(492c) A Framework for Multiscale Consequential Life Cycle Assessment

A significant drawback of normal Life cycle assessment(LCA) methods is its results sometimes becoming irrelevant on real world application due to unintended effects. Conventional Attributional LCA (ALCA) directly compares a functional unit of new technology with a base technology and determines which one is environmentally superior. It doesn’t consider the introduction of this technology into society, its acceptance and the ripple effects that might occur due to such a technology in the real world. Such a problem can be thought of as being analogous to a chemical engineering design problem in a laboratory (attributional LCA) versus a full-sized industry (real world impacts).

Consequential LCA (2) is one method which is currently used to capture these ripple effects in the society. It considers interaction between markets, looks at knock on effects, and changes in production levels. Due to its relative recent development, this method is not yet well established and different methods are practiced for performing a consequential LCA (CLCA). Broadly, the two methods are Hierarchy based (3) and Equilibrium modeling based (4).

Motivation:

It is observed from CLCA literature that hierarchy based methods are prone to system boundary selection problem due to the subjective nature of selecting marginal technologies. Equilibrium based modeling CLCA literature shows that even though the system expansion is easily obtained through economic model use, significant details are lost due to high data aggregation of such models, rendering them useless for application to specific processes. In this presentation, we propose a novel multiscale solution to this problem by developing a CLCA based optimization framework that combines both these methods. The equilibrium models in this framework will help in system expansion which reduces errors in system boundary selection while the hierarchy based approach can be focused on processes where greater resolution and details are required. Along with that, the presence of third finer engineering scale enables designing of processes while performing CLCA, which is a novel approach in the Sustainable Process Design field that has typically used ALCA for determining environmental impacts.

Objective:

The objective of this research work is to create a consequential LCA based optimization framework that utilizes both the CLCA pathways mentioned in the Background. The advantage of integrating these pathways is that this new framework will be able to derive the advantages of each pathway while addressing each other’s inadequacies. It is an extension of the P2P framework for process design to consider consequences of the optimization decisions. P2P framework with its multiscale nature serves as a suitable platform for building this CLCA framework. The engineering scale is the scale for determination of industry level design variables for performing process design. The value chain or upstream network scale is suited to model the hierarchy based CLCA based method using a choice of technology approach. The economy scale which previously used a simple economic Input-Output IO model is replaced with an economic general equilibrium model that can explore interaction between markets, price changes, marginal and non-marginal effects.

Results:

A significant challenge for this work is the integration of equilibrium models with the other scales due to its own optimization structure that is separate from the rest of the framework. Obtaining consequential life cycle inventory data and equilibrium models is significantly difficult as well. The framework will be applied to case studies such as but not limited to carbon fiber use in vehicle manufacturing, process intensification for improving the production efficiency of manufacturing processes, decentralization of manufacturing processes to promote better availability of products and services in rural areas and other interesting problems. We also intend to compare with normal ALCA and check differences in results.

References:

1. Hanes, Rebecca J., and Bhavik R. Bakshi. "Sustainable process design by the process to planet framework." AIChE Journal 61.10 (2015): 3320-3331.
2. Zamagni, Alessandra, et al. "Lights and shadows in consequential LCA." The International Journal of Life Cycle Assessment7 (2012): 904-918.
3. Ekvall, Tomas, and Bo P. Weidema. "System boundaries and input data in consequential life cycle inventory analysis." The International Journal of Life Cycle Assessment3 (2004): 161-171.
4. Earles, J. Mason, et al. "Integrated economic equilibrium and life cycle assessment modeling for policy‐based consequential LCA." Journal of Industrial Ecology3 (2013): 375-384.