Content YARD 1267 SAMUDRA PRATAP Good Governance Day YARD 1267 SAMUDRA PRATAP Why is it in News? The Indian Coast Guard (ICG) inducted its first indigenously designed & built Pollution Control Vessel (PCV) — ICGS Samudra Pratap (Yard 1267) — on 23 December 2025, constructed by Goa Shipyard Ltd (GSL) under the 02-PCV project. The vessel has >60% indigenous content, reinforcing Aatmanirbhar Bharat & Make in India in advanced maritime platforms. It is now the largest vessel in the ICG fleet, significantly upgrading oil-spill response, marine pollution control & EEZ-surveillance capability. Relevance   GS-III | Environment & Disaster Management — strengthens marine pollution response capacity, oil-spill control, IMO-MARPOL compliance, NOS-DCP implementation, Blue Economy sustainability. GS-III | Internal & Coastal Security / Maritime Governance — enhances ICG operational readiness in EEZ surveillance, offshore safety, port-shipping lane protection, marine hazard response. Key Specifications Pollution Control Vessel (PCV)  : Specialised maritime platform for oil-spill & chemical pollution response — equipped with skimmers, booms, dispersant systems, recovery tanks and onboard labs to contain, collect, and treat pollutants at sea. Length: 114.5 m Breadth: 16.5 m Displacement: 4,170 tonnes Type: Pollution Control Vessel (PCV) Dynamic Positioning (DP-1): A computer-controlled system that uses thrusters and sensors to hold the ship’s position and heading automatically without anchors, enabling safe, high-precision operations during pollution-response tasks. Fire-fighting notation (FiFi-2 / FFV-2): An international certification indicating the ship has high-capacity external firefighting systems capable of combating large marine and offshore fires at greater range and water-output levels than standard vessels. Armament: 30 mm CRN-91 gun Two 12.7 mm Stabilised RC guns with integrated fire-control system Critical Systems: Integrated Bridge System (Indigenous) Integrated Platform Management System Automated Power Management System High-capacity External Fire-Fighting System Specialised Pollution-Control Capabilities Oil-spill detection & analysis Oil fingerprinting machine Gyro-stabilised Standoff Active Chemical Detector Pollution-Control Laboratory (onboard) Response operations capability High-precision DP-enabled recovery Pollutant recovery from viscous oil Oil-water separation & contaminant analysis Operational Reach Designed for action within EEZ (≈ 2.37 million sq km) & beyond Strategic Significance  Maritime Environmental Security India handles ~1,500+ tanker movements annually; >70% crude oil imports move by sea. Past oil-spill incidents (Mumbai coast, Ennore, Vizag) exposed limited dedicated response assets. Samudra Pratap strengthens pollution-response readiness for: Offshore platforms Shipping lanes Ports & coastal refineries Blue Economy & IMO Compliance Enhances India’s capability under: MARPOL Convention National Oil Spill Disaster Contingency Plan (NOS-DCP) Aligns with India’s Blue Economy 2047 sustainability goals. Force-structure Upgrade Adds to ICG’s role beyond SAR & coastal security: Environmental protection Marine chemical hazard response Firefighting support to merchant & offshore vessels Aatmanirbhar Defence Industrialisation Strengthens indigenous shipbuilding ecosystem (Goa Shipyard Ltd) Demonstrates domestic capability in niche maritime technologies such as: DP-systems Pollution-control labs Integrated ship automation Context & Background India earlier operated pollution-response assets like ICGS Samudra Prahari (import-technology heavy). Samudra Pratap marks the first fully indigenous PCV, shifting capability from platform-adaptation to purpose-built maritime environmental vessels. Part of a two-ship PCV programme — enhances redundancy & nationwide deployment coverage. Conclusion ICGS Samudra Pratap is India’s first fully indigenous, largest Coast Guard pollution-control vessel, boosting oil-spill response, maritime environmental security, and indigenous defence shipbuilding capacity. Good Governance Day Why is it in News? Good Governance Day (25 December 2025) was observed to commemorate Atal Bihari Vajpayee’s birth anniversary, highlighting accountability, transparency, and citizen-centric governance. The Department of Administrative Reforms & Public Grievances (DARPG) released updates on the Good Governance Index (GGI) — a composite benchmarking tool measuring governance performance across States & UTs. The 2025 observance emphasized e-governance, digital service delivery, evidence-based reforms, and state-level performance improvements across 10 governance sectors. The year also saw major governance conferences including the 28th National Conference on e-Governance (Visakhapatnam, 2025) and IIAS-DARPG Global Governance Conference (New Delhi, 2025). Relevance   GS-II | Governance, Transparency & Accountability — institutionalises evidence-based reforms, citizen-centric service delivery, grievance-redress, RTSA & digital governance outcomes. Good Governance Day — Key Facts Date: 25 December (since 2014) Purpose: Promote citizen-centric, transparent, accountable, responsive, and inclusive governance. Legacy Anchor: Atal Bihari Vajpayee — infrastructure expansion, telecom