Search Results (2,347)

The Soil and Water Assessment Tool (SWAT) model is extensively used globally for hydrological and water quality assessments but encounters challenges in karst regions due to their complex surface and groundwater hydrological environments. This study aims to refine the delineation of hydrological response units within the SWAT model by combining geomorphological classification and to enhance the model with an epikarst zone hydrological process module, exploring the accuracy improvement of SWAT model simulations in karst regions of Southwest China. Compared with the simulation results of the original SWAT model, we simulated runoff and nutrient concentrations in the Mudong watershed from January 2017 to December 2021 using the improved SWAT model. The simulation results indicated that the modified SWAT model responded more rapidly to precipitation events, particularly in bare karst landform, aligning more closely with the actual hydrological processes in Southwest China’s karst regions. In terms of the predictive accuracy for monthly loads of total nitrogen (TN) and total phosphorus (TP), the coefficient of determination (R²) value of the modified model increased by 10.3% and 9.7%, respectively, and the Nash–Sutcliffe efficiency coefficient (NSE) increased by 11.3% and 9.9%, respectively. The modified SWAT model improves prediction accuracy in karst areas and holds significant practical value for guiding non-point source pollution control in agricultural watersheds. Full article

To achieve sustainable swimming pool water management, it is necessary to minimize the consumption of energy, water, and chemical agents to maintain the appropriate water quality. Some of the pollutants are introduced by swimmers and can be relatively easily removed if swimmers take a shower before entering a pool. Thus, this research questions how much of an impact this simple act could have on the water quality and generally on sustainable water management in swimming pools. To address this question, experiments were conducted at the AGH Swimming Pool in Kraków, in a real facility—a hot tub—with the participation of volunteers who took a shower in Variant 1 and did not in Variant 2. The assessment was made on the basis of selected microbiological and physicochemical parameters of swimming pool water, including disinfection by-products. The research results proved that taking a shower can significantly reduce the load of pollutants users introduce into swimming pool water and can contribute to more efficient and ecological treatment of swimming pool water and minimize the negative impact on the health of swimming pool users (microbiological contaminants and precursors of harmful chlorination by-products). Full article

Acid mine drainage (AMD) forms in mining areas during or after mining operations cease. This is a primary cause of environmental pollution and poses risks to human health and the environment. The hydrographic system from the Maramureș mining industry (especially the Baia Mare area) was heavily contaminated with heavy metals for many years due to mining activity, and after the closing of mining activity, it continues to be polluted due to water leaks from the abandoned galleries, the pipes, and the tailing ponds. The mineralization in the Băiuț area, predominantly represented by pyrite and marcasite associated with other sulfides, such as chalcopyrite, covelline, galena, and sphalerite, together with mine waters contribute to the formation of acid mine drainage. The Breiner-Băiuț mining gallery (copper mine) permanently discharges acidic water into the rivers. The efficiency of iron scrap (low-cost absorbent) for the treatment of mine water from this gallery was investigated. The treatment of mine water with iron shavings aimed to reduce the concentration of toxic metals and pH. Mine water from the Breiner-Baiut mine, Romania, is characterized by high acidity, pH = 2.75, and by the association of many heavy metals, whose concentration exceeds the limit values for the pollutant loading of wastewater discharged into natural receptors: Cu—71.1 mg/L; Zn—42.5 mg/L; and Fe—122.5 mg/L. Iron scrap with different weights (200 g, 400 g, and 600 g) was put in contact with 1.5 L of acid mine water. After 30 days, all three treatment variants showed a reduction in the concentrations of toxic metals. A reduction in Cu concentration was achieved below the permissible limit. In all three samples, the Cu concentrations were 0.005 for Sample 1, 0.001 for Sample 2, and <LOQ for Sample 3. The Zn concentration decreased significantly compared to the original mine water concentration from 42.5 mg/L to 1.221 mg/L, 1.091 mg/L, and 0.932 mg/L. These values are still above the permissible limit (0.5 mg/L). The Fe concentration increased compared to the original untreated water sample due to the dissolution of iron scrap. This research focuses on methods to reduce the toxic metal concentration in mine water, immobilizing (separating) certain toxic metals in sludge, and immobilizing various compounds on the surface of iron shavings in the form of insoluble crystals. Full article

