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Subject: Economics

  • Export Preparedness Index (EPI) 2024

    Why in the News?

    NITI Aayog released the Export Preparedness Index (EPI) 2024, assessing export readiness of Indian States and Union Territories. This is the 4th edition of the Index, first launched in August 2020.

    The Index aligns with India’s targets of USD 1 trillion merchandise exports by 2030

    About Export Preparedness Index

    • Evidence based framework to assess strength, resilience and inclusiveness of subnational export ecosystems
    • Recognises the critical role of States and districts in India’s global trade performance
    • Identifies
      • Structural challenges
      • Growth levers
      • Policy opportunities
    • Focus on districts as core units of export competitiveness

    Top Performing States and Union Territories

    A. Large States

    1. Maharashtra
    2. Tamil Nadu
    3. Gujarat
    4. Uttar Pradesh
    5. Andhra Pradesh

    B. Small States, North Eastern States & Union Territories

    1. Uttarakhand
    2. Jammu and Kashmir
    3. Nagaland
    4. Dadra and Nagar Haveli & Daman and Diu
    5. Goa
    [2020] With reference to the international trade of India at present, which of the following statements is/are correct? 

    1. India’s merchandise exports are less than its merchandise imports

    2. India’s imports of iron and steel, chemicals, fertilisers and machinery have decreased in recent years

    3. India’s exports of services are more than its imports of services

    4. India suffers from an overall trade/current account deficit

    Select the correct answer using the code given below: 

    (a) 1 and 2 only (b) 2 and 4 only (c) 3 only (d) 1, 3 and 4 only

  • PFRDA forms high-level committee for assured payouts under NPS

    Why in the news?

    The Pension Fund Regulatory and Development Authority (PFRDA) has constituted a high-level committee to frame guidelines and regulations for assured pension payouts under the National Pension System (NPS), aimed at strengthening retirement income security.

    About the committee

    • Chairperson: Dr. M. S. Sahoo, Former Chairperson, Insolvency and Bankruptcy Board of India (IBBI)
    • Composition: 15 members from legal, actuarial, finance, insurance, capital markets and academia
    • Flexibility: Power to invite external experts and intermediaries as special invitees
    • Nature: Standing advisory committee on structured pension payouts

    Key objectives and terms of reference

    • Assured payout framework: Draft regulations for assured and structured pension payouts, based on PFRDA consultation paper dated 30 September 2025
    • Seamless transition: Smooth shift from accumulation phase to decumulation payout phase
    • Market based assurance: Explore novation and settlement mechanisms for legally enforceable guarantees
    • Operational design: Define lock in period, withdrawal limits, pricing mechanisms and fee structures
    • Risk and legal oversight: Specify capital and solvency norms and examine tax implications for in-system payouts
    • Consumer protection: Standardised disclosure framework to prevent mis selling and manage subscriber expectations

    Significance

    • Enhances predictability and security of retirement income
    • Strengthens trust and attractiveness of NPS
    • Supports the vision of Viksit Bharat 2047 with financial dignity in old age
    [2017] Who among the following can join the National Pension System (NPS)? 

    (a) Resident Indian citizens only 

    (b) Persons of age from 21 to 55 only 

    (c) All State Government employees joining the services after the date of notification by the respective State Governments 

    (d) All Central Governments Employees including those of Armed Forces joining the services on or after 1st April, 2004

  • India must focus on AI and its environmental impact

    Why in the News?

    Artificial Intelligence is expanding rapidly across sectors. However, its environmental costs remain largely ignored in policy discussions. The global ICT sector contributes 1.8-2.8% of global greenhouse gas emissions, with estimates rising to 2.1-3.9%. For the first time, clear data is available on the energy, water, and carbon footprint of AI systems, including Large Language Models (LLMs).

