Search Results (1,638)

Soil contamination with heavy metals often resulting from industrial activities and wastewater discharge is a major ecological problem. Bone meal, a by-product of the agri-food industry, is a promising material for remediating soils affected by heavy metal pollution. Bone meal, rich in phosphorus, calcium, and other essential minerals, provides advantages both in immobilizing inorganic pollutants and in improving soil fertility. This study explores the potential of bone meal as an ecological and sustainable solution for the retention of zinc from soils polluted with wastewater. This study analyzes the physicochemical properties of bone meal, the mechanisms of its interaction with metal ions through adsorption processes as revealed by equilibrium and kinetic studies, and its effects on plant germination. The results indicate a maximum adsorption capacity of 2375.33 mg/kg at pH = 6, according to the Langmuir model, while the pseudo-second-order kinetic model showed a coefficient of R² > 0.99, confirming the chemical nature of the adsorption. At pH 12, the retention capacity increased to 2937.53 mg/kg; however, parameter instability suggests interference from precipitation phenomena. At pH 12, zinc retention is dominated by precipitation (Zn(OH)₂ and Zn–phosphates), which invalidates the Langmuir assumptions; accordingly, the Freundlich isotherm provides a more adequate description. Germination tests revealed species-specific responses to Zn contamination and bone meal amendment. In untreated contaminated soil, germination rates were 84% for cress, 42% for wheat, and 50% for mustard. Relative to the soil + bone meal treatment (100% performance), the extent of inhibition reached 19–21% in cress, 24–29% in wheat, and 12% in mustard. Bone meal mitigated Zn-induced inhibition most effectively in wheat (+31% vs. soil; +40% vs. control), followed by cress (+23–27%) and mustard (+14%), highlighting its species-dependent ameliorative potential. Thus, the experimental results confirm bone meal’s capacity to reduce the mobility of zinc ions and improve the quality of the agricultural substrate. By transforming an animal waste product into a material with agronomic value, this study supports the integration of bone meal into modern soil remediation strategies, aligned with the principles of bioeconomy and sustainable development. Full article

Excessive phosphorus emissions are a significant driver of severe eutrophication in water bodies, and developing an efficient and cost-effective adsorbent for phosphorus removal is imperative. In this study, a Na-type zeolite was synthesized from coal gangue sourced from an open-pit mine in Xinjiang province, China. The synthesis process involved drying, crushing, alkali activation, aging, hydrothermal crystallization, and Na⁺ ion exchange. Orthogonal design identified the optimal synthesis parameters: an alkali-to-ash ratio of 1:1, aging at 20 °C for 12 h, and crystallization at 130 °C for 12 h. Aging time exerted the greatest influence on the phosphate removal efficiency. The optimized zeolite exhibited excellent phosphate adsorption performance, achieving a removal efficiency of up to 96% and a capacity of 16 mg/g. The adsorption kinetics followed both pseudo-first-order and pseudo-second-order models, indicating processes governed by combined physical and chemical mechanisms. Isotherm data fitting with Freundlich and Langmuir models suggested the presence of both homogeneous and heterogeneous active sites. Thermodynamic studies confirmed a spontaneous and endothermic process, increasingly favorable at higher temperatures. Characterizations via scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray fluorescence (XRF) spectroscopy, and Fourier transform infrared (FTIR) spectroscopy confirmed the formation of Na-type zeolite and revealed structural and compositional changes following phosphate adsorption. Aluminum and calcium binding played key roles in the chemical adsorption mechanisms. This work not only offers a high-efficiency, low-cost solution for phosphorus removal from wastewater but also provides a sustainable pathway for the valorization of coal gangue in the Zhundong area of Xinjiang, China. Full article

