Search Results (85)

The article presents a long-term assessment of the surface water quality of six small rivers in the East Kazakhstan region (Breksa, Tikhaya, Ulba, Glubochanka, Krasnoyarka, and Oba) based on hydrochemical monitoring data from the Kazhydromet State Enterprise for the period 2017–2024. A unified water quality classification system was applied, along with statistical methods, including multiple linear regression. The Glubochanka and Krasnoyarka rivers were identified as the most polluted (reaching classes 4–5), with multiple exceedances of Zn (up to 2.96 mg/dm³), Cd (up to 0.8 mg/dm³), and Cu (up to 0.051 mg/dm³). The most stable and highest water quality was recorded in the Oba River, where from 2021 to 2024, water consistently corresponded to Class 2. Regression models of water quality class as a function of time and annual precipitation were constructed to assess the influence of climatic factors. Statistical analysis revealed no consistent linear correlation between average annual precipitation and water quality (correlation coefficients ranging from −0.49 to +0.37), indicating a complex interplay between climatic and anthropogenic factors. Significant relationships were found for the Breksa (R² = 0.903), Glubochanka (R² = 0.602), and Tikhaya (R² = 0.555) rivers, suggesting an influence of temporal and climatic factors on water quality. In contrast, the Oba (R² = 0.130), Ulba (R² = 0.100), and Krasnoyarka (R² = 0.018) rivers exhibited low coefficients, indicating the predominance of other, likely local, sources of pollution. It was found that summer periods are characterized by the highest pollution due to low water flow, while episodes of acid runoff occur in spring. A decrease in pH below 7.0 was first recorded in 2023–2024 in the Ulba and Tikhaya rivers. Forecasts to 2030 suggest relative stability in water quality under current climatic conditions; however, by 2050, the risk of water quality deterioration is expected to rise due to increased precipitation and extreme weather events. This study presents, for the first time, a systematic long-term analysis of small rivers in the East Kazakhstan region, offering deeper insight into the dynamics of surface water quality and providing a scientific foundation for developing adaptive strategies for the protection and sustainable use of water resources under climate change and anthropogenic pressure. The results emphasize the importance of prioritizing rivers with high variability in water quality for regular monitoring and the development of adaptive conservation measures. The research holds strong applied significance for shaping a sustainable water use strategy in the region. Full article

In the present study, a process for the production of 2,2,3,3,4,4,4-heptafluorobutyl acetate (HFBAc) is proposed for the first time. The production process of HFBAc from acetic acid (AAc) and 2,2,3,3,4,4,4-heptafluorobutan-1-ol (HFBol) was carried out at laboratory scale using batch reactive distillation (BRD). The process was conducted at atmospheric pressure in the presence of an acid catalyst, with an excess of AAc relative to HFBol (initial molar ratio of reagents HFBol/AAc is 45/55). During the BRD, the aqueous phase of the distillate was withdrawn from the system, while the organic phase of the distillate was returned as reflux. Since part of AAc is lost along with the aqueous phase of the distillate, a minor excess of AAc is reasonable for maximizing the conversion of the most expensive reagent—HFBol. The losses of AAc and HFBol with the aqueous phase of the distillate were less than 2 mole % and less than 0.5 mole % of the feed, respectively. The purity of HFBAc after BRD was 97.9 wt. %, and the conversion of HFBol exceeded 99 mole % of the feed. The purity of certain product fractions of HFBAc was greater than 99.6 wt. %. The obtained data can be used for industrial technology development to obtain HFBAc. Full article

