Research Papers

Enhancing wind energy forecasting in India: A site-specific comparative analysis of machine learning models and Weibull statistics using long-term data

Yadav Harendra Kumar , Chakraborty Somyajit , Gupta Mohan Narayan , Bhattacharjee Anurag , Yadav Siddhita , Sanyal Aaditya Pratap, Sarkar Jahar, Sarkar Arnab

| 2025

The global pursuit of clean and sustainable energy has elevated wind power as a vital renewable resource. Yet, its inherent variability poses significant challenges for integration into smart grids, where precise forecasting is crucial for grid stability and efficient energy management. Traditional statistical methods often fail to capture the nonlinear dynamics of wind, especially across diverse geographies.

Regulatory Players in Mycorrhizal‐Bacterial‐Plant Interactions

PA Madhuja , Iyer Karan , Koul Vatsala , Kochar Mandira

| 2025

Mycorrhizae contribute significantly for plant growth and development, often providing nutrients such as phosphate and nitrogen, while also enhancing stress tolerance and resistance against phytopathogens. Plant symbiotic mycorrhizal networks harbor bacterial communities that aid mycorrhizal functions and augment plant nutrition and development. Various bacterial associations of mycorrhiza bring forth advantageous traits to mycorrhizal symbiosis and host colonization, which involves a wide range of signaling and regulatory molecules.

Financing India's Decarbonisation Journey – the Role of Private Investment for Mitigation

Shankar Ajay

| 2025

Carbon finance has been moving to the centre of global discussions on climate change. The reality of the impending disaster from global warming is generating a sense of urgency in global elites. At the Conference of Parties in Paris, countries agreed that the rise in global temperatures had to be restricted to 1.5 degrees (UNFCCC, n.d). However, actions to reduce carbon emissions have been inadequate. As a result, this may no longer be feasible.

Advancing Diagnostics for Xanthomonas oryzae pv. oryzae: Challenges and Future Directions

Jain Raghav , Kochar Mandira , Dubey Mukul Kumar , Sharma Shayam Sundar , Yang Wenrong , Cahill David

| 2025

Xanthomonas oryzae pv. oryzae (Xoo) is a widespread bacterial pathogen in rice with worldwide implications. This pathogen causes bacterial blight in rice and is a concern for global food security, causing up to 50% yield loss. This review provides a comprehensive analysis of Xoo, including its global distribution, disease cycle, and current management strategies, while critically evaluating the limitations of existing diagnostic methods. By focusing on Xoo, the paper addresses a gap in research that mostly focuses on the wider Xanthomonas genus.

Bioeconomic Potential of Agro-residues: Agrotextiles in India

Kaushik Vanshika, Pawar Parikshit Abhimanyu , Wali Syed Arif , Sharma Jitendra Vir

| 2025

India, an agrarian economy, generates over 650 million tonnes of agro-residues annually, much of which remain underutilized, leading to environmental pollution and resource loss. Effective management of this biomass presents opportunities for bioeconomic applications, including biogas, bio-composites, fodder, fertilizers, and fibre-based products. Technological advancements have enabled the repurposing of agro-residues into sustainable agrotextiles, such as mulch mats and harvesting nets, fostering rural economic growth while reducing environmental impact.

Hydrogen Rotary Kilns for Ironmaking in India

Will Hall, Abhinav Bhaskar, Mårten Görnerup

| 2025

India’s iron and steel sector faces a significant challenge in decarbonizing over the coming decades, necessitating new technological solutions. A unique hurdle is India’s vast sector of small-scale sponge iron producers, who largely rely on coal-based rotary kilns to produce direct reduced iron (DRI).

The paper, ‘Hydrogen Rotary Kilns for Ironmaking in India: A novel solution for decarbonizing small-scale ironmaking,’ outlines a promising technological route for this segment of the industry.

Towards Earthquake Predictability: A Seismo-Ionospheric Approach Using TEC Anomalies and ARIMA Forecasting

Majumder Madhuparna , Ketholia Yateesh , Ghosh Sayanta

| 2025

Earthquakes have always been a permanent threat to humanity. Monitoring the earthquake precursors using space-based methods can be a new introduction to earthquake studies. The promising analysis of the earthquake precursors such as Ionospheric Perturbations is based on the detection of Ionospheric electron content. Within approximately 3 weeks before an event, negative TEC anomalies have been witnessed.

Promoting an Enhanced Learning About Environment Through a Whole-school Approach and Non-formal Education Tools: A Case Study of GREEN Olympiad

Kahlon Livleen K, Mehta Taru, Barua Monmi , Kazi Saltanat M. , Das Ravi S., Bhushan Kashish

| 2025

Holistic education empowers learners with a transformative impact and improves their living conditions by enhancing their core competencies. A project-based learning approach helps to further facilitate environmental improvement initiatives at individual and institutional levels through a whole-school approach, ensuring sustainability and contributing to measurable results. GREEN Olympiad is a step in this direction and an example of a programme transcending towards education for sustainable development goals.

GREEN Olympiad: A Case Study to Augment Learning through Non-formal Education

Mehta Taru , Kahlon Livleen K

| 2024

With an increase in human aspirations and urbanization, development is happening at a largely unsustainable pace. Hope still resides in the power of education to offset unsustainable actions by promoting Environmentally Responsible Behaviour (ERB) amongst our younger citizenry. ERB can put knowledge into practice, thereby ensuring sustainable environments, healthy communities, and social cohesion. Through programmes like GREEN Olympiad, students are sensitized to enhance their knowledge levels and pave the way to become environment-conscious citizens.

GIS & Machine Learning Based Approaches to Assess Forest and Biodiversity Vulnerability Under Climate Stress: A Case Study from Assam, India

Ghosh Sayanta

| 2025

The study presents an integrated geospatial and machine learning framework to assess forest and biodiversity vulnerability in Assam, India, under projected climate stress scenarios. Using multi-source remote sensing datasets and climate variables, the work applies GIS-based spatial modeling and machine learning algorithms to identify climate hotspots, evaluate forest resilience, and highlight biodiversity-rich yet highly vulnerable landscapes.