Search Results (347)

This study explores the interplay of climate vulnerability and social capital in two rural communities: Brajaballavpur, a high-climate-prone village in the Indian Sundarbans characterized by high ecological fragility, recurrent cyclones, and saline water intrusion affecting water access, livelihoods, and infrastructure; and Jemua, a low-climate-prone village in the land-locked district of Paschim Bardhaman, West Bengal, India, with no extreme climate events. A total of 85 participants (44 in Brajaballavpur, 41 in Jemua) were selected through purposive sampling. Using a comparative qualitative research design grounded in ethnographic fieldwork, data were collected through household interviews, Participatory Rural Appraisals (PRAs), Focus Group Discussions (FGDs), and Key Informant Interviews (KIIs), and analyzed manually using inductive thematic analysis. Findings reveal that bonding and bridging social capital were more prominent in Brajaballavpur, where dense horizontal ties supported collective action during extreme weather events. Conversely, linking social capital was more visible in Jemua, where participants more frequently accessed formal institutions such as the Gram Panchayat, local NGOs, and government functionaries that facilitated grievance redressal and information access, but these networks were concentrated among more politically connected individuals. The study concludes that climate vulnerability shapes the type, strength, and strategic use of social capital in village communities. While bonding and bridging ties are crucial in high-risk contexts, linking capital plays a critical role in enabling long-term social structures in lower-risk settings. The study contributes to both academic literature and policy design by offering a relational and place-based understanding of climate vulnerability and social capital. Full article

Fluctuating weather patterns challenge renewable energy stability in microgrids, making accurate load forecasting essential. This study focuses on power load forecasting in rural microgrids in the Diamond Harbour sector of Kolkata, India. The current research proposes long short-term memory for weather prediction and artificial neural networks for load forecasting under different climatic conditions. The result shows higher prediction accuracy (R²: 0.8852, MSE: 0.0043), outperforming GRU, SVM, ARIMA, and SARIMA, contributing to Sustainable Development Goals 7 and 13, which is essential for a sustainable and resilient power supply. Full article

The Ganga River, a lifeline for millions and a critical freshwater ecosystem, is under threat from escalating plastic pollution driven by widespread usage and inadequate disposal practices. While marine ecosystems have garnered extensive research attention, freshwater systems—particularly in the Global South—remain underexplored, leaving critical gaps in understanding plastic pollution’s sources and pathways. Addressing these gaps, the study documents the prevalence and typology of plastic debris in urban and underexplored rural communities along the Ganga River, India, aiming to suggest mechanisms for a reduction in source-based pollution. A stratified random sampling approach was used to select survey sites and plastic debris was quantified and categorised through transect surveys. A total of 37,730 debris items were retrieved, dominated by packaging debris (52.46%), fragments (23.38%), tobacco-related debris (5.03%), and disposables (single-use plastic cutleries) (4.73%) along the surveyed segments with varying abundance trends. Floodplains displayed litter densities nearly 28 times higher than river shorelines (6.95 items/m² vs. 0.25 items/m²), with minor variations between high- and low-population-density areas (7.14 items/m vs. 6.7 items/m²). No significant difference was found between rural and urban areas (V = 41, p = 0.19), with mean densities of 0.87 items/m² and 0.81 items/m², respectively. Seasonal variations were insignificant (V = 13, p = 0.30), but treatment sites displayed significant variance (Chi² = 10.667, p = 0.004) due to flood impacts. The findings underscore the urgent need for tailored waste management strategies integrating industrial reforms, decentralised governance, and community-driven efforts. Enhanced baseline information and coordinated multi-sectoral efforts, including Extended Producer Responsibility (EPR), are crucial for mitigating plastic pollution and protecting freshwater ecosystems, given rivers’ significant contribution to ocean pollution. Full article

The lack of proper integration of inclusive design, accessibility standards, and universal design principles into urban planning has resulted in public open spaces that exclude many individuals, particularly those with disabilities or other marginalized groups. Integrating these principles is essential to create environments that are accessible, equitable, and beneficial for all individuals, regardless of their abilities, backgrounds, or socioeconomic status. To address this gap, this study analyzes existing research on universal design and accessibility standards to identify challenges and opportunities in the design of inclusive public open spaces. This systematic review seeks to critically explore how the application of universal design principles and accessibility standards supports the creation of inclusive public open spaces. Although universal design focuses on physical accessibility, inclusion in public spaces entails a more complex web of spatial, social, and policy factors. This research systematically evaluates international literature to determine key gaps, best practices, and action-oriented policy and design recommendations. The scope is situated within the Global South, particularly India, to align with the paper’s geographical focus. The findings emphasize that robust enforcement structures, contextual adjustments, and global standards are crucial for the successful implementation of universal design and accessibility integrated with inclusive design. This integration must begin at the initial stages of the design process and be maintained throughout planning, construction, management, and operation. The study further highlights the importance of stakeholder involvement as a critical component at every stage of the design and implementation process. It underscores the need for tailored strategies for urban spaces that incorporate cultural, regional, and socioeconomic characteristics. Additionally, the study highlights the potential of technology and innovation, such as digital accessibility tools and smart city efforts, to improve inclusivity. Finally, the study proposes future research directions, including the impact of inclusive design on social cohesion, the challenges faced in rural and peripheral areas, and the role of modern technology in enhancing public open space design. Full article

