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Evaluating optimal solutions to environmental breakdown

Stafford, Richard, Croker, Abigail R., Rivers, Eleanor M., Cantarello, Elena, Costelloe, Brendan, Ginige, Tilak, Sokolnicki, James, Kang, Kenneth, Jones, Peter J.S., McKinley, Emma and Shiel, Chris 2020. Evaluating optimal solutions to environmental breakdown. Environmental Science and Policy 112 , pp. 340-347. 10.1016/j.envsci.2020.07.008

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Abstract

The severity of environmental threats, especially climate change, biodiversity loss and pollution, are well established, as is the urgent need for them to be addressed. These threats act both in isolation as well as synergistically to contribute to overall ‘environmental breakdown’. Debate exists around the most optimal governance and policy approaches to address these threats and, to date, little quantitative evidence exists to compare the different approaches. Using a modified Bayesian belief network model to assess the probability of environmental threats, we compare and contrast a range of proposed policy solutions to a selection of contemporary environmental problems that have been identified as having the potential to contribute to, or indeed may lead to environmental breakdown. Through interrogation of the models, we conclude that policies that prioritise economic growth at the expense of nature would be largely ineffective, whereas a more integrated approach, adopting comprehensive ‘Green New Deal’ policies combined with nature-based solutions would be the most effective approaches to preventing environmental breakdown, as they address societal and environmental issues simultaneously. We therefore recommend that decision makers take an integrated approach to decision making and policy development, accounting for social, economic and environmental drivers that ensure delivery of multiple benefits and real change.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Earth and Ocean Sciences
Publisher: Elsevier
ISSN: 1462-9011
Date of First Compliant Deposit: 3 August 2020
Date of Acceptance: 7 July 2020
Last Modified: 28 Nov 2020 05:38
URI: http://orca.cf.ac.uk/id/eprint/133910

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