William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, Ohio 43210, USA.
Environ Sci Technol. 2010 Jan 15;44(2):800-7. doi: 10.1021/es902571b.
While methods for aggregating emissions are widely used and standardized in life cycle assessment (LCA), there is little agreement about methods for aggregating natural resources for obtaining interpretable metrics. Thermodynamic methods have been suggested including energy, exergy, and emergy analyses. This work provides insight into the nature of thermodynamic aggregation, including assumptions about substitutability between resources and loss of detailed information about the data being combined. Methods considered include calorific value or energy, industrial cumulative exergy consumption (ICEC) and its variations, and ecological cumulative exergy consumption (ECEC) or emergy. A hierarchy of metrics is proposed that spans the range from detailed data to aggregate metrics. At the fine scale, detailed data can help identify resources to whose depletion the selected product is most vulnerable. At the coarse scale, new insight is provided about thermodynamic aggregation methods. Among these, energy analysis is appropriate only for products that rely primarily on fossil fuels, and it cannot provide a useful indication of renewability. Exergy-based methods can provide results similar to energy analysis by including only nonrenewable fuels but can also account for materials use and provide a renewability index. However, ICEC and its variations do not address substitutability between resources, causing its results to be dominated by dilute and low-quality resources such as sunlight. The use of monetary values to account for substitutability does not consider many ecological resources and may not be appropriate for the analysis of emerging products. ECEC or emergy explicitly considers substitutability and resource quality and provides more intuitive results but is plagued by data gaps and uncertainties. This insight is illustrated via application to the life cycles of gasoline, diesel, corn ethanol, and soybean biodiesel. Here, aggregate metrics reveal the dilemma facing the choice of fuels: high return on investment versus high renewability.
虽然在生命周期评估（LCA）中广泛使用和标准化了汇总排放的方法，但对于汇总自然资源以获得可解释指标的方法却没有达成共识。已经提出了热力学方法，包括能量、火用和生态能分析。这项工作深入了解了热力学汇总的性质，包括对资源之间可替代性的假设以及对正在组合的数据的详细信息的损失。所考虑的方法包括热值或能量、工业累计火用消耗（ICEC）及其变体，以及生态累计火用消耗（ECEC）或生态能。提出了一个从详细数据到汇总指标的度量层次结构。在细粒度级别，详细数据可以帮助确定产品最容易受到消耗的资源。在粗粒度级别，提供了关于热力学汇总方法的新见解。在这些方法中，能量分析仅适用于主要依赖化石燃料的产品，并且不能提供有用的可再生性指示。基于火用的方法可以通过仅包括不可再生燃料来提供与能量分析相似的结果，但也可以考虑材料使用并提供可再生性指数。然而，ICEC 及其变体没有解决资源之间的可替代性，导致其结果主要由稀释和低质量资源（如阳光）主导。使用货币价值来考虑可替代性不考虑许多生态资源，并且可能不适合新兴产品的分析。ECEC 或生态能明确考虑了资源的可替代性和质量，并提供了更直观的结果，但受到数据差距和不确定性的困扰。通过应用于汽油、柴油、玉米乙醇和大豆生物柴油的生命周期来说明这种见解。在这里，汇总指标揭示了燃料选择面临的困境：高投资回报率与高可再生性。