growth, rural connectivity, democratic values & reform-oriented governance. UN Governance Principles Referenced: Participation, accountability, transparency, equity, efficiency, rule of law. Good Governance Index (GGI) — Core Features Launched: 2019 (DARPG) as a diagnostic & comparative governance assessment tool. Coverage: States & UTs grouped into 4 categories for fair comparison: Group-A States, Group-B States North-East & Hill States Union Territories Sectors Covered: 10 governance sectors / 58 indicators, including: Agriculture, Industry, HRD, Health Infrastructure & Utilities Economic Governance Social Welfare Judiciary & Public Safety Environment Citizen-Centric Governance Purpose: Benchmarking, inter-state competition, policy prioritisation, and evidence-based reforms. Governance Performance — Evidence Highlights  Human Development: Progress in retention rates, gender parity, digital access in schools, skilling & placement outcomes. Public Health: Expansion of HWCs, PHC doctor availability, IMR/MMR reduction, immunisation & hospital-bed density. Economic Governance: Tracking GSDP per-capita growth, fiscal deficit ratios, tax-revenue mobilisation, debt-to-GSDP discipline. Infrastructure & Utilities: Gains in rural connectivity, potable water coverage, LPG access, power availability & per-capita consumption. Citizen-Centric Governance: Service delivery acts, grievance-redress outcomes, online public-service access. Environment: Forest-cover change, waste-recycling share, degraded-land proportion, renewable-capacity growth. (The Index enables sector-wise dashboards for progress monitoring and reform targeting.) Top-Performer Context (Illustrative — GGI 2020-21 Benchmarks) Group-A: Gujarat, Maharashtra, Goa Group-B: Madhya Pradesh, Rajasthan, Chhattisgarh NE & Hill: Himachal Pradesh, Mizoram UTs: Delhi GGI-2019 Leaders: Tamil Nadu, Maharashtra, Himachal Pradesh, Puducherry (Used as reference baselines for subsequent performance trends.) 2025 Governance & Reform Ecosystem 28th National Conference on e-Governance (Visakhapatnam, 2025): Theme: Viksit Bharat — Civil Service & Digital Transformation; 1,000+ delegates, National e-Governance Awards, Visakhapatnam Declaration for Digital-First Governance.   IIAS–DARPG Global Governance Conference (New Delhi, 2025): 750+ delegates from 58 countries, release of Viksit Bharat@2047 — Governance Transformed; India elected IIAS Presidency (2025-28).   State Collaborative Initiative (SCI), 2025: 80+ state proposals on AI platforms, digital portals, real-time dashboards; dedicated monitoring portal.   Conclusion Good Governance Day 2025 reinforces Vajpayee’s legacy of citizen-centric, accountable governance, while the Good Governance Index provides a data-driven, sector-wise performance benchmark to drive reforms across States and UTs. Atal Bihari Vajpayee Three-time Prime Minister of India (1996, 1998–2004) — known for coalition stability, economic reforms, telecom liberalisation, National Highways Development Project, and Pradhan Mantri Gram Sadak Yojana. Distinguished Parliamentarian (40+ years) — elected 9 times to Lok Sabha and 2 times to Rajya Sabha; awarded Best Parliamentarian (1994) for his consensus-building and statesmanship. National Honors: Conferred Padma Vibhushan (1992) and Bharat Ratna (2015) for contributions to nation-building, democratic values, and governance reforms. Strategic & Foreign Policy Achievements: Led Pokhran-II nuclear tests (1998), initiated Lahore Bus Diplomacy, strengthened India’s global profile, and promoted peace with strength. Social & Governance Legacy: Advocated inclusive growth, women’s empowerment, infrastructure expansion, good governance, and citizen-centric administration — foundation for Good Governance Day (25 December).

Content The digital narcissus Green washing The digital narcissus Why is it in news? Recent commentaries warn that contemporary Artificial Intelligence systems are increasingly optimised for user-pleasing, affirmation-driven responses, leading to what analysts describe as an era of “intelligent sycophants” — systems that avoid challenge, critique, or contradiction to maximise engagement and retention. The debate highlights societal, cognitive, and democratic risks arising from algorithmic design choices that prioritise comfort over truth, validation over reasoning, and consensus over dissent. Relevance GS-3 (Science & Tech) Algorithmic design ethics, incentive structures in AI systems Risks to cognitive autonomy, misinformation, echo-chambers Practice Question “The danger of AI is not misinformation but affirmation without scrutiny.” Discuss with reference to cognitive autonomy and democratic discourse.