Search Results (4,679)

As climate change intensifies, transitioning the construction sector away from fossil fuels is vital to reducing global greenhouse gas emissions and localized urban pollution. This paper assesses the economic feasibility of electrifying construction machinery by developing an Annualized Cost of Ownership framework that incorporates mobile charging solutions, internalizes environmental and public health operational externalities (CO₂, PM_2.5, NO_x, and SO₂), and relies on Monte Carlo simulation with Cholesky decomposition to capture the interdependencies among cost drivers. We analyze twenty distinct models of excavators and wheel loaders—the two largest contributors to construction-machinery emissions—comprising functionally equivalent diesel and battery-electric variants. Our results show that several compact electric models are already cost-competitive even without internalizing environmental and public health operational externalities. When these are accounted for, the economic advantage of electric machinery increases, particularly in denser urban areas where local air pollution damages are severe. While projected battery cost reductions further lower electric ownership costs, the magnitude of this effect is modest. However, the weak penetration of electric construction equipment in the US underscores that targeted policy interventions—such as point-of-sale rebates, green procurement mandates, tax credits, charging infrastructure subsidies, or the creation of low-emission zones and noise ordinances that advantage electric construction machinery—are needed to accelerate market adoption. These measures are particularly critical in densely populated urban areas, where internalizing local air pollution and public health externalities significantly amplifies the economic value of zero-emission machinery. Full article

This study evaluates the ecological impacts of seawater desalination discharge on coastal marine ecosystems through a sequential analytical framework linking systematic literature synthesis, field-monitoring evidence, spatial analysis, and predictive ecological modeling. The novelty of the study lies in combining multi-regional evidence from Mediterranean coastal zones, Persian Gulf waters, and Pacific coastal environments with threshold-based ecological risk assessment, thereby linking discharge-related environmental stressors with biological responses and ecosystem-function alterations. The systematic review first retained 750 studies published between 2004 and 2024 for qualitative synthesis. On this basis, 59 high-quality references with sufficient numerical information were selected for the main quantitative meta-analysis, while field-monitoring data were used to support the interpretation of distance-based discharge gradients. Spatial interpolation and hierarchical modeling were then applied to evaluate exposure–response patterns and ecological threshold behavior. The results showed that desalination facilities generated measurable ecological impacts mainly within 50–200 m of discharge points, with a critical transition distance of approximately 127 m where hypersaline conditions, typically 1.5–2.0 times ambient seawater levels, were associated with marked changes in marine community structure. Benthic assemblages showed taxon-specific responses, with mollusks and echinoderms exhibiting greater sensitivity than polychaetes and small crustaceans. Marine vegetation declined strongly under combined salinity, thermal, and chemical stress, while phosphonate-based antiscalants accumulated in filter-feeding organisms and produced bioaccumulation factors up to 42.1 times ambient levels. Ecosystem-function indicators, including microbial community composition and sediment organic matter processing, remained altered up to 300 m from discharge points, indicating that functional impacts may extend beyond the primary hypersaline plume. The predictive modeling framework further demonstrated that ecological risk decreased nonlinearly with distance and varied according to discharge intensity, local hydrodynamics, and biological sensitivity. These findings indicate that conventional uniform buffer-based assessment may underestimate the ecological footprint of desalination discharge. Sustainable desalination management should therefore adopt site-specific monitoring, species-sensitive protection thresholds, improved brine-management technologies, and adaptive mitigation strategies based on real-time environmental feedback. Full article

