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A framework for analysing the environmental impact and support decision making in sustainable development context.
- Source :
- Environment Systems & Decisions; Jun2023, Vol. 43 Issue 2, p281-297, 17p
- Publication Year :
- 2023
-
Abstract
- New technologies or development policies are introduced to support reducing Environmental Impact (EI) associated with product system, while EI associated with it is mostly formulated as a function of resources used and emissions imposed under some assumptions including the behaviour of its producers/users. However, interactions of a product system with its surroundings may violate some of those assumptions. The users/producers of a product system may react to a labelled sustainable technology/production policy such that leading to increasing the actual total EI associated with product system and its surroundings systems, higher than the expected EI. This unexpected outcome is called emerging behaviour or rebound effect. A product system interacts with various systems in its lifecycle, upstream before and downstream after usage stage. This paper introduces a structured approach to study the total EI imposed by orchestrating systems engineering, Lifecycle impact assessment, Object Oriented, and Finite-State Machine to model the complex structure of a product system interacting with its surroundings during its lifecycle. This paper aims to propose an approach that can provide insights about possible EI imposed due to introducing a new technology or development policy and analysing the emerging behaviours in downstream and upstream of lifecycle using yet beyond traditional lifecycle impact assessment approach. This insight can support decision making and mitigate the risk that movements toward EI reduction have opposite outcomes. This increases awareness about possible emerging behaviours and allows preparing for them, for example, by developing complementary policies to assure meeting the full potential benefit of sustainable development approaches. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 21945403
- Volume :
- 43
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Environment Systems & Decisions
- Publication Type :
- Academic Journal
- Accession number :
- 163414080
- Full Text :
- https://doi.org/10.1007/s10669-022-09888-6