Delhi and Cloud seeding

Why in News ?

• Context: The Delhi Government, in collaboration with IIT-Kanpur, conducted two back-to-back cloud-seeding trials using a Cessna 206H aircraft to induce artificial rain for pollution mitigation.
• Objective: To scrub pollutants and reduce high Air Quality Index (AQI ~294, “Poor”) levels in Delhi during the post-Diwali pollution spike.

Relevance:

• GS-1 (Geography): Weather modification techniques, monsoon dynamics, cloud microphysics.
• GS-2 (Governance): Inter-agency coordination (Delhi Govt–IIT Kanpur), environmental governance mechanisms.
• GS-3 (Environment & Technology): Air pollution mitigation strategies, artificial rain technology, climate engineering ethics.

What is Cloud Seeding

• Definition: A weather modification technique that enhances rainfall by introducing chemicals (like silver iodide or potassium iodide) into clouds.
• Mechanism:
  • Aircraft releases chemicals into existing clouds.
  • Chemicals act as condensation nuclei.
  • Moisture condenses around them → rain droplets form → precipitation occurs.
• Prerequisites:
  • Presence of moisture-laden clouds.
  • Favorable temperature (around -20°C or lower).
  • Adequate aerosol and humidity levels.

Scientific Objective

• Primary: Increase rainfall by converting atmospheric moisture into precipitation.
• Secondary (in Delhi’s case):
  • Wash down airborne pollutants (PM2.5, PM10).
  • Temporarily reduce smog and improve air quality.

Process in Delhi Trial

• Aircraft: Cessna 206H.
• Rounds Conducted:
  • First: Kanpur → Meerut → Marut Vihar → North Karol Bagh → Burari → Sadulpur → Jhajjar → Kanpur.
  • Second: Meerut → Marut Vihar → North Karol Bagh → Burari → Sadulpur → Bhojpur → Kanpur.
• Chemicals Used: Silver iodide and potassium iodide.
• Outcome: No rainfall recorded over Delhi; only light rain near Meerut.

Key Scientific Challenges

• Cloud Dependency:
  • Requires pre-existing clouds with sufficient moisture.
  • Cannot generate clouds in dry or stable atmospheric conditions.
• Timing:
  • Must target clouds before they drift away; delays can render the effort ineffective.
• Geographical Variability:
  • Success varies with topography, humidity, and wind speed.
• Cost and Scalability:
  • Requires aircraft, chemicals, and real-time weather tracking — resource-intensive.
• Short-Term Effect:
  • Only provides temporary pollution relief, not structural mitigation.

Scientific Assessment & Data

• IITM Pune (2023) & IIT-Kanpur Observations:
  • Only moisture-rich clouds are seedable.
  • Delhi’s winter clouds are often too dry or low-altitude.
  • Timing mismatch reduces success probability.
• DTE Report (2024):
  • India’s earlier trials (Maharashtra, Karnataka, Tamil Nadu) had mixed results; rain often localized and unpredictable.
• IMD’s Position:
  • Efficacy in reducing urban pollution remains unproven.

Expert Insights

• Dr. Suresh D. K. Khilari (Rajalhand College):
  • Delhi’s weather is too complex for consistent success.
  • “You need the right kind of cloud at the right time.”
• Dr. Thara Prabhakaran (IITM Pune):
  • Clouds differ in aerosol content and temperature; not all are seedable.
  • Need for more research, documentation, and localized models.
  • Anthropogenic emissions alter cloud chemistry, reducing predictability.

Environmental and Ethical Concerns

• Unknown Ecological Impacts:
  • Chemical dispersal may affect soil, water, and biodiversity.
• Artificial Weathering:
  • Could disturb regional rainfall patterns or microclimates.
• Equity Issue:
  • Downstream states may experience reduced rainfall if upwind seeding alters natural systems.

Global Perspective

• Success Cases:
  • UAE, Thailand, China, and the US have developed sophisticated seeding programs using radar-linked EWS.
• India’s Status:
  • Conducted sporadic trials since the 1950s (notably in Tamil Nadu, Maharashtra).
  • No standardized success metric or national protocol yet.

Way Forward

• Targeted Research:
  • Study Delhi’s micro-meteorology before large-scale deployment.
• Data-Driven Cloud Profiling:
  • Use radar, satellite, and AI-based forecasting.
• Pilot Zones:
  • Test in Western Ghats or Northeast (higher moisture zones).
• Public Transparency:
  • Publish results, cost-benefit data, and long-term impacts.
• Integrate with Air Quality Plans:
  • Cloud seeding must complement, not replace, emissions reduction.

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