    A clear gap exists between perceived digital efficiency and actual environmental impact. A single ChatGPT query consumes 10 times more energy than a Google search. Training one LLM can emit up to 3,00,000 kg of carbon dioxide. Despite these costs, India has no formal system to measure or disclose AI’s environmental impact. This contrasts with the EU and the US, highlighting a major governance gap.

    What is the scale of AI’s environmental footprint?

    1. Global ICT emissions: Accounts for 1.8-2.8% of global GHG emissions, with upper estimates reaching 3.9%.
    2. Carbon-intensive training: Training a single LLM can emit ~3,00,000 kg of carbon dioxide.
    3. Comparative impact: Emissions from one deep learning model equal emissions from five cars over their lifetime.
    4. Data gap: Carbon footprint data of AI models and users remains fragmented and inconsistent.

    How does AI affect energy consumption patterns?

    1. High energy intensity: Each ChatGPT query consumes 10× more energy than a Google search.
    2. Hidden electricity demand: AI workloads rely on energy-intensive data centres and specialised hardware.
    3. Misleading averages: Claims such as 0.24 watt-hours per AI query underestimate system-wide consumption.

    Why is water consumption emerging as a major concern?

    1. UNEP projection: AI data centres may consume 4.2-6.6 billion cubic metres of water by 2027.
    2. Cooling requirements: Water is extensively used to cool AI servers.
    3. Water security risks: High freshwater withdrawal threatens water-stressed regions.

    What global governance responses are emerging?

    1. UNESCO framework (2021): Recognises negative environmental impacts of AI; adopted by ~190 countries.
    2. European Union leadership:
      1. AI Act, 2024: Introduces environmental accountability in AI governance.
      2. Harmonised AI rules: Address sustainability alongside ethics and safety.
    3. United States approach: Sector-specific regulations addressing AI’s environmental externalities.

    Why does India need a regulatory shift?

    1. Unaccounted externalities: Environmental costs of AI development remain outside policy evaluation.
    2. Regulatory vacuum: No mandatory assessment of AI’s environmental impact.
    3. Climate obligations: AI expansion risks undermining India’s climate mitigation commitments.
    4. Policy imbalance: Focus on innovation without parallel sustainability safeguards.

    How can Environmental Impact Assessment be extended to AI?

    1. EIA framework: India’s EIA Notification, 2006 mandates environmental assessment for infrastructure projects.
    2. Proposed extension: Inclusion of AI development and deployment within EIA scope.
    3. Lifecycle evaluation: Assessment of energy use, water consumption, and emissions across AI lifespans.

    What role can disclosure standards play?

    1. ESG integration: Environmental impact of AI included under ESG disclosure norms.
    2. SEBI alignment: Disclosure of emissions from data centres and computing activities.
    3. EU precedent: Corporate Sustainability Reporting Directive (CSRD) mandates emission disclosure, including AI training.
    4. Transparency outcome: Enables informed policymaking and accountability.

    Which sustainable practices can mitigate AI’s impact?

    1. Pre-trained models: Reduces repeated energy-intensive training.
    2. Renewable energy: Powering data centres through clean energy sources.
    3. Efficiency reporting: Disclosure of AI-specific environmental metrics.
    4. Resource optimisation: Minimising water and energy intensity of AI infrastructure.

    Conclusion

    India’s AI ambitions must align with environmental sustainability. Institutionalising environmental assessment, disclosure norms, and sustainable practices is essential to prevent AI-driven ecological externalities. A regulatory framework that integrates innovation with environmental accountability will ensure AI remains a tool for inclusive and sustainable development.

    PYQ Relevance

    [UPSC 2023] How can Artificial Intelligence help clinical diagnosis? Do you perceive any threat to privacy of the individual in the use of AI in healthcare?

    Linkage: Earlier, UPSC focused on how AI helps healthcare and affects patient privacy. Now, as AI use expands, questions are likely to include its environmental impact, especially energy- and data-intensive AI systems.

  • If data is the new oil, what does that make data centres?

    Why in the News?

