Perceptions of Greenhouse Gas Removal - Mixed Methods UK, 2023-2024

Cox, Emily (2024). Perceptions of Greenhouse Gas Removal - Mixed Methods UK, 2023-2024. [Data Collection]. Colchester, Essex: UK Data Service. 10.5255/UKDA-SN-857507

This dataset examines lay public perceptions of Carbon Dioxide Removal in the four devolved nations of the UK. We focus especially on 'biological' or 'nature-based' carbon removal techniques - perennial biomass crops, peatland restoration, and biochar. We also examine perceptions of trade-offs between options, and between carbon removal more generall versus emissions reduction.

To deal with inevitable framing effects, we split the qualitative sample into two groups - one with a techno-economic framing mirroring current climate discourses, versus one 'everyday life' framing.

We include deliberative workshop methods, providing both in-depth qualitative and small-n quantitative data, with large-n representative survey data.

In addition, we explore the role of novel information devices - specifically Large Language Models (also known as Generative AI) such as ChatGPT as devices for deliberation, examining to what extent these support or disrupt the preceding discourses on carbon removal.

Data description (abstract)

This dataset examines lay public perceptions of Carbon Dioxide Removal in the four devolved nations of the UK. We focus especially on 'biological' or 'nature-based' carbon removal techniques - perennial biomass crops, peatland restoration, and biochar. We also examine perceptions of trade-offs between options, and between carbon removal more generall versus emissions reduction.

To deal with inevitable framing effects, we split the qualitative sample into two groups - one with a techno-economic framing mirroring current climate discourses, versus one 'everyday life' framing.

We include deliberative workshop methods, providing both in-depth qualitative and small-n quantitative data, with large-n representative survey data.

In addition, we explore the role of novel information devices - specifically Large Language Models (also known as Generative AI) such as ChatGPT as devices for deliberation, examining to what extent these support or disrupt the preceding discourses on carbon removal.

Data creators:
Creator Name Affiliation ORCID (as URL)
Cox Emily University of Oxford https://orcid.org/0000-0002-8169-3691
Contributors:
Name Affiliation ORCID (as URL)
Waller Laurie Manchester University https://orcid.org/0000-0001-8071-4908
Bellamy Rob Manchester University https://orcid.org/0000-0001-9592-705X
Palmer James University of Bristol https://orcid.org/0000-0002-1151-1485
Sponsors: Natural Environment Research Council
Grant reference: NE/V013106/1
Topic classification: Science and technology
Society and culture
Psychology
Keywords: CLIMATE CHANGE, CARBON OFFSETTING, PUBLIC OPINION
Project title: CO2RE: UK Greenhouse Gas Removal Hub
Grant holders: Cameron Hepburn, Rob Bellamy
Project dates:
FromTo
March 2020October 2024
Date published: 11 Dec 2024 15:08
Last modified: 16 Dec 2024 17:47

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