Search Results (2,397)

Northern Thailand frequently suffers from severe PM2.5 air pollution, especially during the dry season, due to agricultural burning, local emissions, and transboundary haze. Understanding how pollution moves across regions and identifying source–receptor relationships are critical for effective air quality management. This study investigated the spatial and temporal dynamics of PM2.5 in northern Thailand. Specifically, it explored how pollution at one monitoring station influenced concentrations at others and revealed the seasonal structure of PM2.5 transmission using network-based analysis. We developed a Python-based framework to analyze daily PM2.5 data from 2022 to 2023, selecting nine representative stations across eight provinces based on spatial clustering and shape-based criteria. Delaunay triangulation was used to define spatial connections among stations, capturing the region’s irregular geography. Cross-correlation and Granger causality were applied to identify time-lagged relationships between stations for each season. Trophic coherence analysis was used to evaluate the hierarchical structure and seasonal stability of the resulting networks. The analysis revealed seasonal patterns of PM2.5 transmission, with certain stations, particularly in Chiang Mai and Lampang, consistently acting as source nodes. Provinces such as Phayao and Phrae were frequently identified as receptors, especially during the winter and rainy seasons. Trophic coherence varied by season, with the winter network showing the highest coherence, indicating a more hierarchical but less stable structure. The rainy season exhibited the lowest coherence, reflecting greater structural stability. PM2.5 spreads through structured, seasonal pathways in northern Thailand. Network patterns vary significantly across seasons, highlighting the need for adaptive air quality strategies. This framework can help identify influential monitoring stations for early warning and support more targeted, season-specific air quality management strategies in northern Thailand. Full article

Urban air pollution remains a significant environmental and public health issue, especially in European coastal cities such as Klaipėda. However, there is still a lack of local-scale knowledge on how land use structure influences pollutant distribution, highlighting the need to address this gap. This study addresses this by examining the spatial distribution of nitrogen dioxide (NO₂) concentrations in Klaipėda’s seaport city and several inland and coastal resort towns in Lithuania. The research specifically asks how different land cover types and demographic factors affect NO₂ variability and population exposure risk. Data were collected using passive sampling methods and analyzed within a GIS environment. The results revealed clear air quality differences between industrial/port zones and greener resort areas, confirmed by statistically significant associations between land cover types and pollutant levels. Based on these findings, a Land Use Pollution Pressure index (LUPP) and its population-weighted variant (PLUPP) were developed to capture demographic sensitivity. These indices provide a practical decision-support tool for sustainable urban planning, enabling the assessment of pollution risks and the forecasting of air quality changes under different land use scenarios, while contributing to local climate adaptation and urban environmental governance. Full article

The contamination due to coastal landfill is a growing environmental concern, particularly in fragile marine ecosystems, where leachate can mobilize toxic elements into soil, water, air, and sediment. This study aims to assess the impact of a coastal landfill in Al-Qunfudhah, western Saudi Arabia, on nearby coastal sediments by identifying the concentration, distribution, and ecological risk of potentially toxic elements (PTEs) using geospatial and multivariate analysis tools. The results indicate significant accumulation of Pb, Zn, Cu, and Fe, with Pb reaching alarming levels of up to 1160 mg/kg in the landfill area, compared to 120 mg/kg in the coastal sediments. Zn contamination also exhibited substantial elevation, with values reaching 278 mg/kg in landfill soil and 157 mg/kg in coastal sediment. The enrichment factor values indicate moderate to severe enrichment for Pb (up to 73.20) and Zn (up to 6.91), confirming anthropogenic influence. The contamination factor analysis categorized Pb contamination as very high (CF > 6), suggesting significant ecological risk. Comparison with sediment quality guidelines suggest that Pb, Zn, and Cu concentrations exceeded threshold effect levels (TEL) in some samples, posing potential risks to marine organisms. The spatial distribution maps revealed pollutant migration from the landfill toward the coastal zone, emphasizing the necessity of monitoring and mitigation strategies. As the first comprehensive study on landfill-induced PTEs contamination in Al-Qunfudhah, these findings provide essential insights for environmental management and pollution control policies along the Red Sea coast. Full article