Biopolymer-based nanocomposite film is an efficient material for addressing the increasing levels of pollutants in the environment and also for the production of antimicrobial packing material due to its good film-forming properties, biodegradability, and minimal environmental impact. In particular, chitosan/polyvinyl alcohol/g-C₃N₄ (CS/PVA/g-C₃N₄) nanocomposite films with different weight percentages of PVA were prepared using simple methodologies and characterized using XRD, TGA, FT-IR, DSC, FE-SEM, EDX, and elemental mapping analysis. The XRD and FT-IR results validated the nanocomposite film formation. The FE-SEM images showed the smooth surface of the composite films without any wrinkles; the smoothness of the film increased with increases in the PVA loading, and the surface morphologies of the films were largely unchanged. The EDX and elemental mapping analysis validated the presence and uniform dispersion of g-C₃N₄ within the nanocomposite film. The photocatalytic activity of the CS/PVA/g-C₃N₄ composite films was assessed by the degradation of rhodamine B dye (RhB) and acetophenone under direct sunlight irradiation. The CS/PVA/g-C₃N₄ nanocomposite films exhibited superior degradation efficiency toward the RhB dye and acetophenone compared to the bare polymeric film and the g-C₃N₄ material. The order of degradation for the RhB dye and acetophenone was CS/PVA (1.0) g-C₃N₄ (95.34%, 33.33%) > CS/PVA (1.5) g-C₃N₄ (93.18%, 31.31%) > CS/PVA (0.5) g-C₃N₄ (93.02%, 29.29%) > CS/PVA (90.69%, 26.26%) > g-C₃N₄ (87.56%, 24%), respectively. Furthermore, the antimicrobial activity of the nanocomposite films was tested against E. coli, Pseudomonas sps., Klesiella sps., and Enterococcus sps., and the CS/PVA (1.5)/g-C₃N₄ nanocomposite film offered better antimicrobial properties than the other composite films and bare materials. In conclusion, these biopolymer-based nanocomposites are highly efficient and provide a promising path for the development of various biodegradable polymeric nanocomposites for environmental remediation and antibacterial packing applications. Full article

Global warming and climate change demand rapid and swift action in terms of reducing resource consumption, gas emissions, and waste generation. The textile industry is responsible for a large share of global pollution; therefore, to define a route to tackle part of the issue, a literature review on the current state of research in the field of recycling silk waste was conducted. The methods used to recover, process, and characterize silk waste fibers were summarized. The aim of this work was to investigate the possible applications of recycled silk waste in the field of composite materials for load bearing applications. In this sense, some prominent studies in the field of silk-based composites were reported, favoring thermoplastic materials for sustainability reasons. Studies on nonwoven silk waste fabrics were covered as well, finding an abundance of results but no applications as a reinforcement for composite materials. In a circular economy approach, we believe that the combination of nonwoven silk waste fabrics, thermoplastic polymers, and possibly hybridization with other fibers from sustainable sources could be beneficial and could lead to green and high-performance products. The aim of this work was to summarize the information available so far and help define a route in that direction. Full article

This research proposed the method of using cumulative positive and negative elevation increment indicators based on road segment to identify the slope characteristics of mountain city roads. Furthermore, it proposed the adoption of these indicators, combined with driving dynamics and emission theory, to analyze the correlation mechanism between the road slope and the actual driving fuel consumption and emissions. Three routes with different slope characteristics were selected in the mountain city of Chongqing, and six road driving tests were conducted using a Class N2 heavy-duty diesel vehicle. Finally, a comprehensive and in-depth study on fuel consumption and emission characteristics was carried out. The results show that the cumulative positive and negative elevation increment indicators based on road segment can correctly identify the complex slope characteristics of mountain city roads. Moreover, using the above indicators, the research method based on the theory of driving dynamics and emission successfully revealed the correlation mechanism between the slope of mountain city roads and the fuel consumption and emissions. Overall, the changes in fuel consumption factor and pollutants CO, NO_X, and PN are positively correlated with the change in slope. The increase in slope leads to a rise in load, thereby increasing the required power, fuel consumption, and rich combustion conditions, ultimately leading to an increase in pollutants. It should be noted that driving dynamics also affect fuel consumption and emissions, leading to the specific rate of change between slope and fuel consumption not being consistent and a significant increase in the PN (Particulate Number) on some road sections. In addition, exhaust gas temperature may have a certain impact on emissions. Full article

