Removal Strategies Research Articles

Assessment and Removal Strategy of Microplastic Pollution in River Water in the Krueng Aceh River, Indonesia

Assessment and Removal Strategy of Microplastic Pollution in River Water in the Krueng Aceh River, Indonesia

Effective removal of fluoride ions from contaminated water using electrochemical techniques: A critical review on recent developments and environmental perspective

Worldwide, water pollution poses significant threats to human health, with fluoride contamination emerging as a critical hazard. High fluoride concentrations in water cause severe health impacts, including dental and skeletal fluorosis, neurological damage, and harm to the parathyroid gland, cardiovascular, and reproductive systems. Electrochemical technique is one of the most widely used treatment technologies that has been extensively studied and provides a very effective, low-cost method of removing fluoride from contaminated water. The review reports the comprehensive electrochemical strategies for fluoride ions removal. The sources, toxicity, and impacts of fluoride pollution on health are discussed in this review. A comprehensive analysis of current electrochemical methods, including electrolysis, electrocoagulation, and the electro-fenton process, was provided in the context to facilitate the efficient removal of fluoride ions from wastewater. These methods exhibit high removal efficiencies, reaching up to 95 %, and offer scalability and operational flexibility, making them suitable for both centralized and decentralized water treatment systems. Furthermore, the recent advancements in the development of electrochemical technique for fluoride removal are critically reviewed. This study has prospected the recent developments, recommendations and future outlooks on electrochemical technique for fluoride removal.

Life cycle impact and cost analysis of quarry materials for land-based enhanced weathering in Northern California

Enhanced weathering (EW) is a CO2 removal (CDR) and sequestration strategy that accelerates the natural reactions of minerals that can store carbon from the atmosphere and biotic reactions. One method of EW is to apply finely ground silicate rocks to agricultural lands. EW has been demonstrated in laboratory and field tests, but great uncertainty remains regarding the life-cycle of using locally available rocks on candidate soils. We evaluate the life-cycle impacts, job creation, and cost of scenarios where fines and rocks mined from quarries in Oregon and Northern California are transported by truck and tilled into agricultural soils. Candidate quarry dust samples were classified as dacite, andesite, and olivine-bearing rocks, with EW potentials ranging from 125 to 760 kg CO2/metric tonne rock. We determined the olivine-bearing rock from Southern Oregon could achieve a levelized cost of CDR under the DOE Earthshot target of $100/t CO2, as long as application rates are 25 t/ha or more. Even andesite and dacite materials reach lower costs than commercial direct air capture technologies, with reduction in fines purchase and transport costs critical for achieving the Earthshot target. The results suggest that low-cost EW can be achieved using natural quarry materials, with average removal up to 2.2 t CO2e per hectare per year.

Optimized ceramic membrane-based method for efficient and acid-free rice protein preparation from alkaline extracts

Rice protein, stands out as a high-quality plant-based protein, suitable for dietary supplementation and food processing. Traditional methods, involving alkaline extraction and acid precipitation, are challenged by the extensive use of chemicals and the difficulty in desalination. This study proposed a novel separation method that utilizes ceramic membranes for direct alkali filtration, eliminating the formation of salts by acid neutralization. The membrane pore size and the operating parameters such as transmembrane pressure, cross-flow velocity, and pH were optimized to enable a high flux (>80 L m−2·h−1) and favorable protein rejection (>95 %) while permitting the removal of excess alkali. Additionally, the effects of non-protein substances, e.g., starch, present in the alkaline extract on the separation performance were explored. Subsequently, an optimized strategy for starch removal was proposed, involving the concentration of the alkali extract using an ultrafiltration membrane, followed by enzymatic hydrolysis of starch and diafiltration to eliminate the residuals of starch hydrolysates and alkali. Under stabilization of protein particles by carboxymethyl cellulose, rice protein with a uniform particle size of 25 nm and a purity of over 80 % was produced. The direct removal of alkali from alkali extracts of rice by ceramic membranes presents a promising strategy for producing rice protein with high purity and reduced aggregation degree, enabling better functionalities such as solubility than the conventional alkali-extraction and acid-precipitation method.

