Search Results (152)

Suspended solids (SS) and dissolved organic matter (DOM) in source water consume chlorine during disinfection, yet how this varies among SS fractions with different settling characteristics remains poorly understood. This study investigated chlorine consumption by SS fractions from Kiso River water using sequential centrifugation based on settleability. Raw water was fractionated into five settled SS fractions (F1–F5), an unsettled fine SS and DOM (W5), and a DOM fraction (W6) from 0.2 µm filtration of W5. Fractions F1–F3 reached complete consumption within 12 h, whereas F4 and F5 showed slower, sustained consumption over the full 72 h period. In contrast, W5 and W6 showed minimal chlorine consumption. The rapid and subsequent slower consumption phases were described by first-order and zero-order models, respectively. Normalization by particle number, total particle surface area, and turbidity showed that lower-settleability particles exhibited higher apparent chlorine reactivity per particle despite lower particle number and total particle surface area. Rate parameters normalized by dissolved organic carbon (DOC) concentration showed lower apparent DOM reactivity per unit DOC. These results demonstrate that particle settleability influences chlorine consumption and highlight particulate-associated constituents as important contributors to chlorine demand, with implications for prioritizing removal of fine, low-settleability particles in treatment. Full article

Blasting is an essential operation in surface mining, but it can generate high particulate matter concentrations within a short period. Accurate prediction of blast-induced dust concentration is useful for air quality management, worker protection, and dust control planning. In this study, an interpretable machine learning framework was developed to predict particulate matter with an aerodynamic diameter less than 10 μm (PM₁₀) and total suspended particulate matter (TSP) concentrations induced by blasting in a large surface coal mine. The dataset was derived from published field monitoring records and included blasting design parameters, monitoring distance, material-related variables, and measured dust concentrations. A total of 148 valid samples were used for model development and evaluation. Six tree-based ensemble models, including Extra Trees Regression, Random Forest, Gradient Boosting Regression Trees, extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and categorical boosting (CatBoost), were established and compared. Bayesian optimization was used for hyperparameter tuning, and model performance was evaluated using the coefficient of determination (R²), root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). Under the adopted 80:20 hold-out validation scheme, CatBoost achieved the best test performance for PM₁₀ prediction, with a test R² of 0.9555, RMSE of 444.87 μg/m³, and MAE of 343.48 μg/m³. Extra Trees Regression performed best for TSP prediction, with a test R² of 0.8803, RMSE of 3899.04 μg/m³, and MAE of 3036.27 μg/m³. Residual analysis further indicated that the optimal models had no obvious systematic bias. Shapley additive explanations (SHAP) analysis, supported by within-model feature importance rankings, showed that explosive quantity, number of blastholes, and monitoring distance were the dominant variables affecting PM₁₀ and TSP predictions. The explosive quantity and number of blastholes mainly increased the predicted dust concentration, whereas the monitoring distance generally reduced it. The proposed framework may provide useful support for blast parameter optimization, monitoring point arrangement, and dust control decision-making in surface mines, but further validation using larger multi-site datasets is still needed. Full article

Coastal waters of eastern Guangdong are important fishing grounds and ecologically sensitive areas in the northern South China Sea, where nekton communities are increasingly affected by environmental heterogeneity and human activities. However, systematic studies on the spatial differentiation and driving mechanisms of nekton communities in this region remain insufficient. This study aimed to clarify the community structure, diversity distribution characteristics, and key driving environmental factors of nekton in the coastal waters of eastern Guangdong, and thereby provide scientific support for an ecological health assessment and sustainable utilization of fishery resources in this region. Based on bottom-trawl survey data from 19 stations in the coastal waters of eastern Guangdong, northern South China Sea, this study systematically analyzed the species composition, dominant species, and diversity distribution pattern of nekton and their correlations with environmental factors using methods including the Index of Relative Importance, Alpha diversity indices, Beta diversity indices, and redundancy analysis. A total of 119 nekton species belonging to three phyla, four classes, 14 orders, and 56 families were collected. Among them, there were 79 fish species (accounting for 66.39%), 36 crustacean species (30.25%), and four cephalopod species (3.36%). The dominant species were Trachypenaeus curvirostris and Portunus sanguinolentus (IRI ≥ 1000). Wilcoxon’s test showed that there were significant differences in the Shannon–Wiener index, Gini–Simpson index, and Pielou’s evenness between the nearshore and offshore groups, while no significant regional difference was observed in the richness index. Cluster analysis, based on the Bray–Curtis distance, divided the 19 stations into five clusters, with significant differentiation in species composition and functional structure within the nearshore group. RDA results indicated that environmental factors collectively explained 99.66% of the variation in community structure. Particulate Inorganic Carbon (PIC), Phosphate (PO₄³⁻), Distance to Port, Summer Maximum Chlorophyll-a (Chl-a), and Total Suspended Matter (TSM) were identified as the key driving factors. The coastal waters of eastern Guangdong boast rich nekton species, with significant differences in community structure between nearshore and offshore areas. The heterogeneity of the natural environment and human activity disturbances jointly shape the nekton diversity pattern in this region. The research results can provide a theoretical basis for regional marine ecological protection and fishery resource management. Full article