    India is increasingly seen as a likely destination for global “data dumping” as large data centres expand due to AI growth, government incentives, and geopolitical changes. This is a serious issue because data centres place heavy pressure on electricity, water, land, and environmental regulation, especially in water-stressed cities. Unlike earlier views that treated digital infrastructure as low-impact, data centres are now emerging as resource-intensive industrial units, raising concerns about sustainability, weak regulation, and long-term environmental costs.

    What are Data centers?

    1. Physical Digital Infrastructure: Large facilities that store, process, and manage digital data using servers, storage systems, and networking equipment.
    2. Backbone of the Digital Economy: Support cloud computing, e-governance, AI, fintech, e-commerce, and social media services.

    Why is India vulnerable to becoming a “data dumping” destination?

    1. Geopolitical Stability: Provides predictability compared to other global regions, increasing investor preference.
    2. Fiscal Incentives: Offers subsidised land, power, and expedited clearances for data infrastructure.
    3. Domestic Market Scale: Ensures long-term demand for data storage and processing.
    4. AI-Driven Demand: Accelerates need for hyperscale facilities with high energy density.

    Why are data centres no longer “clean” digital infrastructure?

    1. Electricity Intensity: Requires massive grid capacity, substations, and uninterrupted power supply.
    2. Water Dependence: Uses large volumes for cooling, especially where air cooling is not feasible.
    3. Thermal Pollution: Releases waste heat, intensifying urban heat stress.
    4. Industrial Footprint: Mirrors heavy industry in land use, emissions, and infrastructure strain.

    What environmental risks?

    1. Water Stress: Many Indian cities already face chronic water shortages.
    2. Grid Overload: Clustered data centres require grid upgrades and load balancing.
    3. Externalised Costs: Environmental and infrastructure costs often borne by the public sector.
    4. Weak Enforcement: Post-clearance monitoring and compliance remain inadequate.

    What are the governance and regulatory gaps?

    1. Institutional Lacunae: Noted by the Comptroller and Auditor General, Supreme Court, and National Green Tribunal.
    2. Zoning Weaknesses: Data centres not uniformly classified as heavy infrastructure.
    3. Opacity: Non-disclosure agreements restrict public scrutiny.
    4. Fragmented Oversight: Multiple agencies without integrated regulation.

    What lessons emerge from international and domestic resistance?

    1. United States Experience: Community resistance in Virginia, North Carolina, and Minnesota due to water and energy stress.
    2. Transparency Failures: Projects stalled due to non-disclosure and lack of public consultation.
    3. Course Correction: Developers increasingly engaging communities early to reduce backlash.
    4. Indian Parallel: Similar conditions exist but with weaker civic engagement and regulatory checks.

    Risks of unchecked expansion

    1. Capital Intensity: Limits government bargaining power once investments are sunk.
    2. Subsidy Distortions: Shifts public resources toward private digital infrastructure.
    3. Environmental Injustice: Local communities bear costs without proportional benefits.
    4. Governance Risk: Early-stage policy failures become irreversible later.

    Conclusion

    Data centres must be treated as heavy infrastructure, not neutral digital assets. Without enforceable zoning, water-use ceilings, transparent disclosures, and robust environmental oversight, India risks replicating extractive development models under the guise of digital growth. Sustainable digitalisation requires aligning data infrastructure with ecological limits and democratic accountability.

    PYQ Relevance

    [UPSC 2015] Discuss the advantages and security implications of cloud hosting of servers vis-a-vis in-house machine-based hosting for government businesses.

    Linkage: This question examines the trade-offs between efficiency-driven digital governance and strategic data control. It also connects with current debates on data centres, cloud infrastructure, and data sovereignty, where reliance on cloud hosting raises concerns of security, resilience, and regulatory oversight for government systems.

  • District Led Textiles Transformation (DLTT) Plan

    Why in the News?

    The Ministry of Textiles has launched the District Led Textiles Transformation (DLTT) Plan to convert 100 high potential districts into Global Export Champions and upgrade 100 Aspirational Districts into self reliant textile hubs.

