Advancing participatory sensing and knowledge production methods for city air quality governance: applying the Breathe London Community Programme model
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Air pollution remains a pressing global issue, contributing to millions of deaths annually and disproportionately affecting vulnerable communities. While conventional air quality governance has relied on costly, specialized instruments, recent advances in lower capital cost sensors and digital infrastructure have enabled broader participation in environmental monitoring. This shift creates opportunities for integrating scientific, local, and practical knowledge into air quality governance. However, significant barriers persist, including inequities in access to data, technical resources, capacity constraints, and entrenched power imbalances. The Breathe London Community Programme was developed to address these challenges by integrating community-based knowledge with scientific air quality monitoring. Implemented within a hybrid network of over 400 real-time calibrated air pollution sensors, the BLCP distributed free sensors to 60 community groups across London from 2021 to 2023. The program enabled communities to choose sensor locations, fostering data contextualized by local experiences and redistributing decision-making power. This participatory approach helped facilitate actionable insights that informed local policy changes aimed at reducing pollution exposure. It also expanded governance networks and highlighted pathways for aligning community-based knowledge with institutional frameworks. The findings emphasize the importance of designing participatory methodologies that adapt to diverse community needs, strengthen grassroots capacity, and integrate non-dominant knowledge into decision-making practices. This study demonstrates how democratizing environmental data production and use can enhance the efficacy of air quality governance, providing a model for embedding community-driven knowledge into policy development and decision-making processes globally.
Date Issued
2025-08-01
Date Acceptance
2025-04-29
Citation
Environmental Science and Policy, 2025, 170
ISSN
1462-9011
Publisher
Elsevier
Journal / Book Title
Environmental Science and Policy
Volume
170
Copyright Statement
© 2025 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Identifier
10.1016/j.envsci.2025.104092
Publication Status
Published
Article Number
104092
Date Publish Online
2025-05-20