Search Results (2,710)

Inadequate Municipal Solid Waste (MSW) management constitutes a critical environmental challenge, as approximately 40% of waste reaches uncontrolled disposal sites where open-air incineration generates significant air, soil, and water pollution. The objective of this study was to evaluate the MSW Environmental Management System (EMS) in Chilpancingo de los Bravo, Guerrero, Mexico, through sustainability indicators and applicable Mexican environmental regulations to identify operational and structural deficiencies that guide a comprehensive improvement in its management. The methodology comprised an analysis of the EMS via the Municipal Development Plan, the identification of environmental indicators and applicable Mexican standards, and an evaluation of the EMS through waste characterization and sustainability metrics. A sample of 208 kg was defined in accordance with standards NMX-AA-015-1985 and NMX-AA-022-1985. The results indicate a generation rate of approximately 350 tons per day (1.2 kg/capita/day), with municipal collection coverage of 70% of the territory across 24 daily routes operated by 30 vehicles. Indicators revealed a recycling rate of 4.86%, collection coverage of 79.66%, a 0% treatment rate due to the absence of composting or material recovery facilities, and 95% of waste directed to the Final Disposal Site (FDS). These findings demonstrate substantial deficiencies in the current EMS, highlighting that the systematic application of indicators is an effective diagnostic tool for identifying gaps and guiding evidence-based improvements in MSW governance. Full article

Several review studies have addressed the implications of improper waste management on urban livability conditions at large, but we still do not have an overall picture of the link between poor waste management in Sub-Saharan countries and short- and long-term health impacts. Considering that Sub-Saharan Africa is the location of 19 of the 50 biggest dumpsites in the world, it is important to better understand what we do and do not know so far about this public health–waste management link. This study, therefore, provides an overall understanding of health risks associated with improper waste disposal in Sub-Saharan Africa, with a focus on air, water and soil pollution. Employing a systematic review approach, this study utilized academic databases, including PubMed, ScienceDirect, and Google Scholar, to identify and analyze 27 relevant articles, covering eight Sub-Saharan countries. The review was undertaken by categorizing trends and characteristics under themes of solid waste disposal practices, pollution consequences, and reported health problems. The results showed that air pollution, which was the most widely studied in Sub-Saharan Africa, accounted for 155 deaths/100,000 people. Water pollution has led to outbreaks of cholera, typhoid, and diarrhea, especially in communities near waste sites, while contaminated soil poses long-term risks, including for cancer and developmental harm. The findings also revealed that children, waste workers, and communities living near dumpsites are the most vulnerable. Despite growing evidence of harm, gaps remain in our understanding of chronic and long-term effects due to a lack of longitudinal data and inconsistent methodologies to measure health effects. The study also identified inconsistency in distance-based exposure metrics, as studies used varying distances of residents from waste sites to measure health outcomes. Finally, it highlights the urgent need for improved waste infrastructure, clear landfill siting guidelines, and long-term epidemiological studies to inform health-focused waste policies in Sub-Saharan Africa. Full article

While existing research has established that air pollution-induced “avoidance behavior” significantly drives the growth of online food delivery volumes, the Average Order Value (AOV) remains unexplored. This study utilizes micro-transactional data provided by the store owner and employs machine learning algorithms to detect the impact of air quality (measured by the AQI) on online food delivery AOV and analyze the underlying consumer behavior. The findings indicate that: (1) Air quality deterioration significantly drives up the AOV. The global average response coefficient is 0.0053, showing a 2.4-fold acceleration effect once the AQI crosses the median (66). (2) Crucially, this growth stems from a directional divergence in consumer decision-making. Air pollution leads to the simultaneous occurrence of a reduction in average item quantity (impact coefficient: −0.0014) and a surge in Average Item Price (AIP) (impact coefficient: 0.0066). (3) Causal analysis further identifies a “substitution mechanism.” Specifically, every one-unit decrease in average item quantity induces a CNY 1.098 jump in average item price. These findings suggest a plausible behavioral logic where environmental stress may induce psychological fatigue but does not necessarily trigger “defensive frugality.” Instead, the observed pattern is consistent with a “decision avoidance” mode where consumers streamline item quantities; simultaneously, to hedge against potential experience risks resulting from simplified choices, they appear to utilize saved cognitive resources to target high-value “signature” items. Theoretically, this study fills the gap in environmental stress research regarding the price dimension of online consumption and reveals a behavioral evolution from “pure avoidance” to “value-oriented selection.” Practically, it provides empirical support for online food delivery merchants to optimize product selection, differentiate pricing, and implement precision marketing in dynamic environments. Full article