Pollution is one of the most important issues currently affecting the global population and environment. Therefore, determining the zones where stringent measures should be taken is necessary. In this study, Principal Component Analysis (PCA), Factor Analysis (FA), and t-distributed Stochastic Neighbor Embedding (t-SNE) were utilized for dimensionality reduction and clustering of data series containing the concentration of 10 heavy metals collected at 14 locations. The Hazard Quotient (HQ) and Hazard Index (HI) were utilized to determine the non-carcinogenic risk to the population in the studied zones. The highest concentrations of metals in the samples were those of Fe, Zn, Mn, and Cr. PCA indicated that Fe and Zn (Co and Cd) had the highest contribution on the first (second) Principal Component (PC). FA showed that the three-factor model is adequate for explaining the variability of pollutant concentrations. The factor loadings revealed the strength of association between variables and factors, e.g., 0.97 for Zn, 0.83 for Cr, and 0.99 for Co. HQ for ingestion, ${HQ}_{ing},$ was the highest for Fe (between 6.10 × 10⁻⁵ and 2.57 × 10⁻⁴). HQ for inhalation, ${HQ}_{inh}$, was the biggest for Mn (from 1.41 × 10⁻³ to 1.95 × 10⁻³). HI varied in the interval [0.172, 0.573], indicating the absence of a non-carcinogenic risk. However, since values above 0.5 were determined at four sites, continuous monitoring of the pollution in the sampling locations is necessary. Full article

This study proposes a multi-energy complementary heating system that uses solar energy combined with biomass energy as the main heat source, with electricity as an auxiliary heat source. The system aims to tackle the low efficiency, high energy consumption, and pollution associated with traditional heating methods in rural southern Xinjiang, enhancing performance and productivity. It is designed to operate in five modes based on the region’s climate and building heat load requirements. An experimental platform was set up in eight rural households in Tumushuk City, Xinjiang, where winter heating tests were conducted. The goal of this study was to analyze the economic and environmental benefits of the system. The results showed that the energy utilization efficiencies of the five modes were 56.84%, 74.34%, 70.1%, 63.13%, and 59.68%. The corresponding CO₂ emissions were 3.56 kg/d, 45.09 kg/d, 105.75 kg/d, 30.97 kg/d, and 76.79 kg/d. The environmental and economic costs for each mode were 0.0493 USD/d, 0.6398 USD/d, 1.5029 USD/d, 0.4384 USD/d, and 1.0905 USD/d. It is clear that as an auxiliary heat source, biomass energy is more beneficial than electricity. All five modes maintained indoor temperatures of 18 °C or higher, meeting winter heating needs in cold regions. The results of this study provide important data support for the promotion and application of solar and biomass heating systems in the rural areas of southern Xinjiang and also provide valuable references for solving the problem of decentralized heating in rural areas. Full article

In recent years, the growth of utilizing rural microgrids (RMGs) has been accompanied by various challenges. These necessitate the development of appropriate models for optimal generation in RMGs and RMGs’ coordination. In this paper, two distinct models for RMGs are presented. The first model includes an islanded rural microgrid (IRMG) and the second model consists of three RMGs that are interconnected with one another and linked to the distribution network. The proposed models take into account the uncertainty in load, photovoltaics (PVs), and wind turbines (WTs) with consideration of their correlation by using a scenario-based technique. Three objective functions are defined for optimization: minimizing operational costs including maintenance and fuel expenses, reducing voltage deviation to maintain power quality, and decreasing pollution emissions from fuel cells and microturbines. A new optimization method, namely the Improved Multi-Objective Crow Search Algorithm (IMOCSA), is proposed to solve the problem models. IMOCSA enhances the standard Crow Search Algorithm through three key improvements: an adaptive chaotic awareness probability to better balance exploration and exploitation, a mutation mechanism applied to the solution repository to prevent premature convergence, and a K-means clustering method to control repository size and increase algorithmic efficiency. Since the proposed problem is a multi-objective non-linear optimization problem with conflicting objectives, the idea of the Pareto front is used to find a group of optimal solutions. To assess the effectiveness and efficiency of the proposed models, they are implemented in two different case studies and the analysis and results are illustrated. Full article