Coral sand is characterized by unique particle morphology and pore structure, which result in pronounced dilatancy and a high internal friction angle during shear. The dilatancy angle is a critical parameter for finite element analyses of sand foundation bearing capacity; the inappropriate selection of this parameter can lead to significant computational errors. In this research, a series of consolidated drained triaxial tests were conducted on coral sand samples from the South China Sea to investigate the dilatancy behavior and its effect on shear strength parameters. A dilatancy equation for coral sand was proposed, incorporating the dilatancy index, relative density, and mean effective stress. The results indicate the following: (1) Within the confining pressure range of 25–400 kPa, the stress–strain curves exhibit varying degrees of strain softening. When the effective confining pressure reaches 400 kPa, the dilatant behavior is nearly suppressed, resulting in a transition from dilatancy to contraction; (2) The peak internal friction angle decreases significantly with increasing effective confining pressure. However, the sensitivity to confining pressure varies for samples with different relative densities (Dr = 30–90%), with denser samples showing a more rapid reduction in peak friction angle; (3) At a confining pressure of 25 kPa, the maximum dilatancy angle of coral sand samples reaches 44.2°, significantly exceeding the typical range observed in terrestrial quartz sands. This difference may be attributed to the irregular and angular characteristics of the coral sand particles; (4) Based on Bolton’s dilatancy theory, a dilatancy equation applicable to coral sand was developed, demonstrating a strong linear relationship among the dilatancy index (I_R), relative density (Dr), and peak mean effective stress (p′_f). These findings provide valuable guidance for the selection of strength parameters for engineering applications involving coral sand. Full article

Coalbed methane (CBM), a significant unconventional natural gas resource, holds a crucial position in China’s ongoing energy structure transformation. However, the inherent low permeability, high brittleness, and strong sensitivity of CBM reservoirs to drilling fluids often lead to severe formation damage during drilling operations, consequently impairing well productivity. To address these challenges, this study developed a novel low-damage, plugging, and anti-collapse water-based drilling fluid gel system (ACWD) specifically designed for coalbed methane drilling. Laboratory investigations demonstrate that the ACWD system exhibits superior overall performance. It exhibits stable rheological properties, with an initial API filtrate loss of 1.0 mL and a high-temperature, high-pressure (HTHP) filtrate loss of 4.4 mL after 16 h of hot rolling at 120 °C. It also demonstrates excellent static settling stability. The system effectively inhibits the hydration and swelling of clay and coal, significantly reducing the linear expansion of bentonite from 5.42 mm (in deionized water) to 1.05 mm, and achieving high shale rolling recovery rates (both exceeding 80%). Crucially, the ACWD system exhibits exceptional plugging performance, completely sealing simulated 400 µm fractures with zero filtrate loss at 5 MPa pressure. It also significantly reduces core damage, with an LS-C1 core damage rate of 7.73%, substantially lower than the 19.85% recorded for the control polymer system (LS-C2 core). Field application in the JX-1 well of the Ordos Basin further validated the system’s effectiveness in mitigating fluid loss, preventing wellbore instability, and enhancing drilling efficiency in complex coal formations. This study offers a promising, relatively environmentally friendly, and cost-effective drilling fluid solution for the safe and efficient development of coalbed methane resources. Full article

The small yellow croaker (Larimichthys polyactis), a migratory estuarine-demersal fish critical to East Asian fisheries, has faced severe population declines because of anthropogenic pressures (e.g., overfishing and anthropogenic habitat modification) and shifting environmental conditions. This study investigates its spatio-temporal habitat dynamics in Hangzhou Bay (2017–2023) using fisheries surveys and species distribution models (SDMs), with insights applicable to Pacific Coast migratory fish conservation. We evaluated the performance of eleven modeling algorithms to identify the most accurate model for predicting small yellow croaker distributions. Our results showed that the random forest algorithm outperformed other models, with a high sensitivity (95.238) and specificity (99.49), demonstrating its ability to capture complex non-linear relationships between environmental factors and species distribution. Depth emerged as the most influential factor, accounting for 30% of the importance in the model, with small yellow croakers preferring deeper waters around 60 m. Salinity was the second most important factor, with higher occurrence probabilities in areas where salinity exceeded 25 PSU. Other environmental factors, such as temperature and dissolved oxygen, had relatively smaller impacts on distribution. Spatially, small yellow croakers were predominantly distributed in offshore regions east of 122.5° E, where deeper waters and higher salinity levels provided suitable habitat conditions. This study underscores the need for targeted management measures, such as habitat restoration, to ensure the sustainable management of small-bodied yellow croaker populations. Full article

