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1.
Mar Pollut Bull ; 179: 113713, 2022 Jun.
Article in English | MEDLINE | ID: mdl-35525061

ABSTRACT

Fuzzy Cognitive Mapping (FCM) is a participatory modelling tool used to explore complex systems by facilitating interdisciplinary cooperation and integrating a variety of knowledge systems. Here FCM was used to explore marine microfiber pollution. Through individual interviews with representatives from the research, industry, water and environmental sectors, five stakeholder FCMs were developed and used to produce an aggregated community FCM in a stakeholder workshop. Stakeholder FCMs and the revised community FCM were used to compute how the modelled system reacted to changes under two scenarios developed during the stakeholder workshop; (i) Green Shift and (ii) increased textile consumption and production. Significant differences were observed in scenario results from the stakeholder-based models and the community-based model. For societal challenges characterized by unknowns around the problem and potential solutions, inclusion of a variety of knowledge systems through FCM and deliberation processes contribute to a more holistic picture of the system and its uncertainties.


Subject(s)
Environmental Pollution , Textiles , Cognition , Fuzzy Logic , Industry
2.
Mar Pollut Bull ; 173(Pt B): 113062, 2021 Dec.
Article in English | MEDLINE | ID: mdl-34744010

ABSTRACT

One of the ambitions of the UN Decade of Ocean Science is stakeholder interaction to co-produce new ideas and solutions for policy action plans to ensure that environmental challenges are mitigated in a timely manner. Regulations around the release of microfibres are largely lacking, and we are at an excellent point of departure to test integrative methods of such co-production. We co-designed conceptual maps and Bayesian Belief Networks with probabilistic future scenarios within both inter- and intra-sectoral workshops with industry and scientific stakeholders to gain comparable results of policy action scenarios for curbing the challenge of microfibre pollution within this context. We found that when scientists worked on this alone, their focus was different than when working together with industry directly. Scientists focused on methods for avoiding release into the environment from a technical vantage point, whereas industry emphasized regulatory requirements needed to avoid ambiguity within the sector.


Subject(s)
Environmental Pollution , Water Purification , Bayes Theorem , Forecasting , Policy
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