(250 Words) Engagement Economics → Flattery-by-Design Platform incentives: Algorithms are typically trained to maximise engagement, satisfaction scores, and session time — behaviours empirically correlated with agreement, politeness, and positive emotional reinforcement. Research trends show that models penalised for user dissatisfaction tend to avoid contradiction, nudging outputs toward softer, agreeable responses rather than rigorous challenge. Outcome: A structural bias toward “comfort-first intelligence”, where disagreement appears risky and affirmation becomes default. Cognitive & Behavioural Risks Continuous positive feedback fosters confirmation bias reinforcement, weakening habits of self-correction, doubt, and reflective reasoning. Persistent validation environments can reduce tolerance for disagreement, increasing fragility in deliberative settings (education, workplaces, civic debate). Children and young users risk reduced exposure to argument, critique, and ambiguity, impairing development of dialogic and analytical resilience. Democratic & Institutional Implications If AI ecosystems consistently amplify approval and mute dissent, political discourse risks manufactured consensus rather than contestation. Algorithmic flattery can be instrumentalised by power structures — shaping narratives through curated affirmation, selective visibility, and subtle reality-filtering. This shifts control from explicit censorship → implicit persuasion, eroding plurality, debate, and adversarial truth-seeking that underpin democratic culture. From Rights of Users to Duties of Design Earlier digital ethics debates centred on privacy, bias, fairness; the emerging concern is intellectual autonomy — whether systems challenge, probe, or question where necessary. Ethicists argue for design obligations: Encourage evidence-seeking over affirmation, Preserve space for contradiction, Surface epistemic uncertainty instead of false certainty. Without such safeguards, AI becomes a psychological comfort system, not a cognitive partner. Historical Parallels & Political Economy Human institutions have repeatedly shown that flattery cultures degrade decision-quality — courts, courts of power, corporate boards, monarchies. At scale, algorithmic replication of such environments produces a systemic quiet catastrophe — truth is not suppressed violently but outcompeted by reassurance. The danger is not machine domination, but human intellectual atrophy — when disagreement feels alien and correction feels hostile. Normative Warning — Evolution vs. Stagnation Intellectual progress historically depends on friction, critique, and error-correction. If AI normalises frictionless approval, the habit of saying “I was wrong” weakens — undermining scientific temperament, democratic dialogue, and moral courage. The existential risk described is not technological collapse, but the end of inquiry — a civilisation lulled into agreement. Conclusion The core concern is not AI capability, but what humans ask AI to optimise for. Systems tuned to please rather than probe risk producing a society comfortable but unthinking, where dissent erodes quietly and truth is displaced by agreeable illusion. Green washing  Why is it in news? The Supreme Court (Nov 20, 2025 order) paused fresh mining leases in the Aravalli region until a Management Plan for Sustainable Mining (MPSM) is finalised under central supervision. The case triggered debate after an expert panel recommended that only hills ≥100 m above local relief be treated as “Aravalli”, which would exclude ~92% of hill features (FSI-2010 estimate) from protection — raising fears of expanded mining eligibility, weak oversight and erosion of ecological safeguards. Relevance GS-3 (Environment, Conservation, Pollution) Mining–ecology trade-offs, hydrology & air-shed functions, landscape conservation GS-2 (Governance & Federalism) Transparency, regulatory credibility, Centre–State coordination, judicial oversight Practice Question “Environmental outcomes are increasingly shaped by definitions rather than science.” Examine with reference to the Aravalli mining case.(250 Words) Data & facts-rich context  Age & spread: Among the world’s oldest fold mountains (~1.5–2.5 bn years); stretches ~700 km across Gujarat–Rajasthan–Haryana–Delhi. Hydrology: Acts as a groundwater recharge zone for semi-arid districts; areas around Gurugram–Faridabad–Alwar show severe depletion linked to quarrying & land-use change. Climate & air-shed role: Serves as a barrier to Thar desert winds; loss of ridge cover increases dust load & PM levels in NCR. Forest/green cover: Aravalli region has <7% dense forest cover in many tracts; fragmentation driven by mining, urbanisation, real-estate conversion. Pollution & safety: Studies associate illegal mining belts with land subsidence, habitat loss, heat-island effects, and higher particulate concentration. Economy–governance tension: Mining provides State revenues & local employment, but weak enforcement capacity increases risks of illegal extraction when blanket bans are imposed. Key elements of the Supreme Court position No blanket ban, but a pause on leases except government-sanctioned extraction of “critical minerals”. Recognises the conflict of interest: States depend on mining revenue but also must enforce environmental compliance. Calls for an MPSM to balance resource demand vs. ecological thresholds, under central oversight. Accepted expert-panel suggestion on 100-m local-relief criterion, but did not explain why this definition was preferred — creating ambiguity & trust deficit. Why the definition controversy matters ? Policy consequence: Defining Aravalli only as hills ≥100 m would remove ~92% features from the notified ambit, potentially opening large tracts for leases, construction, or tree felling (even if formally limited to mining decisions). Transparency