Disentangling the coupled, nonlinear impacts of climate change and anthropogenic activities on vegetation dynamics is critical yet challenging for global change research. The Qinghai–Tibetan Plateau (QTP), a highly climate-sensitive and ecologically strategic region, serves as a vital arena for examining such complex socio-ecological attributions. Based on multi-source environmental datasets from 2000 to 2020, this study developed an integrated, spatially explicit framework coupling residual trend analysis (RESTREND) and GeoDetector to quantify individual drivers and nonlinear climate–human interactions. The QTP exhibited a significant, widespread greening trend during 2000–2020, featuring prominent spatial clustering with “High–High” clusters in the southeast and “Low–Low” clusters in the northwest. Attribution modeling revealed that vegetation dynamics were governed not by isolated variables, but by multifaceted, nonlinear synergies among precipitation, temperature, topography, vegetation type, and land-use change. Key interactive pairs, particularly elevation–temperature and slope–precipitation, dramatically increased explanatory power over single-factor models. Crucially, climate–human synergies explained substantially more variance than climate variables alone, bounded by a distinct elevational threshold: human activities dominated vegetation dynamics at mid-elevations (2500–3500 m), while climate factors took over as the primary controller at high altitudes (above 3500 m). Quantitatively, human activities induced vegetation improvement across 38.6% of the plateau, maintained stability in 35.8%, and caused degradation in 25.6%. By successfully merging trend decomposition with spatial stratified heterogeneity analysis, this study provides a transferable approach to uncoupling complex environmental interactions. These insights highlight the intensifying human footprint on alpine ecosystems and advocate for zone-specific adaptive management: mitigating human disturbances at mid-elevations and fostering climate adaptation in higher zones to preserve plateau resilience. Full article

Traditional global localization systems frequently struggle with perceptual ambiguities in dynamic environments and structurally similar scenes, which severely compromises navigation robustness. Concurrently, conventional path planning methodologies rarely integrate proactive safety considerations regarding high-risk environmental features. To resolve these critical limitations, this paper introduces a comprehensive semantic-assisted framework for mobile robots to enhance both global localization and navigation. First, we develop a semantic-aware place representation derived from LiDAR point clouds. By explicitly filtering dynamic objects and assigning category-specific weights, this approach mitigates perceptual aliasing and ensures robust scene recognition. Furthermore, we implement a Hyper-Semantic Point Histogram (HyperSPH) to embed semantic encoding directly into local geometric features. A Semantic Geometric Consistency Filter is subsequently applied to eliminate matching outliers and maximize registration accuracy. For secure navigation, we propose the Semantic-guided Twin Delayed Deep Deterministic Policy Gradient with Long Short-Term Memory (S-TD3-LSTM) algorithm within a deep reinforcement learning architecture. This strategy extracts temporal correlations via Long Short-Term Memory networks and integrates a dedicated semantic cost function to optimize obstacle avoidance policies. Extensive experiments demonstrate that the proposed localization module achieves superior retrieval and pose estimation precision over conventional methods. In complex path planning scenarios, the S-TD3-LSTM algorithm ensures stable convergence and generates highly adaptive trajectories. By proactively identifying and bypassing semantic hazards, the integrated system drastically minimizes exposure to dangerous zones, successfully establishing a rigorous balance between path efficiency and execution safety. Full article

To address the widespread issue of abnormally high pump pressure during hydraulic fracturing of deep-to-ultra-deep reservoirs (burial depth > 4500 m) in the Junggar Basin, this study systematically reveals the mechanical mechanism underlying this phenomenon by integrating well logging curve analysis and elastoplastic mechanics theory. Statistical results demonstrate that the actual fracture initiation pressure of 60% of wells in the target block is significantly higher than the values predicted by traditional elastic theory, primarily attributed to plastic yielding and stress concentration effects around perforations induced by high in situ stress. An elastoplastic rock fracture initiation pressure model is established based on the Mohr–Coulomb criterion and the plastic zone radius criterion, which is applied to predict the fracture initiation pressure of selected wells in the target block. The relative error between the model predictions and field measurements is less than 2%, significantly improving the prediction accuracy of fracture initiation pressure in deep-to-ultra-deep formations. This provides precise guidance for subsequent optimization of operational parameters and selection of pressure ratings for wellhead equipment. The study further clarifies that in situ stress difference, rock yield stress, and the power-law hardening exponent are the key factors controlling the transition of fracture initiation modes. To mitigate the high pump pressure challenge in deep-to-ultra-deep reservoir fracturing, the field application of weighted fracturing fluid effectively increases the wellbore hydrostatic column pressure, reduces wellhead operational pressure, and ensures construction safety. The findings of this study provide critical theoretical and technical support for achieving the goal of “successful fracture initiation and effective fracture control” in deep-to-ultra-deep reservoir fracturing. Full article

