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Mobile Monitoring of Air Pollution in Bengaluru

Updated: Jan 14, 2020

Collection of hyper local air quality data, analysis and insights on variation of air quality on a street to street basis, resulting differential exposure and identification of pollution hotspots


Client: Azim Premji Philanthropic Initiatives (APPI)

Location: Bengaluru

Partner/Collaborators: Clean Air Platform - Bengaluru (CAP-B), Azim Premji Philanthropic Initiatives (APPI)

Duration: Oct 2018 - February 2019

Status: Completed




A major problem with regard to air pollution in Bengaluru is that there is a deep mismatch between ambient levels of air quality and actual exposure which in turn minimises the concern and the urgency to take strong actions to curtail it.


Mobile monitoring project was conceived to provide a highly contextual and hyper-local understanding of air pollution in this city to better assess actual exposure of residents and variation of air quality from street to street. It was also seen as a diagnostic tool to inform evidence based actions towards mitigation at a city, community and individual level. Overall, mobile monitoring was expected to act as a powerful supplement to the use of fixed site regulatory network, filling the gaps in between.

The study broadly looked to address the following questions:

  1. How does air quality measure in and around vulnerable areas such as schools, hospitals and public spaces and high exposure territories such as High Traffic Density Corridors (HTD)

  2. How does hyperlocal concentration of air pollution compare to the measurements of ambient air from the regulatory monitoring network in the city?

  3. What is the quality of air inside the city neighbourhoods?

The project tasks consisted of a concept note to build a case for the project (deep diving into global case studies and contextual understanding of the city) and the ‘Request for Proposal’ (RFP) towards on-ground implementation covering 3 key aspects: Data collection, Data analysis and synthesis and Data presentation.



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