Zebra mussel invasion of North American lakes during the last century may play an important role in the occurrence of toxic cyanobacterial blooms. However, empirical evidence quantifying their influence on cyanobacterial community dynamics at broad spatial scales remains limited. Here, we analyzed data from the U.S. EPA National Lakes Assessment (>1000 lakes) to examine potential linkages among zebra mussels, cyanobacterial community composition, and cyanotoxin levels. The analysis results showed significant differences in cyanobacterial communities between lakes located in areas with and without established zebra mussel populations. The lakes with established zebra mussels exhibited significantly higher microcystin levels and cyanobacterial abundance, but lower phosphorus concentrations. Structural equation modeling was used to confirm and estimate the effect of zebra mussels on microcystin concentrations via different pathways. The results suggest three potential pathways whereby zebra mussels influence microcystin production: (1) altering phosphorus concentration; (2) increasing cyanobacterial abundance; and (3) shifting cyanobacteria community structure. The total effect of zebra mussel establishment resulted in an overall 1.40-fold net increase in microcystin level, which presumably resulted from three contributing factors: (1) a 1.06-fold increase through an increased cyanobacterial abundance; (2) a 1.53-fold increase through a selective force, resulting in increased cyanobacteria toxicity; and (3) a 0.86-fold decrease in microcystin level through total phosphorus decrease. The study highlights the potential role of zebra mussel invasion in altering cyanobacterial composition and influencing microcystin levels in U.S. lakes. Full article

The Sanqi–pine agroforestry (SPA) system is considered a sustainable agroforestry model. However, empirical studies that clearly elucidate the impact of Sanqi cultivation on soil fertility and the heavy metal content within the SPA system are still lacking. This study established monoculture Pinus armandii (MPA) and SPA systems to conduct a comparative analysis of dynamic changes in soil physicochemical properties and the heavy metal content of Sanqi and pine over one year (with semi-monthly sampling), followed by a comprehensive evaluation of soil fertility and heavy metal pollution. Following the land use conversion from MPA to SPA, there was a notable increase in soil moisture (SM), total nitrogen (TN), and nitrate nitrogen (NO₃⁻-N) levels within Sanqi soil. Conversely, total potassium (TK), ammonium nitrogen (NH₄⁺-N), plumbum (Pb), and chromium (Cr) levels experienced a significant reduction. In the case of pine soil, soil moisture (SM), pH levels, and ammonium nitrogen (NH₄⁺-N) content exhibited an increase. However, soil organic carbon (SOC), total phosphorus (TP), total potassium (TK), zinc (Zn), manganese (Mn), plumbum (Pb), and chromium (Cr) contents all significantly decreased. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) demonstrated that Sanqi cultivation not only significantly enhanced soil fertility for Sanqi rather than pine but also reduced the heavy metal content in the soil of both Sanqi and pine within the SPA system. Furthermore, the Nemerow pollution index for both Sanqi and pine soils has decreased, transitioning the pollution status from relatively safe to safe. This suggests that the introduction of Sanqi promotes the sustainable development of the SPA system. Full article

Recent concerns regarding artificial intelligent (AI) technologies have spurred studies into improving wastewater treatment efficiency and identifying low-carbon processes. Treating one cubic meter of wastewater necessarily consumes a certain amount of chemicals and energy. Approximately 20% of the total chemical consumption is attributed to phosphorus and nitrogen removal, with the exact proportion varying based on treatment quality and facility size. To promote sustainability in wastewater treatment plants (WWTPs), there has been a shift from traditional control systems to AI-based strategies. Research in this area has demonstrated notable improvements in wastewater treatment efficiency. This review provides an extensive overview of the literature published over the past decades, aiming to advance the ongoing discourse on enhancing both the efficiency and sustainability of chemical dosing systems in WWTPs. It focuses on AI-based approaches utilizing algorithms such as neural networks and fuzzy logic. The review encompasses AI-based wastewater treatment processes: parameter analysis/forecasting, model development, and process optimization. Moreover, it summarizes six promising areas of AI-based chemical dosing, including acid–base regents, coagulants/flocculants, disinfectants/disinfection by-products (DBPs) management, external carbon sources, phosphorus removal regents, and adsorbents. Finally, the study concludes that significant challenges remain in deploying AI models beyond simulated environments to real-world applications. Full article