Poldw: A Python code to denoise 3C seismic data with a new threshold-free polarization technique

We present a Python code that implements a novel threshold-free polarization strategy for removing random noise from 3C linearly polarized seismic data. The code, which we refer to as polarization denoising through windowing (poldw), uses closed-form formulas along sliding windows that span the data to determine the optimal rotation angles that allow the transfer of most of the signal energy to a given component. The denoised 3C data are obtained after canceling out the other two components, which are assumed to contain predominantly noise, and then rotating back. The method is simple and efficient because it only requires setting the sliding window length. Synthetic and microseismic field data examples show the method’s effectiveness, which significantly improves the signal-to-noise ratio without the need for threshold-based polarization filters. Therefore, these filters can be pipelined in the rotation-based strategy for additional noise removal if necessary. When the data set contains nonlinearly polarized data or significant nonrandom noise, the method is likely to fail. For robustness against non-Gaussian noise and outliers, poldw allows for the use of alternative norms similar to the [Formula: see text]- or [Formula: see text]-norms instead of the energy. In addition to the code, we provide a Jupyter notebook to illustrate the method step by step and reproduce the results of the field data example.

Application of Supervised Learning Methods and Information Gain Methods in the Determination of Asbestos–Cement Roofs’ Deterioration State

This study introduces an innovative approach to evaluate the condition of asbestos–cement (AC) roofs by integrating field data with five distinct supervised learning models: decision trees, KNN, logistic regression, support vector machine, and random forest. A novel methodology for assessing the importance of 380 reflectance bands was employed, offering fresh insights into the key indicators of AC roof deterioration. The research systematically organized and prioritized reflectance bands based on their information gain, optimizing both the selection of relevant bands and the performance of the models in differentiating between low and high intervention priority (LIP and HIP) roofs. The decision tree model, when applied to the top 10 most relevant bands, achieved the highest cross-validation accuracy of 76.047%, making it the most effective tool for identifying AC roof conditions. Additionally, the random forest model demonstrated strong performance across various band groups, further validating its utility. Utilizing the open-source software Weka (version 3.8.6), this study adeptly executed relevance evaluation and model implementation, providing a practical and scalable solution for material characterization, especially in regions where resources for spectral and hyperspectral image analysis are limited. The findings of this study offer valuable tools for government and environmental authorities, particularly in developing countries, where efficient and cost-effective AC roof assessment is crucial for public health and safety. The methodology is adaptable to different urban environments and climatic conditions, supporting global efforts in asbestos management, especially in countries where asbestos regulations are newly implemented. Organized within the CRISP-DM framework, this paper details the methodological phases, presents compelling results on reflectance band relevance, evaluates machine learning models, and concludes with prospects for future research aimed at enhancing asbestos detection and removal strategies.

Green synthesis of a multifunctional β-cyclodextrin modified polymer sorbent using agrarian wastes of Nelumbo nucifera for the efficient sequestration of toxic dyes from polluted water

This study explores an eco-friendly strategy for the effective removal of toxic dyes Malachite Green, Methylene Blue, and Basic Magenta Dye, from water bodies, utilizing a novel β-Cyclodextrin modified Nelumbo nucifera (β-CDNN) sorbent. The sorbent was characterized using different analytical techniques, to assess its dye sorption capability. The analysis of sorption isotherm data revealed that the Freundlich model most accurately represented the equilibrium data. Kinetic studies indicated that the sorption process followed a pseudo-second-order model. At pH 5–8, the sorbent achieved maximum removal efficiencies of 96.7 %, 94.2 %, and 96.3 % for Malachite Green (402.7 mg/g), Methylene Blue (385.6 mg/g), and Basic Magenta Dye (401.03 mg/g), respectively, at equilibrium time 60 mins for MAG & MEB and 80 mins for MAD. The maximum swelling capacity of β-CDNN was recorded at 180.4 % and selectivity assay was performed via a MAG-AO7 dye mixture. The sorbent reusability was recorded for six consecutive cycles without much loss in efficiency. Additionally, β-CDNN exhibited a removal efficiency of 91.3 % in real dye samples. The findings highlight the rapid dye adsorption capabilities of β-CDNN, establishing it as a versatile, cost-effective, and environmentally friendly solution for water remediation, while also underscoring the beneficial use of bio-waste materials.

