Evaluating climate shifts and drought regions in the central Indian river basins.

Climate change, characterized by erratic rainfall patterns and rising temperatures, is enhancing the severity and intensity of drought across India. Considering this impact, assessment of these changes is critical for developing effective adaptation and mitigation strategies. This study employs a stochastic entropy-based approach to compute the inter- and intra-annual rainfall variability for multiple temporal scales.

Water policy review: Ensuring sustainable water management for India.

Water policy legislation is pivotal in shaping water management in countries like India, focusing on clean drinking water and sanitation. Challenges of aging infrastructure, pollution, climate change, and resource limitations persist. Sustainable water management and international cooperation can address these issues.

Relationship between daily precipitation extremes and temperature in changing climate across smart cities of Central India.

The Central India region is observing a rise in extreme precipitation events. Its impact is enhanced across the urban regions due to their higher population and economic potential. In this study, we assessed the historical (1951-2022) Clausius Clapeyron relation between daily precipitation extremes (P) with daily maximum temperature (T) and dew point (DPT) for ten smart cities of Central India.

Spatio-temporal analysis of extreme air pollution and risk assessment.

Extreme air pollution poses global health and environmental threats, necessitating robust policy interventions. This study first analyses the surface mass concentration of major aerosols (such as black carbon, organic carbon, dust, sea salts, and sulphates) to estimate global PM concentrations from 1980 to 2023. The developed model-estimated PM database was validated against data from 526 cities worldwide, showing strong accuracy, with RMSE, r, and R values of 7.

Transforming air pollution management in India with AI and machine learning technologies.

A comprehensive approach is essential in India's ongoing battle against air pollution, combining technological advancements, regulatory reinforcement, and widespread societal engagement. Bridging technological gaps involves deploying sophisticated pollution control technologies and addressing the rural-urban disparity through innovative solutions. The review found that integrating Artificial Intelligence and Machine Learning (AI&ML) in air quality forecasting demonstrates promising results with a remarkable model efficiency.

Transboundary hazard and downstream impact of glacial lakes in Hindu-Kush Karakoram Himalayas.

Glacial Lake Outburst Floods (GLOFs) can generate catastrophic flash floods when the damming structure is breached or overtopped. Some of these glacial lakes are located in transboundary regions where floods originating from the lake in one country could inundate a neighboring country, devastating the population and infrastructure of both nations and influencing socio-political relationships. Therefore, assessing the lakes' hazard is crucial.

Characterizing the spatio-temporal distribution, detection, and prediction of aerosol atmospheric rivers on a global scale.

Aerosol Atmospheric Rivers (AARs) are elongated and narrow regions that carry high concentrations of aerosols (tiny particles suspended in the atmosphere) across large distances, exerting effects on both air quality and human health (Chakraborty et al., 2021, 2022). Monitoring and modeling these aerosols present distinct challenges due to their dynamic nature and complex interactions within the atmosphere.

Spatiotemporal-based automated inundation mapping of Ramsar wetlands using Google Earth Engine.

Wetlands are one of the most critical components of an ecosystem, supporting many ecological niches and a rich diversity of flora and fauna. The ecological significance of these sites makes it imperative to study the changes in their inundation extent and propose necessary measures for their conservation. This study analyzes all 64 Ramsar sites in China based on their inundation patterns using Landsat imagery from 1991 to 2020.

Heat waves characteristics intensification across Indian smart cities.

Indian cities have frequently observed intense and severe heat waves for the last few years. It will be primarily due to a significant increase in the variation in heat wave characteristics like duration, frequency, and intensity across the urban regions of India. This study will determine the impact of future climate scenarios like SSP 245 and 585 over the heat wave characteristics.

Understanding non-stationarity of hydroclimatic extremes and resilience in Peninsular catchments, India.

Climate change significantly impacts the global hydrological cycle, leading to pronounced shifts in hydroclimatic extremes such as increased duration, occurrence, and intensity. Despite these significant changes, our understanding of hydroclimatic risks and hydrological resilience remains limited, particularly at the catchment scale in peninsular India. This study aims to address this gap by examining hydroclimatic extremes and resilience in 54 peninsular catchments from 1988 to 2011.

A study of thyroid profile in patients suffering from the first episode of mania: A cross-sectional study.

Background: Thyroid function is commonly considered in the assessment of mood disorders. Reports of thyroid dysregulation in patients with mania are associated with several confounding factors. To eliminate confounding factors, studies of first-episode mania are desirable.

