Wood burning stoves, participatory sensing, and ‘cold, stark data’

Heydon, James; Chakraborty, Rohit

Abstract

Wood burning stoves triple levels of particulate matter pollution inside the home. Using an exploratory research design informed by coping theory, this study illustrates how sensors revealing this reality fail to influence the perceptions and behaviours of stove users. After four-weeks of participatory sensing, where laypersons used sensors to identify indoor air quality during stove use, the results show how monitoring technology pulls wider preconceptions into the data interpretation process. When faced with numerical data perceived as ambiguous, users draw on preconceptions that frame stoves in a positive light and make comparisons with other indoor emission sources believed to be harmless. This influences the data interpretation process and minimises the threat indicated by sensor technology. It is recommended that participatory sensing research give greater consideration to the role of data presentation in influencing user behaviour, while being more attentive to how socio-cultural knowledges enter the process of interpretation.

Citation

Heydon, J., & Chakraborty, R. (2022). Wood burning stoves, participatory sensing, and ‘cold, stark data’. SN Social Sciences, 2(10), Article 219. https://doi.org/10.1007/s43545-022-00525-2

• Journal Article Type: Article
• Acceptance Date: Sep 12, 2022
• Online Publication Date: Sep 30, 2022
• Publication Date: 2022-10
• Deposit Date: Nov 23, 2022
• Publicly Available Date: Nov 24, 2022
• Journal: SN Social Sciences
• Electronic ISSN: 2662-9283
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 2
• Issue: 10
• Article Number: 219
• DOI: https://doi.org/10.1007/s43545-022-00525-2
• Public URL: https://nottingham-repository.worktribe.com/output/11196518
• Publisher URL: https://link.springer.com/article/10.1007/s43545-022-00525-2