    What is the DLTT Plan

    • A sector specific, district level transformation strategy for textiles
    • Uses data driven categorisation to tailor interventions
    • Covers districts at different stages, from advanced export clusters to foundation stage districts

    Objectives

    • Drive inclusive, sustainable, and export oriented growth in textiles
    • Decentralise policy execution to districts
    • Strengthen MSMEs and formalise the workforce
    • Build globally competitive textile clusters

    Significance

    • Moves India up the textile value chain
    • Diversifies export baskets
    • Strengthens MSMEs and formalises labour
    • Boosts women led and SHG led enterprises
    • Accelerates development in aspirational, eastern, and north eastern districts

    Prelims Pointers

    • DLTT follows a district first approach
    • Uses data driven classification
    • Integrates skilling, infrastructure, and exports
    • Strong focus on inclusive and regional development
    [2022] Which of the following activities constitute the real sector in the economy? 

    1. Farmers harvesting their crops 2. Textile mills converting raw cotton into fabrics 

    2. A commercial bank lending money to a trading company 

    3. A corporate body issuing Rupee Denominated Bonds overseas 

    Select the correct answer using the code given below: 

    (a) 1 and 2 only (b) 2, 3 and 4 only (c) 1, 3 and 4 only (d) 1, 2, 3 and 4

  • [9th January 2026] The Hindu OpED: GSDP share as criterion for central-State transfers

    PYQ Relevance

    [UPSC 2020] Explain the rationale behind the Goods and Services Tax (Compensation to States) Act, 2017. How has COVID-19 impacted the GST compensation fund and created new federal tensions?

    Linkage: COVID-19 exposed structural weaknesses in the GST compensation mechanism.

    This intensified Centre-State fiscal tensions and revived debates on fair and transparent transfer mechanisms in India’s federal framework.

    Mentor’s Comment

    Debates on fiscal federalism in India often oscillate between equity and efficiency. The article examines whether Gross State Domestic Product (GSDP) can be a fair and reliable basis for sharing Central tax revenues among States, especially in the post-GST era where tax attribution has become complex.

    Why in the News

    The article gains significance amid ongoing debates on Central-State fiscal relations, especially after the implementation of GST, which has weakened the direct link between tax collection and the place of economic activity. The issue is critical because ₹75.12 lakh crore was transferred to States between 2020-21 and 2024-25, and the method used to distribute this amount affects State fiscal autonomy and perceived fairness. A key finding is the very high correlation (0.99) between actual transfers and GSDP, compared to a much weaker link with Finance Commission devolution, making GSDP a stronger alternative measure.

    Introduction

    India’s system of fiscal transfers relies heavily on the recommendations of successive Finance Commissions, which distribute Central tax revenues through tax devolution, grants-in-aid, and Centrally Sponsored Schemes (CSS). However, the post-GST tax regime has disrupted the traditional linkage between tax collection location and economic value creation, raising questions about whether existing criteria adequately capture States’ real contribution to national revenues.

    Why is tax collection an unreliable indicator of State-level contribution?

    1. GST structure: Breaks the link between the location of production and the location of tax collection due to destination-based taxation.
    2. Corporate taxation: Attributes tax payments to the registered office location rather than where economic activity occurs.
    3. Multi-State operations: Dilutes State-wise attribution due to labour migration, inter-State supply chains, and inter-corporate transactions.
    4. Example distortion: Automobile manufacturers pay taxes where offices are registered, not necessarily where factories operate; plantation companies record profits centrally despite dispersed production.
    5. Outcome: Direct tax figures reflect collection points, not value creation.

    Why does GSDP emerge as a credible proxy for tax accrual?

