Evaluation of Process- and Input–Output-based Life Cycle Inventory Data with Regard to Truncation and Aggregation Issues

Abstract

Life cycle assessments (LCA) and environmentally extended input-output (EEIO) analyses both strive to account for direct and indirect environmental impacts of goods and services. Different methods have been developed to hybridize these two techniques and minimize the impact of their respective shortcomings on final assessments. These weaknesses, however, have not been extensively studied in a quantitative manner, especially not for complete LCA and EEIO databases. To this end, we jointly analyzed process-based and input-output-based data sets. We first evaluated their complementarity. Though the LCA data was more detailed overall, some sectors of the economy were more precisely represented in the EEIO database. We then contrasted the representation of the different economic sectors in the LCA database with the economic, environmental, and structural importance of these sectors. The weakness of the correlation results led us to conclude that process-inventory efforts have not been systematically directed at the most important sectors of the economy. The LCA data was also used to evaluate the sensitivity of EEIO data to aggregation uncertainty. This sensitivity proved highly inhomogeneous. We conclude the presence of important research inefficiencies stemming from the lack of hybrid perspective in the compilation of LCA and EEIO data.

Assessing the life cycle environmental impacts of wind power: A review of present knowledge and research needs

“…However, the current survey demonstrates that hybrid LCA studies on wind power are still relatively scarce -this fits into a general trend that despite its acknowledged advantages, hybrid techniques have not yet become standard practice in LCA [10]. Hybrid LCA is more challenging to conduct and requires additional data, which may be an explanation for its lack of use.…”

“…While there is no consensus in the LCA community on how to measure the truncation bias of process-LCA, in all explorations into this issue surveyed by MajeauBettez et al [10] it is found that process-LCA fails to account for 30% or more of total indicator values. This predicates that the employment of hybrid LCA methodologies should be a goal of future LCA research on wind power; and that if hybrid techniques on the other hand are not applied, the problem of cut-off errors should at the least be recognized -in existing literature this is not the case.…”

“…On the downside, there is a need to apply cut-off criteria to exclude operations that are not expected to make significant contributions. It is known, however, that added together the excluded contributions are significant [10,11]. The second approach, environmentally extended input-output analysis (EEIOA), is a top-down technique in which inventories are quantified using monetary data at the level of economic sectors.…”

“…However, EEIOA operates at a high aggregation level; the sector resolution in EEIOA is generally too coarse for making LCAs of specific products. Hybrid methods -where process-LCA is used to model important operations, and EEIOA is used to model operations that would otherwise be omitted -can potentially exploit advantages of both approaches, but is more challenging to employ [10][11][12]. Also, depending on the method of hybridization and quality of data [12], most hybrid models may offer limited support for following material flows through product systems.…”

Application of Environmental Input-Output Analysis for Corporate and Product Environmental Footprints—Learnings from Three Cases

“…An EIO analysis is a "top-down" approach, capable of capturing impacts from the entire supply chain and is useable as a screening tool to inform estimation of the anticipated life cycle emissions [2]. However, the approach is also criticised, mainly for being too aggregated, thus causing the need to hybridize with "bottom-up" data collection, where the generic EIO model is evaluated as being insufficient [2,[13][14][15].…”