Citizen science and environmental justice: exploring contradictory outcomes through a case study of air quality monitoring in Dublin. Issue 5 (4th May 2022)

• Record Type: Journal Article
• Authors: Tubridy, Fiadh; Mölter, Anna; Lennon, Mick; Pilla, Francesco
• Is Part Of: Local environment. Volume 27:Issue 5(2022)
• Page Start: 622
• Page End: 638
• Publication Date: 2022-05-04
• Subjects: Citizen science -- air pollution -- environmental justice -- political ecology; Environmental policy -- Periodicals; 363.7
• DOI: 10.1080/13549839.2022.2068143
• Languages: English
• ISSNs: 1354-9839

Abstract

ABSTRACT: Citizen science is advocated as a response to a broad range of contemporary societal and ecological challenges. However, there are widely varying models of citizen science which may either challenge or reinforce existing knowledge paradigms and associated power dynamics. This paper explores different approaches to citizen science in the context of air quality monitoring in terms of their implications for environmental justice. This is achieved through a case study of air quality management in Dublin which focuses on the role of citizen science in this context. The evidence shows that the dominant interpretation of citizen science in Dublin is that it provides a means to promote awareness and behaviour change rather than to generate knowledge and inform new regulations or policies. This is linked to an overall context of technocratic governance and the exclusion of non-experts from decision-making. It is further closely linked to neoliberal governance imperatives to individualise responsibility and promote market-based solutions to environmental challenges. Last, the evidence highlights that this model of citizen science risks compounding inequalities by transferring responsibility and blame for air pollution to those who have limited resources to address it. Overall, the paper highlights the need for critical analysis of the implications of citizen science in different instances and for alternative models of citizen science whereby communities would contribute to setting objectives and determining how their data is used.