This study examines the effect of elevated printing speeds (100–600 mm/s) on the dimensional accuracy and tensile strength of PLA components fabricated via fused deposition modeling (FDM). To isolate the influence of printing speed, all other parameters were kept constant, and two filament variants—natural (unpigmented) and black PLA—were analyzed. ISO 527-2 type 1A specimens were produced and tested for dimensional deviations and ultimate tensile strength (UTS). The results indicate that printing speed has a marked impact on both geometric precision and mechanical performance. The optimal speed of 300 mm/s provided the best compromise between dimensional accuracy and tensile strength for both filaments. At speeds below 300 mm/s, under-extrusion caused weak layer bonding and air gaps, while speeds above 300 mm/s led to over-extrusion and structural defects due to thermal stress and rapid cooling. Black PLA yielded better dimensional accuracy at higher speeds, with cross-sectional deviations between 2.76% and 5.33%, while natural PLA showed larger deviations of up to 8.63%. However, natural PLA exhibited superior tensile strength, reaching up to 46.59 MPa, with black PLA showing up to 13.16% lower UTS values. The findings emphasize the importance of speed tuning and material selection for achieving high-quality, reliable, and efficient FDM prints. Full article

Rapid industrialization and urbanization have progressed in Korea, yet public attention to hazardous pollutants emitted from industrial complexes remains limited. With the increasing coexistence of industrial and residential areas, there is a growing need for real-time monitoring and management plans that account for the rapid dispersion of hazardous air pollutants (HAPs). In this study, we conducted spatiotemporal data collection and analysis for the first time in Korea using real-time measurements obtained through mobile extractive differential optical absorption spectroscopy (Me-DOAS) mounted on a solar occultation flux (SOF) vehicle. The measurements were conducted in the Saha Sinpyeong–Janglim Industrial Complex in Busan, which comprises the Sasang Industrial Complex and the Sinpyeong–Janglim Industrial Complex. BTEX compounds were selected as target volatile organic compounds (VOCs), and real-time measurements of both BTEX and fine particulate matter (PM) were conducted simultaneously. Correlation analysis revealed a strong relationship between PM₁₀ and PM_2.5 (r = 0.848–0.894), indicating shared sources. In Sasang, BTEX levels were associated with traffic and localized facilities, while in Saha Sinpyeong–Janglim, the concentrations were more influenced by industrial zoning and wind patterns. Notably, inter-compound correlations such as benzene–m-xylene and p-xylene–toluene suggested possible co-emission sources. This study proposes a GIS-based, three-dimensional air quality management approach that integrates variables such as traffic volume, wind direction, and speed through real-time measurements. The findings are expected to inform effective pollution control strategies and future environmental management plans for industrial complexes. Full article

Wood, as a natural material that stores carbon, is gaining increasing attention and has potential for use in interior architectural applications. Given the long indoor stay time characteristic of modern society, it is important to scientifically understand the effects of indoor wood application on the occupants. In this study, three residential buildings with an identical area and structure were constructed with different degrees of wood coverage (0%, 45%, 90%) using Larix kaempferi. Subsequently, indoor air quality (IAQ) evaluations and relative humidity measurements were conducted to assess the physical and chemical changes in each environment. The IAQ in wooden and non-wooden environments met the recommended IAQ standards established in South Korea. The results of the 8-month observation showed that, the higher the wood coverage ratio, the more the indoor humidity fluctuations were alleviated, and, in the case of the 90% wood coverage ratio condition, the humidity was maintained 5.2% lower in the summer and 10.9% higher in the winter compared to the 0% condition. To further assess the physiological responses induced by the wooden environment, the heart rate variability (HRV) was measured and compared for 26 participants exposed to each environment for two hours. In environments with a 0% and 90% degree of wood coverage, no statistically significant differences were found in the participants’ HRV indicators. But, in the group exposed to the 45% wooden environment, the results showed an increase in HRV indicators, natural logarithm of high frequency power (lnHF): 4.87 → 5.40 (p < 0.05), and standard deviation of normal-to-normal intervals (SDNN): 30.57 → 38.48 (p < 0.05), which are known indicators of parasympathetic nervous system activation. Full article