Type-II heterojunction In2O3/TiO2 with highly efficient charge separation for boosted photocatalytic NO abatement

Photocatalytic NO degradation often suffers from sluggish charge carrier separation and low selectivity. Herein, a series of In2O3/TiO2 (P25) composites were synthesized to enhance NO abatement. Benefiting from the conspicuous synergistic effect between In2O3 and P25, the In2O3/P25 catalysts demonstrated more than double the NO elimination performance compared to pure P25 and In2O3. The In2O3/P25 sample with 75 wt% In2O3 (In-P25-75) achieved a NO removal efficiency of 51.7 %, higher than reported catalysts (30.0–49.0 %). It was the successful formation of type-II heterostructure that enabled intimate interfacial contact and provided ample electron transfer channels. Moreover, photoluminescence spectra and photoelectrochemical measurement confirmed the improved separation and inhibited recombination of photogenerated charge carriers in In-P25-75, thereby boosting the NO photocatalytic efficiency. ·O2− and ·OH radicals generated by photoinduced electron transfer to the conduction band of P25, along with the induced holes confined to the valence band of In2O3, facilitated the targeted deep oxidation of trace NO into NO3− rather than harmful NO2. This work discloses a promising strategy for the efficient removal of NO from the atmosphere by reducing the emission of hazardous intermediate NO2.

Heavy metal ions in polluted water removable by synthesising a new compounds for dithiocarbamate derivatives

Metal ion poisoning in water and industrial effluents threatens ecosystems and human health. The development of efficient metal ion removal technologies has garnered attention in recent years. This work synthesizes and characterizes dithiocarbamate complexes as metal ion scavengers. Used to make dithiocarbamate ligands. Different metal salts were added to carbon disulfide and the proper amines to initiate substitution reactions. The complexes were characterized using FTIR, UV-Vis, mass spectroscopy, 13C-, 1H-NMR, magnetic susceptibility, melting point, and electrical conductivity molar EC. Data from spectroscopy and analysis indicate the development of two-type macrocyclic complexes with the formula [M(L)]2, where M = FeII, CoII, and ZnII ions. Tetrahedral geometries around the metal core and the second general formula [M(L)(H2O)2]2, where M = MnII, NiII, CuII, suggested octahedral structures. Heavy water pollution has been removed using this essential ligand. Metal ion scavenging of 96–98% was possible with the produced dithiocarbamate complexes. This work developed unique and efficient strategies for metal contamination removal from aquatic settings, promising environmental remediation and human health protection. Optimizing synthesis conditions and scaling up operations are needed to fully use these compounds in real-world applications. KEY WORDS: Dithiocarbamate ligand, Transition metal complexes, Spectral characterization, Coordination chemistry, Dithiocarbamate complexes, Scavenger heavy metal ions Bull. Chem. Soc. Ethiop. 2024, 38(6), 1583-1593. DOI: https://dx.doi.org/10.4314/bcse.v38i6.7

Fabrication of Hierarchically Porous “Fish Cage”‐like Carbonaceous Nanomaterials via Soft Template‐assisted Strategy for Cr Removal: Accelerated Stepped Adsorption and Enhanced Coordination Effect

