Environmental databases have recently become an essential instrument in the sustainability evaluation of products. Unfortunately, these repositories still contain a limited number of chemicals. Furthermore, they are based on an attributional life cycle assessment (LCA) approach that considers fixed mass flows reflecting static industrial settings that are in practice dynamic, which might lead to errors. Building on some recent developments, we explore here an alternative approach to quantify the LCA impact of chemicals based on a network representation of the petrochemical industry coupled with linear programming, stochastic modeling and allocation methods. This method was applied to a network comprising 178 processes and 144 products, generating for most of the chemicals results that are consistent with those available in Ecoinvent for widely used impact categories such as GWP or those included in the ReCiPe 2008 methodology. The network model provides estimates of the life cycle impact embodied in chemicals under varying yields and demands, even for chemicals missing in standard repositories. Overall, we advocate for the use of network models of the petrochemical industry capable of carrying out consequential LCA under uncertainty as a complement to existing databases. This would allow to enlarge the capabilities of LCA repositories, thereby promoting the wider use of LCA in the chemical industry by improving the transparency and flexibility of the LCIA phase.

中文翻译：

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不确定性下的简化生命周期评估集成了石化行业网络和优化技术：Ecoinvent与数学建模

环境数据库最近已成为产品可持续性评估中的重要工具。不幸的是，这些存储库仍包含有限数量的化学物质。此外，它们基于归因生命周期评估（LCA）方法，该方法考虑固定质量流量，该流量反映了实际上是动态的静态工业设置，这可能会导致错误。基于最近的一些发展，我们在此探索一种替代方法，该方法基于石油化学工业的网络表示以及线性规划，随机建模和分配方法来量化化学物质对LCA的影响。此方法已应用于包含178个流程和144个产品的网络，对于大多数化学品而言，其产生的结果与Ecoinvent中针对广泛使用的影响类别（例如，全球升温潜能值）或ReCiPe 2008方法论中所包含的那些结果一致。网络模型提供了对产量和需求变化情况下化学品所包含的生命周期影响的估计，甚至对于标准存储库中缺少的化学品也是如此。总体而言，我们提倡使用能够在不确定性下进行相应LCA的石化行业网络模型，作为对现有数据库的补充。这将允许扩大LCA信息库的功能，从而通过提高LCIA阶段的透明度和灵活性来促进LCA在化学工业中的广泛使用。网络模型提供了对产量和需求变化情况下化学品所包含的生命周期影响的估计，甚至对于标准存储库中缺少的化学品也是如此。总体而言，我们提倡使用能够在不确定性下进行相应LCA的石化行业网络模型，作为对现有数据库的补充。这将允许扩大LCA信息库的功能，从而通过提高LCIA阶段的透明度和灵活性来促进LCA在化学工业中的广泛使用。网络模型提供了对产量和需求变化情况下化学品所包含的生命周期影响的估计，甚至对于标准存储库中缺少的化学品也是如此。总体而言，我们提倡使用能够在不确定性下进行相应LCA的石化行业网络模型，作为对现有数据库的补充。这将允许扩大LCA信息库的功能，从而通过提高LCIA阶段的透明度和灵活性来促进LCA在化学工业中的广泛使用。