Background: Chronic kidney disease (CKD) significantly affects health-related quality of life (HRQoL), impacting physical and mental well-being. This study aimed to identify the key determinants influencing HRQoL among patients with CKD. Methods: A cross-sectional observational study was conducted from July 2022 to March 2023 at the Rajiv Gandhi Cooperative Multi-Specialty Hospital, Palakkad, Kerala, South India, including 154 patients diagnosed with CKD stages 3 to 5. Eligible participants were required to be at least 18 years of age and have a confirmed diagnosis of CKD, specifically stages 3 to 5, with prior treatment. CKD stages were defined according to the Kidney Disease: Improving Global Outcomes (KDIGO) 2012 guidelines, based on estimated glomerular filtration rate (eGFR) thresholds as follows: Stage 3 (eGFR 30–59 mL/min/1.73 m²), Stage 4 (eGFR 15–29 mL/min/1.73 m²), and Stage 5 (eGFR < 15 mL/min/1.73 m²). Participants were classified into stages based on their most recent stable eGFR value at the time of recruitment. HRQoL was assessed using the European Quality of Life-5 Dimensions-3 Levels (EQ-5D-3L) questionnaire. Chi-square, ANOVA, and multivariate regression were used to analyze associations with EQ-5D-3L domains. Results: Out of 154 participants, 68.8% were male, 91.6% were aged over 50 years, and 63.6% were from rural areas. Most had primary education (55.2%) and were unemployed, retired, or housewives (66.2%). As CKD progressed, comorbidities, particularly diabetes mellitus and coronary artery disease (CAD), increased, with Stage 5 showing the highest prevalence. Clinical markers showed significant declines in the glomerular filtration rate (GFR) (Stage 3: 49.16 ± 7.59, Stage 4: 22.37 ± 3.88, Stage 5: 8.79 ± 1.68) and hemoglobin (Stage 3: 10.45 ± 0.84, Stage 4: 8.88 ± 0.60, Stage 5: 7.12 ± 0.53) and an increase in serum creatinine (Stage 3: 1.72 ± 0.40, Stage 4: 3.21 ± 0.44, Stage 5: 7.05 ± 1.46). HRQoL assessments showed significant declines in mobility, self-care, usual activities, pain, and anxiety/depression with advancing CKD. Mobility issues increased from 61.2% in Stage 3 to 62.0% in Stage 5, with greater difficulties in self-care and usual activities at Stage 5. Pain and anxiety/depression worsened across stages. Multivariate analysis identified female gender, older age (≥50 years), lower education, unemployment, multiple comorbidities, smoking, lack of social support, and advanced CKD stages as significant factors linked to impaired HRQoL. CKD stage 5 (GFR < 29 mL/min/1.73 m²) and high serum creatinine (>1.2 mg/dL) were associated with significantly higher odds of impairment in all HRQoL domains. Conclusions: This study highlights that factors such as female gender, older age, lower education, unemployment, multiple comorbidities, smoking, advanced CKD stages, and high serum creatinine levels are associated with reduced quality of life in CKD patients. Conversely, social support acts as a protective factor. The findings emphasize the need for targeted interventions that address both medical care and psychosocial aspects, including lifestyle changes, patient education, mental health support, and community involvement, to improve CKD patients’ well-being. Full article