Computational Fluid Dynamics (CFD) is regarded as an important tool for analyzing the flow field, thermal environment, and air quality around the built environment. However, for built environment applications, the high computational cost of CFD hinders large-scale scenario simulation and efficient design optimization. In the field of built environment research, surrogate modeling has become a key technology to connect the needs of high-fidelity CFD simulation and rapid prediction, whereas the low-dimensional nature of traditional surrogate models is unable to match the physical complexity and prediction needs of built flow fields. Therefore, combining machine learning (ML) with CFD to predict flow fields in built environments offers a promising way to increase simulation speed while maintaining reasonable accuracy. This review briefly reviews traditional surrogate models and focuses on ML-based surrogate models, especially the specific application of neural network architectures in rapidly predicting flow fields in the built environment. The review indicates that ML accelerates the three core aspects of CFD, namely mesh preprocessing, numerical solving, and post-processing visualization, in order to achieve efficient coupled CFD simulation. Although ML surrogate models still face challenges such as data availability, multi-physics field coupling, and generalization capability, the emergence of physical information-driven data enhancement techniques effectively alleviates the above problems. Meanwhile, the integration of traditional methods with ML can further enhance the comprehensive performance of surrogate models. Notably, the online ministry of trained ML models using transfer learning strategies deserves further research. These advances will provide an important basis for advancing efficient and accurate operational solutions in sustainable building design and operation. Full article

This current review examines modeling approaches for renovating reinforced concrete (RC) buildings for vertical forest (VF) application, taking into account structural retrofitting, energy systems, forestry integration, and occupant comfort. The study assesses research conducted with an advanced 3D finite element analysis and the use of retrofitting modeling techniques, including textile-reinforced mortar (TRM), fiber-reinforced polymer (FRP), seismic joints, and green concrete applications. The energy system modeling methods are reviewed, taking into account the complexity of incorporating vegetation and seasonal variations. During forestry integration, three main design parameters are identified, namely, root systems, trunks, and crowns, for their critical role in the structural stability and optimal environmental performance. The comfort models are identified evolving from static to adaptive models incorporating thermal, acoustic, visual and air quality parameters. The current review consists of more than one hundred studies indicating that the integration of natural systems to buildings requires a multidimensional and multidisciplinary approach with sophisticated systems. The findings of this review provide the basis for implementing VF models to RC buildings, while highlighting areas requiring further research and validation. Full article

This study examines the regional disparities in public perceptions of decarbonization and the acceptance of the bioeconomy within Western Macedonia, a Greek region undergoing structural economic change. While the environmental benefits of decarbonization, such as reduced carbon emissions and improved air quality, are widely acknowledged, perceptions of economic and social outcomes, including investments, new business development, and policy support, vary significantly across sub-regions. To this end, a structured survey was conducted among 765 residents, utilizing Likert-scale items to assess attitudes, with demographic data providing a contextual framework. Statistical analyses, incorporating techniques such as one-way analysis of variance (ANOVA), Kruskal–Wallis, and multiple regression, were employed to explore spatial variations and identify the primary drivers of bioeconomy acceptance. The results indicate that perceived government action, visible investment, new enterprises, and a positive view of public sentiment are all significant predictors of acceptance, with institutional support showing the strongest influence. The findings reveal that certain areas feel less engaged in the transition, expressing skepticism about its benefits, while others report more optimism. This disparity in perception underscores the necessity for targeted policy interventions to ensure inclusive and equitable participation. The study emphasizes the necessity for regionally responsive governance, enhanced communication strategies, and tangible local development initiatives to cultivate public trust and support. The study makes a significant contribution to the broader discourse on just transitions by emphasizing the role of place-based perceptions in shaping sustainable change. Full article

According to the World Health Organization (WHO), indoor air quality (IAQ) is becoming a serious global concern due to its significant impact on human health. However, not all relevant health parameters are currently regulated. For example, particle number concentration (PNC) and its associated carbonaceous species, such as black carbon (BC), which are classified as carcinogenic by the International Agency for Research on Cancer (IARC), are not currently regulated. Compared with IAQ studies in other types of buildings, studies focusing on IAQ in hospitals or other healthcare facilities are scarce. Therefore, this study aims to evaluate the impact of these outdoor pollutants, among others, on the indoor environment of a hospital under different atmospheric conditions. To identify the seasonal influence, two different periods of two consecutive seasons (summer 2020 and winter 2021) were selected for the measurements. Regulated pollutants (NO, NO₂, O₃, PM₁₀, and PM_2.5) and nonregulated pollutants (PM₁, PNC, and equivalent BC (eBC)) in outdoor air were simultaneously measured indoor and outdoor. This study also investigated the impact of indoor activities on indoor air quality. In the absence of indoor activities, outdoor sources significantly contribute to indoor traffic-related pollutants. Indoor and outdoor (I-O) measurements showed similar behavior, but indoor concentrations were lower, with peak levels delayed by up to two hours. Seasonal variations in indoor/outdoor ($\mathrm{I}/\mathrm{O}$) ratios were lower for particles than for associated gaseous pollutants. Particle infiltration depended on particle size, with it being higher the smaller the particle size. Indoor activities also significantly affected indoor pollutants. PM_x (especially PM₁₀ and PM_2.5) concentrations were mainly modulated by walking-induced particle resuspension. Vertical eBC profiles indicated a relatively well-mixed environment. Ventilation through open windows rapidly altered indoor air quality. Outdoor-dominant pollutants (PNC, eBC, and NO_X) had $\mathrm{I}/\mathrm{O}$ ratios ≥ 1. Staying in the room with an open window had a synergistic effect, increasing the $\mathrm{I}/\mathrm{O}$ ratios for all pollutants. Higher I/O ratios were associated with turbulent outdoor conditions in both unoccupied and occupied conditions. Statistically significant differences were observed between stable (TKE ≤ 1 m² s⁻²) and unstable (TKE > 1 m² s⁻²) conditions, except for NO₂ in summer. This finding was particularly significant when the wind direction was westerly or easterly during unstable conditions. The results of this study highlight the importance of understanding the behavior of indoor particulate matter and related pollutants. These pollutants are highly variable, and knowledge about them is crucial for determining their health effects, particularly in public buildings such as hospitals, where information on IAQ is often limited. More measurement data is particularly important for further research into I-O transport mechanisms, which are essential for developing preventive measures and improving IAQ. Full article

