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Shifting from volume to economic value in virtual water allocation problems: A proposed new framework and methodology

机译:从虚拟水分配问题中从体积转移到经济价值:拟议的新框架和方法

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Purpose: The water footprint provided a full methodology to operationalise the virtual water concept (the volume of water used along a supply chain to produce products and services). A key theme in the water footprint literature is the efficient allocation of water resources at the global scale given the feasibility of trading water intensive commodities from water rich to water poor areas: this is an economic problem of resource allocation between alternative and competing demands, albeit with a novel international component. Moreover, given that price signals indicating relative scarcity are usually either absent or distorted for water, it is also a problem that can be seen through the lens of environmental (or non-market) valuation. However, to date environmental valuation has not been used to inform the efficient use and allocation of water within and between the different locations encompassed by international supply chains. Methods: Drawing on an agri-food supply chain framework that we propose in this paper, we begin by conceptualising the economic values that accrue to water consumption (blue and green water) and degradation (grey water) at different points along a supply chain. Based on this conceptualisation, we assess the extent to which it is possible to approximate these economic values by relying on existing secondary data on the shadow value of water in different contexts. The use of secondary data in this way is known as benefit (or value) transfer. To achieve this, 706 unit estimates of the economic value of water are collected, standardised and reviewed encompassing off-stream water applications (agriculture, industry and municipal) and in-stream ecosystem services (waste assimilation, wildlife habitat, recreation, hydrological functions and passive uses). From this, a proposed methodology for valuing virtual water is presented and illustrated using the case study of global durum wheat pasta production. Results: The case study shows the total value of the virtual water used to produce one tonne of durum wheat pasta ($212). More importantly, the case study also highlights how variations in economic value between multiple locations where durum wheat is cultivated (Saskatchewan $0.10 m~3, Arizona $0.08 m~3 and Baja California $0.24 m~3) indicate relative water scarcity and thus impact, as well as the potential for a more efficient allocation of virtual water. Conclusions: The main conclusion from this research is that when geographical disparities in the economic value of water use within a supply chain are accounted for, what was perhaps considered sustainable in volume terms, might not, in fact, represent the optimal allocation. However, future research opportunities highlight the need for additional data collection on the economic value of water in several contexts. This additional data would help the environmental valuation community to undertake a more comprehensive and robust approach to virtual water valuation. This paper is accompanied by the Data in Brief article entitled "Dataset on the in-stream and off-stream economic value of water."
机译:目的:水占地面积提供了一种完整的方法,可以运作虚拟水概念(供应链沿供应链使用的水量以生产产品和服务)。水脚印文献中的一个关键主题是全球范围内有效的水资源配置,鉴于富含水贫困地区的贸易水密集型商品的可行性:这是替代和竞争需求之间资源配置的经济问题与新颖的国际组件。此外,鉴于指示相对稀缺的价格信号通常是缺乏或扭曲的水,也是通过环境(或非市场)估值的镜头可以看到的问题。但是,迄今为止,环境估值尚未被用来为国际供应链所包括的不同地点内部和不同地点之间的有效使用和分配信息。方法:在本文中提出的,绘制了我们提出的农业食品供应链框架,我们首先概念概念,沿着供应链的不同点处于耗水量(蓝色和绿色水)和降解(灰水)的经济价值。基于这种概念化,我们评估了通过依赖于不同背景下水的阴影值的现有二级数据来估计这些经济价值的程度。以这种方式使用辅助数据被称为益处(或价值)转移。为实现这一目标,收集了706单位对水的经济价值的估计,标准化和审查包括离岸水应用(农业,工业和市政)和流杂交生态系统服务(废物同化,野生动物栖息地,娱乐,水文功能和水文功能)被动用途)。由此,使用全球杜伦特小麦面食生产的案例研究,提出和说明了对估值虚拟水的提出方法。结果:案例研究表明,用于生产一吨杜兰麦面食的虚拟水的总价值(212美元)。更重要的是,案例研究还突出了杜兰麦小麦栽培的多个地点之间的经济价值变化(萨斯喀彻温省0.10米〜3,亚利桑那州0.08米〜3美元,Baja California $ 0.24 m〜3)表明相对水资源稀缺,因此影响以及更有效地分配虚拟水的潜力。结论:本研究的主要结论是,当供应链中使用水资源的经济价值的地理差异占时,可能在批量术语中考虑的可能性,实际上也不代表最佳分配。然而,未来的研究机会强调了在几种情况下对水的经济价值进行额外数据收集。这一额外数据将有助于环境估值界对虚拟水估值进行更全面且强大的方法。本文伴随着题为“关于流入和越野经济价值的数据集的数据集”。

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