Farmland particulate pollution seriously affects regional atmospheric quality, and exploring efficient field dust control strategies is an urgent need for agricultural ecological protection. This study employed a wind tunnel and online dust monitoring system to investigate the dust reduction effect of straw return in conservation tillage in Beijing farmland under varying wind speeds and precipitation levels, providing theoretical and technical support for straw coverage configuration and dust pollution control. Given the insufficient understanding of the combined impacts of straw coverage, wind speed and precipitation on farmland particulate emissions, this study examined how these key factors jointly affect fine particulate matter (PM_2.5), inhalable particulate matter (PM₁₀), and total suspended particulate (TSP) emissions. A three-factor, three-level response surface experiment modeled these relationships and identified optimal conditions for suppressing PM emissions—51.35% straw coverage, 3.96 m·s⁻¹ wind speed, and 32.36 mm precipitation—yielding average PM_2.5, PM₁₀, and TSP concentrations of 26.31, 31.71, and 42.43 μg·m⁻³, respectively. Field data showed that the mean absolute errors (MAEs) between predicted and measured concentrations were 0.52–5.80, 0.46–3.93, and 1.83–5.68 μg·m⁻³ for PM_2.5, PM₁₀, and TSP, respectively, corresponding to relative prediction accuracies of 90.42–97.95%, 95.03–98.52%, and 93.10–97.21%—indicating strong model accuracy. This approach enhances dynamic monitoring of straw return practices and guides rational field management. By integrating meteorological conditions and particulate emission characteristics, the model can quantitatively assess regional straw coverage and screen optimal straw mulching rates. It provides a clear data reference for decision-makers to formulate targeted dust prevention policies, standardize straw return regulation, and advance eco-friendly and sustainable agricultural production. Full article

Marine mucilage events are intensifying in semi-enclosed seas under accelerating climate- and nutrient-driven pressures, yet their ecosystem-level consequences for aquaculture-linked coastal habitats remain insufficiently documented. This study provides an integrated spatiotemporal assessment of water quality, phytoplankton community structure, and biometric responses of Mytilus galloprovincialis during and after the 2025 mucilage outbreak in the Gulf of Erdek (Sea of Marmara, Türkiye). Mucilage accumulation was associated with sharp increases in turbidity, total suspended solids, and particulate organic matter, alongside declines in dissolved oxygen and pH. Phytoplankton assemblages exhibited marked seasonal restructuring: the mucilage period was characterized by the coexistence of mucilage-forming taxa, non-toxic bloomers, and multiple harmful algal bloom (HAB) groups, including DSP- and ASP-related species, whereas post-mucilage conditions were dominated by non-toxic diatoms with substantially reduced HAB representation. The dinoflagellate species representing the May period in terms of abundance were Noctiluca scintillans and Prorocentrum micans; the diatom species were Chaetoceros radiatus, Cylindrotheca closterium, Pseudo-nitzschia pseudodelicatissima, and Thalassiosira rotula; and the coccolithophore was Phaeocystis pouchetii. Mussel biometric analyses revealed biometric indices and condition values markedly below regional historical baselines during the mucilage event, alongside reduced meat yield, followed by pronounced compensatory growth during the post-mucilage period. Our findings demonstrate that mucilage acts as both a physical and biological stressor, driving short-term ecological shifts in phytoplankton diversity and imposing substantial but reversible physiological impacts on mussel stocks. These results underscore the need for continuous biodiversity monitoring frameworks that integrate mucilage dynamics, HAB occurrence, and aquaculture resilience in regions vulnerable to climate-enhanced organic aggregate formation. 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