Snakebite envenoming remains a critical yet underrecognized public health issue, particularly in tropical and subtropical regions, with India bearing nearly half of the global burden of snakebite-related deaths. Despite its significant impact, underreporting, delayed medical intervention, and insufficiently trained healthcare professionals continue to exacerbate the problem. In response, the Government of India launched the National Action Plan for Prevention and Control of Snakebite Envenoming (NAPSE) in March 2024, aiming to halve snakebite-related deaths by 2030. Key challenges during the development and implementation of NAPSE included the limited multisectoral engagement initially, variations in state-level capacities, and logistical barriers in reaching remote populations. Lessons learned include the value of early stakeholder consultations, the importance of inter-ministerial collaboration, and the need for continuous community engagement. This comprehensive strategy emphasizes strengthening surveillance systems, enhancing anti-snake venom (ASV) distribution and quality, improving healthcare infrastructure, and promoting community awareness through a One Health approach. The plan also addresses critical challenges such as inadequate training at primary healthcare levels, inconsistent ASV supply, and inefficient emergency referral systems. By fostering multisectoral collaboration and targeted interventions, such as strengthening Regional Venom Centres and establishing Poison Information Centre, targeted training, and awareness campaigns, NAPSE aims to reduce mortality and disability associated with snakebite envenoming, aligning with global health objectives and setting an example for regional efforts in Southeast Asia. Full article

Climate-induced migration has emerged as a major concern in India and Bangladesh, due to their geographical vulnerability and socioeconomic conditions. Coastal areas, such as the Sundarbans and the Ganges–Brahmaputra Delta, face relentless threats due to rising sea levels, cyclones, and floods. These factors force millions to relocate, resulting in rural–urban transitions and cross-border movements that worsen urban challenges and socioeconomic vulnerabilities. For this, a systematic literature review of the Scopus database was undertaken using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A detailed review analysis of 65 papers was carried out. The study highlighted key climatic and non-climatic drivers of migration, including natural disasters, resource depletion, poverty, and poor governance. Despite existing adaptation strategies, such as early warning systems, micro-insurance, and climate-resilient practices, gaps remain in addressing long-term resilience and legal recognition for climate migrants. The research emphasizes the need for a holistic, multi-stakeholder approach, integrating adaptive infrastructure, sustainable livelihoods, and international cooperation. Recommendations include bridging research gaps, increasing community participation, and implementing global frameworks, like the Fund for Responding to Loss and Damage. Addressing climate migration through fair, inclusive measures is essential for building resilience and ensuring long-term development in the region. Full article

This study proposes an innovative framework integrating geographic information systems (GISs), water quality index (WQI) analysis, and advanced machine learning (ML) models to evaluate the prevalence and impact of organic and inorganic pollutants across the urban–industrial confluence zones (UICZ) surrounding the National Capital Territory (NCT) of India. Surface water samples (n = 118) were systematically collected from the Gautam Buddha Nagar, Ghaziabad, Faridabad, Sonipat, Gurugram, Jhajjar, and Baghpat districts to assess physical, chemical, and microbiological parameters. The application of spatial interpolation techniques, such as kriging and inverse distance weighting (IDW), enhances WQI estimation in unmonitored areas, improving regional water quality assessments and remediation planning. GIS mapping highlighted stark spatial disparities, with industrial hubs, like Faridabad and Gurugram, exhibiting WQI values exceeding 600 due to untreated industrial discharges and wastewater, while rural regions, such as Jhajjar and Baghpat, recorded values below 200, reflecting minimal anthropogenic pressures. The study employed four ML models—linear regression (LR), random forest (RF), Gaussian process regression (GPR), and support vector machines (SVM)—to predict WQI with high precision. SVM_Poly emerged as the most effective model, achieving testing CC, RMSE, and MAE values of 0.9997, 11.4158, and 5.6085, respectively, outperforming RF (0.9925, 29.8107, 21.7398) and GPR_PUK (0.9811, 68.4466, 54.0376). By leveraging machine learning models, this study enhances WQI prediction beyond conventional computation, enabling spatial extrapolation and early contamination detection in data-scarce regions. Sensitivity analysis identified total suspended solids as the most critical predictor influencing WQI, underscoring its relevance in monitoring programs. This research uniquely integrates ML algorithms with spatial analytics, providing a novel methodological contribution to water quality assessment. The findings emphasize the urgency of mitigating the fate and transport of organic and inorganic pollutants to protect Delhi’s hydrological ecosystems, presenting a robust decision-support system for policymakers and environmental managers. Full article