Cyanobacterial harmful blooms (CyanoHABs) in lakes, estuaries, and freshwater reser-voirs represent a significant risk to water authorities worldwide due to their cyanotoxins and economic impacts. The duration, spread, and severity of CyanoHABs have markedly increased over the past decades. The article addresses CyanoHABs, cyanotoxins, and monitoring methodologies in post-Soviet and Central Asian countries. This particular region was selected for the systematic review due to its relative lack of representation in global CyanoHABs reporting, particularly in Central Asia. The main aim of this systematic review was to analyze the primary literature available from 2010–2024 to examine the current situation of CyanoHAB detection, monitoring, and management in Central Asia and post-Soviet countries. Following a detailed database search in several selected data-bases (Google Scholar, Pubmed, Web of Science (WOS), Scopus, Elibrary, ENU, and KazNU) along with additional hand searching and citation searching, 121 primary articles reporting 214 local cyanobacterial bloom cases were selected for this review. Aquatic cyanotoxins were reported in water bodies of eight countries, including high concentrations of microcystins that often exceeded reference values established by the World Health Organization (WHO). Advancing monitoring efforts in Baltic countries, Belarus, and the Russian Federation differed from only a few Central Asian reports. However, Central Asian aquatic ecosystems are especially threatened by rising anthropogenic pressures (i.e., water use, intensive agriculture, and pollution), climate change, and the lack of adequate ecological surveillance. We hypothesize that recent Caspian seal mass mortality events have been caused by a combination of infection (viral or bacterial) and exposure to algal neurotoxins resulting from harmful algal blooms of Pseudo-nitzschia. We conclude that there is an urgent need to improve the assessment of cyanobacterial blooms in Central Asia and post-Soviet countries. Full article

The “West-to-East Gas Transmission” project has accelerated economic development in Xinjiang and the central-western regions along the pipeline. However, as the pipeline traverses multiple cities and counties in the Tianshan region, it has significantly impacted the local ecology, necessitating a comprehensive assessment. This study employs the Sensitivity-Resilience-Pressure (SRP) model to construct an ecological vulnerability assessment system for the Tianshan region, aiming to analyze changes in ecological vulnerability and evaluate the environmental impact of the “West-to-East Gas Transmission” project. The results indicate that, spatially, ecological vulnerability in the Tianshan region increases progressively from northwest to southeast. Temporally, from 2000 to 2010, the mean Ecological Vulnerability Index (EVI) exhibited a decreasing trend, with values of 0.476, 0.464, and 0.462, primarily shifting to lower vulnerability levels. From 2010 to 2020, the EVI showed an increasing trend, with values of 0.462, 0.466, and 0.468, predominantly transitioning from heavy to very heavy vulnerability. The key influencing factors of ecological vulnerability in the Tianshan region, ranked by importance, are NDVI, NPP, land use type, annual precipitation, and aridity. Furthermore, the “West-to-East Gas Transmission” project consists of three main pipelines (Lines 1, 2, and 3), for which buffer zone analyses were conducted at radii of 1 km, 3 km, and 5 km. The results indicate that ecological vulnerability patterns remained consistent across different buffer zone sizes, and larger buffer radii were associated with lower mean EVI values along the pipeline. After pipeline construction, the mean EVI along Line 1 decreased from 0.566 to 0.550, while the EVI along Line 2 remained nearly unchanged. In contrast, the mean EVI along Line 3 increased from 0.434 to 0.447. Regarding changes in ecological vulnerability levels, along Line 1, the area of improvement (18.83%) exceeded the area of deterioration (1.09%), primarily due to the high proportion of very heavy vulnerability zones (>80%), which are more likely to transition to lower vulnerability levels. Along Line 2, ecological vulnerability remained relatively stable, indicating minimal environmental impact. However, along Line 3, the improvement area (3.81%) was significantly smaller than the deterioration area (20.52%), suggesting that construction of Line 3 had a more pronounced ecological impact, leading to greater degradation of the ecological vulnerability along its route. Full article

