Implementation of Agent-Based Models to support Life Cycle Assessment: A review focusing on agriculture and land use

Marvuglia, Antonino; Gutiérrez, Tomás Navarrete; Baustert, Paul; Benetto, Enrico

doi:10.3934/agrfood.2018.4.535

Cited by 26 publications

(20 citation statements)

References 79 publications

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“…Such platforms ease model development with an explicit and natural representation of human behaviour, which allows non-computer scientists to be included in the modelling process. Thus, decision-makers can be involved from the early modelling stages and, as underlined by (Marvuglia et al, 2018), the transparency of these participatory modelling processes favour the acceptance of the final decision by different stakeholders. Besides, these platforms are continuously upgraded, and one could imagine that they could later automatically integrate the LCA data, as some already do with GIS for example (e.g., GAMA).…”

Section: Limitations and Perspectives Of The Coupling Methodologymentioning

confidence: 99%

“…One critical review that focusses on the uncertainty in ABM and LCA-coupled models was found (Baustert and Benetto, 2017). Marvuglia et al (2018) -Several case studies are covered by two or more papers. The paper by (Navarrete Gutierrez et al, 2015a) was also covered by (Marvuglia et al, 2016), who made a return on experience.…”

Section: Selection Of Articlesmentioning

confidence: 99%

“…The first reason is that the computational improvements in the modelling of complex systems were made recently. In addition, the required expertise in both fields is not highly prevalent, as noted by (Marvuglia et al, 2018). If ABM can contribute towards a better behavior-driven modelling in LCA, an overall picture of the coupling strengths and weaknesses is still missing to take full advantage of the capabilities of agent-based modeling for LCA methodology.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Micolier

Loubet

Taillandier

et al. 2019

Journal of Cleaner Production

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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.

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Section: Limitations and Perspectives Of The Coupling Methodologymentioning

confidence: 99%

Section: Selection Of Articlesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Micolier

Loubet

Taillandier

et al. 2019

Journal of Cleaner Production

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show abstract

“…Many studies have noted that the steady-state and linear nature of LCA is a major limitation and have explored the options to address this by introducing a dynamic approach using tools such as agent-based modelling (ABM) [6,9,10]. In addition to ABM, there are other tools available such as discrete-event simulation (DES) and system dynamics (SD) to assess the dynamic aspects of the biomass supply chain.…”

Section: Introductionmentioning

confidence: 99%

Lifecycle Assessment of Biomass Supply Chain with the Assistance of Agent-Based Modelling

Aalto

Korpinen

et al. 2020

Sustainability

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Even though biomass is characterised as renewable energy, it produces anthropogenic greenhouse gas (GHG) emissions, especially from biomass logistics. Lifecycle assessment (LCA) is used as a tool to quantify the GHG emissions from logistics but in the past the majority of LCAs have been steady-state and linear, when in reality, non-linear and temporal aspects (such as weather conditions, seasonal biomass demand, storage capacity, etc.) also have an important role to play. Thus, the objective of this paper was to optimise the environmental sustainability of forest biomass logistics (in terms of GHG emissions) by introducing the dynamic aspects of the supply chain and using the geographical information system (GIS) and agent-based modelling (ABM). The use of the GIS and ABM adds local conditions to the assessment in order to make the study more relevant. In this study, GIS was used to investigate biomass availability, biomass supply points and the road network around a large-scale combined heat and power plant in Naantali, Finland. Furthermore, the temporal aspects of the supply chain (e.g., seasonal biomass demand and storage capacity) were added using ABM to make the assessment dynamic. Based on the outcomes of the GIS and ABM, a gate-to-gate LCA of the forest biomass supply chain was conducted in order to calculate GHG emissions. In addition to the domestic biomass, we added imported biomass from Riga, Latvia to the fuel mixture in order to investigate the effect of sea transportation on overall GHG emissions. Finally, as a sensitivity check, we studied the real-time measurement of biomass quality and its potential impact on overall logistical GHG emissions. According to the results, biomass logistics incurred GHG emissions ranging from 2.72 to 3.46 kg CO2-eq per MWh, depending on the type of biomass and its origin. On the other hand, having 7% imported biomass in the fuel mixture resulted in a 13% increase in GHG emissions. Finally, the real-time monitoring of biomass quality helped save 2% of the GHG emissions from the overall supply chain. The incorporation of the GIS and ABM helped in assessing the environmental impacts of the forest biomass supply chain in local conditions, and the combined approach looks promising for developing LCAs that are inclusive of the temporal aspects of the supply chain for any specific location.

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“…[35, p. 641] One means of addressing the limitations of snapshot and aggregate data is through the incorporation of ABM to project possible system states, or to generate data for assessment tools. This is the approach taken by scholars looking to incorporate ABM and LCA [36,37]. Life cycle assessment (LCA) is a tool for holistically assessing the environmental impacts of a product's entire life cycle, and it can be expanded out into life cycle sustainability assessment (LCSA) by incorporating social and economic indicators [30].…”

Section: Modeling Complex Systems For Sustainability Sciencementioning

confidence: 99%

Application of Agent-Based Modeling to Complex Systems

Zupko¹,

Robert²

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Implementation of Agent-Based Models to support Life Cycle Assessment: A review focusing on agriculture and land use

Cited by 26 publications

References 79 publications

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

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

Lifecycle Assessment of Biomass Supply Chain with the Assistance of Agent-Based Modelling

Application of Agent-Based Modeling to Complex Systems

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