Dynamic metabolism modelling of urban water services--demonstrating effectiveness as a decision-support tool for Oslo, Norway.
Dynamic metabolism modelling of urban water services--demonstrating effectiveness as a decision-support tool for Oslo, Norway.
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DOI：
10.1016/j.watres.2014.05.004
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发表时间：
2014-09
期刊：
影响因子：
12.8
通讯作者：
G. Venkatesh;S. Sægrov;H. Brattebø
中科院分区：
文献类型：
--
作者：
G. Venkatesh;S. Sægrov;H. Brattebø
城市供水服务面临多方面的挑战，不同的利益攸关方要求改进可持续性的经济、社会和环境层面的绩效。对此，城市自来水公司系统地更多地关注水安全、气候变化适应和缓解、环境生命周期评估(LCA)、总成本效率等标准，以及如何在水-能源-碳关系中改善其运营。本文作者共同开发了一个“动态新陈代谢模型”(DMM)。该模型是为在城市供水服务的可持续性评估中通用而开发的，并已在挪威奥斯陆进行了初步测试。其目的是采用整体性的系统观点来分析城市水和废水系统中资源流动的新陈代谢和环境影响，以便为审查这类系统的未来战略和干预选择提供一种工具。本文描述了该模型及其在分析时间段2013-2040年奥斯陆的应用。介绍了影响决策和干预的外部因素，以及在与挪威奥斯陆自来水和废水处理厂官员协商后为测试制定的现实情景。公用事业公司打算启动的可能干预措施被定义和数字解释以并入模型，并确定指标值在时间段内的变化。本文旨在论证DMM作为给水废水处理企业决策支持工具的有效性和有用性。审议的情景和确定的干预措施并不包括可能与水废水公用事业有关的所有可能情景和干预措施。
Urban water services are challenged from many perspectives and different stakeholders demand performance improvements along economic, social and environmental dimensions of sustainability. In response, urban water utilities systematically give more attention to criteria such as water safety, climate change adaptation and mitigation, environmental life cycle assessment (LCA), total cost efficiency, and on how to improve their operations within the water-energy-carbon nexus. The authors of this paper collaborated in the development of a ‘Dynamic Metabolism Model’ (DMM). The model is developed for generic use in the sustainability assessment of urban water services, and it has been initially tested for the city of Oslo, Norway. The purpose has been to adopt a holistic systemic perspective to the analysis of metabolism and environmental impacts of resource flows in urban water and wastewater systems, in order to offer a tool for the examination of future strategies and intervention options in such systems. This paper describes the model and its application to the city of Oslo for the analysis time period 2013–2040. The external factors impacting decision-making and interventions are introduced along with realistic scenarios developed for the testing, after consultation with officials at the Oslo Water and Wastewater Works (Norway). Possible interventions that the utility intends to set in motion are defined and numerically interpreted for incorporation into the model, and changes in the indicator values over the time period are determined. This paper aims to demonstrate the effectiveness and usefulness of the DMM, as a decision-support tool for water-wastewater utilities. The scenarios considered and interventions identified do not include all possible scenarios and interventions that can be relevant for water-wastewater utilities.