gap: Committee data, methods, GIS layers and impact modelling are not publicly disclosed → decisions rely on trust instead of evidence. Ecological principle: Reforestation ≠ guaranteed compensation for deforestation; recovery of soil depth, aquifers, native biodiversity may take decades or fail entirely. Green-Wall paradox: The Centre’s Aravalli Green Wall Project promotes afforestation, yet ongoing fragmentation through quarrying undercuts landscape-scale restoration. Core issues highlighted by the debate Governance deficit: Lack of open datasets, cumulative-impact assessments, satellite audits, and public consultations. Regulatory asymmetry: Project-wise clearances ignore landscape connectivity & aquifer systems. Urban-ecology risk: NCR air-shed and water security are directly linked to ridge integrity; piecemeal approvals raise systemic risk. Institutional trust: Past weak performance on air pollution & enforcement fuels scepticism about narrow technical re-definitions. Implications for policy & federalism Mining–environment trade-off shifts from scientific thresholds to definitional manoeuvres. Centre–State coordination must address illegal mining, cross-border transport chains, royalty incentives, and independent monitoring. Judicial oversight remains pivotal, but opaque expert processes undermine legitimacy. Way forward  Publish the MPSM: assumptions, spatial layers, hydrology models, biodiversity data, and clear vulnerability zoning. Adopt landscape criteria: treat ridges, inter-fluves, corridors, recharge zones as a single ecological unit, not only ≥100-m peaks. Independent compliance audits using remote sensing + ground-truthing, quarterly public dashboards. No-go mapping for high-risk aquifer & erosion zones; graded permissions only in low-impact belts with strict caps. Align Green-Wall & mining policy through restoration guarantees, bonds, and long-term monitoring.

Content Telangana likely to get five more Geographical Indication (GI) tags soon Why manufacturing has lagged in India What is the Bureau of Port Security and its role? Did an ancient flood contribute to Keezhadi’s abandonment? ISRO rocket LVM-3 places 6000-kg US satellite — its heaviest — into orbit Only 1 in 4 marginal farmers in India linked to cooperatives, report finds Large share of India’s PM2.5 not emitted directly, but chemically formed in the atmosphere: CREA Study Telangana likely to get five more Geographical Indication (GI) tags soon Why is it in news? Telangana is close to securing five new Geographical Indication (GI) tags — Narayanpet jewellery making, Hyderabad pearls, Banjara tribal jewellery, Banjara needle craft, and Batik paintings — after completion of field studies and documentation. Additional GI applications are pending for Armoor turmeric, Nalgonda chitti dosakai, Kollapur Benishan mango, Mahadevpur tussar silk, Jagtial sesame, and Nayakpod masks. In the last two years, the State obtained two new GI tags — Hyderabad lac bangles (2024) and Warangal chapata chilli (2025) — taking the total to 18 GI-tagged products. Relevance GS-III: Economy — Inclusive Growth, MSMEs, Rural Development GI-linked value addition, craft-cluster livelihoods, FPO linkages, women-led enterprises GS-I: Indian Culture & Heritage Protection of traditional crafts, tribal art, cultural identity Telangana GI Ecosystem Total GI-tagged products (current): 18 Includes: Pochampally Ikat, Adilabad Dokra, Warangal Durries, Hyderabad Haleem, etc. GI Authority: Geographical Indications Registry, Chennai (under DPIIT). Legal Basis: Geographical Indications of Goods (Registration and Protection) Act, 1999. Ownership & Value Effects Protects place-linked identity & brand premium Ensures exclusive usage rights to local producers Enables authentication & traceability Economic Linkages GI clusters typically show Price premium: 10–30% (avg. Indian handicrafts/food GIs) Higher rural employment multipliers in craft-based economies Cultural Impact Safeguards intangible heritage, artisanal skills, tribal crafts Strengthens community identity & transmission of traditional knowledge Sectoral Significance of the Proposed GI Tags Banjara crafts (jewellery + needlework) → protects tribal livelihood chains, encourages women-led craft enterprises. Hyderabad pearls → reinforces historic trade heritage, boosts export-tourism branding. Narayanpet jewellery making → formal recognition to regional artisanal metalwork traditions. Batik paintings → strengthens handloom-art crossover markets and design innovation. Takeaways GI = place-specific, collective intellectual property (not individual trademark). Registered under DPIIT; validity: 10 years; renewable. Pre-eminent Telangana GIs: Pochampally Ikat, Adilabad Dokra, Warangal Durries, Hyderabad Haleem. Recent additions: Hyderabad lac bangles (2024), Warangal chapata chilli (2025). Upcoming pipeline: Armoor turmeric, Kollapur Benishan mango, Mahadevpur tussar silk, etc. Why manufacturing has lagged in India ? Why is it in news? A recent discussion on A Sixth of Humanity by economist Arvind Subramanian revisits why India has lagged behind China and South Korea in industrialisation despite comparable starting points. The argument applies the ‘Dutch Disease’ framework to India — suggesting that high