Mutel Chris, Liao Xun, Patouillard Laure, Bare Jane, Fantke Peter, Frischknecht Rolf, Hauschild Michael, Jolliet Olivier, de Souza Danielle Maia, Laurent Alexis, Pfister Stephan, Verones Francesca
Paul Scherrer Institute, 5232 PSI Villigen, Switzerland.
Industrial Process and Energy Systems Engineering, Ecole Polytechnique Fédérale de Lausanne, EPFL Valais Wallis, Rue de l'Industrie 17, CH-1951 Sion, Switzerland.
Int J Life Cycle Assess. 2019 May 1;24(5):856-865. doi: 10.1007/s11367-018-1539-4.
Regionalized life cycle impact assessment (LCIA) has rapidly developed in the past decade, though its widespread application, robustness, and validity still faces multiple challenges. Under the umbrella of UNEP/SETAC Life Cycle Initiative, a dedicated cross-cutting working group on regionalized LCIA aims to provides an overview of the status of regionalization in LCIA methods. We give guidance and recommendations to harmonize and support regionalization in LCIA for developers of LCIA methods, LCI databases, and LCA software.
A survey of current practice among regionalized LCIA method developers was conducted. The survey included questions on chosen method spatial resolution and scale, the spatial resolution of input parameters, choice of native spatial resolution and limitations, operationalization and alignment with life cycle inventory data, methods for spatial aggregation, the assessment of uncertainty from input parameters and model structure, and variability due to spatial aggregation. Recommendations are formulated based on the survey results and extensive discussion by the authors.
Survey results indicate that majority of regionalized LCIA models have global coverage. Native spatial resolutions are generally chosen based on the availability of global input data. Annual modelled or measured elementary flow quantities are mostly used for aggregating characterization factors (CFs) to larger spatial scales, although some use proxies, such as population counts. Aggregated CFs are mostly available at the country level. Although uncertainty due to input parameter, model structure, and spatial aggregation are available for some LCIA methods, they are rarely implemented for LCA studies. So far, there is no agreement if a finer native spatial resolution is the best way to reduce overall uncertainty. When spatially differentiated models CFs are not easily available, archetype models are sometimes developed.
Regionalized LCIA methods should be provided as a transparent and consistent set of data and metadata using standardized data formats. Regionalized CFs should include both uncertainty and variability. In addition to the native-scale CFs, aggregated CFs should always be provided, and should be calculated as the weighted averages of constituent CFs using annual flow quantities as weights whenever available. This paper is an important step forward for increasing transparency, consistency and robustness in the development and application of regionalized LCIA methods.
区域化生命周期影响评估（LCIA）在过去十年中迅速发展，但其广泛应用、稳健性和有效性仍面临多重挑战。在联合国环境规划署/SETAC生命周期倡议的框架下，一个专门的区域化LCIA跨领域工作组旨在概述LCIA方法中的区域化现状。我们为LCIA方法开发者、LCI数据库开发者和LCA软件开发者提供指导和建议，以协调和支持LCIA中的区域化。
对区域化LCIA方法开发者的当前实践进行了调查。调查内容包括所选方法的空间分辨率和尺度、输入参数的空间分辨率、原生空间分辨率的选择及其局限性、与生命周期清单数据的操作化和一致性、空间聚合方法、输入参数和模型结构的不确定性评估以及空间聚合导致的变异性。根据调查结果和作者的广泛讨论制定了建议。
调查结果表明，大多数区域化LCIA模型具有全球覆盖范围。原生空间分辨率通常根据全球输入数据的可用性来选择。年度建模或测量的基本流量数量大多用于将特征因子（CFs）聚合到更大的空间尺度，尽管有些使用代理数据，如人口数量。聚合后的CFs大多在国家层面可用。虽然一些LCIA方法可以提供输入参数、模型结构和空间聚合带来的不确定性，但它们在LCA研究中很少得到应用。到目前为止，对于更精细的原生空间分辨率是否是降低总体不确定性的最佳方法尚无定论。当空间差异化模型的CFs不易获取时，有时会开发原型模型。
应使用标准化数据格式，以一套透明且一致的数据和元数据形式提供区域化LCIA方法。区域化CFs应包括不确定性和变异性。除了原生尺度的CFs外，还应始终提供聚合后的CFs，并且只要可行，应使用年度流量数量作为权重，将其计算为组成CFs的加权平均值。本文是朝着提高区域化LCIA方法开发和应用的透明度、一致性和稳健性迈出的重要一步。
