A new method to estimate the lifetime of long-life product categories
A new method to estimate the lifetime of long-life product categories
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DOI：
10.1111/jiec.13093
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发表时间：
2020-12-12
影响因子：
5.9
通讯作者：
Cullen, Jonathan M.
中科院分区：
文献类型：
--
作者：
Dunant, Cyrille F.;Shah, Trishla;Cullen, Jonathan M.
提高回收和再利用率是COP 21制定的目标的核心部分。然而，所谓的循环经济的实际实施及其真正潜力并不容易确定。这是因为任何干预措施的影响和实施时间尺度都取决于对产品寿命的了解，而这往往是未知的。这在建筑业尤其如此，占全球排放量的39%，其中11%是体现。当缺乏自下而上的数据时，大多数物质流分析（MFA）模型将简单地假设一系列合理的预期寿命。在这项工作中，我们提出了一种新的识别方法，使用高质量，但高度汇总的贸易数据，并使用它来建立一个“死亡率曲线”的建筑物和其他持久的产品。这种识别方法旨在为现有的MFA模型提供更可靠的输入。由于基础数据的普遍可用性，它被广泛应用。将其用于英国的贸易数据，我们将包装/家庭废料的产品分类确定为1年，车辆/设备的产品分类为1至10年左右，建筑产品分类为50年左右。识别方法，然后使用经典的方法，使用自下而上的数据的车辆进行验证。
Increased recycling and reuse rates are a central part of the objectives laid out by the COP21. Nonetheless, the practical implementation of what has been called the circular economy, as well as its true potential, are not easily established. This is because the impact and implementation time scales of any intervention depend on knowing the lifetime of products, which is frequently unknown. This is particularly true in construction, responsible for 39% of worldwide emissions, 11% of which are embodied. Most material flow analysis (MFA) models will simply assume a range of plausible life expectancies when bottom-up data are lacking. In this work, we propose a novel method of identification using the high quality but highly aggregated trade data available and use it to establish a "mortality curve" for buildings and other long-lasting products. This identification method is intended to provide more reliable inputs to existing MFA models. It is widely applicable because of the general availability of the underlying data. Using it on United Kingdom trade data, we identify product classes at 1 year for packaging/home scrap, 1 to around 10 years for vehicles/equipment, and around 50 years for construction. The identification approach was then validated by using classical approaches using bottom-up data for vehicles.