A novel analysis of COVID 19 risk in India incorporating climatic and socioeconomic Factors.

This study investigates the influence of climate variables (pressure, relative humidity, temperature and wind speed) in inducing risk due to COVID 19 at rural, urban and total (rural and urban) population scale in 623 pandemic affected districts of India incorporating the socioeconomic vulnerability factors. We employed nonstationary extreme value analysis to model the different quantiles of cumulative COVID 19 cases in the districts by using climatic factors as covariates. Wind speed was the most dominating climatic factor followed by relative humidity, pressure, and temperature in the evolution of the cases.

Assessment of Risk and Resilience of Terrestrial Ecosystem Productivity under the Influence of Extreme Climatic Conditions over India.

Analysing the link between terrestrial ecosystem productivity (i.e., Net Primary Productivity: NPP) and extreme climate conditions is vital in the context of increasing threats due to climate change.

Assessment of the impacts of climatic variability and anthropogenic stress on hydrologic resilience to warming shifts in Peninsular India.

Most parts of the world are witnessing climatic warming and the trend is expected to increase in the future. It is important to assess the response of watershed hydrology to this warming. Moreover, human interactions and climatic variability influence the water balance of a catchment.

Diagnosing climate change impacts and identifying adaptation strategies by involving key stakeholder organisations and farmers in Sikkim, India: Challenges and opportunities.

Narrowing the gap between research, policy making and implementing adaptation remains a challenge in many parts of the world where climate change is likely to severely impact water security. This research aims to narrow this gap by matching the adaptation strategies being framed by policy makers to that of the perspectives of development agencies, researchers and farmers in the Himalayan state of Sikkim in India. Our case study examined the perspectives of various stakeholders for climate change impacts, current adaptation strategies, knowledge gaps and adaptation barriers, particularly in the context of implementing the Sikkim State Action Plan on Climate Change through semi-structured interviews carried out with decision makers in the Sikkim State Government, researchers, consultants, local academia, development agencies and farmers.

Assessment of ecosystem resilience to hydroclimatic disturbances in India.

Recent studies have shown an increasing trend in hydroclimatic disturbances like droughts, which are anticipated to become more frequent and intense under global warming and climate change. Droughts adversely affect the vegetation growth and crop yield, which enhances the risks to food security for a country like India with over 1.2 billion people to feed.

Plexiform Angiomyxoid Myofibroblastic Tumor (PAMT) of Stomach with Synchronous Bilateral Cystic Ovarian Neoplasms, a Rare Case Presentation.

Plexiform Angiomyxoid Myofibroblastic Tumor (PAMT) is a recently identified mesenchymal tumor of the stomach, which was first described in the year 2007 and was added in the 2010 WHO classification of tumors of the digestive system World J Gastroenterol 16(6): 2835-2840, 2010. It closely resembles with other gastric tumors but distinctly varies in clinical management as well as the histopathology. We had a 51 year, female patient, laborer by profession with low socio economic status, who had abdominal pain with vomiting since 6 months.

Application of artificial neural network, fuzzy logic and decision tree algorithms for modelling of streamflow at Kasol in India.

The prediction of streamflow is required in many activities associated with the planning and operation of the components of a water resources system. Soft computing techniques have proven to be an efficient alternative to traditional methods for modelling qualitative and quantitative water resource variables such as streamflow, etc. The focus of this paper is to present the development of models using multiple linear regression (MLR), artificial neural network (ANN), fuzzy logic and decision tree algorithms such as M5 and REPTree for predicting the streamflow at Kasol located at the upstream of Bhakra reservoir in Sutlej basin in northern India.

Fate of pharmaceutical compounds in hydroponic mesocosms planted with Scirpus validus.

A systematic approach to assess the fate of selected pharmaceuticals (carbamazepine, naproxen, diclofenac, clofibric acid and caffeine) in hydroponic mesocosms is described. The overall objective was to determine the kinetics of depletion (from solution) and plant uptake for these compounds in mesocosms planted with S. validus growing hydroponically.

Applying Fuzzy logic and the point count system to select landfill sites.

The treatment of solid waste is currently one of the major environmental problems facing municipalities. Thousands of tonnes of waste are generated each day, requiring a large area for disposal purposes. It is difficult to find suitable areas for the construction of such sanitary landfills as numerous criteria must be met, and landfill sites vary considerably in terms of their sophistication.