    1. Economic base representation: Captures the size and intensity of economic activity within a State.
    2. Uniform tax base assumption: Assumes broadly similar tax administration efficiency across States.
    3. Empirical validation: Correlation between GSDP and GST collections stands at 0.75 for 2023-24.
    4. High correlation with transfers: Correlation of 0.91 between GSDP and total Central tax transfers.
    5. Policy neutrality: Avoids contentious attribution disputes inherent in GST accounting.

    How do actual transfers align with GSDP shares?

    1. Overall transfers: ₹75.12 lakh crore transferred during 2020-25, including FC devolution, grants, and CSS.
    2. High-alignment States:
      1. Uttar Pradesh: 15.81% transfer share vs 16.85% population share.
      2. Maharashtra: High tax contribution (40.3%) but only 6.64% of transfers, reflecting redistribution.
    3. Mismatch States:
      1. Bihar: Receives 8.65% transfers despite only 4.66% GSDP share.
      2. West Bengal: 6.96% GSDP share vs 6.69% transfers.
    4. Interpretation: Transfers broadly track economic output, not tax collections.

    How does the equity-efficiency trade-off emerge in fiscal transfers?

    1. Redistributive bias: FC criteria prioritize equity over efficiency by favoring population and income distance.
    2. Regional disparities: Persist due to differential expenditure needs and fiscal capacity.
    3. Efficiency trade-off: GSDP-based transfers better reflect contribution but reduce redistributive scope.
    4. Evidence: Correlation between GSDP and FC devolution shares is only 0.58, indicating weak alignment.
    5. Outcome: GSDP balances fairness and efficiency more transparently than current metrics.

    Which States gain or lose under a pure GSDP-based system?

    1. Major gainers: Tamil Nadu and Karnataka: High production but lower tax attribution due to GST mechanics.
    2. Major losers: Uttar Pradesh, Bihar, Madhya Pradesh: Benefit currently from redistributive weights.
    3. Exception States: Haryana, Karnataka, Maharashtra: GSDP share lower than tax collection due to tax concentration effects.
    4. Inference: GSDP corrects distortions arising from centralized tax accounting.

    Conclusion

    The debate on using GSDP as a basis for Central-State transfers highlights the need to realign India’s fiscal federal framework with the realities of the post-GST economy. While redistribution remains essential for equity, greater reliance on GSDP can improve transparency, efficiency, and trust by linking transfers more closely with economic activity. A calibrated approach, combining GSDP-based devolution with targeted grants, offers a balanced pathway to strengthen cooperative federalism.

  • Why silver prices surfed at 160% wave in 2025

    Introduction

    Silver’s price escalation in 2025 reflects a transformation from a quasi-precious metal into a critical industrial and financial asset. Unlike gold, silver’s value is increasingly driven by its role in energy transition technologies, electronics, and advanced manufacturing, compounded by global supply constraints and portfolio diversification strategies amid macroeconomic uncertainty.

    Why in the News?

    Silver prices recorded an unprecedented 160% rise in 2025, crossing ₹1,00,000 per kg for the first time in December and extending gains into early 2026. This surge marks a sharp departure from earlier years when silver lagged behind gold despite industrial relevance. The rally is significant due to the simultaneous occurrence of global supply shortages, rising industrial demand, financial market inflows, and policy-driven monetary easing, indicating a structural rather than speculative price shift.

    Why did silver prices rise steadily through 2025?

    1. Price escalation trend: Silver spot prices rose from ₹85,913 per kg in January 2025 to ₹2,46,889 per kg by January 2026, reflecting sustained monthly gains rather than episodic spikes.
    2. Contrast with gold: While gold reached record highs, silver outperformed gold in percentage terms, breaking its traditional role as a lagging asset.

    How did monetary policy fuel silver’s rally?

    1. Interest rate expectations: Anticipation of rate cuts by the US Federal Reserve reduced opportunity costs of holding non-yielding assets.
    2. Liquidity expansion: Easing global monetary conditions increased capital flows into commodities as inflation hedges.
    3. Debasement trade: Weakening of the US dollar revived investor preference for hard assets, including silver.