The negative impact of heavy metal pollution, specifically chromium (VI), on human health is well‐documented. To solve this issue, hollow anisotropic hierarchically porous “Fish Cage”‐like carbonaceous nanomaterial (N,S‐HFC‐180) with multi‐active groups is synthesized. Hierarchically porous structure provides stepped adsorption effect. The addition of K2C2O4 leads to the specific surface area of N,S‐HFC‐180 increases to 1914.21 m2·g‐1 (an increase of ~552 times compared to HFC‐180). Thiourea introduces multi‐active groups act as “Barbs” in “Fish Cage” further reducing Cr(VI) to Cr(III) and sequestrating Cr(III) by coordination effect. Subsequent batch studies suggest that N,S‐HFC‐180 exhibits a high removal capacity of 164.29 mg·g‐1 for Cr(VI) at pH = 2. The kinetics and isotherm analyses display an outstanding maximum adsorption capacity of 393.88 mg·g‐1 at 298 K. In addition, even after seven cycles, the removal rate of Cr(VI) using N,S‐HFC‐180 remains > 85.00%, and it effectively reduces the concentration of electroplating wastewater from 55.82 to 0.14 mg·L‐1. Pore filling, chemical reduction and chelation, hydrogen bond and electrostatic attraction are the primary adsorption drivers. The results suggest that, the recoverable N,S‐HFC‐180 highlights its viability for practical applications in wastewater treatment processes.

Sulfur Fluoride Exchange Enabled Polysufate Adsorbents: Flexible Group Embedded in Polymer Backbone Regulation Strategy for Organic Solvent Removal from Water.

Removal of organic solvents (such as chloroform, toluene, etc.) in trace amounts using adsorbents from water is a challenge due to their low removal efficiencies and poor selectivities. Herein, four polysulfates (P1-P4) with different flexible group embedded backbones were synthesized via a sulfur fluoride exchange (SuFEx) reaction, and their swelling behaviors in organic solvents were investigated. P1 with a flexible ethyl group on its backbone can selectively swell in aprotic organic solvents with medium and high polarities about 30-fold its original weight, which is much higher than that of P4 with rigid benzene on its backbone. Moreover, molecular dynamic (MD) simulation results showed that the swelling mechanism could be put down to the electrostatic and van der Waals forces between the polysulfates and organic solvents. Surprisingly, the polysulfates can be used to remove chloroform and toluene from water with removal efficiencies of up to 99.26 and 99.42%, respectively. Furthermore, the polysulfates also exhibited high selectivities and anti-interference performances toward chloroform in the presence of other pollutants and different acid/base environments. Our work provides a strategy to construct adsorbents with high efficiencies for removal of low concentrations of organic solvents from water.

Computational analysis of bare and alkali metal-encapsulated Al12N12 nanocages for enhanced removal of fluoroquinolone antibiotics from wastewater

Antibiotics, particularly fluoroquinolones, and their residues pose significant risks to both aquatic and human life, underscoring the need for effective removal strategies. While nanomaterials show promise in addressing this issue, the theoretical understanding of their interactions with antibiotics has been limited. In this context, we conducted DFT calculations to explore the interactions between fluoroquinolone antibiotics and the Al12N12 nanocage, aiming to provide valuable data for future experimental investigations. In the present research, the adsorption behavior of fluoroquinolone (FQ) antibiotics including ciprofloxacin (C17H18FN3O3), gemifloxacin (C18H20FN5O4), levofloxacin (C18H20FN3O4), moxifloxacin (C21H24FN3O4), delafloxacin (C18H12ClF3N4O4) and ofloxacin (C18H20FN3O4) onto the surface of the bare and metal-encapsulated Al12N12 (Li-Al12N12 and Na-Al12N12) nanocages are studied using dispersion corrected density functional theory (DFT-D) calculations. The primary purpose is to explore the potential application of these nanomaterials for efficient fluoroquinolone removal. The results indicate that the encapsulation of Li or Na inside Al12N12 nanocage enhances the adsorption of the FQs. The desorption process is also investigated in acidic medium, revealing that Li-Al12N12 and Na-Al12N12 cages emerge as superior candidate than the bare Al12N12 nanocage for controlled FQs removal applications. The Li-Al12N12 and Na-Al12N12 are introduced as promising candidates for fluoroquinolone removal in aqueous medium. This study might provide an innovative perspective for future investigations in the field of the drug pollution removal using aluminum nitride-based nanomaterials.

