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Peer-reviewedCC BY-NC-ND 4.0Nature Communications

Unveiling hidden air pollution exposure and impacts with low-cost sensor network-based frameworks

  • Navdeep Agrawal1,2
  • Nimit Godhani1,3
  • Sourangsu Chowdhury4
  • P. C. Anandh1
  • Anil Kumar1
  • Piyush Rai5,6
  • Sachchida Nand Tripathi1,7,8,9
9 affiliations
  1. 1National Aerosol Facility, Indian Institute of Technology Kanpur, Kanpur, India
  2. 2Department of Geoinformatics, Netaji Subhas University of Technology, Delhi, India
  3. 3Center for Climate Change Research, Indian Institute of Tropical Meteorology, Pune, India
  4. 4CICERO Center for International Climate Research, Oslo, Norway
  5. 5Department of Computer Science and Engineering, Indian Institute of Technology Kanpur, Kanpur, India
  6. 6Department of Intelligent Systems, Indian Institute of Technology Kanpur, Kanpur, India
  7. 7Kotak School of Sustainability, Indian Institute of Technology Kanpur, Kanpur, India
  8. 8Department of Civil Engineering, Indian Institute of Technology Kanpur, Kanpur, India
  9. 9Department of Sustainable Energy Engineering, Indian Institute of Technology Kanpur, Kanpur, India
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Abstract

India has made some progress in mitigating severe air pollution; however, many regions continue to experience fine particulate matter (PM2.5) levels exceeding World Health Organization and national standards. Despite this, local-scale exposure information beyond urban centers, intra-regional inequities, and short-term mortality impacts remain poorly understood. This study integrates dense, low-cost sensor-based PM2.5 measurements with machine learning models, recent family health survey data, and India-specific relative risk information to assess sub-regional exposure inequity among socioeconomic groups and short-term mortality impacts in Bihar, one of the most polluted and understudied states of India. Here we show a clear north-south divide in PM2.5 exposure, with northern districts having mean exposure levels 1.2 times higher. District-level mortality (per 100,000) varied up to 1.7-fold, with daily mortality showing 3.2-fold variability. We observe limited exposure inequity at the state level but substantial inter- and intra-regional inequities within Bihar.

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Cite

BibTeXRIS
BibTeX
@article{agrawal2026unveiling,
  title = {{Unveiling hidden air pollution exposure and impacts with low-cost sensor network-based frameworks}},
  author = {Navdeep Agrawal and Nimit Godhani and Sourangsu Chowdhury and P. C. Anandh and Anil Kumar and Piyush Rai and Sachchida Nand Tripathi},
  journal = {Nature Communications},
  year = {2026},
  month = sep,
  doi = {10.1038/s41467-026-77148-1},
  url = {https://doi.org/10.1038/s41467-026-77148-1},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - Unveiling hidden air pollution exposure and impacts with low-cost sensor network-based frameworks
AU  - Navdeep Agrawal
AU  - Nimit Godhani
AU  - Sourangsu Chowdhury
AU  - P. C. Anandh
AU  - Anil Kumar
AU  - Piyush Rai
AU  - Sachchida Nand Tripathi
PY  - 2026
DA  - 2026/09/02
JO  - Nature Communications
DO  - 10.1038/s41467-026-77148-1
UR  - https://doi.org/10.1038/s41467-026-77148-1
AB  - India has made some progress in mitigating severe air pollution; however, many regions continue to experience fine particulate matter (PM2.5) levels exceeding World Health Organization and national standards. Despite this, local-scale exposure information beyond urban centers, intra-regional inequities, and short-term mortality impacts remain poorly understood. This study integrates dense, low-cost sensor-based PM2.5 measurements with machine learning models, recent family health survey data, and India-specific relative risk information to assess sub-regional exposure inequity among socioeconomic groups and short-term mortality impacts in Bihar, one of the most polluted and understudied states of India. Here we show a clear north-south divide in PM2.5 exposure, with northern districts having mean exposure levels 1.2 times higher. District-level mortality (per 100,000) varied up to 1.7-fold, with daily mortality showing 3.2-fold variability. We observe limited exposure inequity at the state level but substantial inter- and intra-regional inequities within Bihar.
SN  - 2041-1723
ER  -