The transport sector is a major contributor to urban air pollution and greenhouse gas emissions in Pakistan, posing significant challenges to sustainable development and climate commitments. This study develops the first technology-resolved, high-resolution, multi-pollutant emission inventory and scenario analysis for Pakistan’s transport sector, addressing key gaps in previous studies that lacked integrated multi-pollutant assessments, comprehensive coverage of non-road sources, and long-term scenario comparisons. The analysis integrates road and non-road transport sources within the Greenhouse Gas–Air Pollution Interactions and Synergies (GAINS) modeling framework. Emissions are projected for 2024–2050 under a business-as-usual (BAU) scenario and three mitigation pathways: an Electric Vehicle Transition (EVT) emphasizing transport electrification, a Euro-VI scenario focusing on stringent fuel and vehicle emission standards, and an integrated nationally determined contribution strategy (NDC+) scenario combining electrification, regulatory improvements, and structural transport reforms. In 2024, transport-related emissions are estimated at approximately 22 kt of fine particulate matter (PM_2.5), over 300 kt of nitrogen oxides (NO_x), and nearly 39 Mt of carbon dioxide (CO₂), alongside substantial emissions of other gaseous pollutants and short-lived climate forcers. By 2050, the NDC+ scenario achieves the largest reductions relative to business-as-usual, demonstrating that coordinated electrification and emission control strategies can simultaneously reduce air pollution and greenhouse gas emissions. The results demonstrate strong synergies between climate mitigation and air quality improvement, showing that integrated strategies combining electrification with stringent emission standards can simultaneously reduce greenhouse gas emissions and major air pollutants while advancing cleaner and more sustainable mobility. This analysis provides a consistent and policy-relevant evidence base derived from best-available data and modeling tools to support Pakistan’s NDC implementation, sustainable mobility planning, and integrated air quality and climate strategies, with lessons transferable to other rapidly developing economies. Full article

High-throughput plant phenotyping (HTPP) is increasingly limited by the mismatch between the need for field-relevant, fine-grained phenotypic information and the restricted capability of conventional observation platforms under complex agricultural conditions. Ground mobile robots are emerging as the key carrier for resolving this gap because they combine close-range sensing, autonomous mobility, and physical interaction within real field environments. In this paper, a structured scoping review is presented using a closed-loop perception–decision–action pipeline as the organizing principle. Within this framework, recent advances are synthesized from the perspectives of multimodal fusion, localization-aware sensing, motion planning, deep-learning-based phenotypic analysis, active observation, robotic intervention, and edge deployment. The review further clarifies the complementary roles of Unmanned Aerial Vehicles (UAVs), Unmanned Ground Vehicles (UGVs), and air–ground collaboration in multiscale phenotyping workflows. Beyond summarizing technologies, the article provides three concrete deliverables: a structured taxonomy of mobile phenotyping systems; comparative tables covering sensing modalities, localization/navigation methods, and AI models; and a research agenda linking technical progress to field deployability. The synthesis highlights four persistent bottlenecks, namely environmental generalization, annotation scarcity, limited standardization and reproducibility, and the gap between advanced models and agricultural edge hardware. Overall, ground robots are identified not merely as sensing platforms, but as the central system architecture for advancing mobile phenotyping toward autonomous, fine-grained, and field-deployable operation. Full article

Municipal solid waste disposed of in open dumpsites and unlined landfills contaminates groundwater, soils, and air across urban areas of low- and middle-income countries. Nevertheless, impacts across all three environmental media have not been systematically assessed together. We conducted a PRISMA 2020-compliant systematic review of 286 peer-reviewed studies from PubMed, Dimensions, and OpenAlex, applying structured eligibility screening and quality appraisal using an adapted JBI checklist. Heavy metals—lead, cadmium, chromium, and zinc—were the most frequently detected contaminants in leachate and groundwater, commonly exceeding WHO drinking water guidelines by one to three orders of magnitude. Soil contamination by potentially toxic elements was documented at virtually all open dumpsites studied, persisting for decades after site closure. Particulate matter at South Asian MSW sites reached up to 41 times the WHO 2021 annual guideline. Microplastics acting as heavy metal carriers and dumpsite leachate as a source of antimicrobial resistance genes were identified as emerging risks outside standard monitoring frameworks. Non-carcinogenic hazard indices exceeded acceptable thresholds in the majority of health risk studies reviewed. Engineered containment was the strongest predictor of contamination severity across all sites. Phytoremediation, constructed wetlands, and biofiltration showed promise as mitigation approaches. Critical evidence gaps remain for Central Asia, harmonized reporting standards, and longitudinal monitoring data. Full article