This study estimates the association between respiratory outcomes among employees of a secondary aluminum plant and airborne pollutants. Additionally, it looks into the relationship between pulmonary dysfunction in workers and X-Ray repair cross-complementing one (XRCC1) gene polymorphisms. 110 exposed workers and 58 non-exposed workers were enrolled in the study. Measurements were conducted on sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and particulate particles. Pulmonary function was tested. Eosinophil cationic protein (ECP), C-reactive protein (CRP), matrix metalloproteinase-1 (MMP-1), interleukin 6 (IL6), granulocyte-macrophage colony-stimulating factor (GM-CSF), XRCC1 protein, and genotyping of XRCC1 gene polymorphisms were examined. The annual average concentrations of particulate matter (PM_2.5, PM₁₀), total suspended particulates (TSP), SO₂, and NO₂ were lower than the permissible limit. The areas around ovens, evaporators, and cold rolling mills exhibited the highest amounts. The majority of employees in these departments had impaired lung function. Prolonged exposure was associated with a significant decrease in forced expiratory volume in 1 s (FEV1%) and forced vital capacity (FVC%) among the exposed group (p = 0.001 & 0.04, respectively). Serum XRCC1 levels were significantly higher among exposed workers (p = 0.02). Inflammatory biomarkers showed no statistically significant differences between groups. Aluminum workers are at risk of developing respiratory disorders. The level of serum XRCC1 may serve as a potential biomarker for detecting susceptible workers. Full article

Driven by rapid global urbanization and expanding urban footprints, air pollution, particularly from industrial emissions and vehicular exhaust, has intensified, with rising concentrations of inhalable particulate matter (PM) posing direct threats to public health. To address this challenge, we conducted field measurements of ambient PM concentrations across diverse urban plant communities and quantitatively compared their capacity to mitigate four key size-fractionated pollutants: total suspended particles (TSPs), PM₁₀, PM_2.5, and PM₁. Our objective was to identify the most effective plant community type for PM abatement in urban settings. Results demonstrate that: (1) evergreen broad-leaved forests exhibit the highest overall PM removal efficiency among all studied communities; (2) removal efficacy declines markedly with decreasing particle size, indicating limited capacity to capture ultrafine particles (e.g., PM₁); and (3) seasonal performance peaks in summer, especially for deciduous broad-leaved forests attributable to maximal leaf area index, enhanced stomatal activity, and favorable meteorological conditions. By rigorously evaluating species composition, canopy structure, and seasonal dynamics, this study provides empirically grounded guidance for evidence-based urban greening strategies aimed at optimizing airborne particulate mitigation worldwide. Full article

The wastewater generated during coffee processing contains high levels of acidity and organic matter, posing substantial environmental hazards, particularly in rural areas where traditional treatment methods are financially infeasible. This research assesses the field-scale effectiveness of Chrysopogon zizanioides (vetiver grass) in phytoremediation of coffee wastewater in Huánuco, Peru, with particular attention to how plant maturity affects treatment outcomes. A comparative analysis was performed on untreated and vetiver-filtered effluent from infiltration ponds at four growth stages (6, 8, 19, and 21 months), with measurements of pH, chemical oxygen demand (COD), biochemical oxygen demand (BOD₅), and suspended solids (TSS, SS) conducted according to standardized methods. The findings indicate notable improvements in water quality, as the pH rose from 4.07 ± 0.32 to 5.82 ± 0.40 (p < 0.001) and organic loads decreased by 39–41% (COD: 38,600 ± 12,100 to 23,000 ± 8500 mg L⁻¹ O₂; BOD₅: 27,700 ± 9400 to 16,500 ± 5600 mg L⁻¹ O₂). Total Suspended Solids (TSS) were reduced by 26%, while the settleable suspended solids fraction (SS) decreased by 69%, indicating strong particulate removal through combined filtration and sedimentation mechanisms. Mature vetiver stands (21 months old) showed better results, underscoring the importance of root development for effective phytoremediation. Strong correlations were observed between COD and BOD₅ (r = 0.92), while pH negatively correlated with organic and particulate parameters. The study presents empirical evidence supporting vetiver-based systems as an economical and sustainable approach to decentralized wastewater treatment in coffee-growing areas. Furthermore, it provides actionable insights for improving phytoremediation by focusing on plant maturity, which can be readily adapted for large-scale implementation in resource-constrained settings. The findings underscore the potential of nature-based technologies to address environmental challenges while supporting local economies dependent on coffee production. Full article

