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多维不确定性下的随机预期生命周期评估:预测欧洲未发现的微藻化合物的生产。

Stochastic Ex-Ante LCA under Multidimensional Uncertainty: Anticipating the Production of Undiscovered Microalgal Compounds in Europe.

机构信息

Department of Planning, Aalborg University, Rendsburggade 14, 9000Aalborg, Denmark.

出版信息

Environ Sci Technol. 2022 Nov 15;56(22):16382-16393. doi: 10.1021/acs.est.2c04849. Epub 2022 Oct 13.

Abstract

Due to their biodiversity, microalgae represent a promising source of high-value compounds that bioprospecting is aiming to reveal. Performing an ex-ante Life Cycle Assessment (LCA) to anticipate and potentially minimize the environmental burden associated with the European production of a bioprospected microalgal compound is subject to substantial and multi-factorial uncertainty as the compound remains undiscovered. Given that any microalgal strain could potentially host the compound of interest, the ex-ante LCA should consider this bioprospecting uncertainty together with the uncertainty on the technology and the production mix. Using a parameterized cultivation simulation and consequential LCA model and an extensive stochastic pseudo Monte Carlo approach, we define and propagate techno-operational, bioprospecting, and production mix uncertainties for a microalgal compound being currently bioprospected in Europe. We perform global sensitivity analysis using different sampling strategies to identify the main contributors to the total output variance. Overall, the uncertainty propagation allowed us to define and analyze the probabilistic scope for the potential environmental impacts in the emerging production of high-value microalgal compounds in Europe based on current knowledge. These findings can support policy-making as well as actors in the microalgal sector toward technological paths with lower environmental impact.

摘要

由于其生物多样性,微藻代表了有前途的高价值化合物来源,生物勘探旨在揭示这些化合物。由于所勘探的化合物尚未被发现,因此对欧洲生产生物勘探微藻化合物的环境负担进行事先的生命周期评估(LCA)以进行预测并可能最小化这种负担,存在大量多方面的不确定性。鉴于任何微藻菌株都有可能成为目标化合物的宿主,因此事先的 LCA 应该考虑到生物勘探的不确定性以及技术和生产组合的不确定性。我们使用参数化培养模拟和后续的 LCA 模型以及广泛的随机伪蒙特卡罗方法,为当前在欧洲进行生物勘探的微藻化合物定义和传播技术操作、生物勘探和生产组合的不确定性。我们使用不同的抽样策略进行全局敏感性分析,以确定总输出方差的主要贡献者。总体而言,不确定性传播使我们能够根据现有知识,为欧洲新兴的高价值微藻化合物生产中的潜在环境影响定义和分析概率范围。这些发现可以为政策制定者以及微藻行业的参与者提供支持,以选择对环境影响较小的技术路径。

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