Industrial ecology tools are increasingly being used in ways that require high computational times. In the policy arena, this becomes problematic when practitioners want to live‐test various alternatives in a responsive and web‐based platform. In research, computational times come into play when analyzing large systems with multiple interventions or when requiring many runs for, for example, Monte Carlo simulations. We demonstrate how the computational time of a number of commonly used industrial ecology tools can be reduced significantly, potentially by multiple orders of magnitude. Our case study was the optimization of scenario calculations in Environmentally Extended Input–Output Analysis (EEIOA). Instead of recalculating the Leontief inverse after individual changes to the interindustry relations, as is done traditionally in EEIOA scenario analysis, we give formulations to find the total value of the change in the environmental indicators in one calculation step. We illustrate these novel formulations both for a simple hypothetical system and for the full EXIOBASE EEIO model. The use of explicit formulas decreases the computational time to the degree that it becomes possible to carry out these analyses in live or web‐based environments. For our case study, we find an improvement of up to four orders of magnitude.

中文翻译：

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有效地计算环境扩展的投入产出情景和循环经济模型

工业生态工具正以需要大量计算时间的方式越来越多地被使用。在政策领域，当从业人员想要在响应式和基于Web的平台中对各种替代方案进行实时测试时，这将成为问题。在研究中，计算时间在分析具有多个干预措施的大型系统或需要进行多次运行（例如，蒙特卡洛模拟）时发挥作用。我们演示了如何显着减少多个常用工业生态工具的计算时间（可能会减少多个数量级）。我们的案例研究是环境扩展投入产出分析（EEIOA）中方案计算的优化。在个体间更改产业间关系之后，不必重新计算Leontief逆，正如在EEIOA情景分析中传统上所做的那样，我们给出公式以在一个计算步骤中找到环境指标变化的总值。我们为简单的假设系统和完整的EXIOBASE EEIO模型说明了这些新颖的公式。使用显式公式将计算时间减少到可以在实时或基于Web的环境中进行这些分析的程度。对于我们的案例研究，我们发现最多可以改进四个数量级。使用显式公式将计算时间减少到可以在实时或基于Web的环境中进行这些分析的程度。对于我们的案例研究，我们发现最多可以改进四个数量级。使用显式公式将计算时间减少到可以在实时或基于Web的环境中进行这些分析的程度。对于我们的案例研究，我们发现最多可以改进四个数量级。