public-sector wages distorted labour markets, pulled workers away from manufacturing, raised domestic prices, appreciated the real exchange rate, and weakened manufacturing competitiveness. The debate reopens larger questions on technological upgradation, wage dynamics, inequality, and structural transformation in India’s growth model. Relevance GS-III: Economy — Growth, Structural Transformation, Employment Manufacturing stagnation, wage–productivity dynamics, inequality GS-III: Industry & Infrastructure / Industrial Policy Technology adoption, export orientation, PLI, R&D ecosystem Key Facts & Data Manufacturing share in GDP India: broadly 15–17% for three decades, declining recently relative to services China: rose from ~25% (1990s) to 28–30%+ during industrial boom South Korea: sustained 25–27% during export-led industrialisation Employment structure India: manufacturing employs ~11–12% of workforce; large informal share China/South Korea: manufacturing central to productivity & wage gains Wage dynamics in India Entry-level IT wages stagnant since early 2000s (real terms barely improved) Platform firms (Swiggy, Zomato, Ola, Blinkit) rely on labour-intensive, low-productivity models rather than technology-deepening Inequality signal Top-end wealth and corporate profits grew faster than median wage/productivity, indicating lop-sided growth. Dutch Disease  Originally used to study Netherlands’ 1959 Groningen gas discovery. Mechanism: Resource boom → higher wages & capital shift into booming sector Currency appreciation / price rise → imports cheaper, exports costlier Manufacturing becomes uncompetitive → stagnation or decline Extension to India (policy variant): Expansion of high-wage government sector → manufacturing cannot match wages at existing productivity Higher incomes raise domestic prices → real exchange-rate appreciation even without nominal rupee change Demand tilts toward cheaper imports, hurting local manufacturing. Critical Interpretation of the Argument Strengths of the hypothesis Explains factor-market distortion: skilled labour moves to safer, better-paid government jobs Clarifies link between wages, prices, competitiveness, and structural transformation Limitations Classic Dutch-disease arises from natural-resource windfalls, not deliberate wage policy Ignores why firms did not upgrade technology over time to sustain higher wages Public sector wages may be symptom, not core cause, of weak industrial policy and ecosystem gaps. Technology & Wage Question Induced-innovation theory (Habakkuk, Allen, Acemoglu) High wages → firms invest in automation, capital-biased technology → productivity & wage growth Seen in Germany, Japan, South Korea with labour scarcity India’s contrast Large labour reserves reduced incentive to automate Manufacturing became labour-absorbing but low-productivity, limiting wage growth Services growth did not diffuse productivity economy-wide. Structural Bottlenecks Beyond Wages Shallow export orientation vs. East Asian export discipline Weak firm size-upgrading (missing middle; dominance of micro-units) Patchy industrial policy and cluster-level support Low R&D intensity and technology adoption Logistics, power, and compliance frictions historically higher than peers. Policy Implications  Shift from labour-abundance reliance to technology-deep manufacturing Strengthen export-linked manufacturing clusters and scale-up pathways Invest in skills, automation readiness, design & R&D Reform wage-productivity linkages: raise productivity alongside wages, not suppress wages Leverage PLIs, supply-chain localisation, semiconductors, electronics, green manufacturing with stronger technology absorption. What is the Bureau of Port Security and its role? Why is it in news? The Centre has constituted the Bureau of Port Security (BoPS) as a statutory body under Section 13 of the Merchant Shipping Act, 2025 to strengthen port and coastal security amid rising maritime, smuggling, piracy, and cybersecurity threats. The move coincides with major reforms in India’s maritime governance — including the Indian Ports Act, 2025, Coastal Shipping Act, 2025, and Modernised Merchant Shipping Legislation, 2025 — aimed at modernising port regulation, improving security oversight, and supporting trade efficiency. Relevance GS-III: Internal Security & Infrastructure Port security architecture, cyber-maritime threats, anti-smuggling, trafficking control GS-II: Federalism & Regulation Centre–State powers, regulation of non-major ports, governance reforms What is the Bureau of Port Security (BoPS) and what is its role? Institutional design Statutory body under the Ministry of Ports, Shipping & Waterways Modelled on the Bureau of Civil Aviation Security (BCAS) Legal mandate to enforce International Ship and Port Facility Security (ISPS) Code and global security standards Core functions Single-point regulatory oversight & coordination across ports and ships Standardised security audits, risk assessments, certification & compliance CISF designated as Recognised Security Organisation (RSO) → prepares security plans, trains private & State port agencies Graded security implementation across major and non-major ports Cyber & intelligence role Dedicated division for cybersecurity of port IT/OT systems