Rapid industrial, urbanisation and population growth have recently led to increased pressure on the solid waste management infrastructure of Durgapur city, resulting in negative impacts to water and air quality. The study assesses the environmental impacts of insufficient solid waste disposal activities on the groundwater, surface water and air. The results indicate that areas around open dumping sites are severely deteriorated with high groundwater, surface water pollution and increased particulate matter in the air especially in winter. These findings suggest that buffer zones, containment infrastructure and improved air quality monitoring will be needed to regulate air pollution from this sector. The study highlights for the policymakers and urban planners to consider a sustainable waste management framework which would help to ensure the protection of the environment and public health of the Durgapur.

Access to quality eye care is vital for public health, yet in Bangladesh, it is hindered by inadequate infrastructure, limited facilities, and insufficiently trained personnel. This study examines the accessibility and spatial distribution of eye health services in Dhaka City Corporation using Geographic Information Systems (GIS), Eight Key Informant Interviews (KIIs), and Six Focus Group Discussions (FGDs). GIS analysis revealed that only 14% of the city is adequately served, 45% is overserved, and 41% is underserved. The Average Nearest Neighbour (ANN) analysis indicated a significantly dispersed pattern (ANN ratio = 3.34; z-score = 20.49; p < 0.001). Key challenges include financial constraints (66.7% of respondents), poor accessibility for people with disabilities, transportation barriers, and lack of service information. While 68.8% of participants were satisfied with services and gender parity was noted, gaps in coverage and consistency persist. The findings call for equitable distribution of resources, mobile outreach, and improved affordability.

This study spatially analyzes localized geography of health insurance coverage among Scheduled Tribe (ST) households in India, revealing persistent regional disparities using nationally representative data from NFHS-5 and advanced spatial analytical techniques. Employing Exploratory Spatial Data Analysis (ESDA), Geographically Weighted (GW) correlation and Empirical Bayes Smoothing (EBS), the research identifies significant north-south and east-west rifts in economic status and insurance access. The findings reveal marked regional disparities, with significantly higher insurance coverage in southern and western districts, particularly in Kerala, Tamil Nadu, Andhra Pradesh, and parts of Gujarat compared to persistently low coverage in northern and eastern states such as Uttar Pradesh, Bihar, Jharkhand, and West Bengal. A Lorenz curve (Gini coefficient: 0.36) indicates moderate nationwide inequality in insurance coverage among ST households. Southern and western districts, notably in Kerala, Tamil Nadu, and Gujarat, exhibit stronger insurance penetration than northern and northeastern regions. While some ST populations in poorer northern areas benefit from targeted schemes, vast stretches of central and northeastern India remain underserved due to low economic development and weak healthcare infrastructure. Local Moran’s I analyses highlight High-High clusters in southern India and Low-Low clusters in the north-central belt, underscoring entrenched spatial disadvantage. The clustering effect suggests that health policy interventions in these regions have likely benefited from regional policy diffusion, where best practices and institutional capacities spill over into neighboring districts, creating reinforcing zones of success. Bivariate and GW correlation visualizations display a strong positive association between wealth status and insurance coverage, especially in southern and central regions. Conversely, regions with high proportions of BPL and poor ST households demonstrate strong negative correlations, indicating a double burden geography of economic vulnerability and exclusion from insurance schemes. Importantly, the findings emphasize the localized need for inclusive policy interventions to ensure universal access of insurance coverage for ST households, especially in identified vulnerable regions.

Farmers in most parts of Ethiopia are limited in their ability to produce crops by a lack of rain and its inconsistency, and climate change may make matters worse. One of the most common natural disasters is drought because it depletes natural resources, causes environmental destruction, and destroys the ecology that supports all life. Water harvesting is a desirable strategy for mitigating this problem. However, the identification of optimal sites for rainwater harvesting (RWH) is an important step to maximize the amount of water harvested and minimize the ecological impact. In this study, the remotely sensed data and geospatial modeling with the analytical hierarchical process (AHP) and Multi-Criteria Decision Analysis (MCDA) approach were used to identify a potential site for rainwater harvesting in the drought-prone area of Genale Dawa River Basin. The analysis has taken into account several thematic layers, such as soil texture, soil depth, slope, rainfall, land use land cover, separation from a road and a settlement, and drainage density. To locate the potential site, the aforementioned thematic layers were given the appropriate weights based on their relative value by AHP integrated with a GIS environment. This study identifies five potential classifications on the suitability map range from extremely suitable to not suitable. According to our result, 11.4% of the study area is extremely suitable, 49% is highly suitable, 34.1% is moderately suitable, 5.4% is barely acceptable, and 0.02% is not suitable. The outcome of the suitability map is particularly practical for decision-makers and planners to choose the best locations for rainwater harvesting.