Unveiling the role of artificial intelligence in tetracycline antibiotics removal using UV/sulfite/phenol advanced reduction process

UV/sulfite-based advanced reduction processes (ARP) have attracted increasing attention due to their high capability for removing a wide range of pollutants. Therefore, developing UV/sulfite ARP systems with assisted Artificial Intelligence (AI) models is considered an efficient strategy for sustainable pollutant removal. The present study delves into modeling and optimizing photodegradation of tetracycline (TC) antibiotics under UV/sulfite/рhenol reԁuсtion рroсess (UV/SPAP) using integrаteԁ Artifiсiаl Neurаl Networks (ANN), Suррort Veсtor Regression (SVR), аnԁ Genetiс Algorithm (GA). The сonсentrаtions of рhenol (X1) аnԁ sulfite (X2), рH (X3), reасtion time (X4), аnԁ TC сonсentrаtion (X5) in our exрerimentаl setuр were varied, аnԁ use the generаteԁ ԁаtа to trаin AI moԁels. The findings revealed that the AI-optimized performance is very effective in predicting and optimizing the removal of TC, thereby providing a sustainable water treatment approach. In general, SVR performed better based on scaling coefficients and ANN using different criteria indicated that X4 and X5 parameters were statistically significant. Oрtimаl rаnges for X1, X2, X3, X4, аnԁ X5 аre ԁetermineԁ to be 6.34, 3, 8.45, 80.13, аnԁ 1, resрeсtively. This аррroасh highlights the imрortаnсe of integrаting AI аnԁ ARP for sustаinаble environmentаl mаnаgement.

Preparation of NH2-MIL-101(Fe) Metal Organic Framework and Its Performance in Adsorbing and Removing Tetracycline.

Tetracycline's accumulation in the environment poses threats to human health and the ecological balance, necessitating efficient and rapid removal methods. Novel porous metal-organic framework (MOF) materials have garnered significant attention in academia due to their distinctive characteristics. This paper focuses on studying the adsorption and removal performance of amino-modified MIL-101(Fe) materials towards tetracycline, along with their adsorption mechanisms. The main research objectives and conclusions are as follows: (1) NH2-MIL-101(Fe) MOF materials were successfully synthesized via the solvothermal method, confirmed through various characterization techniques including XRD, FT-IR, SEM, EDS, XPS, BET, and TGA. (2) NH2-MIL-101(Fe) exhibited a 40% enhancement in tetracycline adsorption performance compared to MIL-101(Fe), primarily through chemical adsorption following pseudo-second-order kinetics. The adsorption process conformed well to Freundlich isotherm models, indicating multilayer and heterogeneous adsorption characteristics. Thermodynamic analysis revealed the adsorption process as a spontaneous endothermic reaction. (3) An increased adsorbent dosage and temperature correspondingly improved NH2-MIL-101(Fe)'s adsorption efficiency, with optimal performance observed under neutral pH conditions. These findings provide new strategies for the effective removal of tetracycline from the environment, thus holding significant implications for environmental protection.

Using demographic modeling to develop post‐fire restoration strategies for a native shrub in a sage scrub community

Mediterranean‐climate shrublands are key biodiversity hotspots and carbon storage pools, but are increasingly threatened by climate change, non‐native species, and altered fire regimes. Fires are important to historic shrubland disturbance cycles but can also promote non‐native plants, which may limit post‐fire native shrub recovery. Increasing drought with climate change could also reduce post‐fire shrub regeneration. I developed a stochastic, individual‐based demographic model (IBM) for the native shrub Artemisia californica, parameterized from an experimental removal of non‐native annuals after a 2013 fire in southern California. The IBM simulated A. californica recovery for 7 years after fire under different rainfall conditions (drought or pre‐drought) and non‐native removal strategies (from no years to all 7 years). Drought lowered A. californica canopy volume 7 years after fire by 90% or more. Rainfall in the second year after fire, when most A. californica germination occurred, had particularly strong effects on final canopy cover. Non‐native removal in all 7 years increased canopy volume by three times under drought conditions and 3.5 times under pre‐drought conditions. Targeting non‐native removal in the first 2 years proved nearly as effective, achieving from 88% (drought) to 95% (pre‐drought) the benefits of removal in all 7 years. In sum, low rainfall may be the most important limitation on post‐fire shrub recovery, but removal of non‐natives in years of pulsed shrub recruitment can be an effective restoration strategy even under drought conditions. More generally, this study illustrates how demographic models can help optimize the targeting of scarce management and restoration resources.