Collection & exchange of security intelligence; coordination with national cyber agencies Scope of threat coverage Maritime terrorism, smuggling (arms/drugs), human trafficking, illegal migration, poaching, piracy Digital intrusions & cyber-sabotage in port operations What challenges in coastal and port security does India face, and how will BoPS address them? Multi-agency fragmentation Roles split across Coast Guard, Navy, CISF, State Marine Police, Customs, Port Authorities → gaps in coordination Non-uniform standards Varied security protocols across major vs. non-major ports Rising maritime-crime footprint Increased drug & arms smuggling via sea routes, illegal migration, and grey-zone activities Cyber-vulnerability Growing digitisation of ports → exposure to ransomware, data breaches, navigation system tampering Trade scale-risk mismatch Rapid growth in cargo & port capacity outpacing legacy security frameworks How BoPS mitigates these ? Unifies command & oversight → reduces duplication and response delays Standardises security architecture across all ports via CISF-led plans Integrates intelligence & cyber defence within port systems Ensures continuous compliance with ISPS & international benchmarks Creates nationwide port-security ecosystem supporting trade + safety together Key Legislative Reforms (2025) Indian Ports Act, 2025 → replaces 1908 Act Modernises regulation, safety, environmental norms, port conservancy Aims to improve ease of doing business & sustainability Coastal Shipping Act, 2025 Simplifies licensing, boosts domestic coastal trade & Indian-flagged vessels Modernised Merchant Shipping Legislation, 2025 Aligns India with global maritime safety & operational standards BoPS Act / provisions (2025) Establishes statutory port-security regulator Maritime Growth — Data Signals Cargo handled: ↑ from 974 MMT (2014) → 1,594 MMT (2025) Port capacity: ↑ 57% (last decade) Ship turnaround time: ↓ to ~48 hours (≈ global benchmarks) Coastal shipping volumes: ↑ 118% Inland waterways cargo: ↑ from 18.1 MMT (2014) → 145.5 MMT (2025) (≈ 8x rise) Global recognition: 9 Indian ports in World Bank Container Port Performance Index What criticisms exist? Centralisation concerns Greater Union control over non-major (State-run) ports → termed a “silent cost to maritime federalism” by some States Procedural safeguards Powers of port, conservancy, and health officers for entry/inspection seen as broad, with unclear judicial guardrails Note: Critiques target the legislation & governance design, not the BoPS institution per se. Keezhadi — Flood-Burial & OSL Dating Study Why is it in news? A new study by researchers from the Physical Research Laboratory (PRL), Ahmedabad and the Tamil Nadu Department of Archaeology has used Optically Stimulated Luminescence (OSL) dating to determine when flood sediments buried parts of the Keezhadi settlement along the Vaigai river. The findings suggest that portions of the site were covered by flood-borne sediments roughly ~1,000 years ago, helping distinguish when people lived there from when nature buried the remains. The study was published in Current Science (October 25) and strengthens efforts to build a scientific timeline for the Keezhadi cultural landscape beyond literary references from the Sangam corpus. Relevance GS-I: Indian Culture / Archaeology Urban settlement archaeology, Sangam-era material culture GS-I & GS-III: Geography–Environment Interface River dynamics, floods, settlement relocation, late-Holocene climate context Facts & Data — Keezhadi Excavation Context Location: Keezhadi, Sivaganga district, Tamil Nadu — on the Vaigai floodplain. Excavations have revealed: Brick walls, channel-like drains, fine clay floors, pottery fragments Settlement layout suggesting urban planning, craft activity, and trade linkages Key research challenge: Sangam poems mention towns & trade, but lack precise chronology → archaeology + geoscience used to build timelines. What did the new study examine? Focus: Sediment layers covering the archaeological structures, not the bricks themselves. Hypothesis: Flooding events of the Vaigai deposited sand–silt–clay layers that buried the settlement remains. Goal: Date when burial occurred → infer damage/abandonment phases of the settlement. Method: Optically Stimulated Luminescence (OSL) Quartz grains accumulate energy from natural radiation while buried. Sunlight resets this clock when grains are exposed at the surface. In the lab, grains are stimulated with light → measured luminescence = time since last exposure → approximates time of burial. Study details: Four sediment samples from two pits (KDI-1, KDI-2) Samples extracted using light-tight metal tubes to prevent exposure. Result: OSL dates indicate flood-deposit burial ~1,000 years ago (late Holocene phase). Climate & River Dynamics  The late Holocene climate in South India shows wet–dry fluctuations and river course shifts. The Vaigai today flows a few kilometres away from the mound → supports long-term channel migration. Implication: Floods + course shifts may have damaged infrastructure disrupted water access triggered abandonment or relocation of settlements. Why the finding matters (Archaeological Significance)? Differentiates two timelines: Period of habitation vs. period