The present study was motivated by the need to enhance indoor air quality and reduce airborne disease transmission in dense urban environments where high-rise residential buildings face challenges in achieving effective natural ventilation. The problem lies in the lack of scalable and convenient tools to optimize natural ventilation rate, particularly in urban settings with varying building heights. To address this, the scientific technique developed with an innovative metric, the urbanized natural ventilation effectiveness factor (uNVeF), integrates regression analysis of wind direction, velocity, air change rate per hour (ACH), window configurations, and building height to quantify ventilation efficiency. By employing a field measurement methodology, the measurements were conducted across 25 window-opening scenarios in a 13.9 m² residential unit on the 35/F of a Hong Kong public housing building, supplemented by the Hellman Exponential Law with a site-specific friction coefficient (0.2907, R² = 0.9232) to estimate the lower floor natural ventilation rate. The results confirm compliance with Hong Kong’s statutory 1.5 ACH requirement (Practice Note for Authorized Persons, Registered Structural Engineers, and Registered Geotechnical Engineers) and achieving a peak ACH at a uNVeF of 0.953 with 75% window opening. The results also revealed that lower floors can maintain 1.5 ACH with adjusted window configurations. Using the Wells–Riley model, the estimation results indicated significant airborne disease infection risk reductions of 96.1% at 35/F and 93.4% at 1/F compared to the 1.5 ACH baseline which demonstrates a strong correlation between ACH, uNVeF and infection risks. The uNVeF framework offers a practical approach to optimize natural ventilation and provides actionable guidelines, together with future research on the scope of validity to refine this technique for residents and developers. The implications in the building industry include setting up sustainable design standards, enhancing public health resilience, supporting policy frameworks for energy-efficient urban planning, and potentially driving innovation in high-rise residential construction and retrofitting globally. Full article

Mercury (Hg) poses a significant threat to human health and ecosystems, garnering increased attention in environmental studies. This paper evaluates the dynamics of Hg accumulation in various common tree leaves, specifically white poplar, linden, and cherry plum, throughout their growing season. The findings offer valuable insights into air quality and the ability of urban vegetation to mitigate mercury pollution in urban areas. A case study was conducted in Turda, a town in northwestern Romania, where a former chlor-alkali plant operated throughout the last century. Although the plant ceased its electrolysis activities over 25 years ago, the surrounding soil remains contaminated with mercury (Hg) due to the significant amounts released during its operation. The results indicated that the Hg concentration varied between 2.4 and 7.3 mg kg⁻¹ dry weight (dw), exceeding the intervention threshold for soil of 2.0 mg kg⁻¹. Additionally, the Hg content in the leaf samples consistently increased over time, influenced by leaf age and tree species. The Hg content increased in the following order: cherry plum < white poplar < linden. On average, white poplar leaves accumulated 72 ng Hg g⁻¹ dw, linden leaves 128 ng Hg g⁻¹ dw, and cherry plum leaves 47 ng Hg g⁻¹ dw during the six-month monitored period from April to September. The results obtained can be used to evaluate the potential of different tree species for mitigating atmospheric Hg contamination and to elaborate on the suitable management of fallen leaves in the autumn. Full article

