Current Affairs 26th July 2024 for UPSC Prelims Exam

White Category Sectors

Context: Industries classified under the ‘white category’ by the Central Pollution Control Board (CPCB) will no longer need prior permissions from state pollution control boards to establish and operate.

Categorisation Of Industries: Based On Their Pollution Load

• The Ministry of Environment, Forest and Climate Change (MoEFCC) has established a system for categorising industrial sectors based on their environmental impact.
• This categorization is determined by the Pollution Index (PI), which assesses the level of emissions (air pollutants), effluents (water pollutants), hazardous waste production, and resource consumption.
• The criteria for determining the PI are derived from several sources, including the Water (Prevention and Control of Pollution) Cess (Amendment) Act, 2003, the Environment (Protection) Act, 1986, and the Doon Valley Notification, 1989, all issued by the MoEFCC.
• The PI ranges from 0 to 100, with higher values indicating a greater degree of pollution attributable to the sector.
• The categorization of industrial sectors based on the PI is as follows:
  • Red Category: 60 and above, high pollution.
    • Example: Paper, Oil Refineries, Synthetic fibres industries
  • Orange Category: 41 and 59, moderate pollution.
    • Examples: Coal Washeries, Soft drinks manufacturing, Silk and saree Painting.
  • Green Category: 21 and 40, lower pollution.
    • Example: Aluminium, Ayurvedic medicine.
  • White Category: 20 or less, minimal or no pollution.
    • Examples:  Solar Power, Bio Manure, and Wind power industries.

NISAR Mission

Context: The launch of the NISAR mission was pushed to next year.

NASA-ISRO Synthetic Aperture Radar (NISAR) Mission

• Collaboration: NISAR is a collaborative project between NASA and ISRO, positioned in Low Earth Orbit (LEO).
• Contributions:
  • NASA: L-band radar, GPS, data storage, and payload data subsystem
  • ISRO: S-band radar, GSLV launch system, and the spacecraft itself.
• Objective: NISAR aims to monitor Earth’s ecosystems, surfaces, and ice masses, offering insights into biomass, natural hazards, sea level changes, and groundwater levels.
• Function: The satellite will observe the Earth’s land and ice-covered surfaces globally every 12 days, covering both ascending and descending passes.
• Significance: It will help to study the dynamic processes happening on Earth’s surface, like the retreat of glaciers, changes in vegetation and forest cover, and even the movements during earthquakes and volcanoes.
  • It will provide new insights into our understanding of processes like climate change or natural hazards.
• Features:
  • The satellite is powerful enough to capture changes as small as 1cm in size during its repeated observations over the same terrain.
  • Dual-Frequency Imaging Radar: Equipped with both L-band and S-band synthetic aperture radar (SAR) instruments.
    • This is the 1st satellite mission to utilise two distinct radar frequencies for monitoring changes on Earth’s surface.
  • Cloud-Penetrating SAR Technology: The SAR technology on NISAR can penetrate cloud cover and collect data both day and night, regardless of weather conditions.
  • Antenna: The satellite includes a large 39-foot antenna reflector, made of gold-plated wire mesh, which focuses radar signals for both emission and reception.

AI and Environmental Concerns

Context

• Google reported a 13% increase in its emissions footprint in 2023 compared to the previous year.
• This rise was mainly due to a 17% increase in electricity consumption in its data centres and supply chains, driven by expanded deployment and usage of artificial intelligence (AI) tools.

AI’s Energy Consumption

• Energy-Intensive Technology: AI is recognized for its transformative potential across various sectors, including climate change solutions. However, it is also becoming known for its significant emissions footprint.
• Energy Comparison: Studies indicate that a simple AI query (e.g., to OpenAI’s ChatGPT) can use between 10 and 33 times more energy than a standard Google search, with image-based AI searches consuming even more.

Reasons for Higher AI Emissions

• Data Processing: AI models process significantly more data than a simple search query, requiring more electrical signals for processing, storing, and retrieving data.
• Heat Generation: The intensive processing work generates more heat, necessitating enhanced cooling solutions in data centres, such as more robust air conditioning systems.

Global Impact and Projections

• Rising Energy Demand: Data centres currently account for about 1% to 1.3% of global electricity demand. Projections by the International Energy Agency (IEA) suggest this could double to between 1.5% and 3% by 2026.
• Comparison with Electric Vehicles: Despite the increasing number of electric vehicles, their global electricity consumption is about 0.5%, significantly less than that of data centres.

Regional Data Center Electricity Consumption

• Ireland: Due to favourable tax breaks and incentives, Ireland hosts a large number of data centres, consuming 18% of the national electricity demand.
• United States: In the U.S., data centres consume between 1.3% and 4.5% of the national electricity demand.
• India: Specific figures for India were not provided, but the country is expected to see a rapid increase in data centre activities and AI deployment.

Environmental Impact in India

• The environmental toll of AI and data centres in India, is not only the increased electricity consumption but also the heightened demand for water resources.
• The data centre serving OpenAI’s GPT-4 model in Iowa, U.S., reportedly consumed 6% of the local district’s water supply in July 2022.
• India is on the brink of widespread AI adoption, which necessitates strategic planning to minimise environmental impacts and enhance efficiency in data centre operations.

Future Outlook

A study by the Boston Consulting Group posited that AI could lead to a 5-10% reduction in global emissions by 2030 by optimising corporate and industrial processes to eliminate waste and inefficiencies. This could also generate significant economic value, estimated between $1.3 trillion and $2.6 trillion.

Examples, Case Studies and Data

• Severity of Climate Change (GS 3): WHO estimates 2,50,000 additional deaths per year (2030-2050) due to malnutrition, malaria, diarrhoea, and heat stress.
  • Direct health costs: $2-4 billion per year by 2030.
  • Vulnerable regions: Developing countries with weak health infrastructure.
  • India: A study by SRIHER indicates extreme heat doubles the risk of stillbirth and miscarriage for pregnant women.

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