Atmospheric particulate matter poses a high risk by carrying potentially toxic components such as polycyclic aromatic hydrocarbons (PAHs). The major sources of these potentially toxic compounds include traffic-related emissions and winter heating, implying the combustion of fossil fuels or biomass. Air pollution, especially chronic exposure, poses the most serious human health hazard in childhood, and several studies emphasise the importance of research on the potential impacts of air pollution in school environments. While indoor air quality studies are already available in Hungary, investigations on outdoor air pollution in school environments are missing. To fill this gap, in a medium-sized Hungarian town, Veszprém, six schools were selected to assess air quality in the outdoor environments where schoolchildren spend their breaks and have physical training. These schools represent different locations and conditions, from high-trafficked sites to suburban environments. Using resuspended dust samples, environmental quality was assessed based on PAH contents of the samples and ecotoxicity tests (Vibrio fischeri bacterial bioassay). Ecotoxicity of the samples moved in a wide range, from highly toxic to non-toxic. PAH measurements indicated considerable contamination in the case of one sample taken from a suburban area. Source apportionment demonstrated that winter heating is also an important pollution source. Full article

This two-week pilot study within the Horizon Europe EDIAQI project evaluated the real-life performance of portable air filtration units in two office environments (a small office and a shared kitchen) under continuous device operation and daily filter replacement. Indoor particle concentrations were monitored continuously using low-cost sensors (LCS) from three providers and supported by gravimetric measurements, while daily activity logs documented occupancy patterns, printing, cooking, and other source events together with purifier ON/OFF status. Particulate matter (PM) mass concentrations showed no systematic improvement during purifier ON periods; instead, temporal variability was dominated by indoor activities and episodic emissions, with occasional short-term peaks around filter replacement suggestive of minor resuspension. Chemical analysis provided a clearer picture: polycyclic aromatic hydrocarbons (PAHs) responded differently across fractions and compositions. Across monitored locations, high-molecular-weight PAHs in the PM₁ fraction decreased during purifier ON periods (approximately 30% lower on average), whereas low-molecular-weight PAHs measured in total suspended particles (TSP) were higher during ON periods, indicating that semi-volatile fractions and activity/ventilation dynamics can outweigh simple filtration effects. Overall, the findings highlight a gap between laboratory-derived filtration performance metrics and outcomes in occupied, mixed-source indoor environments and emphasise the importance of device sizing, placement, airflow mixing, and complementary source control and ventilation strategies when deploying filtration-based IAQ interventions. Full article

Automated pavement distress classification using high-resolution Unmanned Aerial Vehicle (UAV) imagery is pivotal for intelligent transportation systems. However, long-term UAV monitoring faces a continuous stream of evolving distress types and changing remote sensing background textures, necessitating Class-Incremental Learning (CIL) capabilities. Existing methods struggle to balance stability and plasticity, especially under the severe storage limitations typical of local edge stations in air–ground collaborative systems. This data scarcity leads to catastrophic forgetting and confusion among fine-grained distress categories. To address these challenges, we propose a data-efficient approach named Analytic Geometric Alignment (AGA). Our framework mainly consists of three key components. First, to overcome the optimization gap between the feature extractor and the fixed geometric target, we introduce a Subspace-Aware Analytic Initialization (SAI) that computes a closed-form projection to instantly align the feature subspace with the ETF manifold before each task training. Second, on this aligned basis, a Decoupled Geometric Adapter (DGA) is incorporated to facilitate continuous non-linear adaptation to complex aerial textures. Finally, for stable incremental training, we design a Memory-Prioritized Regression (MPR) loss to enforce tighter geometric constraints on replay samples, significantly enhancing model stability. Extensive experiments on the UAV-PDD2023 dataset demonstrate that AGA significantly outperforms state-of-the-art methods, showcasing excellent robustness and data efficiency. Full article