Background: The framework of measuring effective coverage is conceptually straightforward, yet translation into a single metric is quite intractable. An estimation of a metric linking need, access, utilization, and service quality is imperative for measuring the progress towards Universal Health Coverage. A coverage metric obtained from a household survey alone is not succinct as it only captures the service contact which cannot be considered as actual service delivery as it ignores the comprehensive assessment of provider–client interaction. The study was thus conducted to estimate a one-composite metric of effective coverage by linking varied datasets. Methods: The study was conducted in a rural, remote, and fragile setting in India. Tools encompassing a household survey, health facility assessment, and patient exit survey were administered to ascertain measures of contact coverage and quality. A gamut of techniques linking the varied surveys were employed such as (a) exact match linking and (b) ecological linking using GIS approaches via administrative boundaries, Euclidean buffers, travel time grid, and Kernel density estimates. A composite metric of effective coverage was estimated using linked datasets, adjusting for structural and process quality estimates. Further, the horizontal inequities in effective coverage were computed using Erreygers’ concentration index. The concordance between linkage approaches were examined using Wald tests and Lin’s concordance correlation. Results: A significantly steep decline in measurement estimates was found from crude coverage to effective coverage for an entire slew of linking approaches. The drop was more exacerbated for structural-quality-adjusted measures vis-à-vis process-quality-adjusted measures. Overall, the estimates for effective coverage and inequity-adjusted effective coverage were 36.4% and 33.3%, respectively. The composite metric of effective coverage was lowest for postnatal care (10.1%) and highest for immunization care (78.7%). A significant absolute deflection ranging from −2.1 to −5.5 for structural quality and −1.9 to −8.9 for process quality was exhibited between exact match linking and ecological linking. Conclusions: Poor quality of care was divulged as a major factor of decline in coverage. Policy recommendations such as bolstering the quality via the effective implementation of government flagship programs along with initiatives such as integrated incentive schemes to attract and retain workforce and community-based monitoring are suggested. Full article

Cardiovascular disease is among the leading causes of mortality and morbidity globally. Over three-quarters of CVD-related deaths now occur in low- and middle-income countries (LMICs); India accounts for one-fifth of global CVD-related deaths, especially among the younger population. The objective of this study was to evaluate the prevalence of CVD among the Indian adult population. We systematically searched Scopus and PubMed from January 2000 to December 2024 to identify relevant articles and pooled the prevalence of CVD using random-effects meta-analysis. Among the 14,647 records screened, 501 full-text articles were assessed for eligibility and 15 studies were included in the final analysis. The pooled prevalence of CVD was 11% (95% CI: 0.09–0.17). Subgroup analysis showed prevalence rates of 12% among males and 14% among females. Urban areas had a higher prevalence (12%) compared to rural areas (6%), with a significant difference. Our study shows the significant prevalence of cardiovascular disease (CVD) in India, particularly in urban areas, with slightly higher rates among females. Focused public health strategies are required to mitigate the growing burden of CVD, along with preventive measures, to reduce further increases in disease prevalence and related fatalities. Full article

This extensive study examines the solar rooftop photovoltaic potential (RTP) over polluted cities in major geographic and economic zones of India. The study examines the climatology of solar radiation attenuation due to aerosol, clouds, architectural effects, etc. The study exploits earth observations from ground, satellite, and radiative transfer modeling (RTM) in conjunction with geographic information systems tools. The study exploits long-term observations of cloud properties from the Meteosat Second Generation (MSG) satellites operated by EUMETSAT and aerosol properties data gathered from ground-based measurements provided by AERONET. The innovation in the study is defined in two steps. Firstly, we estimated the RTP using the current state of the art in the field, which involved using suitability factors and energy output based on the PVGIS simulations and extrapolating these for effective rooftop areas of the cities. Secondly, we advanced beyond the current state of the art by incorporating roof morphological characteristics and various area share factors to assess the RTP in more realistic terms. These two steps were applied under two different scenarios. The study determined that the optimum tilt angle is equal to the cities’ latitude for installing solar PV systems. In addition, the research emphasizes the advantages for the environment while offering energy and economic losses. According to our findings, the RTP in the rural city examined in this study is 31% greater than the urban city of India under both scenarios. The research has found that the metropolitan city, which boasts a maximum rooftop area of approximately 167 km², could host a significant RTP of around 13,005 ± 1210.71 (6970 ± 751.38) MWh per year under scenario 1 (scenario 2). Overall, solar radiation losses due to aerosol effects dominate radiation losses due to cloud effects on the city scale. Amongst all polluted cities, estimated financial losses due to aerosols, clouds, and shadows are 11,241.70 million, 4439 million, and 1167.65 million rupees, respectively. Our findings emphasize the necessity of accounting for air pollution for accurate solar potential assessments in thoughtful city planning. The creative approach that utilizes publicly available data establishes a strong foundation for penetrating solar photovoltaic (PV) technology into society. This integration could significantly contribute to climate change mitigation and adaptation efforts, promoting environmentally sustainable urban development and prevention strategies. Full article