Tropical coastal waters are increasingly recognized as critical reservoirs for virulent, antibiotic-resistant enteric pathogens, yet seasonal dynamics governing their spatial distribution remain poorly characterized. We hypothesized that hydrological shifts and anthropogenic nutrient enrichment drive the seasonal distribution, virulence profiles, and antimicrobial resistance (AMR) of Escherichia coli, Salmonella spp., and Shigella spp. in the Jaffna Peninsula, Sri Lanka. Across 25 coastal sites during dry and transitional seasons, we integrated physicochemical water quality assessment, culture-based enumeration, PCR-based virulence gene profiling, Minimum Inhibitory Concentration (MIC) assays, GIS mapping, and statistical analyses. Key water quality parameters, including ammonium, nitrite, and total phosphorus, showed significant seasonal variation (p < 0.05), reflecting distinct hydrological regimes across seasons. A total of 220 E. coli, 200 Salmonella spp., and 100 Shigella spp. isolates were examined for virulence gene profiles and antibiotic tolerance. E. coli was detected at 80–88% of sites, Salmonella spp. at 72–88%, and Shigella spp. at 32–48%. Among E. coli isolates, stx1 was detected at 20–28% of sites and eae at 16% across both seasons. The stn gene was detected in Salmonella spp. at 12–28% of sites seasonally. Virulence profiling confirmed STEC harbouring stx1, stx2, and eae; Salmonella spp. carried stn; and Shigella spp. possessed invasion-associated genes. Trimethoprim–sulfamethoxazole resistance was recorded in 63.2% of E. coli, 33.0% of Salmonella spp., and 31.0% of Shigella spp. isolates at the lowest tested concentration of 4 µg/mL., while ciprofloxacin and piperacillin–tazobactam retained greater efficacy. Correlation analyses revealed significant associations among faecal contamination, nutrient enrichment, and virulence gene prevalence, implicating untreated sewage discharge and eutrophication as likely ecological factors associated with pathogen occurrence. These findings designate the Jaffna coastal zone as a significant reservoir of virulent AMR enteric pathogens, underscoring the urgent need for integrated One Health surveillance and seasonally adaptive coastal water quality management. Full article

Oil-dependent urban regions face persistent ecological and societal issues following extraction, including land degradation and infrastructural neglect. Despite the discourse on environmental justice and extractivism, a research gap exists regarding the transition of post-extractive cities from recognizing environmental harm to implementing territorial rehabilitation strategies. This study examines Poza Rica, Mexico, a critical city in the oil industry, as a case study for restorative justice and urban transition after extraction. Utilizing a qualitative case study approach with planning documents, technical reports, environmental regulations, spatial data, and community input, the research evaluates the territorial impacts of seventy years of oil extraction and explores restoration pathways. The results indicate a landscape characterized by abandoned wells, environmental liabilities, and the integration of former extraction zones into urban areas. In the Tampico–Misantla Basin, 49.5% of wells remain inactive, with only 2.7% meeting contemporary closure standards. In Poza Rica, nearly 98% of urban growth from 1997 to 2016 occurred in regions previously linked to oil extraction. The article posits that restorative justice in post-extractive cities necessitates more than mere financial restitution. It advocates for a territorial restitution framework centred on remediation, economic transformation, and community governance, illustrating how former extraction sites can evolve into assets for urban resilience and sustainable development. Full article