Urban rivers often contain a complex mixture of contaminants including per- and polyfluoroalkyl substances (PFAS), metals, and various salts. This study aimed to investigate the sediment–water partitioning characteristics of PFAS in urban rivers and analyze the hydrochemical causes of this specific feature. We sampled paired water and sediment samples from urban rivers in a reclaimed water irrigation area in Beijing City. The average total PFAS concentrations in the river water and sediment were 28.44 ± 16.37 ng/L and 6.41 ± 4.20 ng/g dw, respectively. Short-chain PFAS from C4 to C6 and PFCA congeners dominated in the water, while long-chain PFAS above C8 and PFSA congeners dominated in the sediment. The average sediment–water ratio (Log K_d) of PFAS at each site showed an increasing trend with chain length, and was generally higher than that observed in seawater, natural rivers, and lakes, indicating a specific sediment–water partitioning behavior of PFAS in urban rivers. This difference is likely due to the distinct hydrochemical characteristics of the urban rivers, where elevated TDS, the presence of surfactants, and the coexistence of multiple heavy metal ions collectively promote PFAS adsorption onto suspended particulate matter and enhance their accumulation in sediments through sedimentation. Full article

Giving consideration to cooking activity is important for sustainable housing. In contexts of limited ventilation, imposed by energy saving concerns, cooking causes deterioration of indoor air quality (IAQ) and occupants’ discomfort. This study presents a cooking event detection system that may support IAQ control to minimize the impact of cooking. The system consists of a multi-sensor device and a deep-learning neural network (DNN). The device monitors temperature (T), relative humidity (RH), suspended particulate matter (PM), CO₂, the responses of sensors to volatile organic compounds (VOCs), and other gases (NO₂, CO, CH₂O) in the kitchen zone. The collected data are processed by the DNN. The detection system generates a response every 7 s, indicating either ’COOKING’ or ’NO COOKING’. Feature vector selection was based on classification performance and cost considerations. Cooking event misdetections generate unjustified IAQ control costs: economic ones (UEC), when the system detects a non-existent event, and environmental ones (UEN), when the system fails to detect an actual event. In this study, several well-performing detection systems were developed, with miss rates ranging from 5.1% to 20.5% and false detection rates ranging from 7.7% to 11.7%. The results show that gas sensor responses—particularly to VOCs—had greater utility for cooking event detection compared with T, RH, CO₂, and PM. The cost analysis demonstrated that IAQ control supported by the developed cooking event detection systems could generate higher total unjustified environmental costs when the unit cost ratio UEN/UEC exceeded 1.25, or higher total unjustified economic costs when the unit cost ratio UEN/UEC was below 1.43. We believe this work will contribute to the development of novel automatic IAQ control systems supported by event detection. Full article

Non-point source pollution poses a severe threat to the water quality of the Li River. This study conducted field monitoring of pollution loads from different land-use types on Maozhou Island in the Li River during the 2023 rainy season. Runoff water quality from vegetable plots, orchards, and bamboo forests consistently exceeded standards, with vegetable plots being the primary source of pollution. Their total phosphorus (TP) concentration exceeded standards by nearly 25 times, contributing the highest annual load. The transport of pollutants (TP, total nitrogen(TN), chemical oxygen demand(COD_Cr)) was closely correlated with suspended solids (SS), with the finest particles (<5 μm) identified as the primary carrier exhibiting the strongest pollutant enrichment capacity (e.g., in vegetable fields, the correlation coefficient r between < 5 μm particles and TP was >0.85, p < 0.01). Rainfall patterns significantly influenced pollutant concentrations; TN and TP levels increased with preceding dry days, while phosphorus output from vegetable plots decreased with rising average rainfall temperature. Compared to bamboo forests, vegetable plots and orchards exhibited lower soil adsorption capacity. This study recommends a connectivity-based strategy prioritizing the interception of heavily enriched fine particulate matter (<5 μm) through runoff control and enhanced wetland retention functions. These findings underscore the importance of controlling fine particulate matter for reducing non-point source pollution and maintaining ecological health in the Lijiang River basin. Full article