Mechanism of adsorption and targeted degradation of antimicrobial micropollutant sulfamethoxazole in aquatic environments

FHWSB as an integrated absorptive catalyst, based on Walnut shell biochar (WSB) via hydrochloric acid modification and ferrous chloride impregnation, was prepared, reacted with H2O2 to generate active free radicals •OH and •O2−, which oxidized and degraded about 80% of micro-pollutant sulfamethoxazole (SMX) from water, effectively resolving micro-pollutants' removal being inefficient because of high toxicity, persistence, and bioaccumulation in existed methods. It was clarified the specific degradation pathways and mechanisms of SMX by FHWSB synergistic H2O2 via characterization and analysis assisted DFT calculations. Furthermore, it was found that the toxicity of a series of intermediates produced by SMX degraded continued to decline, consistent with its direction of degradation via toxicological analysis. The work provides a simple and feasible strategy for the effective removal of antibiotic micro-pollutants in aquatic environments.

Random and systematic uncertainty in ship‐based seawater carbonate chemistry observations

AbstractSeawater carbonate chemistry observations are increasingly necessary to study a broad array of oceanographic challenges such as ocean acidification, carbon inventory tracking, and assessment of marine carbon dioxide removal strategies. The uncertainty in a seawater carbonate chemistry observation comes from unknown random variations and systematic offsets. Here, we estimate the magnitudes of these random and systematic components of uncertainty for the discrete open‐ocean carbonate chemistry measurements in the Global Ocean Data Analysis Project 2022 update (GLODAPv2.2022). We use both an uncertainty propagation approach and a carbonate chemistry measurement “inter‐consistency” approach that quantifies the disagreement between measured carbonate chemistry variables and calculations of the same variables from other carbonate chemistry measurements. Our inter‐consistency analysis reveals that the seawater carbonate chemistry measurement community has collected and released data with a random uncertainty that averages about 1.7 times the uncertainty estimated by propagating the desired “climate‐quality” random uncertainties. However, we obtain differing random uncertainty estimates for subsets of the available data, with some subsets seemingly meeting the climate‐quality criteria. We find that seawater pH measurements on the total scale do not meet the climate‐quality criteria, though the inter‐consistency of these measurements improves (by 38%) when limited to the subset of measurements made using purified indicator dyes. We show that GLODAPv2 adjustments improve inter‐consistency for some subsets of the measurements while worsening it for others. Finally, we provide general guidance for quantifying the random uncertainty that applies for common combinations of measured and calculated values.

Precise target capture and the dynamic separation of Sn(IV) in highly acidic media by combining N and P donor covalent organic framework silica-based composite adsorbents

