In Search of a Consistent Solution to Allocation of Joint Production

Abstract

Summary Three consistency problems are identified that arise when partitioning a product system with joint production according to an allocation key, such as revenue or mass of the joint products, namely: lacking consistency of rationales and procedures; lacking consistency of monetary, mass, and energy balances in the partitioned product systems; and lacking consistency of results across model resolution and classification of the intermediate flows. Different solutions to these consistency problems are described, including the attempt of ecoinvent to solve the third consistency problem with a system model that uses revenue allocation at the point of substitution. The problems with the different practical implementations are described. For each of the three consistency problems, a solution is proposed and combined into a single consistent solution. The consistency of rationales and procedures is ensured by asking only one question at a time and performing a separate allocation and calculation for each question. The problem of maintaining monetary, mass, and energy balances is solved by a generalized allocation correction. The identified problem with consistency of results across model resolution and classification is solved by redefining the point of substitution. It is described what consequences the solutions will have if their results are misused for decision making that will shift demand between products.

Waste is not a service

“…And even stronger, if the process "has only one product output, this is the reference product." The principles of ecoinvent v3 have been further elaborated by Weidema (2018). The consistency problems that are discussed in that paper in fact arise from an attempt to distinguish production processes and disposal processes and then to tweak disposal processes in a production format.…”

Suggested use? On evidence‐based decision‐making in industrial ecology and beyond

“…To make data inputs more valid or their validity at least testable, scholars have been promoting data transparency (Hertwich et al., 2018). Recent examples of similar efforts include proposals for interactive visualization of data (Font Vivanco et al., 2019); general, method‐independent data model (Pauliuk, Heeren, Hasan, & Müller, 2019); investigation of uncertainty quantification and distribution in LCA (Ross & Cheah, 2019; Weidema, 2018); estimation of uncertainty (Min & Rao, 2018) and aggregation bias (Zhang, Caron, & Winchester, 2019) in using multiregional IO tables; and quantitative evaluation of MFA data quality and uncertainty (Schwab & Rechberger, 2018; Schwab, Laner, & Rechberger, 2017). Along this line, the Journal of Industrial Ecology ( JIE ) has developed data openness badges to acknowledge authors’ efforts in making data transparent and accessible.…”

Can smart factories bring environmental benefits to their products?: A case study of household refrigerators

“…The background datasets are adopted according to the regional correlation level (the average levels of China, Europe, and World), and they are consistent with the actual technical situations of Haier. Based on the actual situation and existing literatures (ISO, ; Weidema, ), the multifunctionality of co‐production is addressed. For the background multifunctional processes in the Gabi databases, the inventory data have been allocated to reference output flow according to various principles like market value, gross calorific value, mass, and volume.…”