Delhi’s air pollution problem is not only a matter of emissions entering the atmosphere. A new study shows that once pollution becomes severe, the particles themselves can reduce sunlight reaching the ground, weaken near-surface winds and shrink the layer of air in which pollutants disperse. The result is a feedback loop that can make already dangerous pollution episodes harder to break.
The study, titled “Improving aerosol-radiation interactions in the operational forecasting system – AIRWISE”, was published in Atmospheric Chemistry and Physics on September 21. Researchers from the Indian Institute of Tropical Meteorology, Savitribai Phule Pune University, the National Centre for Medium Range Weather Forecasting, the University of California, Los Angeles, and the National Center for Atmospheric Research examined Delhi’s pollution and weather conditions between September 2023 and January 2024.
Its central finding is important for how the capital understands and manages winter pollution. Aerosols, the tiny particles suspended in the air, can absorb and scatter sunlight. When less sunlight reaches the surface, the ground heats less during the day. That reduces the natural movement of air, weakens mixing and makes the atmosphere more stable. The layer of air close to the ground, where pollutants normally spread, becomes thinner, while weaker winds carry less pollution away.
This does not mean that weather is the original cause of Delhi’s pollution. The study instead describes a feedback process in which high concentrations of particles modify local atmospheric conditions. Emissions build the pollution burden, while the altered sunlight, wind and atmospheric stability can help keep that burden concentrated near the ground.
The effect was particularly visible during the severe pollution episode between November 1 and 10, 2023. Heavy pollution reduced the sunlight reaching the ground by up to about 80 watts per square metre, according to the study. The resulting cooling weakened winds and reduced the movement that helps disperse pollutants. The atmosphere’s ability to disperse pollution fell by as much as 20 per cent in November.
During that episode, PM2.5 levels reached about 500 micrograms per cubic metre, with daytime concentrations generally between 200 and 300 micrograms per cubic metre. The afternoon layer of air that helps spread pollution became approximately 100 to 200 metres thinner, while winds weakened by up to 0.4 metres per second. In the model, near-ground PM2.5 increased by as much as 37 to 40 micrograms per cubic metre as a result of these interactions.
The January episode showed a somewhat different pattern. PM2.5 levels peaked at about 550 micrograms per cubic metre amid low temperatures, high humidity, weak winds, fog and low clouds. These conditions already favour the accumulation of pollution close to the ground. The additional impact of reduced sunlight was smaller because there was less sunlight available to be blocked in the first place.
Even so, the model found that winds weakened by about 0.2 metres per second and the pollution-dispersing air layer became 40 to 50 metres thinner. Near-ground PM2.5 increased by about 25 micrograms per cubic metre in the model. The atmosphere’s dispersal capacity fell by 10 to 12 per cent in January, the study said.
These findings matter because air-quality forecasting is not simply a matter of measuring emissions and extrapolating their effect. Forecasts also depend on how accurately models represent interactions between particles, radiation and meteorology. If a model underestimates the extent to which aerosols block sunlight or change atmospheric stability, it may also underestimate how long severe pollution will remain concentrated over the city.
The researchers found that their calculated sunlight levels were closer to measurements recorded at Indira Gandhi International Airport. That comparison provides a specific indication that the study’s treatment of aerosol-radiation interactions improved the representation of conditions near Delhi, at least for the episodes examined.
The work also exposes a limitation in the forecasting systems used to support air-quality decisions. AIRWISE, or the Air Quality Warning and Integrated Decision Support System for Emissions, was developed through a collaboration between the Indian Institute of Tropical Meteorology, the India Meteorological Department and the National Center for Atmospheric Research. The system has been operational since 2018 and provides real-time air-quality forecasts across India.
According to the study, AIRWISE has had operational success but remains limited in reproducing extreme pollution-loading events over northern India, particularly during the crop-residue-burning season in the states surrounding Delhi. These high-impact episodes are often underestimated partly because of inaccuracies in representing the interaction between aerosols, radiation and meteorology.
That limitation has an institutional consequence. Forecasts are used to inform public warnings and decisions on pollution-control measures, but their usefulness depends on accurately identifying both the intensity and persistence of an episode. A forecast that misses the effect of pollution on atmospheric mixing can understate the severity of the conditions that residents will experience at street level.
The study therefore places forecasting within the wider structure of Delhi’s pollution governance. Air-quality management is often organised around emergency actions taken after pollution levels have already risen. However, the research indicates that once the atmosphere is heavily loaded with particles, the conditions for dispersal can deteriorate further. Temporary responses may then be operating against an atmospheric system that has become less favourable to rapid improvement.
Manoj Kumar, an analyst at the Centre for Research on Energy and Clean Air, said the findings reinforce the need to reduce pollution at its sources rather than rely mainly on temporary measures after pollution has accumulated. He said aerosols can block sunlight, reduce surface heating and slow the movement of air near the ground, allowing pollution to build up further.
Kumar said consistent, targeted and time-bound reductions were required across major sources, including industry, power plants and other combustion sources. His comments were presented in the report as an interpretation of the study’s implications, rather than as a finding by the researchers themselves.
The evidence also clarifies the relationship between weather and responsibility. Low temperatures, humidity, fog, weak winds and low clouds can worsen pollution conditions, while crop-residue burning and other regional sources can add to the particle load. But weather does not remove the importance of emissions control. The feedback described in the study begins with particles in the atmosphere, and higher particle concentrations create a greater opportunity for the feedback to intensify.
This is particularly significant for a dense city such as Delhi, where large numbers of people live and travel close to the ground-level air layer affected by these changes. The study does not quantify the health effects on residents, nor does it establish how every pollution episode will behave. Its results are based on specific conditions observed between September 2023 and January 2024. But it does show that atmospheric processes can amplify the persistence of pollution in ways that need to be represented more accurately in forecasting systems.
The larger urban question is whether pollution policy can remain primarily reactive when the atmosphere itself becomes less capable of dispersing pollutants after severe episodes begin. The study does not prescribe a new administrative framework, but it identifies a technical and governance requirement: forecasts must account for the interaction between emissions, sunlight and wind, while pollution-control agencies must act before concentrations reach levels at which the feedback becomes stronger.
What the research confirms is that Delhi’s pollution episodes are not static accumulations of emissions. They are dynamic events in which particles can influence the local conditions that determine whether pollution disperses or remains trapped. The study’s next practical test lies in how such improved modelling is incorporated into operational forecasts and whether more accurate warnings support earlier and sustained reductions in emissions across the sources identified in the report.