Modeling non-point source pollution dynamics in inland lake basins is essential for safeguarding water quality, maintaining ecosystem integrity, protecting public health, and advancing long-term environmental sustainability. This study explores non-point pollution dynamics in the Sapanca Lake basin, Turkey, in association with the basin’s land use, land cover, hydrology, pollutant sources, and water quality parameters. The required data were gathered via a three-year monitoring program, which was carried out at 12 sampling stations around the lake, as well as using the collecting field measurements and GIS databases. Stepwise multiple regression analysis was employed to determine the best relation between non-point pollutants and land features. The results showed that urbanization and population density have significant correlations with the total nitrogen (TN) and total phosphorus (TP) in the study areas. Rivers crossing pristine areas, such as forests and uncultivated lands, demonstrated better water quality, thereby positively contributing to the lake ecosystem conservation. The highest nutrient loads were observed in streams that flow through highly urbanized sub-basins, followed by predominantly agricultural areas. This is likely due to runoff from urban environments, leaching from cultivated land, and contributions from livestock and tourism facilities. Conversely, densely forested regions exhibited the lowest levels of nutrient loads, highlighting their capacity for nutrient retention. The peak levels of non-point source pollution (TN = 5.22 mg/L and TP = 0.53 mg/L) were recorded in catchments with the highest degree of urbanization, whereas the lowest values (TN = 0.28 mg/L and TP = 0.04 mg/L) were found in the least urbanized areas. These findings emphasize that nutrients primarily impact water quality because of increasing urban and agricultural activities, while forested land plays a vital role in preserving lake water quality. To ensure sustainable water quality in lake basins, it is essential to strike a careful balance between protective measures and utilization policies, prioritizing conservation efforts. Full article

The total maximum daily load (TMDL) system divides the watershed into unit basins for implementation and evaluates water quality by assessing whether targets have been achieved based on investigated data through continuous monitoring. River water quality is influenced by the amount and type of pollutants entering the river, making continuous monitoring, along with analysis and evaluation, essential for the ongoing development of policies and systems aimed at improving water quality. In this study, basic data for water quality management were gathered by analyzing the pollution contributions of the main river (the Seomjin River) and its tributaries, identifying major pollutant sources, and conducting trend analyses. The delivery pollution load of the Seombon D unit basin, one of the main watersheds of the Seomjin River in South Korea, shows a rapid increasing trend (BOD, 1.2–2.4, 2020), which is different from the trend in the B unit watershed of the Boseong River, also a tributary. The rapid increase is presumed to be due to the characteristics of Seombon D, including the inflow of pollution sources of Seombon C, an upstream point. The D unit basin of Seombon is located in the middle of the unit watersheds that divide the main stream of the Seomjin River in Korea into A, B, C, D, E, and F. This increase is thought to be due to the inflow of pollutants specific to Seombon D’s characteristics and the influence of the upstream Seombon C unit basin. In the pollution load contribution rate analysis of Seombon D, it was found that the contribution rate from Seombon C, the upstream area (BOD, 38.42–120.08%), was higher than that of the Boseong B unit basin tributary. The self-purification capacity of Seombon D is believed to have contributed to the improvement in its water quality. It is essential to manage the upstream Seombon C unit basin to sustainably improve the water quality of the Seombon D unit basin. Therefore, managing Seombon C is deemed necessary to further enhance the water quality of Seombon D. Full article

Background: Chronic stress, characterized by sustained activation of physiological stress response systems, is a key risk factor for numerous health conditions. Allostatic load (AL), a biomarker of cumulative physiological stress, offers a quantitative measure of this burden. Lifestyle habits such as alcohol consumption and smoking, alongside environmental exposures to toxic metals like lead, cadmium, and mercury, were individually implicated in increasing AL. However, the combined impact of these lifestyle habits and environmental factors remains underexplored, particularly in populations facing co-occurring exposures. This study aims to investigate the joint effects of lifestyle habits and environmental factors on AL, using data from the NHANES 2017–2018 cycle. By employing linear regression and Bayesian Kernel Machine Regression (BKMR), we identify key predictors and explore interaction effects, providing new insights into how cumulative exposures contribute to chronic stress. Results from BKMR analysis underscore the importance of addressing combined exposures, particularly the synergistic effects of cadmium and alcohol consumption, in managing physiological stress. Methods: Descriptive statistics were calculated to summarize the dataset, and multivariate linear regression was performed to assess associations between exposures and AL. BKMR was employed to estimate exposure–response functions and posterior inclusion probabilities (PIPs), focusing on identifying key predictors of AL. Results: Descriptive analysis indicated that the mean levels of lead, cadmium, and mercury were 1.23 µg/dL, 0.49 µg/dL, and 1.37 µg/L, respectively. The mean allostatic load was 3.57. Linear regression indicated that alcohol consumption was significantly associated with increased AL (β = 0.0933; 95% CI [0.0369, 0.1497]; p = 0.001). Other exposures, including lead (β = −0.1056; 95% CI [−0.2518 to 0.0408]; p = 0.157), cadmium (β = −0.0001, 95% CI [−0.2037 to 0.2036], p = 0.999), mercury (β = −0.0149; 95% CI [−0.1175 to 0.0877]; p = 0.773), and smoking (β = 0.0129; 95% CI [−0.0086 to 0.0345]; p = 0.508), were not significant. BKMR analysis confirmed alcohol’s strong importance for AL, with a PIP of 0.9996, and highlighted a non-linear effect of cadmium (PIP = 0.7526). The interaction between alcohol and cadmium showed a stronger effect on AL at higher exposure levels. In contrast, lead, mercury, and smoking demonstrated minimal effects on AL. Conclusions: Alcohol consumption and cadmium exposure were identified as key contributors to increased allostatic load, while other exposures showed no significant associations. These findings emphasize the importance of addressing lifestyle habits and environmental factors in managing physiological stress. Full article