The presence of antibiotics and antibiotic resistance genes (ARGs) in natural habitats has recently sparked increased concern. Vertical-flow constructed wetlands (VFCWs) represent a novel approach to reducing these new contaminants. In the current work, four laboratory-scale VFCW models with various substrates were built to decrease oxytetracycline (OTC) and ARGs. The findings showed that the combination of zeolite and activated carbon exhibited high OTC removal efficiency (up to 97%), with lesser accumulation than in other experimental groups. Furthermore, the combination of zeolite and activated carbon had the lowest absolute and relative abundance of ARGs. This was ascribed to the synergistic benefits of zeolite and activated carbon in CW-D, which exceeded other VFCWs in terms of ARGs removal efficiency. The treatment groups had a considerable but not absolute inhibitory impact on ARGs proliferation; this was attributable to the fact that many dominant bacteria in the community under antibiotic stress were antibiotic-resistant, allowing ARGs to propagate more easily. Network analysis and correlation analysis emphasized the importance of horizontal gene transfer (HGT) in ARGs dissemination, and antibiotic pressure is unlikely to have a substantial influence on ARGs propagation in the medium-term future. Furthermore, it was found that hydrophilic phages and Legionella species might serve as possible hosts for ARGs. Full article

The quality of medicinal plants is closely related to the ecological factors of their growing environment, as their efficacy is reflected in the content of key medicinal components, which in turn indicates the quality of the plants. This study measured the daily variations in major constituents, including lobetyolin, polysaccharides, and total flavonoids, in Codonopsis pilosula (Franch.) Nannf., which in the Changzhi and Jincheng regions of Shanxi Province, China is known as Lu Tangshen. Throughout its growth cycle. Additionally, the study explored the effects of 11 ecological factors (both climatic and soil variables) on the primary medicinal components of C. pilosula. Through block experiments and comparisons between future data predictions and actual measurements, the reliability of the model and the consistency of block experimental data were ultimately confirmed. Principal component analysis (PCA), stepwise multiple linear regression analysis, and nonlinear polynomial modeling were employed to investigate the relationships between ecological factors and quality-related constituents (polysaccharides, total flavonoids, and lobetyolin). The results showed that linear models effectively explained daily temperature (DT) with an adjusted R² exceeding 0.8, but due to the inherently nonlinear nature of the data, it is evident that linear models are fundamentally inadequate for accurately capturing the underlying relationships. Therefore, their fit for total flavonoids and lobetyolin was suboptimal. The introduction of nonlinear polynomial models (second-, fourth-, and fifth-order) significantly improved the model fit, indicating the existence of complex nonlinear relationships between ecological factors and medicinal components. For polysaccharides, the fourth-order model demonstrated the best performance, while fifth-order models were required to adequately describe the relationships for total flavonoids and lobetyolin. Based on the best models, the optimal ranges for key ecological factors were identified: polysaccharides were best influenced by atmospheric pressure (AP) between 9.1 and 9.3 kPa, air relative humidity (ARH) between 30% and 60%, 40 cm soil mean annual temperature (40cmMAT) between 27.5 °C and 28.5 °C, soil pH between 9.68 and 9.72, and soil nitrogen (N) content between 7 and 9 mg/kg. For total flavonoids, narrow optimal ranges were observed for temperature, humidity, and pH (MAT between 10 °C and 15 °C, 40cmMAT between 27.5 °C and 28.5 °C, and pH between 9.68 and 9.72). Lobetyolin showed optimal conditions at AP of 9.1 to 9.3 kPa, 40cmMAT of 28.0 °C to 28.5 °C, ARH of 65% to 75%, pH near 9.70, and days after planting (DAP) between 10 and 50. The adoption of higher-order polynomial models clarified critical nonlinear inflection points and optimal ecological ranges, providing a refined reference for enhancing the content of medicinal components. These findings offer valuable insights for precision cultivation strategies aimed at improving the quality of C. pilosula. Full article

Background: Obesity, characterized by excess body fat, has been recognized as one of the main global health problems of the current times. This article, based on the data from the Cohort study of risk factors for non-communicable diseases in Indonesia (FRPTM), aims to analyze the food consumption patterns and their association with the risk of obesity and related non-communicable diseases (NCDs) in the Indonesian population. Methods: The article presents data collected from 867 respondents aged 25 years and above observed for 5 years: 2011, 2013, 2015, 2017 and 2019. It includes sociodemographic characteristics, consumption (1 × 24-h recall), anthropometry, and biomedical data (lipid profile, blood glucose, blood pressure). Results: The study identified cereals as the food group consumed in the largest amount and the largest contributor to energy, protein, carbohydrates and fiber intake. The fats and oils group exceeded the recommended intake, while vegetable and fruit consumption, and consequently the fiber intake, were far below the recommendations. The energy and macronutrient intake, and the percentage of respondents with excessive intake levels, were consequently increasing during the studied years. The consumption patterns were associated with the incidence of obesity, which increased from 43.9% in 2011 to 69.9% (central obesity) and 67.9% (BMI-based obesity) in 2019. Conclusions: The dynamics of the consumption patterns clearly impacted the obesity prevalence. At the same time, the NCDs biomarkers measured remained relatively stable despite increasing obesity and macronutrient intake over the study period. The study provides important insights into diet-related risks for obesity in Indonesia, with a potential to inform public health policies and relevant intervention strategies. Full article

