On hazy winter mornings in Delhi, the air people breathe at street level may not reveal the full extent of pollution exposure.
A new peer-reviewed study published in npj Clean Air reports that fine particulate matter (PM2.5) concentrations were up to 60% higher at around 100 metres above ground compared to levels recorded near the surface during severe haze episodes. The findings raise concerns that conventional ground-based monitoring systems may be underestimating exposure risks in high-rise urban environments.
Researchers deployed a custom-built drone equipped with low-cost particulate matter sensors to conduct vertical air profiling over South Delhi in March 2021. On one particularly hazy morning, PM2.5 levels reached approximately 160 micrograms per cubic metre at 100 metres altitude, compared to around 100 micrograms per cubic metre at ground level.
Lead author Ajit Ahlawat, Assistant Professor at Delft University of Technology, said the results indicate that “ground-based monitoring alone substantially underestimates actual exposure to pollution in the lower urban boundary layer, especially during haze episodes.”
Delhi’s early morning haze is closely linked to shallow nocturnal boundary layers layers of air near the ground that form overnight and can drop below 200 metres. When wind speeds weaken and temperatures fall, pollutants emitted from traffic, industry and waste burning remain trapped.
High relative humidity further worsens the situation. Pollution particles absorb moisture through a process known as hygroscopic growth, increasing in size and mass. Certain chemical compounds such as ammonium nitrate and ammonium chloride enhance this effect, particularly when humidity levels exceed 70%.
Under such humid pre-sunrise conditions, particle growth can lead to higher pollution concentrations at elevated levels than those measured at the surface.
Traditional air quality monitors, typically placed five to ten metres above ground, do not capture these vertical variations.
The study also evaluated the performance of the widely used WRF-Chem air quality model. During haze episodes, the model underestimated relative humidity by more than 30% at around 100 metres altitude and predicted PM2.5 levels roughly 50% lower than those measured by the drone.
Co-author Mira Pöhlker, professor at the Leibniz Institute for Tropospheric Research (TROPOS) and Leipzig University, attributed the discrepancy to a “dry bias” in the model, limiting its ability to simulate aerosol hygroscopic growth under high-humidity conditions.
Researchers noted that the model does not fully represent multiphase chemistry and particle phase transitions — processes that significantly enhance secondary aerosol formation in humid environments.
If forecasting systems fail to capture early-morning pollution spikes accurately, public health advisories may not reflect peak exposure conditions, potentially leaving vulnerable populations at risk.
India’s air quality monitoring network is largely ground-based and designed primarily for regulatory compliance. It does not routinely measure how pollutants are distributed vertically within the atmospheric boundary layer.
Prachi Goyal, Clean Air Asia representative in India, said drone-based vertical profiling is technically feasible as a supplementary tool. Unmanned aerial systems can sample multiple altitudes within short timeframes, enabling scientists to understand mixing heights, pollutant layering and boundary layer suppression during stagnant conditions.
However, integrating drones into routine monitoring would require clear calibration standards, humidity correction protocols, aviation permissions and data quality controls. Experts emphasise that low-cost sensors cannot replace regulatory-grade stations, but when properly calibrated, they can generate high-resolution datasets useful for improving air quality models and emission strategies.
The findings have particular relevance for cities dominated by multi-storey buildings, where millions of residents and office workers spend much of their time on higher floors.
Most exposure assessment frameworks assume relatively uniform near-surface pollutant concentrations. However, under strong temperature inversions and shallow mixing conditions, substantial vertical gradients can develop.
Experts say incorporating vertical variability into exposure modelling, indoor–outdoor infiltration studies and building ventilation guidelines could significantly improve long-term health risk assessments in dense urban centres.
As Indian cities continue to grow upward, the study suggests that understanding how pollution behaves above the streets may be just as important as measuring what lingers along them.