Advancing LCA by Integrating Socio-Technical Complexity through Agent-Based Modelling (UTC 8:00 AM)
Session Organizer : Kasper Lange, Ryu Koide, Jonathan Cohen, Agnese Fuortes, Paul Carrey, Gustavo Gallegos, Michał Bączyk, Tianran Ding (Life-Cycle Thinking for Complex-Systems Initiative)
Institution : Amsterdam University, Amsterdam
Location / Local Time : Amsterdam / 9:00 AM
Abstract :
We are a group of researchers who adopt a complexity-oriented approach to study topics relevant to the Industrial Ecology (IE) community. We recognise the growing need for a dedicated space to discuss modelling approaches, challenges, and opportunities. This session is organised by a network of researchers to advance the methodology and application of complexity-based approaches in this field.
Methodologically, we employ Agent-Based Modelling (ABM) and other complexity-oriented computational tools to represent the complex interactions between various actors and their surrounding environments and integrate them with IE tools.
In this session, we will briefly introduce why complexity is an important issue for IE research, particularly for understanding socio-technical systems, modelling policy interventions, and addressing deep uncertainty. We will then present how ABM can contribute to different flavours of LCA, which has attracted recent advancements in the field (e.g., prospective, dynamic, consequential, and territorial LCA).
After that, participants will be invited to join an interactive discussion to collectively identify the types of complexity we commonly encounter in IE research, examine how conventional IE methods currently address these complexities, and explore the opportunities and challenges of integrating complexity-oriented methods into IE research.
The session is composed of the following presentations and interactive discussions:
Introduction to complexity (10 min)
- What is complexity? (e.g., emergence, feedback, heterogeneity, spatio-temporal dynamics)
- Why do we need complexity science methods in industrial ecology? (e.g., circular economy, energy system, rebound effect, user behaviour)
- Overview of agent-based modelling and computational simulation methods
- Introduction of Life-Cycle Thinking for Complex-Systems Initiative
Contribution of agent-based modelling to the advancement of LCA (10 min)
- Dynamicity and temporality: Prospective and Dynamic LCA
- Causality: Consequential LCA
- Scale: Territorial LCA
Paradigm shifts in IE research through integrating agent-based modelling (5 min)
- Decision-makers in complex socio-technical systems
- Endogenised modelling of policy interventions
- Decision making under deep uncertainty
Interactive discussion (30 min):
- What types of complexity arise in your research or application area?
- How are these complexities currently addressed using IE methods (e.g., LCA, MFA, EEIOA)?
- How might complexity science methods (e.g., ABM) be integrated into IE research to tackle these complexities? What challenges remain?
Reflection and concluding remarks (5 min)
Overall, this session aims to establish a shared understanding of complexity in IE research and clarify the benefits and challenges of integrating complexity science. Such a session will provide a virtual space to engage with fellow modellers and further discuss methods and applications to study sustainable practices.
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