Siddharth Nobell1, Arnab Majumdar1, Shovon Mukherjee1, Sukumar Chakraborty1, Sanjoy Chatterjee1, Soumitra Bose1, Anindita Dutta  2,3, Sandhya Sethuraman3, Daniel M. Westervelt4, Shairik Sengupta5, Rakhi Basu6,7, V. Faye McNeill  This email address is being protected from spambots. You need JavaScript enabled to view it.3,8 

1 Enviome Research, Kolkata 700091, India
2 Department of Medicine, University of Chicago, Chicago, IL 60637, USA
3 Department of Chemical Engineering, Columbia University, New York, NY 10027, USA
4 Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY 10964, USA
5 Indian Institute of Science, Bangalore 560012, India
6 The World Bank Group, Washington, DC 20433, USA
7 Conveh, Irvine, CA 92614, USA
8 Department of Earth and Environmental Sciences, Columbia University, New York, NY 10027, USA

Received: January 12, 2023
Revised: June 20, 2023
Accepted: August 11, 2023

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

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Nobell, S., Majumdar, A., Mukherjee, S., Chakraborty, S., Chatterjee, S., Bose, S., Dutta, A., Sethuraman, S., Westervelt, D.M., Sengupta, S., Basu, R., McNeill, V.F. (2023). Validation of In-field Calibration for Low-Cost Sensors Measuring Ambient Particulate Matter in Kolkata, India. Aerosol Air Qual. Res. 23, 230010.


  • In-field calibration adds value to data from low cost PM2.5 sensor networks.
  • Multiple co-locations allowed testing of the in-field calibration approach.
  • Corrected low cost PM2.5 sensors performed with high accuracy in Kolkata.
  • Results show importance of regional and secondary as well as local PM2.5 sources.


Low-cost sensors (LCS) provide opportunities for neighborhood-level air pollution data collection, yet significant knowledge gaps remain regarding the accurate application and interpretation of LCS. In this study, we present an in-field calibration of a network of 20 low-cost ambient particulate matter sensors (LCS) in greater Kolkata, India, operating between October 2018–April 2019. In order to understand LCS performance in relation to local reference-grade PM2.5 monitors (RGMs), three of these LCS were co-located with RGMs operated by the West Bengal Pollution Control Board at Rabindra Bharati University (RBU), Victoria Memorial (VICTORIA), and Padmapukur (Howrah, PDM). Data from the co-locations were used to calibrate the LCS network using random forest regression and multiple linear regression approaches. Measured relative humidity and temperature were significant model features. Agreement between the LCS and RGM for 24-h averaged PM2.5 measurements was strongest at RBU, with an uncalibrated root mean squared error (RMSE) of 27.1 µg m–3, followed by PDM (32.6 µg m–3) and VICTORIA (50.7 µg m–3). Multiple linear regression was used to derive calibration models. Cross-calibration between co-located LCS-RGM pairs was tested. The LCS data after cross-calibration correctly identified days as being in or out of attainment with the 24h National Ambient Air Quality Standard of 60 µg m–3 91% of the time. The corrected data accurately identifies days with an India scale Air Quality Index of “poor” or worse 94% of the time. This suggests that LCS can be a useful supplement to RGM networks for air quality management. Diurnal trends and a high level of correlation across the hybrid LCS-RGM network suggest regional and secondary sources of PM2.5 are important in Kolkata.

Keywords: Air pollution, Air quality, Atmospheric aerosols, PM2.5, Urban aerosols

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