Background: Healthcare-associated infections (HAIs) remain a critical patient safety challenge. Hand hygiene is considered the most effective preventive measure, yet traditional monitoring captures only compliance, not technique quality. This prospective before–after study evaluated whether real-time visual feedback via the Semmelweis UV-fluorescence system is associated with improved hand hygiene quality, measured by ATP bioluminescence and microbiological culture. Methods: Three clinical departments (the Intensive Care Unit, Hematology, and Gynecology) at a Romanian tertiary hospital were purposively selected. Seventy-one healthcare workers (HCWs) were enrolled. The 12-week study comprised Phase 1 (baseline, weeks 1–4), Phase 2 (active intervention with Semmelweis feedback, weeks 5–8), a one-week washout (week 9), and Phase 3 (sustainability assessment, weeks 10–12). Paired ATP-CFU samples were collected weekly. Within-group comparisons used Kruskal–Wallis H tests with post hoc Dunn’s tests and Bonferroni correction. Secondary outcomes included Semmelweis global and zone-specific coverage and the correlation between subject-level Semmelweis coverage and ATP bioluminescence (Spearman’s rho). Results: A total of 781 paired ATP-CFU samples and 497 Semmelweis evaluations were analyzed. Mean ATP declined from 195.9 RLU at baseline to 148.2 RLU in Phase 2 (−24.4%) and 154.8 RLU in Phase 3 (−21.0%; Kruskal–Wallis H = 102.73, p < 0.001). CFU/mL declined from 84.8 to 66.2 (−21.9%) and 70.7 (−16.6%; H = 22.48, p < 0.001). Post hoc comparisons confirmed significant Phase 1 versus Phase 2 and Phase 1 versus Phase 3 differences for both markers (all p < 0.01), while Phase 2 versus Phase 3 was non-significant, indicating stabilization at an improved level. Subject-level Semmelweis coverage correlated negatively with ATP (rho = −0.665, 95% CI −0.778 to −0.510, p < 0.001), supporting construct validity at the operator level. Semmelweis global coverage was 93.1% (Phase 2) and 90.6% (Phase 3); interdigital spaces showed the highest inadequacy rate (73.9% protocol-based, 92.5% targeted). Conclusions: Real-time visual feedback via UV-fluorescence imaging was associated with significant and sustained improvements in hand hygiene quality beyond baseline. ATP, CFU, and Semmelweis assessments captured complementary, non-redundant dimensions, supporting multimodal evaluation. Interdigital spaces and fingertips remained persistent failure points requiring targeted educational reinforcement. Full article

Water resource management in the Sahelian-Sudanian transition zone faces growing uncertainty under climate change, yet hydrological projections remain scarce for the Oti-Pendjari basin (West Africa). This study develops an integrated modelling chain combining CMIP6 multi-model evaluation, bias correction, and GR4J hydrological modelling to project streamflow changes under SSP2-4.5 and SSP5-8.5 over 2021–2100. Eleven CMIP6 models were evaluated against ERA5 reanalysis data (1960–2014) using NSE, KGE, and MAE; the three best-performing models were bias-corrected using Linear Scaling, Variance Scaling, Quantile Mapping, and Quantile Delta Mapping. Linear Scaling proved most effective, with CMCC-ESM2 best reproducing observed precipitation (NSE and KGE up to 0.9), while the multi-model approach performed best for temperature. The GR4J model, calibrated at Porga, Mandouri, and Mango (KGE: 0.609–0.668), satisfactorily reproduces intermediate flows and flood dynamics, although structural limitations persist for low flows (KGE [1/Q]: −0.65 to −0.71). Projections reveal a marked divergence between scenarios: SSP2-4.5 yields September peak flow increases of +5.7% to +16.7%, whereas SSP5-8.5 leads to slight decreases of −1.1% to −3.6%, likely driven by increased potential evapotranspiration partially offsetting precipitation gains. These findings underscore the critical importance of scenario selection and model uncertainty in regional water resource planning. Full article

