using ‘fit for purpose’ recycled water rather than drinking water for non-potable uses, but also using high grade recycled water for indirect potable use. The question arises how to value such new water sources. The ‘value’ of a scarce natural resource such as water is not confined to traditional economic accounting models and undervaluation of the resource could encourage undesirable consumer behaviour in terms of increased volumes of use of a ‘free’ resource. Costs include direct costs, distribution and other capital assets, but these have not always been fully passed on to customers. Costs and benefits also include ‘externalities’ not captured in traditional accounting models such as environmental and social costs. Including full costs is crucial for informed policy decisions. This background is motivation for the research problem posed in this thesis: How can a triple bottom line approach be used to provide a costing model for the full cost of Class A+ recycled water for use in South East Queensland? This thesis provides a Triple Bottom Line (TBL) approach that reports economic, environmental and social costs and applies it to the case study of two advanced water treatment plants in South-East Queensland, each plant using different processing systems for the production of recycled water from treated waste water. Difficulties associated with producing such a model are highlighted via the case studies and externalities are identified. This thesis synthesises results from previous research from a number of disciplines, such as environmental management and engineering (Reungoat et al. 2010a; Halliday 2006), psychology (Menegaki et al. 2009) and economics (Frontier Economics 2011), and adds an accounting dimension. Realistic examples are provided via the case studies, and the thesis investigates the least-documented social aspect of a TBL approach via an extensive survey of perspectives and motivations of recycled water customers, both actual and potential, at the same case study location. The model suggests a broad range of interactions between stakeholders, assumptions made regarding the substitution of recycled water for marginal potable water supplies, environmental considerations such as greenhouse gas reporting, and the political and social costs of introducing a recycled water supply for potable and non-potable use. The thesis demonstrates that on many levels management of key stakeholders is crucial and the social and political costs of decisions are high and suggests critical perceptions that have not previously been fully addressed well, such as stakeholder management in terms of media, information provision and awareness of and reasons for the polarisation of opinion on the subject of purified recycled water, particularly for indirect potable/drinking water use.

5.0Engineering value
7.0Research novelty
6.0Business relevance

Links and sources

Need this topic turned into a technical roadmap?

Full Self Driving can prepare a custom autonomous driving literature review, code map, dataset map, and B2B technology assessment.

Request B2B research

Comments

No comments yet. Be the first to share your thoughts on this paper.
Login or register to leave a comment