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Abstract: Sustainable development indicators (SDIs) have emerged as a tool to measure progress towards sustainable development for a number of fields. However, no indicator initiative to date has been aimed at biosolids management at local authority, regional or national levels. This paper presents a study where stakeholders involved in the management of biosolids in Ireland participated in the development of SDIs for managing biosolids at the local/regional level. A significant 81% of participating stakeholders find SDIs either ‘useful’ or ‘very useful’ as a tool for managing biosolids. A suite of 22 indicators has been developed and arranged according to the driving force-pressure-state-impact-response (DPSIR) indicator framework. The indicators address all the domains of biosolids management namely, production, quality, cost, legislation/regulation, training/research and recycling/disposal. The stakeholder approach is recognition that no effective indicator set can be developed without the input of stakeholders. [Copyright &y& Elsevier]

Abstract: This paper reports the formulation and application of a framework of catchment-level water resource management indicators designed to integrate environmental, economic and social aspects of sustainability. The framework of nine indicators was applied to the River Dee and River Sinos catchments in Scotland and Brazil, respectively, following an indicator selection process that involved inputs from water management professionals in both countries, and a pilot exercise in Scotland. The framework was found to capture a number of key sustainability concerns, and was broadly welcomed by water resource managers and experts as a means of better understanding sustainable water resource management. Issues relating to poor water quality and public water supply were particularly prominent in the findings for the Sinos, while findings for the Dee suggested that more attention might be focused on building institutional capacity and public participation in catchment management. The use of some proxy indicators was required in both catchments due to poor data availability, and this problem may hinder the further development of indicator frameworks that attempt to better integrate environmental, economic and social dimensions of sustainability. [Copyright &y& Elsevier]

Sustainable development is being reconsidered as a process with unknown endpoint. Outputs of sustainable urban water systems defined as 'policies, projects, laws, technologies, and consumption and reuse amounts associated with urban water sustainability goals' are therefore being viewed as inadequate monitoring instruments. I propose a new methodology for sustainability monitoring whereby normality of a system is diagnosed through normality of its supporting inputs in lieu of normality of its complex outputs. Supporting inputs are 'intents and behaviors that support system goals'. Supporting inputs follow a principle of self-organization to remain in the norm and behavior zone commonly associated with system goals. This implies that normality of supporting inputs can be inferred from their longitudinally normal or Gaussian distribution that can be explored by significance tests; in particular, the Shapiro-Wilk test which is most powerful for n < 50. We identify fourteen supporting inputs of sustainable urban water systems - such as internet searches, community campaigns, staff training, agent-principal reporting and legislation propositions about water sustainability – and define quantitative indicators for them. The Shapiro-Wilk test and Kolmogorov-Smirnov test (K–S) of these indicators and a subsequent Boxplot outlying examination of non-normal indicators are undertaken in Yazd – a desert city in central Iran with a historic record in water conservation – in the light of its complex wastewater speculation. Qualitative examination of non-normal supporting inputs confirms the ability of our statistical methodology to detect problems in the system. • This paper proposes a new methodology for monitoring sustainability of urban water systems. • Normality of the system is inferred from normality of its supporting inputs. • Supporting inputs are intents and behaviors that support system goals. • Normality of supporting inputs is inferred from their longitudinally normal distribution. • Fourteen supporting inputs and their quantitative indicators are identified for significance tests. [ABSTRACT FROM AUTHOR]