Ecological security patterns are widely used to support ecological restoration planning in fragile regions, but commonly used resistance-surface approaches often fail to sufficiently account for erosion-related landscape instability in the Loess Plateau. Herein, we developed a planning-oriented ecological security pattern for Linfen, China, by identifying ecological sources using an ecosystem health index and incorporating soil erosion sensitivity as a regional modifier of the ecological resistance surface. Using Linkage Mapper and circuit theory, we extracted modeled ecological corridors, high-current–density pinch points, and candidate barrier areas for restoration priority under an erosion-sensitive resistance scenario, and then compared these outputs with those derived from the baseline resistance surface. The erosion-sensitive scenario yielded 814.22 km of modeled ecological corridors, together with high-current–density pinch points and restoration-priority barrier areas. Incorporating soil erosion sensitivity altered the spatial configuration of corridors and priority areas, indicating that erosion-prone terrain can alter modeled structural connectivity in the Loess Plateau. These outputs should be interpreted as scenario-based structural-connectivity results rather than as independently validated species-movement pathways. Through distinguishing priority areas where ecological connectivity improvement overlaps erosion-sensitive terrain, the results can help align territorial spatial zoning, ecological restoration actions, and soil erosion-control measures in Linfen. This study provides a spatially explicit planning reference for ecological restoration screening and corridor-planning prioritization in the city of Linfen.
Pharmaceutically active compounds (PhACs) are increasingly detected in surface waters and treated effluents. However, their removal during conventional treatment remains inconsistent because of their recalcitrance and variable speciation. Geopolymers offer a sustainable remediation solution, as they are highly tunable and can be synthesised from low-cost aluminosilicate precursors, including industrial byproducts. Nevertheless, research on geopolymer–PhAC is fragmented. Adsorption studies are often conducted in simplified batch systems, and photocatalysis data tend to focus on antibiotics. This review aims to consolidate and critically assess geopolymer-based adsorption and geopolymer-supported photocatalysis for PhAC removal. Emphasis is on the mechanistic connections between PhAC descriptors, geopolymer characteristics, and process variables. Adsorption performance ranges from 19–99
Assessment of soil water infiltration through reliable estimation of the infiltration rate is key to informed decision-making for sustainable ecosystem management. This study was conducted to evaluate the performances of the Kostiakov, Modified Kostiakov, Horton, Swartzendruber, Brutsaert and Philip models in estimating cumulative infiltration depth under loam, sandy loam and loamy sand soil textures. The measured infiltration data from the double ring infiltrometer were fitted to the infiltration models and their goodness-of-fit statistics were verified by the Coefficient of Determination ( R^2 ), Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE). The Goodness-of-fit statistics for all Cumulative infiltration estimating models across the three locations within the study area associated with different soil textures show that the Modified Kostiakov model generally outperformed the other models based on the relatively higher mean R^2 and low RMSEs, MAEs and MAPEs. The estimation accuracy was in the order of Modified Kostiakov > Kostiakov > Swartzendruber > Horton > Brutsaert > Philip models. The influence of soil texture on the model accuracy was also in the order of Loam > Sandy loam > Loamy sand soil textures. The results of this study indicate that the use of the Modified Kostiakov model in hydrological evaluations can improve the accuracy of irrigation system design under verified field conditions.
Rapid urbanisation in Ghana has outpaced municipal infrastructure, leaving cities like Accra struggling to manage daily waste. Municipalities and private waste management companies are struggling with significant uncollected municipal solid waste and a high reliance on unsanitary disposal methods. These problems result in serious environmental degradation (increasing greenhouse gas emissions from open dumping and burning) and public health issues. Despite Ghana’s robust legislative framework, a significant functional disconnect exists between policy formulation and local implementation. This study evaluated Ghana’s existing legislative frameworks governing its solid waste management system to identify systemic gaps and explore the potential to integrate informal waste pickers into a formal, inclusive, and sustainable circular economy. Employing a convergent mixed-methods research design, the study utilised a semi-structured questionnaire to collect data from 13 purposively selected expert stakeholders across different governing bodies. This allowed for a quantitative descriptive method to identify systemic trends and a qualitative thematic analysis of open-ended responses. This ensured a complete evaluation of the MSW governance landscape in Ghana. The findings reveal an institutional maze characterised by fragmented law enforcement, financial constraints, and the absence of formal monitoring systems. The findings also show that informal waste pickers lack recognition, social protection, and technical support. The study recommends data-driven modelling approaches that align and integrate institutional frameworks with inclusive social policies such as optimisation, multi-criteria decision-making tools, and life-cycle assessments. This paper provides an evidence-based roadmap for transitioning to a resilient governance framework, offering practical insights for building urban sustainability capable of addressing climate change.
Urban transportation systems face increasing challenges due to traffic congestion, travel delays, and operational inefficiencies, particularly in municipal solid waste collection services. Traditional route planning methods, including shortest-path algorithms such as Dijkstra’s algorithm, primarily optimize a single factor such as travel distance or travel time, which may not adequately represent the complex traffic and infrastructure conditions encountered in urban environments. Despite advances in route optimization, limited research has integrated coverage-based routing with multi-criteria evaluation within a unified framework. To address this gap, this study proposes an integrated route optimization framework that combines the Hamiltonian Circuit concept with the Analytic Hierarchy Process (AHP). The Hamiltonian Circuit ensures complete coverage of waste collection locations without duplication, while AHP evaluates alternative routes using multiple criteria, including travel time, traffic volume, distance, road width, parking effects, encroachment, and intersection density. The framework is validated using a municipal waste collection network in Vellore, Tamil Nadu, India. The results identify Route 3 as the most efficient alternative, providing the best overall balance among operational and transportation-related criteria. Compared with conventional single-factor approaches based solely on distance or travel time, the proposed framework offers a more comprehensive assessment of route performance. The study demonstrates that integrating graph-based routing with multi-criteria decision-making (MCDM) can support more effective municipal service planning and assist urban authorities in improving operational efficiency and sustainable transportation management.
