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

Heydon, James; Chakraborty, Rohit


Assistant Professor in Criminology

Rohit Chakraborty


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.


Heydon, J., & Chakraborty, R. (2022). Wood burning stoves, participatory sensing, and ‘cold, stark data’. SN Social Sciences, 2(10), Article 219.

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
Peer Reviewed Peer Reviewed
Volume 2
Issue 10
Article Number 219
Public URL
Publisher URL


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