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美国废物生命周期评估假设的全球变暖潜能影响:一种基于扰动的决策支持方法。

Global warming potential implications of US waste LCA assumptions: A perturbation-based approach for decision support.

作者信息

Anshassi Malak

机构信息

Department of Environmental Engineering, Florida Polytechnic University, United States.

出版信息

Waste Manag. 2025 Aug 1;204:114953. doi: 10.1016/j.wasman.2025.114953. Epub 2025 Jun 20.

Abstract

Waste management decision makers often rely on LCA findings to determine effective strategies to reduce environmental impacts, of which climate change mitigation has become centerstage. The complexity of conducting an LCA for waste management decision making is typically simplified using comprehensive models developed for wide region (e.g., United States, United Kingdom, Denmark) containing geographic and temporal metadata particular to the region. The aims of this study are to: 1) determine hotspot assumptions triggering the greatest sensitivity to the global warming potential (GWP) indicator for the management of various waste components in the US; and 2) inform on data collection approaches decision makers may use to improve their waste LCA by applying the findings of the first aim to a US context. A perturbation analysis was conducted for several recycling, landfilling, and combusting parameters using the Solid Waste Optimization Framework (SWOLF) Model. For landfilling, critical assumptions included landfill gas management factors such as lifetime gas collection efficiency, the type of gas management employed, and the bulk decay rate. In recycling, the most influential factor was the material substitution ratio. For combustion, key parameters were the avoided emissions from the electrical grid mixture and the types of metals recovered from the ash. Whenever data is available it should be supplemented in place of defaults to reduce uncertainty in waste LCA tools, especially the parameters highlighted that have influential impacts on results.

摘要

废物管理决策者通常依靠生命周期评估(LCA)的结果来确定减少环境影响的有效策略,其中减缓气候变化已成为核心问题。在进行用于废物管理决策的LCA时,其复杂性通常会通过使用为广大区域(如美国、英国、丹麦)开发的综合模型来简化,这些模型包含特定于该区域的地理和时间元数据。本研究的目的是:1)确定在美国对各类废物组分管理中,引发对全球变暖潜能值(GWP)指标最大敏感性的热点假设;2)通过将第一个目标的研究结果应用于美国的实际情况,为决策者提供数据收集方法方面的信息,以便他们改进废物LCA。使用固体废物优化框架(SWOLF)模型对几个回收、填埋和燃烧参数进行了扰动分析。对于填埋,关键假设包括填埋气管理因素,如气体收集寿命效率、采用的气体管理类型和总体衰减率。在回收方面,最有影响的因素是材料替代率。对于燃烧,关键参数是电网混合中避免的排放量以及从灰烬中回收的金属类型。只要有数据可用,就应补充数据以取代默认值,以减少废物LCA工具中的不确定性,特别是那些对结果有重大影响的突出参数。

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