Recently, how to improve the aquaculture efficiency of sea cucumber Apostichopus japonicus and promote the sustainable development of its artificial cultivation has become an increasingly important issue. The pond water environment plays important roles in the survival rate and growth of A. japonicus seedlings. This study investigated the changes in water quality and plankton from June to November in A. japonicus ponds. The seawater temperature, pH, dissolved oxygen, salinity, nitrogen, and active phosphate contents were measured, and the planktonic species were detected and identified. The results showed that the seawater temperature ranged from 11.2 to 29.9 °C, and the highest temperature did not exceed the tolerance survival limits of A. japonicus. The changes in pH, dissolved oxygen, and salinity were also suitable for growth. A total of six phyla and 14 species of planktonic algae were detected, among which diatoms were dominant, and the dominant species changed over time. In the early stage, it was Chroomonas acuta, then, after it was Nitzschia sp., and then it returned to C. acuta again later. The biomass and density of algae peaked in week 5 (p < 0.05), but decreased to their lowest in week 18. The changes in chlorophyll-a content were consistent with the biomass of algae. Both the chlorophyll-a and pheophytin contents peaked in weeks 5 and 10 (p < 0.05). The changes in suspended particulate matter (SPM) and particulate organic matter (POM) were synchronized, and they peaked in weeks 5 and 12. These results suggested that the planktonic algae have the functions of a food supply and an environmental indication, and changes in chlorophyll-a, pheophytin, SPM, and POM support the food source reserve for A. japonicus. This study provides important information for the artificial cultivation of sea cucumber seedlings in a pond, and it is useful to promote the sustainable development of the sea cucumber industry. Full article

An ongoing challenge in pelagic oceanography and limnology is to quantify and understand the distribution of suspended particles and particle aggregates with sufficient temporal and spatial fidelity to understand their dynamics. These particles include biotic (mesoplankton, organic fragments, fecal pellets, etc.) and abiotic (dusts, precipitates, sediments and flocks, anthropogenic materials, etc.) matter and their aggregates (i.e., marine snow), which form a large part of the total particulate matter > 200 μm in size in the ocean. The transport of organic material from surface waters to the deep-sea floor is of particular interest, as it is recognized as a key factor controlling the global carbon cycle and hence, a critical process influencing the sequestration of carbon dioxide from the atmosphere. Here we describe the development of an oceanographic instrument, the Pelagic Laser Tomographer (PLT), that uses high-resolution optical technology, coupled with post-processing analysis, to scan the 3D content of the water column to detect and quantify 3D distributions of small particles. Existing optical instruments typically trade sampling volume for spatial resolution or require large, complex platforms. The PLT addresses this gap by combining high-resolution laser-sheet imaging with large effective sampling volumes in a compact, deployable system. The PLT can generate spatial distributions of small particles (~100 µm and larger) across large water volumes (order 100–1000 m³) during a typical deployment, and allow measurements of particle patchiness over spatial scales to less than 1 mm. The instrument’s small size (6 kg), high resolution (~100 µm in each 3000 cm² tomographic image slice), and analysis software provide a tool for pelagic studies that have typically been limited by high cost, data storage, resolution, and mechanical constraints, all usually necessitating bulky instrumentation and infrequent deployment, typically requiring a large research vessel. Full article

Forest canopies effectively remove airborne particles, reducing the frequency of atmospheric haze and improving air quality as well as playing a crucial role in maintaining human health. In this study, we examined the retention of particulate matter by Picea crassifolia Kom. (P. crassifolia) needles using an aerosol regenerator in two typical catchments, while the concentrations of dissolved trace elements (Na, Zn, Pb, and Cd) were determined only in the Tianlaochi catchment. The results showed that the retention of airborne particles was lower in the Tianlaochi catchment (e.g., total suspended particles (TSP): 0.0049 μg cm⁻² in summer) than in the Sancha catchment (e.g., TSP: 0.0145 μg cm⁻²) in summer and autumn, while the opposite trend was found in winter and spring, with Tianlaochi catchment reaching higher TSP levels (0.0230 μg cm⁻² in spring) compared to Sancha catchment (0.0205 μg cm⁻²). The big tree exhibited the highest particulate retention, with a maximum flux of 84.870 μg cm⁻², indicating it was the most effective at particle trapping. The highest Na, Zn, Cd, and Pb values absorbed by the needle samples were 1.794 mg L⁻¹, 11.345 μg L⁻¹, 0.081 μg L⁻¹, and 4.316 μg L⁻¹, respectively. P. crassifolia needles absorbed more Na, Zn, and Cd in July and August than in June. The absorption capacity of the needles decreased in the order Na > Zn > Pb > Cd. P. crassifolia forest can effectively reduce airborne particulate matter. Our study provides a theoretical foundation to examine the role of forest ecosystems in the retention of atmospheric particulate matter in the Qilian Mountains region. Full article