of environmental burial Provides a process-based narrative: settlements respond to hydrological hazards, not only political decline. Guides future excavations: variable sediment thickness across pits suggests differential preservation of older layers. Limits & Scope of Interpretation OSL dates the burial sediments, not the construction age of structures. Does not prove modern-type climate change → indicates long-term fluvial processes. Requires integration with ceramic typology, carbon dates, cultural layers, and stratigraphy. ISRO LVM-3 — 6-tonne US Satellite Launch Why is it in news? ISRO’s LVM-3 (Launch Vehicle Mark-3) successfully placed the 6,000-kg US communications satellite “BlueBird Block-2” into orbit — the heaviest foreign satellite ever launched by India. This was LVM-3’s third consecutive commercial mission under NewSpace India Ltd (NSIL), reinforcing India’s position in the global heavy-lift launch market and demonstrating reliability after its role in Chandrayaan-3. Relevance GS-III: Science & Technology / Space Sector Heavy-lift capability, cryogenic tech, commercial launch ecosystem Core Facts & Data  Launch vehicle: LVM-3 (GSLV-Mk III) – India’s heavy-lift rocket Payload mass: ~6,000 kg (heaviest satellite launched by ISRO to date) Payload customer: U.S. AST SpaceMobile Orbit: Near-equatorial LEO for direct-to-mobile broadband constellation Mission profile: Satellite released ~21 km lower than target orbit → onboard propulsion to raise orbit Commercial arm involved: NSIL Earlier LVM-3 high-value missions: Chandrayaan-3 (2023) OneWeb constellation launches — 72 satellites placed in orbit across two missions About LVM-3 Class: Heavy-lift, 3-stage launcher Stage 1: Two S200 solid strap-on boosters Stage 2: L110 liquid core stage Stage 3: C25 cryogenic upper stage (LOX + LH₂) Lift capability GTO: ~4–5 tonnes LEO: 8–10 tonnes (mission-dependent) Designed as India’s workhorse for deep-space & heavy satellites What makes this mission significant?  Market Positioning Demonstrates India’s entry into the heavy-satellite launch segment, competing with SpaceX Falcon-9, Ariane-5/6 Cost-competitiveness advantage LVM-3 offers lower launch costs than Western providers → boosts commercial demand Technology credibility Repeated success = higher global customer confidence in ISRO/NSIL Strategic signalling Enhances India’s role in satellite broadband constellations & dual-use space markets About the Payload — BlueBird Block-2   Purpose: Direct-to-mobile satellite broadband connectivity (no ground towers needed) Use-cases Remote-area coverage, disaster communications, maritime connectivity Constellation vision: Global space-based mobile network (competes with Starlink variants) India’s Commercial Launch Trajectory — Evidence ISRO commercial launches (last decade): ~45 missions Shift toward LEO broadband constellations — OneWeb + BlueBird NSIL contract portfolio expanding → growth in global launch services exports Broader Strategic Relevance  Space economy expansion → supports Make in India + export revenues Private–public ecosystem integration (NSIL, IN-SPACe, startups) Strengthens technological sovereignty in heavy-lift & cryogenic capability Supports ambitions in Gaganyaan crewed missions & deep-space exploration Challenges & Next-Step Priorities Fleet cadence & capacity — increase launch frequency for competitiveness Reusability roadmap — RLV/Next-gen launchers to cut costs further Global competition pressure from SpaceX rideshare pricing Supply-chain deepening — domestic ecosystem for engines, avionics, composites Only 1 in 4 marginal farmers in India linked to cooperatives, report finds Why is it in news? The State of Marginal Farmers in India 2025 report by the Forum of Enterprises for Equitable Development (FEED) — released on Kisan Diwas (Dec 23, 2025) — finds that less than 25% of marginal farmers are active members of agricultural cooperatives, despite marginal farmers constituting ~60–70% of India’s agricultural households. The report assesses cooperative access and outcomes across six states — Andhra Pradesh, Bihar, Himachal Pradesh, Maharashtra, Tripura, and Uttarakhand — and highlights structural exclusion, digital divides, and gender gaps within the cooperative ecosystem. Relevance GS-III: Agriculture, Inclusive Growth, Rural Institutions Role of PACS, credit access, service-hub model, livelihood outcomes GS-II: Social Justice / Participation Gaps Gender exclusion, digital divide, elite capture, governance capacity Key Facts & Data — Who are marginal farmers? Definition: Own < 1 hectare of land. Share in agrarian structure: 60–70% of farm households; backbone of smallholder agriculture. Yet only ~1 in 4 are cooperative members — signalling weak institutional inclusion. Role of Cooperatives & PACS — Why they matter ? Primary Agricultural Credit Societies (PACS) = lowest tier of the cooperative system; closest interface for rural households. Provide credit, input supply, procurement & marketing channels, and increasingly digital/public services (PDS, e-governance links). Function as rural service hubs in several states → linked to better livelihood outcomes. What the report finds ? — Evidence from Six States Low participation especially in Bihar, Tripura, Himachal Pradesh. Barriers