The discourse around ‘nature-based solutions’ (NBSs) is quite recent, but this paper contends that, as knowledge and practice, the notion of NBS is not novel. Indigenous and rural communities are known to work closely with nature to fulfil their water needs, eke out sustainable livelihoods, and cope with climate variability and the impacts of natural disasters. India is a country where NBS has been a tradition for millennia. Water has been sustainably managed here and related societal challenges successfully met through the use of nature, natural systems, or natural processes within rural as well as urban settings. However, despite the merits, in recent times, many of the old NBSs have come to be neglected and degraded, being increasingly replaced by gray infrastructure. These changes are deepening the water crisis in the country, with the rapidly transforming peri-urban locations being an important area of concern. This paper outlines some of the major NBS forms traditionally established and used in different parts of India. Thereafter, using an integrated analytical framework for assessing sustainability of NBS (developed under project NATWIP), the value of the NBS legacy in India will be analyzed. Finally, the paper proposes important lessons as a way forward for enhancing water sustainability in peri-urban India that is based on the adoption and rejuvenation of the disappearing NBS science in the country. Full article

Coal accounts for over half of India’s energy needs currently. However, it has resulted in significant environmental impacts such as altering land cover and land surface temperatures. This study quantifies the land surface temperature (LST) of Dhanbad City (India)—home to India’s largest coal reserves. It uses the Landsat 8 image data to evaluate urban and rural temperature variations across different land use–land cover (LULC) classes. Using a Geographically Weighted Regression Model (GWR), we examined the spatial heterogeneity of the LST using key environmental indices, such as the Normalized Difference Vegetation Index (NDVI), Modified Normalized Difference Water Index (MNDWI), Normalized Difference Moisture Index (NDMI), and Normalized Difference Barren Index (NDBI). The seasonal LST variations revealed significant urban–rural area temperature disparities, with rural regions exhibiting stronger correlations with the key indices above. The GWR model accounted for 78.31% of the spatial variability in LST, with unexplained heterogeneity in urban areas linked to anomalies identified in the coal mining area fire map. These findings underscore the necessity of targeted mitigation strategies to reduce high LST values in coal fire-affected regions, with localized spatial measures in mining areas. Full article

India’s rapidly growing automobile industry has intensified the need for sustainable fuel alternatives to reduce dependency on imported fossil fuels and mitigate greenhouse gas (GHG) emissions. This study examines the potential of second-generation biorefineries as a comprehensive solution for efficient biomass valorization in India. With a projected bioethanol demand of 10,160 million liters by 2025 for India’s 20% ethanol blending target, there is an urgent need to develop sustainable production pathways. The biorefinery approach enables simultaneous production of multiple valuable products, including bioethanol, biochemicals, and bioproducts, from the same feedstock, thereby enhancing economic viability through additional revenue streams while minimizing waste. This paper systematically analyzes available biomass resources across India, evaluates integrated conversion technologies (biochemical, thermochemical, and synergistic approaches), and examines current policy frameworks supporting biorefinery implementation. Our findings reveal that second-generation biorefineries can significantly contribute to reducing GHG emissions by up to 2.7% of gross domestic product (GDP) by 2030 while creating rural employment opportunities and strengthening energy security. However, challenges in supply chain logistics, technological optimization, and policy harmonization continue to hinder large-scale commercialization. The paper concludes by proposing strategic interventions to overcome these barriers and accelerate the transition toward a sustainable circular bioeconomy in India. Full article

The swift expansion of financial technology (FinTech) can substantially improve financial inclusion, especially in the rural regions of emerging nations such as India. FinTech has the potential to drive inclusive growth, reduce inequalities, and foster sustainable economic development. This research examines the determinants affecting the adoption of FinTech services in rural India by synthesizing three theoretical frameworks: The Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and the Technology Readiness Index (TRI). A mixed methods approach that combines partial least squares structured equation modeling (PLS-SEM) and fuzzy set comparative qualitative analysis (fsQCA) was used to evaluate the suggested framework. The integrated PLS-SEM and fsQCA offer a comprehensive, elegant, and resilient method for data analysis. While fsQCA addresses more intricate patterns within the data, PLS-SEM effectively identifies the relationships among significant factors. This makes the mixed method approach more judicious and advantageous than the single method approach. The findings showed that attitude (β = 0.35), perceived behavioral control (β = 0.28) from the Theory of Planned Behavior (TPB), perceived ease of use (β = 0.31) from the Technology Acceptance Model (TAM), and perceived insecurity (β = −0.19) from the Technology Readiness Index (TRI) all have a big impact on how people use FinTech. The findings also indicate that the desire to adopt FinTech positively influences financial inclusion among rural residents. These research findings enhance the debate on sustainable development by demonstrating how specific FinTech interventions can close the financial inclusion gap, empower rural populations, and achieve various Sustainable Development Goals (SDGs). The study’s findings could help governments, banks, and FinTech firms aiming to enhance the accessibility and use of digital financial services in rural India. Full article