This study evaluates the multi-year taxonomic diversity and functional structure of beetle assemblages (Coleoptera) within Sub Arini Park, a historic urban green space in Sibiu, Romania. Following a preliminary baseline and methodological calibration phase in 2023, systematic monitoring was conducted during the 2024 and 2025 seasonal cycles utilizing standardized pitfall trapping across diverse park zones. We explicitly tested two hypotheses: (H1) that long-standing historic park management preserves a resilient and functional insect community structure, and (H2) that local spatial heterogeneity and microhabitat variations significantly drive species distribution. A total of 14,843 individuals belonging to 39 species were analyzed. While total abundance exhibited a slight decrease from 2024 (N = 7112) to 2025 (N = 6551), true diversity metrics (Hill numbers) revealed a significant increase in raw species richness (q = 0) from 30 to 39 species, alongside an enhanced equity of frequent species (Shannon diversity, q = 1, increased from 4.26 to 5.12). Functional guild analysis and multivariate PCA demonstrated a highly structured biocenotic distribution; specialist and hygrophilous species (e.g., Carabus variolosus Fabricius, 1787) were strictly constrained to high-humidity riparian corridors, whereas thermophilous generalists dominated open lawns under high anthropogenic stress. Our spatial analysis identified critical degradation within these heavily managed zones, specifically driven by intensive mowing, soil compaction, and organic debris removal. These findings confirm both hypotheses, revealing that the park operates as a heterogeneous mosaic of ecological refugia rather than a uniform habitat block. Crucially, this study provides a concrete, quantitative basis—derived from empirical thresholds of species richness, abundance shifts, and mapped microhabitat preferences—for implementing nature-based management strategies (such as establishing buffer zones with reduced mowing frequencies, limiting trampling, and retaining coarse woody debris) aimed at mitigating urban biodiversity loss and maintaining vital biological pest control services in Central–Eastern Europe. Full article

Deep excavation groups in soft soil can endanger adjacent historic buildings. This paper presents a 3D finite element analysis of a project in Ningbo, employing the HSS constitutive model. Three excavation schemes were compared. The small-zone staged excavation from near to far proved optimal: relative to the conventional large-block scheme, it reduced maximum wall displacement on the heritage-building side by 37.0% and building tilt by 54.0%; servo struts were then introduced in the critical sub-excavation and optimized via response surface methodology. A layered control hierarchy was revealed—wall bulging is governed by the third and fourth struts (F₃ ≈ F₄ > F₂), and mean settlement by the third strut (F₃ > F₂ ≈ F₄). Building tilt control relies on synergistic action of all three struts (F₃ > F₂ > F₄), with significant antagonistic interactions among struts at high force levels. The optimal combination (F₂ = 1200 kN, F₃ = 1800 kN, F₄ = 1550 kN) limits maximum tilt to 0.380‰, well below the 1.0‰ code limit, and remains robust under various weighting scenarios. Full article

Ammonia is a promising zero-carbon energy carrier for maritime decarbonisation, but its deployment is limited by safety risks that are not adequately addressed by conventional marine fuel safety frameworks. This study critically reviews safety assessment, risk management and control strategies for ammonia storage and handling in maritime applications using a PRISMA-informed literature synthesis. Evidence is analysed across hazard characterisation, storage configurations, transfer operations, risk assessment methods, mitigation barriers and regulatory frameworks. The review shows that ammonia safety is governed by coupled release–exposure–barrier interactions shaped by storage condition, tank configuration, pressure–temperature behaviour, material compatibility, transfer mode, ventilation, ship geometry and human intervention. Existing methods, including HAZID, HAZOP, risk matrices and QRA, support hazard screening and prioritisation, but remain limited in representing flashing two-phase releases, dense gas dispersion, confined-space accumulation, exposure duration, ventilation effectiveness and safeguard timing under maritime conditions. CFD, FTA, Bayesian approaches and Monte Carlo analysis offer higher analytical resolution, but their reliability is constrained by limited validation data, uncertain leak-frequency inputs and simplified assumptions for human exposure and emergency response. Effective risk control therefore requires a toxicity-centred barrier strategy linking containment integrity, ammonia-compatible materials, gas and process monitoring, emergency shutdown, ventilation, water-based mitigation, PPE, competency-based training and emergency planning. Current regulatory and classification guidance provides an essential foundation but remains fragmented and insufficiently aligned with ammonia-specific requirements for exposure modelling, safety-zone definition and approval pathways. This review contributes a maritime-specific synthesis of ammonia storage and handling safety by connecting hazard behaviour, storage design, transfer operations, risk assessment limitations, control-barrier logic and regulatory approval needs. The findings highlight the need for validated source-term models, full-scale release and dispersion data, exposure-based safety criteria and harmonised regulatory pathways to support the safe and scalable use of ammonia in maritime decarbonisation. Full article

