Purpose

Model uncertainties in life cycle assessment (LCA) can arise due to the lack or limited knowledge of the system (epistemic), or due to the inherent spatial and/or temporal variability of the processes that characterize it (stochastic). Scenario analysis is often used to address such uncertainties. However, the analysis does not provide information on which scenario is more representative of the system, or more likely to occur. To account for model uncertainties in LCA, the approach presented here estimates the likelihood of occurrence of the scenarios by assigning probabilities to the events characterizing them.

Method

An integrated life cycle assessment (LCA) and quantitative risk assessment (QRA) approach was developed to include the likelihood of occurrence of future events, and their consequences, in the definition of one representative scenario. The integration of the two tools was conceived at a framework level, with the inclusion of probability estimates as weighting factors for the scenario results. These probability estimates for each scenario allow improving the spatial and temporal representativeness of the model of the system.

The approach was applied to a landfill case study to test its applicability in defining the impacts of a landfill reference scenario. Twelve scenarios were developed to represent the potential variation of landfill conditions over time. In particular, the degradation and failure of the containment systems, and the flooding of the site, were the main events considered in the scenario definition. An event tree was built to estimate the probability of occurrence of each scenario.

Results

Expected values and standard deviations were computed for all impact categories based on the impacts and their probabilities. Additional information on the probability of obtaining a certain impact was further provided by the impact curve built as function of the impacts and their cumulative probability.

Conclusions

Overall, the results of the study highlight the potential of the approach and the relevance of the information that the results can provide on the impact of a landfill, and more generally a system, under varying conditions over time.

中文翻译：

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整合生命周期评估（LCA）和定量风险评估（QRA）以解决模型的不确定性：在环境和工程条件变化的情况下定义垃圾填埋场参考案例

目的

生命周期评估（LCA）中的模型不确定性可能是由于缺乏或有限的系统知识（经验性），或者由于表征该过程的过程的固有空间和/或时间可变性（随机性）而引起的。情景分析通常用于解决此类不确定性。但是，该分析没有提供有关哪种方案更能代表系统或更有可能发生的信息。为了解决LCA中的模型不确定性，此处介绍的方法通过将概率分配给表征事件的概率来估计场景发生的可能性。

方法

开发了一种集成的生命周期评估（LCA）和定量风险评估（QRA）方法，以在一种代表性场景的定义中包括未来事件发生的可能性及其后果。两种工具的集成是在框架级别上构想的，其中包括概率估计值作为方案结果的加权因子。针对每种情况的这些概率估计值可以改善系统模型的时空代表性。

该方法已应用于垃圾填埋场案例研究，以测试其在定义垃圾填埋场参考方案的影响方面的适用性。开发了十二种方案来表示垃圾填埋场条件随时间的潜在变化。特别是，安全壳系统的退化和故障，以及场地的洪水泛滥是方案定义中考虑的主要事件。建立了事件树来估计每种情况的发生概率。

结果

根据影响及其概率计算所有影响类别的预期值和标准偏差。根据影响及其累积概率构建的影响曲线进一步提供了有关获得特定影响概率的其他信息。

结论

总体而言，研究结果强调了该方法的潜力以及该结果可提供的信息在一段时间内变化的条件下对垃圾填埋场（更一般而言是一个系统）的影响的相关性。