    What role did industrial demand play in driving prices?

    1. Energy transition demand: Silver usage expanded in solar panels, batteries, and electronics, making it integral to climate-transition infrastructure.
    2. Artificial Intelligence applications: AI-driven data centres and electronics increased silver consumption across high-conductivity components.
    3. Demand breadth: Unlike gold, silver’s value is supported by simultaneous investment and consumption demand, amplifying price momentum.

    Why did global supply fail to keep pace with demand?

    1. By-product mining constraint: Silver production depends largely on extraction alongside other metals, limiting supply responsiveness.
    2. Supply-demand imbalance: Global silver output did not rise proportionately despite demand expansion in renewables and electronics.
    3. Critical mineral status: The US Geological Survey added silver to its critical minerals list, highlighting strategic vulnerability.
    4. Geopolitical signalling: China’s inclusion of silver in its critical minerals list reinforced scarcity perceptions.

    How did physical shortages in global markets amplify prices?

    1. London market disruption: Physical silver shortages emerged in London, a key global trading hub.
    2. Inventory depletion: Stockpiles in the US declined sharply as inventories were drawn down to meet rising demand.
    3. Delivery constraints: Supply mismatches reduced confidence in paper silver contracts, increasing preference for physical holdings.

    What role did financialisation and ETFs play?

    1. ETF inflows: Silver Exchange Traded Funds attracted strong inflows, especially after September 2025.
    2. Passive investment growth: Low-cost ETFs expanded retail and institutional exposure to silver.
    3. Momentum reinforcement: ETF buying converts price expectations into actual market demand.

    Why did fear psychology matter in this rally?

    1. Stockpiling behaviour: US inventory accumulation triggered expectations of prolonged shortages.
    2. Self-fulfilling cycle: Fear of missing out encouraged accelerated buying, pushing prices higher.
    3. Market signalling: Rising prices validated scarcity narratives, reinforcing investor confidence.

    Conclusion

    The 2025 silver rally represents a structural realignment driven by industrial indispensability, constrained supply, financialisation, and macroeconomic easing. Unlike past speculative cycles, silver’s price surge reflects deeper shifts in global production systems and energy priorities. Managing such strategic commodities will be central to future economic resilience and sustainable growth.

    PYQ Relevance

    [UPSC 2024] What are the causes of persistent high food inflation in India? Comment on the effectiveness of the monetary policy of the RBI to control this type of inflation.

    Linkage: The silver rally shows how global liquidity and supply constraints drive commodity inflation beyond the reach of monetary policy. It helps explain limits of RBI tools in controlling cost-push inflation, strengthening GS-III answers on inflation management.

  • Indian Railways Becomes World’s Largest Electrified Rail

    Why in the News?

    Indian Railways has become the largest electrified rail network in the world, with about 99.2 percent of its broad gauge network electrified as of November 2025.

    About Indian Railways Electrification Achievement

    • Indian Railways is India’s national transporter and one of the world’s largest railway networks
    • It has achieved near complete electrification of its broad gauge routes
    • The milestone was achieved under Mission 100 percent Railway Electrification

    Background

    • Railway electrification in India began in 1925
    • Mission mode acceleration started after 2014

    Objectives of Mission 100 percent Railway Electrification

    • Eliminate diesel traction
    • Shift to clean electric traction
    • Reduce carbon emissions and air pollution
    • Lower fuel import dependence
    • Improve speed, reliability, and operational efficiency

    Key Features and Data

    • About 99.2 percent of nearly 70,000 route kilometres electrified
    • Electrification speed increased from
       • 1.42 km per day during 2004 to 2014
       • More than 15 km per day during 2019 to 2025
    • 25 States and Union Territories fully electrified
    • Only around 0.8 percent network remains non electrified

    Renewable Energy Integration

    • Solar capacity increased from 3.68 MW in 2014 to about 898 MW in 2025
    • Supports cleaner traction and lower operational emissions
    • Aligns with India’s renewable energy and climate goals

    Technological Advancements

    • Use of Automatic Wiring Trains
    • Mechanised Overhead Equipment foundation systems
    • Faster and safer electrification with reduced manual intervention
    [2025] Consider the following statements: 

    I. Indian Railways have prepared a National Rail Plan (NRP) to create a future ready railway system by 2028

    II. ‘Kavach’ is an Automatic Train Protection system developed in collaboration with Germany. 

    III. ‘Kavach’ system consists of RFID tags fitted on track in station section. 

    Which of the statements given above are not correct? 

