A recent report from IIT Kanpur, shared by Delhi’s Environment Minister, suggests that the city’s cloud seeding experiment was somewhat successful. The report cites improved rainfall data and cleaner air quality at three specific locations. However, a closer examination, as highlighted in a previous Hindustan Times report, reveals significant methodological issues that cast doubt on these claims.
The report’s reliance on modelled rainfall estimates from Windy.com, rather than actual measured data, is a primary concern. Furthermore, the assertions of improved air quality suffer from equally serious flaws in their assessment and reporting, raising questions about the scientific validity of the findings.
The IIT Kanpur report detailed reductions in PM2.5 and PM10 levels at three locations – Mayur Vihar, Karol Bagh, and Burari – after the first seeding. It proposed that the seeding particles helped settle these pollutants due to increased moisture content, especially given negligible winds. However, this analysis overlooks critical scientific reporting standards.
Key Criticisms of the IIT-K Report:
1. Missing Units: The report fails to specify units for PM2.5 and PM10 measurements. Scientifically, these values should represent concentrations (mass per volume of air), typically in micrograms per cubic metre. Without units, it’s impossible to verify the claimed improvements or compare them against established air quality standards.
2. Unspecified Time Periods: Crucial details regarding the averaging period for measurements and their exact timing are absent. Whether the data represents 15-minute averages, hourly concentrations, or 24-hour rolling averages is unknown. This ambiguity prevents an understanding of the duration and comparability of any claimed improvements.
3. Ignoring Natural Daily Patterns: The cloud seeding operations were conducted between 2 pm and 5 pm. This timeframe remarkably coincides with Delhi’s natural daily air quality improvement cycle. Data from various air quality monitoring stations consistently shows that air quality tends to improve in the afternoon due to higher temperatures, which reduce pollutant accumulation near the ground. This natural phenomenon, evident across multiple locations, makes it impossible to definitively attribute any observed air quality changes to the cloud seeding experiment itself without accounting for these daily variations.
The report cites data from only three locations, despite acknowledging data collection from twenty. Critically, the afternoon improvement pattern, where air quality naturally gets better, is a consistent observation across different monitoring stations in the city. This makes the IIT Kanpur report’s conclusions about the cloud seeding experiment’s efficacy questionable, as it fails to isolate the impact of the intervention from natural environmental cycles.