Urban areas are increasingly exposed to water-related challenges, including flood risk and water scarcity, amplified by climate change, population growth, and extensive soil sealing. Addressing these pressures requires integrated stormwater management (SWM) strategies that balance hydraulic, environmental, and social objectives. This study introduces a novel, replicable Key Performance Indicator (KPI)-based assessment framework for 36 green–blue and grey sustainable stormwater management systems (SWMSs), designed to enable cross-typology, multiscale comparison. Six KPIs, encompassing flood regulation, water consumption, water quality, air quality, environmental amenity, and biodiversity potential, are derived through a critical synthesis and harmonisation of the literature and complemented with new parameters and sub-parameters to address existing methodological gaps. The framework structures evaluations into six analytical tables and one summary table, ensuring transparent, systematic, and comparative assessment of heterogeneous solutions. Application to a pilot project in Rome demonstrates how integrating KPI evaluation with parametric hydraulic modelling provides actionable insights for solution selection. It also facilitates identification of potential synergies between performance dimensions, enhancing its value as a decision-support tool in preliminary design. Overall, the study demonstrates the research value of multi-scalar, performance-based approaches for urban water planning, highlights the transferability of resilient stormwater strategies in climate-sensitive contexts, and identifies promising avenues for future research, including multi-sectoral integration, trade-off analysis, and cross-platform application. Full article

This study investigates the primary electromagnetic sources of acoustic noise in single-phase induction motors and proposes design-oriented strategies for noise reduction. A 370 W, four-pole, 80-frame single-phase induction motor was designed, analyzed, and experimentally validated. Finite Element Method (FEM) simulations were conducted using Ansys Maxwell 2D to examine the effects of magnetic field distortion, magnetic saturation, and rotor eccentricity on torque ripple and inductance variation. The results demonstrate that these factors significantly increase electromagnetic force harmonics acting on the stator teeth and frame, leading to vibration and acoustic noise generation. In addition, inductance fluctuations caused by interphase magnetic coupling and air-gap harmonics were found to increase current harmonic content and potentially excite structural resonances. The influence of capacitor selection and winding configuration on magnetic saturation, phase displacement, and torque ripple was systematically evaluated. Prototype motors were manufactured and acoustic noise measurements were performed to experimentally validate the simulation results. Unlike previous studies that often investigate these parameters separately, this work presents a coupled analysis that explicitly links capacitor selection, winding configuration, and rotor eccentricity to inductance variation, torque ripple, and acoustic noise generation. The findings provide practical design guidelines for the development of low-noise single-phase induction motors and contribute to reducing electromagnetic vibration and acoustic emissions in electric machine design. Full article

Most computational studies of vehicle hydroplaning have emphasized structural realism through fluid–structure interaction, tire deformation, tread geometry, and pavement surface characterization. By contrast, the hydrodynamics governing the flow in the tire vicinity, particularly the role of turbulence, have received comparatively limited attention. In a significant number of studies, the flow has been treated as laminar despite turbulent flow conditions, while in a few other studies turbulence modeling has been adopted without an explicit assessment of its impact on hydroplaning predictions. In this study, we present a simplified three-dimensional computational fluid dynamics (CFD) model designed to isolate the flow regimes governing hydroplaning and to quantify the mean effect of the turbulence modeling on the predicted hydroplaning speed. Using a finite-volume formulation with a volume-of-fluid representation of the air–water interface, the flow around and beneath a smooth 0.7 m-diameter tire sliding in locked-wheel mode over a flooded, nominally smooth pavement is simulated. The tire is represented as a rigid body with an idealized rectangular bottom patch whose area is determined from the tire load and inflation pressure, avoiding the need to prescribe a measured or assumed deformed footprint. Steady-state hydroplaning is modeled for a uniform upstream water film thickness of 7.62 mm with a 0.5 mm gap between the tire and the pavement, over tire inflation pressures ranging from approximately 100 to 300 kPa, and predictions are verified against the empirical NASA hydroplaning equation. For these conditions, simulations without turbulence closure exhibit a consistent, systematic underprediction of the hydroplaning speed of approximately 13.5% relative to the NASA relation. Incorporating turbulence effects through Reynolds-averaged closures substantially reduces this bias, with average deviations of about 6% for the realizable k–ε model and 2.4% for the shear stress transport (SST) k–ω model. An analysis of the results indicates that hydrodynamic lift is dominated by pressure buildup associated with stagnation at the lower leading edge of the tire, with a significant contribution from shear-dominated flow in the thin under-tire gap, and that turbulence acts to moderate the integrated lift from these pressure fields. These results demonstrate that explicitly accounting for turbulence in the tire vicinity is essential for reproducing empirical hydroplaning trends and for avoiding systematic bias in CFD-based hydroplaning predictions. Full article