Vegetation dynamics and their underlying driving mechanisms have emerged as a prominent research focus in ecological studies of the Chinese Loess Plateau (CLP). Current investigations, however, employ simplified methodologies in analyzing the influencing factors, limiting their capacity to comprehensively elucidate the intricate and multidimensional mechanisms that govern vegetation transformations. Utilizing fractional vegetation cover (FVC) datasets spanning 2000 to 2021, this research applies both XGBoost-SHAP and Geodetector approaches for comparative analysis of the driving factors and precise quantification of climatic change (CC) and human activity (HA). The results indicate that: (1) The CLP has experienced an annual FVC increase of 0.62%, with 95.1% of the region demonstrating statistically significant vegetation improvement. (2) Precipitation and land use emerge as the primary determinants of FVC spatial distribution, with their interactive effects substantially exceeding the impacts of individual factors. (3) While both XGBoost-SHAP and Geodetector methodologies consistently identify the primary driving factors, notable discrepancies exist in their assessment of temperature’s relative importance, revealing complementary dimensions of ecological complexity captured by different analytical paradigms. (4) Approximately 94.3% of FVC variations are jointly influenced by HA and CC, with anthropogenic factors predominating at a contribution of 67%. Land use modifications, particularly transitions among cropland, grassland, and forests, constitute the principal mechanism of human influence on vegetation patterns. This investigation enhances the understanding of vegetation responses under combined natural and anthropogenic pressures, offering valuable insights for ecological rehabilitation and sustainable development strategies on the CLP. Full article

Arid and semiarid ecosystems face significant water scarcity due to high evaporation rates exceeding precipitation. This study examines temporal variations in water relations of two woody species, Vachellia schaffneri (S. Watson) Seigler & Ebinger, and Prosopis laevigata (Humb. & Bonpl. ex Willd.) M.C. Johnst, and one epiphyte, Tillandsia recurvata (L.) L. (Bromeliaceae), to assess their drought tolerance and water storage capacity. We hypothesized that species with greater water storage capacity would exhibit lower drought tolerance due to reduced osmotic adjustments, whereas species with lower storage capacity would maintain turgor through osmotic regulation and cell wall rigidity. Predawn and midday water potentials (Ψ_pd, Ψ_md) were measured, and pressure–volume (P–V) curves were used to derive parameters such as saturated water content (SWC), osmotic potential (π_o), turgor loss point (Ψ_TLP), relative water content at Ψ_TLP (RWC_TLP), bulk modulus of elasticity (ε), and full turgor capacitance (C_FT). Significant correlations were found between C_FT and Ψ_TLP (positive), π_o (positive), and ε (negative). P. laevigata and T. recurvata exhibited higher water storage capacities (41.46 and 26.45 MPa⁻¹, respectively) but had a lower ability to maintain cell turgor under drought conditions. In contrast, V. schaffneri exhibited the lowest water storage capacity (11.88 MPa⁻¹) but demonstrated the highest ability to maintain cell turgor (Ψ_TLP = −1.31 MPa) and superior osmotic adjustments (π_o = −0.59 MPa). Both V. schaffneri and P. laevigata exhibited rigid cell walls, whereas T. recurvata displayed greater elasticity in its cell structures. The lowest moisture content in V. schaffneri suggests increased flammability and fire spread potential. Future studies should focus on live fuel moisture content across more species, explore seasonal variations in hydraulic traits, and integrate these physiological parameters into fire risk models to enhance wildfire prediction and management. Full article