A silica-based adsorbent (P507@COF-TpAzo/SiO2) with nitrogen and phosphorus donors was prepared for industrial separation and recovery of Sn(IV) by in-situ growth of covalent organic framework (COF) on a silica substrate combined with vacuum impregnation. The materials were tested and analyzed by the scanning electron microscope (SEM), X-ray diffraction (XRD) and other characterization techniques, which demonstrated that the adsorbent has an enormous specific surface area, excellent heat resistance, and a regular morphological structure. The static experimental results showed that the adsorbent displayed remarkable selectivity for Sn(IV) in high HCl and HNO3 concentration environments, with excellent kinetics (∼60 min) and outstanding adsorption capacities (60.02 mg/g in 3 M HCl, 92.59 mg/g in 3 M HNO3) in different media at 3 M acidity. Cycle performance testing demonstrated that the adsorbent exhibited excellent stability (cycle times ≥8). Analysis using Fourier transform infrared spectroscopy (FT-IR) and X-ray photoelectron spectroscopy (XPS) showed that the synergistic adsorption results of N and P were reflected, mainly by the synergistic complexation of P=O and N=N-C. The potential sites for the adsorption of the adsorbent towards Sn(IV) were predicted by density functional theory (DFT) calculations, and the adsorbent demonstrated a more stable binding energy with Sn(IV). Finally, dynamic separation and efficient enrichment (>210) of Sn(IV) in highly acidic wastewater were realized by designing a penetrating column separation process. P507@COF-TpAzo/SiO2 satisfied the requirements of the dynamic adsorption experiments, bridging the research gap of dynamic separation, and provides a new strategy for the industrial removal and recovery of Sn(IV), as well as a way for environmental protection and industrial green production.

Effects of settleable versus unsettled biofloc removal strategy on aquaculture system performance and microbial community

The management of biofloc quality and quantity is critical in biofloc-based aquaculture systems. This research explores the effects of the selective removal of settleable and unsettled bioflocs on biofloc quality, fish growth, nitrogen transformation and bacterial community dynamics in these systems. Nile tilapia (Oreochromis niloticus) was reared at a density of 2.7 kg/m3 in nine 250-L conical breeding tanks over a 47-day period. Systems where unsettled bioflocs were removed outperformed others, achieving a 26 % higher weight gain in tilapia and maintaining more stable and lower levels of total ammonia (0.45 mg-N/L) and nitrite (0.35 mg-N/L). Additionally, these systems maintained a healthier bacterial environment, evidenced by a 27 % increase in beneficial bacterial populations and a 30 % reduction in harmful bacteria. Conversely, tanks removing settleable bioflocs showed a 19 % higher microbial diversity but experienced fluctuations in nitrogen levels. Notably, the intestinal bacterial community in tilapia from the unsettled biofloc group closely mirrored (87 % similarity) that of their corresponding bioflocs, with significant pathogenic symptoms observed (p < 0.05). These findings suggest the importance of implementing precise biofloc management strategies, highlighting that the selective removal of unsettled bioflocs enhances fish growth and improves overall system health. Future research should explore the mechanistic relationships between settleable and unsettled bioflocs to refine management strategies that bolster sustainability and economic benefits.

Boron-doping tunes nitrogen species to abundant edge-N and B-N matrix for efficient phosphate removal in capacitive deionization: Additional accessible sites and defective centers

The elimination of eutrophication necessitates the implement of a clean and efficient phosphate removal strategy. Capacitive deionization (CDI) is recently regarded a promising approach for removing pollutants from aqueous environment with high-efficiency, facile operation, and low-energy consumption. Development of electrode materials with good properties is crucial for CDI. In this study, novel edge-N-modified boron-doped hierarchical carbon composites (MBCNs) were prepared via a hard template strategy for phosphate electrosorption. According to the pseudo-second-order kinetic, the MBCN2 electrode exhibited a dynamic capacity of 196.02 mg PO43− g−1 in 150 min with an initial concentration of 100 mg PO43− L−1 at 1.2 V. And it also demonstrated an exceptional saturation capacity of 399.70 mg PO43− g−1 under the Langmuir model. Based on theoretical analysis and experimental results, the incorporation of boron atoms in the carbon framework indicated a dual reinforcement. This included an enhanced proportion of edge-N modifications for defective centers and sufficient high-polarity B-N matrix for additional available active sites. The joint contribution of edge-N and B-N matrix revealed favorable electrical double layer capacitance, which resulted in good phosphate removal performance. This work disclosed the synergistic impact of dual nonmetallic atom doping, providing insights into the efficient phosphate removal anode for CDI.