Coupling agent-based modeling with territorial LCA to support agricultural land-use planning. (20th December 2022)

• Record Type: Journal Article
• Authors: Ding, Tianran; Achten, Wouter M.J.
• Is Part Of: Journal of cleaner production. Volume 380:Part 1(2022)
• Publication Date: 2022-12-20
• Subjects: Territorial LCA -- Agent-based modeling -- Geographical information systems -- Land planning; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2022.134914
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: Life cycle assessment (LCA) is applied to assess large-scale systems supporting policymaking. However, most LCA studies focused on evaluating the impacts of policies and strategic planning on a static basis ignoring the dynamic nature of the territory in which the policies are implemented. This study aims to develop a dynamic territorial LCA approach, linking agent-based modeling (ABM) with the territorial LCA approach. ABM is a widely used tool to simulate dynamic emerging systems considering human factors, and the territorial LCA is a recently developed approach featuring assessing multi-functional territories. To prove the concept, the framework of the dynamic territorial LCA was implemented in a case study of promoting bioenergy crops in an agricultural territory of the southern region of Belgium (Wallonia), considering farm size, familiarity, and revenue. Geographical Information Systems (GIS) was employed to assess site-specific environmental impacts of individual decisions. The case study contrasts spatial and temporal dynamics of the territory if implementing demonstration farms at different locations, assuming adopters will be provided with subsidies over simulation time, and farmers' familiarities increase when nearby farmers turn into adopters. The results show that different initial locations for demonstration farms would lead to different dynamic results at the territorial level. Such knowledge on the interactions between human behaviors and land-use scenarios could bring insights for policymaking, supporting reasonable land planning at the territorial level. Besides, by employing GIS to estimate spatially explicit inventory of unit processes, this work fills the research gap of the lack of application linking LCA, ABM, and GIS together. Further studies could be conducted to, e.g., explore the introduction of multiple land use functions (besides bioenergy production) and various policy schemes, enhance socio-economic impact assessment, and combine with other approaches to support decision making, e.g., participatory modeling and spatial optimization.