Lake eutrophication is governed by persistent anthropogenic nutrient inputs, primarily nitrogen (N), phosphorus (P) and cryptic internal nutrient cycling processes that sustain bioavailable nutrient pools. While the impact of external nutrient loads on lake eutrophication has been extensively studied, the role of internal nutrient cycling in lake ecosystems remains underexplored. In this study, the hierarchical bootstrap generalized linear model (HBGLM) to long-term summer water quality data (1999–2020) from Lake Dianchi, China, to explore the relative importance of nitrogen (N), phosphorus (P), as well as the limitations of N and P on the growth of phytoplankton. The results revealed that from 1999 to 2020, the Chla and TP concentrations decreased by 49% and 78%, respectively, and that internal nutrient cycling significantly influenced changes in nutrient concentrations, reflecting the relationships among N, P, and chlorophyll a (Chla). Particularly in 2007, 2013, and 2017, the long-term trends of the TN:TP ratio, an indicator of potential nutrient limitation in the lake, were consistent with changes in the distributions of the average slopes of TN and TP across different periods, indicating that these years primarily exhibited patterns of colimitation by N and P or P limitation, indirectly confirming that Lake Dianchi will transition from N and P colimitation to being limited primarily by P. This study reveals that N is typically the primary limiting element, while P is a key element promoting water eutrophication. To further validate improvements to existing eutrophication mitigation models, conducting carefully de-signed experiments at different scales is recommended. Full article

Bamboo forest density is a factor that critically impacts the growth of moso bamboo, soil quality, and productivity. In this study, four bamboo forest density treatment groups were established under a long-term bamboo-stocking retention model, namely 1200 ± 100, 1800 ± 100, 2400 ± 100, and 3000 ± 100 plants·hm⁻², while a traditional management model focused on selective logging, with a bamboo forest density of 2100 ± 100 plants·hm⁻² (CK), serving as the control group. The study aimed to investigate the impact of bamboo forest density on bamboo shoots, roots, and soil, identify key influencing factors, and determine the optimal management density for this management model. Under the novel management model, bamboo shoot yield and number exhibited a unimodal response to stand density. At a density of 2400 plants·hm⁻², the bamboo shoot yield reached its highest value of 18,822 kg·hm⁻², with 7080 shoots·hm⁻². Under the density of 2400 plants·hm⁻², the specific root length, specific root surface area and total nitrogen, phosphorus and potassium contents of 0–1 mm fine roots were higher, and the contents of soil organic matter, total nitrogen, available phosphorus and available potassium were also better. Correlation analysis showed that the bamboo shoot yield and the number of shoots were closely related to soil quality (water content, organic matter, total nitrogen, available phosphorus and available potassium), and the effect of root total nitrogen content on shoot yield was particularly significant (the explanation rate was 75.7%). The comprehensive growth status assessment (D3 > D4 > D2 > CK > D1) showed that there were differences in the performance of different density treatment groups. This information could help bamboo farmers improve yield while protecting soil quality. Full article