This study examines the gap concerning occupants’ perceived thermal comfort and objectively measured indoor conditions in a green university building in Riyadh. The purpose is to assess occupant satisfaction with thermal conditions, compare subjective responses with physical measurements, and derive design and operational implications for educational buildings in hot-arid climates. The primary aim was to assess occupant satisfaction with indoor thermal conditions and to measure key environmental parameters to provide a thorough assessment of thermal comfort. A cross-sectional approach was used, combining subjective data from the Center for the Built Environment (CBE) Occupant Indoor Environmental Quality (IEQ) survey with objective measurements of air temperature, relative humidity, mean radiant temperature, and air velocity, which were documented over five consecutive working days during the mid-winter period in Riyadh. These parameters were explored using the CBE Thermal Comfort Tool to calculate Predicted Mean Vote (PMV) and Predicted Percentage Dissatisfied (PPD) indices. Statistical analyses examined the relationship between occupant-reported comfort and measured environmental conditions. Results showed that only 36% of occupants reported satisfaction with thermal comfort, while 48% expressed dissatisfaction. In contrast, objective measurements indicated stable indoor conditions within recommended comfort ranges (average temperature 23 °C, humidity 30–34%, MRT 24 °C, air velocity 0.5–1.0 m/s), with PMV values near neutral (−0.2 to 0.0) and PPD below 6%. The observed discrepancy highlights the influence of regional climate, individual adaptability, and perceived control. These findings emphasize the need to integrate both subjective feedback and objective measurements to develop occupant-centered strategies that enhance comfort and well-being in sustainable educational buildings in hot-arid climates. Full article

Membrane distillation (MD) is an attractive technology for desalination driven by renewable energy and low-grade heat sources. However, specific practical guidelines for intermittent operations, typical of such alternative energy sources, are still limited—particularly with respect to established shutdown measures to mitigate adverse effects on the overall system performance. The present study compares continuous and intermittent air-gap MD desalination at a lab-scale by evaluating performance parameters and scaling development. Apart from a slightly lower distillate productivity and a similar distillate quality under intermittent conditions, no direct difference in MD performance between continuous and intermittent experiments was detected. Nevertheless, online monitoring by image analysis with optical coherence tomography revealed more advanced scaling development during intermittent operation, with larger scaling volumes and cover ratios, particularly after implementing a membrane rinsing and preservation protocol with demineralized water. Membrane autopsies revealed that intermittency led to alterations in the development of the crystal morphology of predominantly CaCO₃ scaling. These changes were attributed to enhanced nucleation and modified growth kinetics triggered by recurring shutdown and start-up phases. Overall, the findings showed that intermittency had an adverse effect in terms of scaling behavior, highlighting the need for operating protocols tailored to each specific MD application. Full article

High-speed operation is a key pathway to higher power density in modern EV traction systems, and multi-parameter optimization is essential for enhancing its high-speed performance. This study investigates a 20,000 r/min interior double-V permanent-magnet flat-wire motor via finite-element simulations to systematically examine the effects of multiple interacting parameters—including flat-wire layer number, stator slot geometry, magnet grade, and rotor magnetic barrier angle—on the electromagnetic performance under high-speed operating conditions. The results indicate that increasing winding layers significantly reduces high-speed torque; an eight-layer design decreases torque by about 50% compared to a four-layer one, while a six-layer arrangement offers a favorable torque-loss trade-off. Wider slots lower the average torque but reduce torque ripple by approximately 27%, whereas deeper slots increase tooth flux density and reduce efficiency. Higher-grade magnets enhance air-gap flux and torque at elevated cost. Rotor magnet angle optimization reveals a trade-off between peak torque and ripple, with a symmetric 100°/100° design achieving balanced performance. These findings clarify structural–control interactions and support the multi-objective design of high-speed flat-wire permanent-magnet motors. Full article