Translating citizen-generated air quality data into evidence for shaping policy

Sachit Mahajan (), Ming-Kuang Chung, Jenny Martinez, Yris Olaya, Dirk Helbing and Ling-Jyh Chen
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Sachit Mahajan: ETH Zurich
Ming-Kuang Chung: Academia Sinica
Jenny Martinez: Universidad Nacional de Colombia
Yris Olaya: Universidad Nacional de Colombia
Dirk Helbing: ETH Zurich
Ling-Jyh Chen: Academia Sinica

Palgrave Communications, 2022, vol. 9, issue 1, 1-18

Abstract: Abstract The practice of participatory sensing for environment monitoring has rapidly evolved over the years. There has been a steady growth of citizen-based air quality monitoring projects that aim to build partnerships, knowledge-sharing platforms, awareness, and ultimately resilience to issues related to air quality. Whilst citizen science has reshaped air quality research by bringing a fresh perspective on democratizing science for the public good, there is little research about how citizen-generated data can be used for facilitating and improving evidence-based policymaking. To address the problem in a structured manner, we examine the existing literature related to citizen science, air quality, and policymaking to understand the existing gaps and opportunities. That is followed by a review of major grassroots and collaborative citizen science air quality monitoring initiatives in Asia, Africa, Europe, and Latin America. We explore the range of citizen science methods and applications to understand how they are creating opportunities for dialog between practitioners and policymakers, discuss the concerns about citizen-generated data, and see if the data is used for policy action. Finally, we propose a methodology for integrating data-based evidence into shaping policy. The methodology combines scientific evidence, participation, and deliberation to realize the full potential of citizen science in air quality monitoring.

Date: 2022
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DOI: 10.1057/s41599-022-01135-2

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