In developing countries, indoor air pollution in rural areas is often attributed to the use of solid biomass fuels for cooking. Such fuels generate particulate matter (PM), carbon monoxide (CO), carbon dioxide (CO₂), polyaromatic hydrocarbons (PAHs), and volatile organic compounds (VOCs). PM created from biomass combustion is a pollutant particularly damaging to health. This rigorous study employed a personal sampling device and multi-stage cascade impactor to collect airborne PM (including PM_2.5) and deposited ash from 20 real-world kitchen microenvironments. A robust analysis of the PM was undertaken using a range of morphological, physical, and chemical techniques, the results of which were then compared to a controlled burn experiment. Results revealed that airborne PM was predominantly carbon (~85%), with the OC/EC ratio varying between 1.17 and 11.5. Particles were primarily spherical nanoparticles (50–100 nm) capable of deep penetration into the human respiratory tract (HRT). This is the first systematic characterisation of biomass cooking emissions in authentic rural kitchen settings, linking particle morphology, chemistry and toxicology at health-relevant scales. Toxic heavy metals like Cr, Pb, Cd, Zn, and Hg were detected in PM, while ash was dominated by crustal elements such as Ca, Mg and P. VOCs comprised benzene derivatives, esters, ethers, ketones, tetramethysilanes (TMS), and nitrogen-, phosphorus- and sulphur-containing compounds. This research showcases a unique collection technique that gathered particles indicative of their potential for penetration and deposition in the HRT. Impact stems from the close link between the physico-chemical properties of particle emissions and their environmental and epidemiological effects. By providing a critical evidence base for exposure modelling, risk assessment and clean cooking interventions, this study delivers internationally significant insights. Our methodological innovation, capturing respirable nanoparticles under real-world conditions, offers a transferable framework for indoor air quality research across low- and middle-income countries. The findings therefore advance both fundamental understanding of combustion-derived nanoparticle behaviour and practical knowledge to inform public health, environmental policy, and the UN Sustainable Development Goals. Full article

In southern China, the long-term irrational utilization of land resources has caused severe damage to the ecology and environment of the entire region. Serious issues such as soil degradation and water erosion have led to the decline of soil quality and productivity. In this study, the spatial distribution characteristics of soil carbon, nitrogen, and phosphorus in Zhuxi watershed, Changting County, southern China, were analyzed by coupling geostatistics with GIS. The analysis generated several important results: (1) The concentrations of soil organic matter (OM), alkali-hydrolyzable nitrogen (AN), and available phosphorus (AP) are at moderate levels, and AP exhibits local enrichment in the downstream farmland, while the concentrations of total nitrogen (TN) and total phosphorus (TP) remain at low levels. (2) The optimal theoretical model for AN is an exponential model, while other nutrients follow spherical models. Except for AP, which has a nugget effect exceeding 75%, the nugget effects of other nutrients range between 25% and 75%, indicating that their spatial distribution is moderately correlated. According to Kriging interpolation results, the distribution of OM, TN, and AN shows a clear trend of decreasing from northeast to southwest, followed by a gradual increase, which is generally consistent with the direction of rivers. The trends of TP and AP are more irregular, generally decreasing from downstream to upstream. (3) OM, TN, and AN exhibit a negative correlation with the degree of soil erosion, indicating that soil erosion is associated with the loss of carbon and nitrogen nutrients. However, the impact on phosphorus is relatively insignificant. Full article

Elevated phosphorus levels in wastewater created significant environmental concerns, including the degradation of surrounding soil structure, inhibition of plant growth, and potential threats to human health. To address this issue, a self-standing nanofibrous composite membrane based on PA-66/PVA-15%La(OH)₃ was fabricated via electrospinning, followed by glutaraldehyde (GA) crosslinking and alkali hydrolysis to create an interpenetrating structure, where PA-66 provided the overall mechanical strength of the membrane, while La served as a functional component for the adsorption of phosphate. The chemical composition, surface morphology, thermal stability, and mechanical properties of the resulting membranes were characterized using ATR-FTIR, SEM, TGA, and tensile testing, respectively. Furthermore, the adsorption performance of the membranes was evaluated systematically through static and dynamic adsorption. The Langmuir isotherm model yielded a theoretical maximum adsorption capacity of 21.39 mg/g for phosphate ions. Notably, over 96% of this capacity was retained even in the presence of interfering ions. Moreover, dynamic adsorption experiments demonstrated that the membrane can deal with 1.74 L of phosphate-containing wastewater at a low flow rate of 1.0 mL/min and 1.46 L at a high flow rate of 2.0 mL/min, respectively, while consistently maintaining a phosphate removal efficiency exceeding 90%. A controlled release of phosphate ions from a phosphate-adsorbed membrane was successfully demonstrated using Mougeotia cultivation, implying the potential for phosphorus resource recovery. Full article

