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Data and methodological needs to assess uncertainty in the carbon footprint of ICT products

机译:评估ICT产品碳足迹不确定性的数据和方法论需求

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Several pressures have led to unprecedented corporate interest in “carbon footprinting” or life cycle assessment (LCA) of products. These pressures include historically high energy prices, climate change regulation, corporate sustainability efforts, and announcements from several major retailers that environmental data will be required from suppliers. There are significant challenges in standardizing such calculations and several proposed standards include those from the British Standards Institute, the International Standards Organization, and the World Resources Institute/World Business Council on Sustainable Development [1, 2]. This work discusses the particular challenges relevant to the information technologies (IT) industry''s ongoing investigation into the environmental impact of their products. IT products are complex and experience high turnover both in their manufacturing and assembly process flows as well as the supply chains used to procure materials and components. Often the results of quantifying environmental impacts are dominated by significant uncertainty and variability in the calculation of footprints, particularly for complicated products with large supplier networks. The existence of uncertainty is undisputed, and yet efforts to quantify uncertainty and variability in carbon footprints and life cycle assessments remain nascent at best. This research helps elucidate the data and methodological challenges in assessing uncertainties in the carbon footprinting of laptop and desktop computers.
机译:多种压力已导致企业对产品的“碳足迹”或生命周期评估(LCA)产生了空前的兴趣。这些压力包括历史上高昂的能源价格,气候变化法规,企业可持续发展努力,以及几家主要零售商宣布将要求供应商提供环境数据。标准化这些计算存在很大的挑战,一些拟议的标准包括英国标准协会,国际标准组织和世界资源研究所/世界可持续发展商业理事会的标准[1、2]。这项工作讨论了与信息技术(IT)行业正在进行的对其产品的环境影响的调查有关的特殊挑战。 IT产品非常复杂,其制造和组装流程以及用于采购材料和组件的供应链都具有很高的周转率。量化环境影响的结果通常以足迹计算中的显着不确定性和可变性为主导,尤其是对于具有大型供应商网络的复杂产品而言。不确定性的存在是无可争议的,但是量化碳足迹的不确定性和可变性以及生命周期评估的努力充其量仍处于起步阶段。这项研究有助于阐明在评估便携式计算机和台式计算机的碳足迹不确定性方面的数据和方法挑战。

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