Climate scenarios are indispensable for exploring future development pathways and informing robust mitigation strategies. However, the rapid expansion of climate change research and increasingly complex integrated assessment methods have created a vast and fragmented landscape of scenario information, much of which remains locked in unstructured textual descriptions. This study introduces the Global Climate Scenario Narratives (GCSN), a comprehensive repository developed through a hybrid machine learning and large language model (LLM) framework. By systematically mining approximately 90,000 peer-reviewed articles, the GCSN identifies and structures over 50,000 distinct scenario narratives across diverse temporal and spatial scales. Unlike traditional numerical datasets, GCSN focuses on the qualitative logic and policy settings that underpin climate projection. With its multi-dimensional classification and transparent architecture, GCSN serves as a foundational reference resource that facilitates cross-study scenario comparison, enhances policy-relevant synthesis, and provides a structured knowledge base for the next generation of climate change research.
India is the third-largest emitter of greenhouse gases and a developing nation whose per-capita GDP is about one-fifth of the global average. To implement the Paris Agreement, India must reconcile its economic ambitions—defined by the Viksit Bharat vision of reaching high-income status—with climate action. Moving beyond standard “middle-of-the-road” (SSP2) growth assumptions, this study presents a novel mitigation scenario using the REMIND integrated assessment model calibrated to a high-growth trajectory (6.2% annual GDP growth over 2025-2050). We compare a Current Policy baseline with a Net-zero scenario (NZ2070) aligned with India’s 2070 net-zero target. In the NZ2070 pathway, emissions peak around 2035 at 4.2 Gt CO2/yr (12.5% above 2025 levels) before declining. Decarbonization hinges on a massive expansion of renewable electricity (generation 8.3 PWh or 84% of total electricity by 2050), a managed phase-down of unabated coal power (peaking at 293 GW in 2030), and extensive electrification. Green hydrogen and biomass emerge as critical solutions for hard-to-abate sectors post-2045. While near-term abatement costs are modest, achieving net-zero requires an implicit carbon price of $429/tCO2 by 2070. Our results demonstrate that India can approach high-income levels while meeting its climate goals, provided near-term investments, amounting to an additional 1.4% of GDP annually (∼$175 billion/yr through 2050) in energy supply sectors, are consistently aligned with long-term targets. This pathway offers a technically rigorous, net-zero-consistent benchmark for assessing India’s recently submitted 2035 Nationally Determined Contribution, and indicates scope to strengthen its near-term ambition.
Transitioning from fossil fuel-based to renewable energy (RE) generation is critical for meeting climate goals but entails major social and economic challenges across the coal–thermal value chain, including job losses, asset stranding, and revenue disruptions. Existing research largely focuses on technical, financial, or environmental aspects, with little attention to these social and economic costs, and no established way to integrate them into formal energy system models. This study proposes a novel and mathematically tractable framework that classifies social and economic impacts as ‘capital stranding’ per MW of prematurely retired coal capacity and ‘operational stranding’ per kWh of avoided thermal generation. Such classification is designed to enable future inclusion of these costs directly into energy planning models (typically large-scale optimisation models), filling a key gap in current approaches. We apply the framework to Karnataka’s electricity system for 2020, a particularly relevant case as the state has aggressively integrated RE into its grid. While our findings are Karnataka-specific, the framework is adaptable and can be extended to other regions with appropriate datasets, which forms the basis of our ongoing research. By embedding socio-economic concerns into technical planning, this work provides policymakers with tools to design just and inclusive transition strategies that minimize disruptions while advancing sustainability.
Anthropogenic methane emissions are adversely impacting the global climate. Among the anthropogenic sources, oil and gas sectors are significant contributors to the atmospheric methane budget. Effectively controlling methane emissions from oil and gas installations requires precise quantification of their emission levels. However, in the Indian context, data on methane emissions or concentrations over oil and gas installations are still inadequate for comparison with the global level. The present study reports methane concentration levels over 54 upstream oil and gas facilities covering three major onland hydrocarbon-producing basins of India – the Cambay Basin, the Krishna-Godavari (K-G) Basin and the Assam-Arakan Fold Belt (AAFB). We utilized TROPOspheric Monitoring Instrument (TROPOMI) data to retrieve atmospheric methane concentrations over the oil and gas sites for the period April 2024 to March 2025. The study reveals a gradual increase in atmospheric methane concentrations across all installations during the monitoring period. The annual average methane levels observed over the facilities range from 1900 to 1964 ppb, with an overall mean of 1935 ppb, which is slightly higher than the local and global background values. Seasonal variations in atmospheric methane concentrations in the form of monsoon minima, post-monsoon maxima and winter highs are evident across all the installations. Geographically, methane concentrations are highest over the facilities of AAFB Basin, followed by the Cambay Basin, with the minimum in the K-G Basin. The study concludes that, in general, methane concentrations over the studied upstream oil and gas installations are not significantly high. However, many of the facilities necessitate greater operational controls to reduce the observed concentrations. The study is expected to lay the groundwork for emission quantification from India’s oil and gas sector and help achieving the goal of net-zero emissions.