Wheat is a crucial crop for human nutrition, and the demand for high-quality indicators within the “from farm to fork” concept is increasing. Based on this premise, this study examined how, at the farm level, the fertilization system can influence key quality indicators relevant to wheat production and final products. This research was conducted under specific conditions of the Western Plain of Romania at the Agricultural Research and Development Station (ARDS), Lovrin, during 2015–2017. Fertilization involved the autumn application of phosphorus (concentrated superphosphate; 0, 40, 80, 120, 160 kg ha⁻¹ active substance, a.s.) and potassium (potassium chloride; 0, 40, 80, 120 kg ha⁻¹ a.s.). Nitrogen (ammonium nitrate; 0, 30, 60, 90, 120 kg ha⁻¹ active substance) was applied in spring in two stages. The combination of these three fertilizers resulted in 18 fertilized variants (T2 to T19), tested alongside an unfertilized control (T1). The experimental variants were arranged in four randomized replications. Grain quality was assessed based on protein content (PRO, %), gluten (GLT, g 100 g⁻¹), gliadins (Gliad, %), glutenins (Glut, g 100 g⁻¹), high-molecular-weight glutenins (HMW, g 100 g⁻¹), low-molecular-weight glutenins (LMW, g 100 g⁻¹), and the gliadin/glutenin ratio (Gliad/Glut). Compared to the average values for each indicator across the experiment, certain variants produced values above the mean, with statistical significance. Variant T16 stood out by producing values above the mean for all indicators, with statistical confidence. Multivariate analysis showed that five indicators with very strong (PRO, GLT) and strong (HMW, Glut, LMW) influence grouped in PC1, while two indicators (Gliad, Gliad/Glut) with very strong and strong influence grouped in PC2. The analysis revealed varying levels of correlation between the applied fertilizers, with nitrogen (N) showing very strong and strong correlations with most indicators, while phosphorus and potassium showed moderate-to-weak correlations. Regression analysis generated mathematical models that statistically described how each indicator varied in relation to the fertilizers applied. Full article

Global warming and climate deterioration are primarily driven by massive greenhouse gas emissions, making the comprehensive assessment of agricultural emissions imperative. This study integrates multiple datasets to achieve three objectives: (1) quantifying agricultural greenhouse gas emissions, (2) identifying regional influencing factors, and (3) exploring mitigation strategies. In this study, a random forest regression model was used to fit the data, providing a new perspective for the analysis of emission factors. Key findings reveal fertilization and irrigation as the dominant emission drivers, with significant regional variations. Specifically, (1) fertilization practices, particularly nitrogen application, exert a greater influence than phosphorus on carbon emissions; (2) irrigation impacts correlate strongly with regional water usage patterns among staple crops; (3) distinct emission patterns emerge across China’s northeast–southwest divide, reflecting variations in grain crop impacts and climatic responses. The study proposes three mitigation approaches: precision fertilization, adaptive irrigation management, and crop structure optimization. These strategies provide actionable pathways for China to meet agricultural emission reduction targets while advancing sustainable development goals. Full article

