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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

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Dr Laura Fogg Rogers Laura.Foggrogers@uwe.ac.uk
Associate Professor of Knowledge Exchange in Engineering

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Enda Hayes Enda.Hayes@uwe.ac.uk
Prof in Air Quality & Carbon Management/School Director (Research & Enterprise)

Kris Vanherle

P�ter I P�pics

Stephan Slingerland

Corra Boushel Corra.Boushel@uwe.ac.uk@uwe.ac.uk@uwe.ac.uk
Research Associate in CLAiR City Communications

Sophie Laggan



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.

Citation

Fogg-Rogers, L., Hayes, E., Vanherle, K., Pápics, P. I., Chatterton, T., Barnes, J., …Longhurst, J. (2021). Applying social learning to climate communications- visualising 'people like me' in air pollution and climate change data. Sustainability, 13(6), Article 3406. https://doi.org/10.3390/su13063406

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 29, 2024
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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