    (a) I and II only (b) II and III only (c) I and III only (d) I, II and III

  • India Inaugurates Global Standard Environmental and Solar Calibration Facilities  

    Why in the News?

    India has inaugurated the world’s second National Environmental Standard Laboratory and the world’s fifth National Primary Standard Facility for Solar Cell Calibration at CSIR National Physical Laboratory, New Delhi.

    National Environmental Standard Laboratory NESL

    • An apex national facility for testing, calibration and certification of air pollution monitoring instruments
    • Designed specifically for Indian climatic and environmental conditions

    Location

    • CSIR National Physical Laboratory, New Delhi

    Institutions Involved

    • Council of Scientific and Industrial Research
    • CSIR National Physical Laboratory

    Objectives

    • Establish India specific environmental measurement standards
    • Improve accuracy and reliability of air quality data
    • Support implementation of National Clean Air Programme

    Key Features

    • Calibration under Indian conditions such as temperature, humidity and dust load
    • Provides traceable and standardised pollution data
    • Supports regulators, startups, MSMEs and domestic manufacturers
    • Only UK and India currently have such national level facilities

    Significance

    • Strengthens pollution governance
    • Reduces dependence on foreign calibration labs
    • Improves credibility of air quality monitoring across India

    National Primary Standard Facility for Solar Cell Calibration

    • A high precision metrology facility for calibration of solar cells
    • Ensures globally comparable photovoltaic measurements

    Location

    • CSIR National Physical Laboratory, New Delhi

    Key Features

    • Uses Laser based Differential Spectral Responsivity system
    • Achieves world leading uncertainty of 0.35 percent (k=2)
    • Developed in collaboration with Physikalisch-Technische Bundesanstalt
    • Only the fifth such facility worldwide

    Importance

    • Supports solar manufacturing and R and D
    • Enhances trust in Indian photovoltaic performance data
    • Boosts renewable energy transition and exports

     Significance

    • Positions India as a global leader in environmental and energy metrology
    • Strengthens Make in India and Atmanirbhar Bharat
    • Supports climate action, clean energy goals and evidence based policymaking

    Prelims Pointers

    • NESL is linked to air pollution monitoring
    • Solar calibration facility ensures international PV measurement standards
    • CSIR NPL is India’s national metrology institute
    • Only five countries globally have national primary solar calibration facilities
    [2014] With reference to technology for solar power production, consider the following statements: 

    1. ‘Photovoltaics’ is a technology that generates electricity by direct conversion of light into electricity, while ‘Solar Thermal’ is a technology that utilizes the Sun’s rays to generate heat which is further used in electricity generation process. 

    2. Photovoltaics generates Alternating Current (AC), while Solar Thermal generates Direct Current (DC). 

    3. India has manufacturing base for Solar Thermal technology, but not for photovoltaics. 

    Which of the statements given above is/are correct? 

    (a) 1 only (b) 2 and 3 only (c) 1, 2 and 3 only (d) None of the above

  • Indian aviation safety, its dangerous credibility deficit

    Why in the News?

    Indian aviation safety has come under scrutiny following the AI-171 crash (June 2025) and the subsequent handling of its investigation. The article highlights a sharp contrast between India’s stated compliance with International Civil Aviation Organization (ICAO) norms and actual investigative practices.