This paper aims to assess the water quality of the Ismailia Canal, Egypt, in accordance with Article 49 of Law 92/2013. QUAL2K and Convolutional Neural Networks and Long Short-Term Memory (CNN-LSTM) are utilized to simulate the water quality parameters of dissolved oxygen (DO), pH, biological oxygen demand (BOD), chemical oxygen demand (COD), total phosphorus (TP), nitrate nitrogen (NO₃-N), and ammonium (NH₃-N) in winter and summer 2023. The parameters of the QUAL2K and CNN-LSTM models were calibrated and validated in both winter and summer through trial and error, until the simulated results agreed well with the observed data. Additionally, the model’s performance was measured using different statistical criteria such as mean absolute error (MAE), root mean square (RMS), and relative error (RE). The results showed that the simulated values were in good agreement with the observed values. The results show that all parameter concentrations follow and did not exceed the limit of Article 49 of Law 92/2013 in winter and summer, except for dissolved oxygen concentration (8.73–4.53 mg/L) in winter and summer, respectively, which exceeds the limit of 6 mg/L, and in June, biological oxygen demand exceeds the limit of 6 mg/L due to increased organic matter. It is imperative to compare QUAL2K and CNN-LSTM models because QUAL2K provides a physics-based simulation of water quality processes, whereas CNN-LSTM employs deep learning in modeling complex temporal patterns. The two models enhance prediction accuracy and credibility towards enabling enhanced decision-making for Ismailia Canal water management. This research can be part of a decision support system regarding maximizing the benefits of the Ismailia Canal. Full article

With the rapid development of urbanization and the economy in recent years, increased human activities along the Yinghe River in Fuyang City and industrial expansion have degraded the water quality. Various sewage discharges have elevated nitrogen and phosphorus levels in the water body, disrupting its original ecological balance and exacerbating environmental issues. Therefore, studying the water purification capacity of the Fuyang region is particularly important. Using the InVEST model, this paper analyzes temporal changes and spatial differences in water purification capacity by quantifying nitrogen and phosphorus retention. The results show the following: The water purification capacity of Fuyang exhibits a spatial pattern of higher effectiveness in the north and lower effectiveness in the southwest. This study represents the strength of water purification capacity as the sum of regional output of nitrogen and phosphorus nutrients, based on which different types of areas are divided into water purification capacity deficit areas and water purification capacity control areas, and then combined with the different impacts of different land use types on the regional water purification capacity, corresponding countermeasures are proposed to optimize the water purification capacity of Fuyang City. Full article

The aim of this study was to explore the decomposition characteristics of Tamarix chinensis litter and its soil-improving capacity under different salinities. Four treatments were designed: a control (CK) treatment without saline water injection and three treatments encompassing slightly (SS, 0.4% soil salinity), moderately (SM, 0.8%), and highly saline (SH, 1.2%) conditions. T. chinensis litter at three degrees of decomposition (undecomposed, semidecomposed, and already decomposed) was studied. After 180 days, the litter substrate quality, 0–10 cm soil physicochemical properties, and enzyme activities were measured. Correlation analysis and structural equation modeling were employed to elucidate the interactions and response patterns among soil salinity, the decomposition characteristics of T. chinensis litter, and the physicochemical properties and enzyme activities of surface soil. The results revealed the following: (1) With increasing soil salinity, the contents of litter lignin, cellulose, total carbon and nitrogen residues first decreased but then increased, reaching minima under SM, whereas the content of hemicellulose residue exhibited the opposite trend. With increasing degree of litter decomposition, the contents of lignin and cellulose residues decreased, whereas the contents of hemicellulose, total nitrogen and phosphorus residues increased. (2) With increasing soil salinity, the soil water content, organic matter content, total nitrogen content, and activity of several enzymes increased, peaking under SH. The pH performance followed the order of SS > SM > CK > SH. The total carbon and phosphorus contents first increased but then decreased, with a maximum under SS. The activity of N-acetylamino glucosidase first decreased but then increased and was greatest at moderate and high salinities. (3) The soil water content and level of enzyme activity were significantly correlated with the litter substrate quality. Salinity negatively affected litter substrate residues but positively affected soil physicochemical properties. Litter decomposition under different soil salinities indirectly influenced soil enzymes by affecting soil properties, whereas salinity modulated soil properties directly or through litter decomposition. T. chinensis litter decomposition notably increased enzyme activity in moderate- to high-salinity alkali coastal soils, offering insights for low-efficiency T. chinensis forest management and saline–alkali soil remediation in the Yellow River Delta. Full article