Spatially Differentiated Multi-Sectoral Mitigation Strategies Needed to Reduce PM2.5 Exposures in India
11 affiliations
- 1Centre for Climate Studies
- 2Indian Institute of Technology Bombay
- 3Environmental Science and Engineering Department
- 4Department of Civil and Environmental Engineering
- 5University of California
- 6Zachry Department of Civil and Environmental Engineering
- 7Texas A&M University
- 8University of Washington
- 9Center for Study of Science, Technology and Policy (CSTEP
- 10School of Public Health
- 11Department of Chemical Engineering
Abstract
Air pollution in India contributes to approximately 1 million deaths annually due to exposure to ambient fine particulate matter (PM 2.5 ). Here, we demonstrate that interventions to achieve the goals of India’s National Clean Air Program require adopting a multi-sector, multi-scale approach to link air pollution sources to human exposure. To support this objective, we developed PAVITRA (Air pollution management and intervention tool for India), a computationally efficient and high-fidelity air quality management tool. The tool integrates the InMAP reduced-complexity air quality model tailored for India, with the SMoG (Speciated Multi-pOllutant Generator)-COALESCE emissions inventory. By deploying over 2,000 simulations, we established how emissions from multiple sectors at different spatial scales contribute to PM2.5 throughout India. We find dissimilar emission drivers of PM 2.5 exposure at regional, state, and city scales, with especially large spatial differences in the relative contributions of domestic, agriculture, and transport sources. We also find that targeted state-level interventions may be nearly as effective as uniform nationwide strategies. These results highlight the limitations of one-size-fits-all policies. Rather, we demonstrate the value of coordinated but differentiated mitigation strategies at regional, state, and city jurisdictional scales for effective air quality management in India. Reduced-complexity modeling tools such as PAVITRA present a way forward to support rapid evaluation of sector and scale-specific mitigation strategies for effective, science-based policy development.
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BibTeX
@misc{balasubramanian2026spatially,
title = {{Spatially Differentiated Multi-Sectoral Mitigation Strategies Needed to Reduce PM2.5 Exposures in India}},
author = {Srinidhi Balasubramanian and Lucas Rojas-Mendoza and Neeldip Barman and Yuzhou Wang and Zainab Arub and Shivam Saxena and Bujin Bekbulat and Piyush Bhardwaj and Julian D. Marshall and Joshua S. Apte and Chandra Venkataraman},
howpublished = {ChemRxiv},
year = {2026},
month = sep,
doi = {10.26434/chemrxiv.15008347/v1},
url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008347/v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Spatially Differentiated Multi-Sectoral Mitigation Strategies Needed to Reduce PM2.5 Exposures in India
AU - Srinidhi Balasubramanian
AU - Lucas Rojas-Mendoza
AU - Neeldip Barman
AU - Yuzhou Wang
AU - Zainab Arub
AU - Shivam Saxena
AU - Bujin Bekbulat
AU - Piyush Bhardwaj
AU - Julian D. Marshall
AU - Joshua S. Apte
AU - Chandra Venkataraman
PY - 2026
DA - 2026/09/04
PB - ChemRxiv
DO - 10.26434/chemrxiv.15008347/v1
UR - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008347/v1
AB - Air pollution in India contributes to approximately 1 million deaths annually due to exposure to ambient fine particulate matter (PM 2.5 ). Here, we demonstrate that interventions to achieve the goals of India’s National Clean Air Program require adopting a multi-sector, multi-scale approach to link air pollution sources to human exposure. To support this objective, we developed PAVITRA (Air pollution management and intervention tool for India), a computationally efficient and high-fidelity air quality management tool. The tool integrates the InMAP reduced-complexity air quality model tailored for India, with the SMoG (Speciated Multi-pOllutant Generator)-COALESCE emissions inventory. By deploying over 2,000 simulations, we established how emissions from multiple sectors at different spatial scales contribute to PM2.5 throughout India. We find dissimilar emission drivers of PM 2.5 exposure at regional, state, and city scales, with especially large spatial differences in the relative contributions of domestic, agriculture, and transport sources. We also find that targeted state-level interventions may be nearly as effective as uniform nationwide strategies. These results highlight the limitations of one-size-fits-all policies. Rather, we demonstrate the value of coordinated but differentiated mitigation strategies at regional, state, and city jurisdictional scales for effective air quality management in India. Reduced-complexity modeling tools such as PAVITRA present a way forward to support rapid evaluation of sector and scale-specific mitigation strategies for effective, science-based policy development.
ER -