    Introduction

    India is a signatory to the Chicago Convention and follows ICAO Annex 13, which mandates transparent, independent, and timely aircraft accident investigations. However, recent aviation incidents reveal a widening gap between formal compliance and institutional practice. The handling of the AI-171 crash reflects structural weaknesses in investigation autonomy, regulatory enforcement, and safety oversight, undermining public confidence and international credibility.

    What triggered concerns about India’s aviation safety credibility?

    1. AI-171 Crash (June 12, 2025): Aircraft crashed shortly after take-off from Ahmedabad; 242 passengers onboard, only one survivor, 19 deaths on the ground.
    2. Immediate Institutional Response: Cockpit Voice Recorder (CVR) and Digital Flight Data Recorder (DFDR) recovered within days, yet findings delayed.
    3. Contrast with Norms: ICAO requires timely disclosure and independent investigation; delays contradict this principle.
    4. Pattern Recognition: This incident can be linked with earlier aviation safety lapses, indicating a systemic issue rather than an aberration.

    How does the investigation process reveal institutional weaknesses?

    1. Delayed Preliminary Report: Released one month later, despite early data recovery.
    2. Flight Control Anomalies: Report acknowledged engine power loss and control switches moving to “cut-off” within seconds.
    3. Pilot Testimony Ignored: Cockpit voice recordings indicated the pilot denied manually cutting fuel.
    4. Opaque Disclosure: Only selective information released; full datasets not shared with public or independent bodies.

    Why is exclusion of international investigators a serious concern?

    1. NTSB Role Marginalised: Despite early participation, the US National Transportation Safety Board limited to technical assistance.
    2. Breakdown in Trust: Reported friction between Indian authorities and international experts.
    3. Global Best Practice: Major aviation investigations rely on multi-national expert participation to ensure neutrality.
    4. Credibility Impact: Isolationism weakens confidence in findings and raises suspicion of narrative control.

    What does the article reveal about regulatory failure and enforcement gaps?

    1. Repeated Safety Violations: India recorded three fatal aviation accidents in 15 years, including Mangalore (2010) and Kozhikode (2020).
    2. Unimplemented Recommendations: Court of Inquiry findings and ICAO standards not fully enforced.
    3. DGCA Dilution: Aviation regulations modified under airline pressure, weakening oversight.
    4. IndiGo Example: Rapid expansion despite unresolved safety concerns highlighted regulatory accommodation.

    How does digital opacity worsen aviation safety accountability?

    1. Encrypted Communication Systems: Airlines using WhatsApp-based safety apps restrict audit trails.
    2. Data Access Control: Safety data accessible only to company and regulator, excluding public scrutiny.
    3. Delayed Emergency Directives: DGCA issued Emergency Airworthiness Directive months after earlier crashes.
    4. Outcome: Reduced traceability, weakened whistleblower protection, and compromised safety culture.

    Why is India’s approach diplomatically and strategically damaging?

    1. ICAO Standing: India’s credibility as a compliant aviation state weakened.
    2. Soft Power Impact: Aviation safety failures affect India’s reputation as a reliable global transport hub.
    3. Precedent Risk: Normalisation of opaque investigations threatens long-term passenger safety.

    Conclusion

    India’s aviation safety challenge is not rooted in absence of laws or expertise, but in erosion of investigative credibility, regulatory accommodation, and transparency deficits. Restoring trust requires institutional independence, international cooperation, and strict adherence to ICAO norms. Without these, aviation safety risks becoming procedurally compliant but substantively compromised.

    PYQ Relevance

    [UPSC 2024] What is the need for expanding the regional air connectivity in India? In this context, discuss the government’s UDAN Scheme and its achievements.

    Linkage: The expansion of regional air connectivity under the UDAN Scheme strengthens GS Paper III (Infrastructure-Airports) by promoting balanced regional development and economic integration. However, as highlighted by recent aviation safety concerns, rapid airport expansion must be accompanied by robust regulatory oversight and safety governance, linking infrastructure growth with institutional accountability.