Coiled tubing (CT) plays a pivotal role in oil and gas well intervention operations due to its advantages, such as flexibility, fast mobilization, safety, low cost, and its wide range of applications, including well intervention, cleaning, stimulation, fluid displacement, cementing, and drilling. However, CT is subject to fatigue and mechanical damage caused by repeated bending cycles, internal pressure, and environmental factors, which can lead to premature failure, high operational costs, and production downtime. With the development of CT properties and modes of application, traditional fatigue life prediction methods based on analytical models integrated in the tracking process showed, in some cases, an underestimate or overestimate of the actual fatigue life of CT, particularly when complex factors like welding type, corrosive environment, and high-pressure variation are involved. This study addresses this limitation by introducing a comprehensive machine learning-based approach to improve the accuracy of CT fatigue life prediction, using a dataset derived from both lab-scale and full-scale fatigue tests. We incorporated the impact of different parameters such as CT grades, wall thickness, CT diameter, internal pressure, and welding types. By using advanced machine learning techniques such as artificial neural networks (ANNs) and Gradient Boosting Regressor, we obtained a more precise estimation of the number of cycles to failure than traditional models. The results from our machine learning analysis demonstrated that CatBoost and XGBoost are the most suitable models for fatigue life prediction. These models exhibited high predictive accuracy, with R² values exceeding 0.94 on the test set, alongside relatively low error metrics (MSE, MAE and MAPE), indicating strong generalization capability. The results of this study show the importance of the integration of machine learning for CT fatigue life analysis and demonstrate its capacity to enhance prediction accuracy and reduce uncertainty. A detailed machine learning model is presented, emphasizing the capability to handle complex data and improve prediction under diverse operational conditions. This study contributes to more reliable CT management and safer, more cost-efficient well intervention operations. Full article

Devices for assessing the quality of animal environments are important for maintaining production animals, thus improving animal well-being and mitigating pollutant emissions. Therefore, an IoT system was developed and preliminarily assessed across various livestock housing types, including those for pigs, dairy cows, and rabbits. This system measures and transmits key parameters, such as ambient temperature; relative humidity; light intensity; sound pressure; levels of carbon dioxide, ammonia, and hydrogen sulfide; and particulate matter and volatile organic compound concentrations. These data are sent from the sensors to a gateway and then displayed on a dashboard for monitoring. A preliminary evaluation of the system’s performance in controlled conditions revealed that the device’s accuracy and precision were within 2.7% and 3.3% of the measured values, respectively. The system was deployed in three case studies involving rabbit, pig, and dairy cow farms. The results demonstrated its effectiveness in assessing pollutant emissions and identifying critical situations where gas concentrations exceeded threshold levels, thus posing a risk to the animals. By systematically applying this technology on livestock farms to obtain a detailed understanding of the microclimatic and air quality conditions in which the animals live, animal welfare can be significantly improved. Full article

This work uses state-of-the-art climate model data at 30 European airport locations to examine how climate change may affect summer take-off distance required—TODR—and maximum take-off mass—MTOM—for a 30-year period centred on 2050 compared to a historical baseline (1985–2014). The data presented here are for the Airbus A320; however, the methodology is generic and few changes are required in order to apply this methodology to a wide range of different fixed-wing aircraft. The climate models used are taken from the 6th Coupled Model Intercomparison Project (CMIP6) and span a range of climate sensitivity values; that is, the amount of warming they exhibit for a given increase in atmospheric greenhouse gas concentrations. Using a Newtonian force-balance model, we show that 30-year average values of TODR may increase by around 50–100 m, albeit with significant day-to-day variability. The changing probability distributions are quantified using kernel density estimation and an illustration is provided showing how changes to future daily maximum temperature extremes may affect the distributions of TODR going forward. Furthermore, it is projected that the 99th percentile of the historical distributions of TODR may by exceeded up to half the time in the summer months for some airports. Some of the sites studied have runways that are shorter than the distance required for a fully laden take-off, which means they must reduce their payloads as temperatures and air pressures change. We find that, relative to historical mean values, take-off payloads may need to be reduced by the equivalent of approximately 10 passengers per flight, as these significant increases (as high as approximately 60%) show a probability of exceeding historical extreme values. Full article