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Rural areas across India often record PM2.5 concentrations close to those in cities, with Odisha among seven states where rural pollution exceeded the national annual standard and an urban-rural difference of less than 10 per cent, according to an analysis of 2014 to 2023 pollution data.
The analysis by India Air Quality & Energy Insights released on August 17, 2026 combines village-level boundary data released by the Survey of India for 27 states and Union territories with annual PM2.5 estimates from the Atmospheric Composition Analysis Group at Washington University in St Louis. It examines whether India’s city-focused clean air policies adequately address pollution beyond urban boundaries.
In 2023, urban PM2.5 concentrations were higher than rural levels in 22 of the 24 states with comparable estimates. However, 16 states had an urban-rural difference of less than 10 per cent. The gap was below 5 per cent in Punjab, Rajasthan, Bihar and Goa.
Kerala and West Bengal were the only states where rural PM2.5 concentrations were slightly higher than urban levels, by 0.8 per cent and 0.4 per cent respectively. Tamil Nadu and Karnataka recorded almost identical concentrations, with differences of just 1.2 per cent and 1.9 per cent.
Odisha was among the states where rural PM2.5 exceeded India’s annual National Ambient Air Quality Standards (NAAQS) of 40 microgrammes per cubic metre, despite the urban-rural difference being below 10 per cent. The other states in this category were West Bengal, Punjab, Rajasthan, Bihar, Madhya Pradesh and Delhi.
The finding is significant for Odisha, where clean air interventions cannot be limited to major urban centres if pollution levels in rural areas also remain above the national standard.
A substantial urban-rural difference does not necessarily mean that rural areas have clean air. Chhattisgarh recorded the largest gap in 2023, with urban PM2.5 concentrations 31.3 per cent higher than rural levels, followed by Uttarakhand at 29.8 per cent.
The difference was 19.1 per cent in Tripura, 17.6 per cent in Sikkim, 15.2 per cent in Maharashtra, 15.2 per cent in Haryana and 14.0 per cent in Jharkhand. Uttar Pradesh recorded an 11.4 per cent difference.
Yet, rural PM2.5 exceeded the NAAQS in Chhattisgarh at 48.4 microgrammes per cubic metre, Tripura at 47.4 microgrammes per cubic metre, Haryana at 63.9 microgrammes per cubic metre, Jharkhand at 46.3 microgrammes per cubic metre and Uttar Pradesh at 60.7 microgrammes per cubic metre.
The Odisha finding comes against a broader backdrop of pollution sources and energy use that extend beyond urban boundaries. Rural and semi-urban areas are also undergoing changes in transport, household energy use, agriculture and economic activity, all of which can influence emissions.
This is particularly relevant as Odisha expands its energy transition and electric mobility initiatives. The state has been pushing electric vehicles and charging infrastructure, while rural and remote districts continue to face challenges related to electricity reliability, transport access and energy use. Such changes make it important to understand how emissions are evolving outside major cities as well.
The analysis also points to the limitations of assessing clean air solely through designated urban areas. Pollution can move across administrative boundaries, while emission sources can be located far from the cities where air quality is monitored.
The 2014-2023 comparison found that rural PM2.5 concentrations declined in 22 of the 24 states with comparable urban and rural estimates, while urban PM2.5 declined in 23 states.
The average decline was broadly similar, at 7.0 per cent in rural areas and 6.4 per cent in urban areas.
However, state-level trends varied. Rural PM2.5 increased in Chhattisgarh and Maharashtra by 1.3 per cent and 4.1 per cent, respectively. In Chhattisgarh, both rural and urban PM2.5 increased by 1.3 per cent and 4.8 per cent, respectively.
In Maharashtra, the two categories moved in opposite directions. Rural PM2.5 increased by 4.1 per cent, while urban PM2.5 5 declined.5 per cent.
Several states recorded declines in both categories. Rural PM2.5 fell by 14.8 per cent in West Bengal, 14.6 per cent in Bihar and 13.9 per cent in Uttarakhand. Urban PM2.5 declined by 16.0 per cent, 14.7 per cent and 10.3 per cent respectively in the three states.
The findings show that there has been no uniform urban-rural trajectory over the decade.
The findings have implications for the National Clean Air Programme (NCAP), whose implementation has primarily focused on designated cities.
The analysis argues that where urban-rural differences are below 10 per cent, pollution is not confined to city boundaries. At the same time, even in states where the urban-rural gap is larger, rural concentrations can remain above the national standard.
The analysis therefore points towards a wider regional and airshed-based approach, with rural areas included in air quality monitoring, emissions inventories, source apportionment studies, mitigation planning and assessment of progress.
The methodology used annual PM2.5 raster estimates from the Atmospheric Composition Analysis Group at Washington University in St Louis at a spatial resolution of 0.01 degrees by 0.01 degrees. The analysis covered 10 years, from 2014 to 2023.
These data were combined with the Survey of India’s village boundary dataset covering approximately 586,000 village-level polygons across 27 states and Union Territories. Each village was classified as Urban, Rural, Partly Urban or Other.
The approximately 586,000 polygons were dissolved by state and settlement category, producing 84 state classification zones. The zones were then overlaid on each year’s PM2.5 raster to calculate mean concentrations, generating 840 state classification year estimates.
The analysis calculated the urban-rural difference as the percentage difference between urban and rural PM2.5 relative to rural PM2.5.
The estimates represent mean annual PM2.5 concentrations across the mapped area of each settlement category rather than population-weighted exposure. An urban estimate therefore represents the average concentration across mapped urban areas of a state, while a rural estimate represents the average across its rural areas.