to inclusion Complex membership procedures & documentation Long distances to PACS and weak last-mile presence Limited working capital → low service reliability Persistent social exclusion (caste, class, gender) Consequences Higher dependence on informal credit/markets Slower income growth, higher vulnerability to climate & price shocks Digital Divide — Facts Tripura: 77.8% cooperatives use no digital tools Bihar: 25% cooperatives report zero digital adoption Digital use largely informational, not transformational Women & older farmers face skill constraints, limiting benefits. Gender & Leadership Gaps Women members registered: 21.25 lakh (2.125 million) Women directors on cooperative boards: 3,355 → very low leadership conversion Barriers: restrictive norms, mobility limits, unpaid care burden → decision-making remains male-dominated. Where access exists — Impact is measurable ? Income outcomes 45% cooperative-linked marginal farmers report income increase ~21% report decline/stagnation Livelihood security 49% members report improved security; ~16% remain insecure Financial inclusion 67% members access credit/financial services via cooperatives Productivity 42% report improved crop yields; 22.5% report decline States with PACS as integrated service centres show stronger positive outcomes. Why are marginal farmers excluded? Institutional design gaps: procedures, documentation, capital constraints Geographical inequity: uneven spread of PACS, long travel costs Social hierarchies: elite capture, weak voice for women & marginal groups Capability deficit: limited digital literacy, low management capacity Policy-practice gap: cooperative reforms focus on scale, not inclusion. Policy Relevance  Strengthen last-mile cooperative presence in low-coverage districts Simplify membership & governance norms; ensure grievance & transparency Capital infusion + professionalisation of PACS operations Targeted digital capacity-building, especially for women & elderly farmers Promote integrated PACS (credit + inputs + procurement + services) to maximise impact. Large share of India’s PM2.5 not emitted directly, but chemically formed in the atmosphere: CREA Study Why is it in news? A new analysis by the Centre for Research on Energy and Clean Air (CREA) finds that a large share of India’s PM2.5 pollution is not directly emitted, but is chemically formed in the atmosphere from precursor gases, especially sulphur dioxide (SO₂) from coal-based power plants. The study shows that up to 42% of India’s PM2.5 is secondary particulate matter, mainly ammonium sulphate, and warns that unless India targets SO₂ and other precursor emissions, air-quality gains under NCAP will remain limited and short-lived. Relevance GS-III: Environment / Air-Pollution Governance Secondary PM2.5, SO₂ control, coal-power emissions, NCAP strategy gaps GS-III: Energy–Environment Trade-offs FGD policy, precursor-gas regulation, public-health externalities Key Facts & Data — PM2.5 Composition in India Share of secondary PM2.5 (national): up to 42% — predominantly ammonium sulphate Primary precursor: SO₂ → reacts with ammonia & atmospheric oxidants → secondary sulphate aerosols India = world’s largest SO₂ emitter ~60% of national SO₂ emissions from coal-fired power plants FGD policy gap: ~78% of coal plants exempted from installing Flue Gas Desulphurisation (FGD) → weak SO₂ control at source State-level Evidence (CREA assessment using NASA MERRA-2, 2024) Highest ammonium sulphate contribution Chhattisgarh — 42% Odisha — 41% Across states: ammonium sulphate = 17–42% of PM2.5 mass Most states cluster at 30–40% annually Seasonal profile (pan-India) Winter: 31–52% of PM2.5 Post-monsoon: 27–53% Summer: 11–36% Monsoon: 4–26% ➝ Secondary PM remains significant year-round, and dominant in polluted months. Delhi Case Study — What drives severe episodes? ~33% of Delhi’s annual PM2.5 = secondary ammonium sulphate Seasonal dominance: Post-monsoon: 49% of PM2.5 Winter: 41% Summer/Monsoon: ~21% Episodes are driven largely by regional SO₂ plumes + secondary formation, not only local primary emissions. What the findings imply ? PM2.5 challenge ≠ just road dust / primary emissions Secondary particulate matter is a core driver, not a marginal factor. Coal-power SO₂ controls are pivotal FGD exemptions undermine health & NCAP outcomes States with dense thermal clusters show highest secondary sulphate loads Policy–monitoring gap Current strategies emphasise PM10 & visible dust sources Chemical composition & precursor gases (SO₂, NO₂, NH₃) remain under-regulated. CREA’s Policy Message (Evidence-linked) Reinstate mandatory FGD installation across all coal-based TPPs Integrate precursor-gas reduction targets in NCAP revision Expand speciated PM monitoring (sulphate, nitrate, ammonium) alongside mass concentration Coordinate regional emission controls during winter/post-monsoon high-risk periods. What is Secondary PM2.5? Primary PM2.5: emitted directly (dust, combustion soot, vehicle exhaust) Secondary PM2.5: forms in the atmosphere when gaseous precursors react: SO₂ → sulphates (ammonium sulphate) NOx → nitrates NH₃ (agriculture, waste) → reacts with SO₂/NOx aerosols Secondary particles are finer, more toxic, and travel long distances → regional pollution episodes.