This study assessed the baseline indoor environmental quality (IEQ) of secondary school classrooms in Tanzania by measuring temperature, relative humidity, noise, lighting, and indoor air quality. Objective measurements were conducted using calibrated sensors in 14 classrooms across five schools, with data collected during occupied school hours and additional noise measurements during unoccupied periods. All classrooms are naturally ventilated through operable windows and doors. The findings reveal a pattern of cumulative IEQ deficiencies: classroom temperatures frequently exceeded the recommended 20–24 °C range, reaching means as high as 30.4 °C, while relative humidity varied widely, with levels occasionally surpassing 65%. Noise levels consistently exceeded the World Health Organization (WHO)’s recommended 35 dBA threshold, with significant differences observed between occupied and unoccupied periods (p = 0.02). Light distribution was uneven, with significantly higher lux levels near windows than at classroom centers (p < 0.001), and artificial lighting was generally insufficient due to infrastructure limitations. Although CO₂ concentrations remained below the 1000 ppm threshold, indicating adequate ventilation, particulate matter levels were often elevated, with PM2.5 reaching up to 58.80 µg/m³ and PM10 up to 96.90 µg/m³, exceeding health-based guidelines. Together, these findings suggest that students are exposed to multiple environmental stressors that may impair health, comfort, and academic performance. This study provides a critical baseline for future research and context-specific interventions aimed at improving learning environments in Tanzanian schools and similar settings in East Africa. Full article

This study investigates the impact of teacher decisions and other contextual factors on indoor air quality (IAQ) in mechanically ventilated elementary school classrooms using low-cost air quality sensors. Four classrooms at a K–8 school in San Jose, California, were monitored for airborne particulate matter (PM), carbon dioxide (CO₂), temperature, and humidity over seven weeks. Each classroom was equipped with an HVAC system and a portable air cleaner (PAC), with teachers having full autonomy over PAC usage and ventilation practices. Results revealed that teacher behaviors, such as the frequency of door/window opening and PAC operation, significantly influenced both PM and CO₂ levels. Classrooms with more active ventilation had lower CO₂ but occasionally higher PM_2.5 due to outdoor air exchange, while classrooms with minimal ventilation showed the opposite pattern. An analysis of PAC filter material and PM morphology indicated distinct differences between indoor and outdoor particle sources, with indoor air showing higher fiber content from clothing and carpets. This study highlights the critical role of teacher behavior in shaping IAQ, even in mechanically ventilated environments, and underscores the potential of low-cost sensors to support informed decision-making for healthier classroom environments. Full article

Air pollution monitoring in ungauged zones presents unique challenges yet remains critical for understanding environmental health impacts and socioeconomic dynamics in the Eastern Mediterranean region. This study investigates air pollution patterns in northwestern Syria during 2019–2024, analyzing NO₂ and CO concentrations using Sentinel-5P TROPOMI satellite data processed through Google Earth Engine. Monthly concentration averages were examined across eight key locations using linear regression analysis to determine temporal trends, with Spearman’s rank correlation coefficients calculated between pollutant levels and five meteorological parameters (temperature, humidity, wind speed, atmospheric pressure, and precipitation) to determine the influence of political governance, economic conditions, and environmental sustainability factors on pollution dynamics. Quality assurance filtering retained only measurements with values ≥ 0.75, and statistical significance was assessed at a p < 0.05 level. The findings reveal distinctive spatiotemporal patterns that reflect the region’s complex political-economic landscape. NO₂ concentrations exhibited clear political signatures, with opposition-controlled territories showing upward trends (Al-Rai: 6.18 × 10⁻⁸ mol/m²) and weak correlations with climatic variables (<0.20), indicating consistent industrial operations. In contrast, government-controlled areas demonstrated significant downward trends (Hessia: −2.6 × 10⁻⁷ mol/m²) with stronger climate–pollutant correlations (0.30–0.45), reflecting the impact of economic sanctions on industrial activities. CO concentrations showed uniform downward trends across all locations regardless of political control. This study contributes significantly to multiple Sustainable Development Goals (SDGs), providing critical baseline data for SDG 3 (Health and Well-being), mapping urban pollution hotspots for SDG 11 (Sustainable Cities), demonstrating climate–pollution correlations for SDG 13 (Climate Action), revealing governance impacts on environmental patterns for SDG 16 (Peace and Justice), and developing transferable methodologies for SDG 17 (Partnerships). These findings underscore the importance of incorporating environmental safeguards into post-conflict reconstruction planning to ensure sustainable development. Full article