Road dust carries various contaminants and causes urban non-point source pollution in waterbodies through runoff. Road dust samples were collected in each month in two years and then sieved into five particle size fractions. The concentrations of ten heavy metals (As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Zn, Fe) in each fraction were measured. The particle size fraction load index, coefficient of divergence, and Nemerow integrated risk index were used to analyze the temporal variation of pollution load and ecological risk in different particle size fractions. The advanced three-way model and wavelet analysis were used in quantitative identification and time-series analysis of sources. Results showed that both the pollution load and ecological risk of most heavy metals showed a decreasing trend from the finest fraction (P1) to the coarsest fraction (P5). The frequency of heavy metals in P1 posing extreme risk was about two times that of P5. Main types of heavy metal sources were similar among different fractions, whereas the impact intensity of these sources varied among different fractions. Traffic exhaust tended to accumulate in finer particles, and its contribution to Cu in P5 was only 35–55% of that in other fractions. Construction contributed more to coarser particles, and its contribution to Pb was increased from 45.34% in P1 to 65.35% in P5. Wavelet analysis indicated that traffic exhaust showed periodicities of 5–8 and 10–13 months. Fuel combustion displayed the strongest periodicity of 12–15 months, peaking in winter. Full article

Non-point source pollution poses a significant threat to global water security, and risk assessment and key source area (CSA) identification are critical for its management. While source–sink landscape models are widely used for non-point source pollution evaluation, their application in karst regions is challenged by ecological fragility, shallow soil layers, and severe soil erosion, limiting their effectiveness in accurately identifying pollution risks and CSAs. This study focuses on the Caohai Lake basin in southwestern China; it integrates the landscape-weighted load index (LWLI) and the universal soil loss equation (USLE) to assess non-point source pollution risks in the basin with the aim of precisely delineating critical source areas (CSAs). Total phosphorus (TP) and total nitrogen (TN) served as key predictors of water quality, and their responses to the LWLI and USLE were analyzed in the karst environment. The results revealed the following: (1) source landscapes cover 65% of the basin area, with cropland (40%) being the primary contributor to nitrogen pollution; (2) the LWLI and USLE explain 50–67% of the TP and TN variations during the wet season, with a sharp increase in water quality risk when the LWLI exceeds 0.75; and (3) high-risk and very high-risk areas account for 36.3% and 15.3% of the basin, respectively, and are concentrated in the northwest and south, where intensive agriculture and severe soil erosion dominate. These findings provide a scientific basis for non-point source pollution control in the Caohai Lake basin. Full article

Urban non-point source (NPS) pollution is an important risk factor that leads to the deterioration of urban water quality, affects human health, and destroys the ecological balance of the water environment. Reasonable risk prevention and control of urban NPS pollution are conducive to reducing the cost of pollution management. Therefore, based on the theory of “source–sink” in landscape ecology, combined with the minimum cumulative resistance (MCR) model, this study considered the influence of geographic-environment factors in Shenyang’s built-up area on pollutants in the process of entering the water body under the action of surface runoff, and evaluated its risk. The results indicated that the highest pollution loads are generated by road surfaces. High-density residential zones and industrial zones are the main sources of urban NPS pollution. Impervious surface ratios and patch density were the dominant environmental factors affecting pollutant transport, with contributions of 56% and 40%, respectively. The minimum cumulative resistance to urban NPS pollution transport is significantly and positively correlated with the distance from water bodies and roads. Higher risk areas are mainly concentrated in the center of built-up areas and roads near the Hun River. Green spaces, business zones, public service zones, development zones, and educational zones demonstrate the highest average risk index values, exceeding 29. In contrast, preservation zones showed the lowest risk index (7.3). Compared with the traditional risk index method, the method proposed in this study could accurately estimate the risk of urban NPS pollution and provide a new reference for risk assessments of urban NPS pollution. Full article