To what extent can agent-based modelling enhance a life cycle assessment? Answers based on a literature review

Abstract

Life cycle assessment (LCA) has proven its worth in modelling the entire value chain associated with the production of goods and services. However, modelling the consumption system, such as the use phase of a product, remains challenging due to uncertainties in the socioeconomic context. Agent-based models (ABMs) can reduce these uncertainties by improving the consumption system modelling in LCA. So far, no systematic study is available on how ABM can contribute towards a behavior-driven modelling in LCA. This paper aims at filing this gap by reviewing all papers coupling both tools. A focus is carried out on 18 case studies which are analysed according to criteria derived from the four phases of LCA international standards. Criteria specific to agent-based models and the coupling of both tools, such as the type and degree of coupling, have also been selected. The results show that ABMs have been coupled to LCA in order to model foreground systems with too many uncertainties arising from a behaviour-driven use phase, local variabilities, emerging technologies, to explore scenarios and to support consequential modelling. Foreground inventory data have been mainly collected from ABM at the use phase. From this review, we identified the potential benefits from ABM at each LCA phase: (i) scenario exploration, (ii) foreground inventory data collection, (iii) temporal and/or spatial dynamics simulation, and (iv) data interpretation and communication. Besides, methodological guidance is provided on how to choose the type and degree of coupling during the goal and scope phase. Finally, challenging LCA areas of research that could benefit from the agent-based approach to include behaviour-driven dynamics at the inventory and impact assessment phase have been identified.

Comparing the environmental performance of distributed versus centralized plastic recycling systems: Applying hybrid simulation modeling to life cycle assessment

“…Different types of simulation modeling methods have been applied in many LCA studies, specifically to analyze decision‐making for sustainable policy implementation, improve representation of the use phase (Mashhadi & Behdad, 2018), and analyze the effect of supply chain and market penetration on the environmental impacts of emerging technologies (Micolier et al., 2019). This LCA study employed hybrid simulation modeling to better represent the local conditions in order to generate results that are more relevant to the intended audience.…”

Do We Need a New Sustainability Assessment Method for the Circular Economy? A Critical Literature Review

“…Methods are often combined to alleviate each other's weaknesses. LCA has been used in combination with SD, ABM, EEIOA, and other methods to answer specific questions with more accuracy (Micolier et al, 2019;Yang, 2019). When SD is coupled with LCA, it adds temporal aspects to LCA (Peng et al, 2018), and LCA/SD coupling has been used to assess the economic and environmental performance of circular product systems (Asif et al, 2016).…”

“…Small scale dynamic MFA; tracks material flows in production systems (Widok et al, 2011) SD with greater details on specific part of the system (Morgan et al, 2017) None 242 281 ABM Dynamic LCA of systems with no central control; models market potential (Micolier et al, 2019) Dynamic analysis integrating microeconomic and macroeconomic data; models market potential (Al Irsyad et al, 2019) Dynamic MFA of systems with no central control; models market potential (Bollinger et al, 2012) SD of systems where heterogeneity and emergence matters; models market potential (Brailsford et al, 2019) DES of technical infrastructure populated with individuals; models market potential (Abel and Faust, 2020) None 59 OR LCA of a system optimal state; decision when faced with multiple conflicting criteria (Thies et al, 2019) Macroeconomic impact of optimal local value chains; decision when faced with multiple conflicting criteria (Johansen et al, 2017) Optimization of material flows (Cooper et al, 2020) SD models system, OR finds optimal system configuration; decision when faced with multiple conflicting criteria (Linnéusson et al, 2020) DES models system, OR finds optimal system configuration; decision when faced with multiple conflicting criteria (Linnéusson et al, 2020) DES models system, OR finds optimal system configuration; decision when faced with multiple conflicting criteria (Wu et al, 2020) None ABM, agent-based modeling; SD, system dynamics; MFA, material flow analysis; EEIOA, environmentally extended input output analysis; LCA, life cycle assessment; OR, operations research; DES, discrete event simulation. contribution of a system to the environmental and economic pillars of sustainability but do not usually account for social aspects (Merli et al, 2018), while emergy and exergy focus on the environment through energy accounting.…”

Agent-based modeling and simulation in the research of environmental sustainability. A bibliography

“…An additional study was included following the suggestion of an annonymous reviewer. The final set is cited in references [103][104][105][106][107][108][109][110][111][112][113].…”