The Kubuqi Desert serves as a critical zone for both renewable energy development and ecological management in China. Large-scale photovoltaic (PV) deployment has fundamentally altered the regional underlying surface, impacting near-surface wind–sand dynamics. To elucidate these disturbance mechanisms, we selected three representative surfaces—a PV area, a resource base, and Qixing Lake—and conducted field observations from September to December 2023 using meteorological towers and wind erosion sensors. Results indicate that all surfaces significantly attenuated near-surface wind speeds by over 30% through modified flow field structures. A strong linear positive correlation existed between wind speed and friction velocity (R² ≈ 0.99). Notably, for the same friction velocity, the actual wind speed required to initiate sand movement was lowest in the PV zone (high k) and highest at Qixing Lake (low k), signifying enhanced surface stability due to PV infrastructure and moisture. Threshold analysis revealed distinct initiation speeds: >6.0 m·s⁻¹ in peripheral quicksand, >4.3 m·s⁻¹ in inter-panel zones, and >4.6 m·s⁻¹ beneath panels. The tilted PV panels accelerate airflow downward, generating cyclonic vortices that intensify sand particle impacts under and between panels. This study reveals the tri-dimensional mechanism of wind regulation–sand suppression–stability enhancement, providing theoretical support for mitigating wind–sand disasters while advancing green energy in desert regions. Full article

Mapping wildfire patterns in Wildland–Urban Interface (WUI) areas is a fundamental tool for fire management and prevention, particularly in regions where urban expansion occurs in close proximity to natural vegetation. This mapping approach makes it possible to identify critical zones and to support more effective interventions adapted to the specific conditions of each territory. This work analyzed wildfires in the state of Tocantins, Brazil, using detailed geospatial data and advanced analysis techniques and statistics to characterize the dynamics of burned areas. Data used for the project were retrieved from MapBiomas and the Geoprocessing Laboratory of the Public Ministry of Tocantins (LABGEO), applying logistic regression models to explore the relationship between the distance of WUIs and the frequency of wildfires. The methodology covered the spatial distribution of fires and the different dynamics observed by type and size of burned area, allowing for a more detailed analysis. The results indicated significant variations in the proportion of burned areas inside and outside the WUIs, suggesting that proximity to these interfaces plays a critical role in the occurrence pattern of fires. Notably, Palmas, the state capital, stood out as one of the municipalities with the highest concentration of impacts in WUI areas, highlighting the relevance of these zones in environmental risk management. The study emphasizes the importance of adopting regional approaches that consider local specificities in the management and prevention of wildfires. The integration of geospatial data with robust statistical methodologies can guide more effective management strategies, assisting in the planning of public policies adapted to the socio-environmental dynamics of Tocantins. Full article

As the Kingdom of Saudi Arabia (KSA) accelerates its transition toward smart mobility under Vision 2030, establishing a robust digital infrastructure is paramount for the safe deployment of autonomous vehicles (AVs). High-definition (HD) maps serve as a critical foundation for this infrastructure, yet their deployment is severely bottlenecked by extreme operational costs, massive data processing payloads, and rapid environmental variations across vast highway networks. To address these challenges, this paper proposes a comprehensive, localized national strategy structured around three key tasks. First, it establishes a unified national HD map standard to guarantee seamless interoperability and data sharing among competing AV manufacturers and government transport authorities. Second, it implements an AI-powered baseline workflow using Mobile Mapping Systems (MMS) for high-fidelity static map construction, anchored and validated within designated pilot zones, including the King Abdulaziz University campus and key sectors in the Kingdom. Third, it deploys a decentralized, vision-based crowdsourcing system that leverages active public and commercial vehicle fleets for real-time map maintenance. By integrating a sovereign edge-cloud AI infrastructure that respects local Personal Data Protection Law (PDPL), this framework bridges the gap between high-accuracy baseline mapping and long-term economic sustainability, offering an actionable technical roadmap for scaling a resilient digital transport layer across the Kingdom. Full article