Dr Laura Fogg Rogers Laura.Foggrogers@uwe.ac.uk
Associate Professor of Knowledge Exchange in Engineering
Applying social learning to climate communications- visualising 'people like me' in air pollution and climate change data
Fogg-Rogers, Laura; Hayes, Enda; Vanherle, Kris; P�pics, P�ter I; Chatterton, Tim; Barnes, Jo; Slingerland, Stephan; Boushel, Corra; Laggan, Sophie; Longhurst, James
Authors
Enda Hayes Enda.Hayes@uwe.ac.uk
Prof in Air Quality & Carbon Management/School Director (Research & Enterprise)
Kris Vanherle
P�ter I P�pics
Tim Chatterton
Dr Jo Barnes Jo.Barnes@uwe.ac.uk
Professor of Clean Air
Stephan Slingerland
Corra Boushel
Sophie Laggan
Assistant Vice Chancellor, Environment and Sustainability Jim Longhurst James.Longhurst@uwe.ac.uk
Professor
Abstract
Technological approaches to carbon emission and air pollution data modelling consider where the issues are located and what is creating emissions. This paper argues that more focus should be paid to people-the drivers of vehicles or households burning fossil fuels (‘Who’) and the reasons for doing so at those times (‘Why’). We applied insights from social psychology (social identity theory and social cognitive theory) to better understand and communicate how people’s everyday activities are a cause of climate change and air pollution. A new method for citizen-focused source apportionment modelling and communication was developed in the ClairCity project and applied to travel data from Bristol, U.K. This approach enables understanding of the human dimension of vehicle use to improve policymaking, accounting for demographics (gender or age groups), socioeconomic factors (income/car ownership) and motives for specific behaviours (e.g., commuting to work, leisure, shopping, etc.). Tailored communications for segmented in-groups were trialled, aiming to connect with group lived experiences and day-to-day behaviours. This citizen-centred approach aims to make groups more aware that ‘people like me’ create emissions, and equally, ‘people like me’ can take action to reduce emissions.
Journal Article Type | Article |
---|---|
Acceptance Date | Mar 15, 2021 |
Online Publication Date | Mar 19, 2021 |
Publication Date | Mar 19, 2021 |
Deposit Date | Mar 19, 2021 |
Publicly Available Date | Mar 19, 2021 |
Journal | Sustainability |
Electronic ISSN | 2071-1050 |
Publisher | MDPI |
Peer Reviewed | Peer Reviewed |
Volume | 13 |
Issue | 6 |
Article Number | 3406 |
Series Title | Special Issue "The Social Psychology of Climate Change: New Challenges for a Healthier and More Sustainable World" |
DOI | https://doi.org/10.3390/su13063406 |
Keywords | social identity theory; social cognitive theory; self-efficacy; climate change; carbon emissions; air pollution; climate communications |
Public URL | https://uwe-repository.worktribe.com/output/7215722 |
Publisher URL | https://www.mdpi.com/2071-1050/13/6/3406 |
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Applying social learning to climate communications- visualising 'people like me' in air pollution and climate change data
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Licence
http://creativecommons.org/licenses/by/4.0/
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
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