MgO-based adsorbents are promising for mitigating water eutrophication via efficient recovery of nitrogen (N) and phosphorus (P). However, systematic investigations into how Mg precursors regulate MgO formation, pore development, and N/P recovery performance of modified biochar (MBC) remain scarce, with the underlying mechanisms yet to be clarified. Herein, MBCs were fabricated using five distinct Mg precursors. Results showed that MBCs with tailored structures exhibited varied adsorption capacities and kinetics, with adsorption rate positively correlated with total pore volume (TPV) and average pore size (APS). Among them, HO-MBC had the largest pore diameter and volume, facilitating rapid struvite growth, achieving maximum adsorption capacities of 645 mg/g for PO43--P and 237 mg/g for NH4+-N. HO-MBC further exhibited superior practicality: it maintained efficacy over a broad pH range (5.0-10.0), formed larger struvite crystals (15-40 mu m), and its lower SBET enhanced selectivity for N/P recovery while reducing impurity adsorption. Moreover, N/P-saturated HO-MBC (NP@HO-MBC) significantly promoted seed germination and growth, soil application enabled sustained N/P release and heavy metal (Cd, Zn) immobilization, showing potential as both controlled-release fertilizer and soil remediation agent. This work provides valuable insights for rational MBC design and their integrated application in wastewater treatment and soil remediation.

Urban fire has been one of the most significant threats to humans and is not completely avoidable in the modern era. To manage fire risk more effectively, it is critical to identify key factors that influence fire risk. However, conducting proper risk assessments is very challenging due to the complex interactions among these factors and their regional specificity. The current study classifies multiple counties in the United States into normal and rich groups, analyzing the disparities in fire incidents, fire losses, and fire losses/GDP after logarithmically transforming them into two groups: 3.3%, 5.63%, and 8.66%, respectively. Then an ensemble learning model based on MI-RF and MI-SVM-RFE is constructed to identify the key socio-economic factors influencing fire risk in each group. The results show that the MI-RF model demonstrates superior feature selection performance, with an average dimensionality reduction rate of 72.78% and an accuracy rate of 82.9%. The key social-economic factors influencing fire incidents and fire losses in rich cities are 21 and 22, while in normal cities are 14 and 29. The relevant factors affecting the number of fire incidents and the amount of fire losses in each group are not entirely congruent. These findings provide valuable insights for further analysis and interpretation of the underlying reasons for the disparities in fire risk factors, which are related to urban socio-demographic characteristics and economic activities, thereby supporting policymakers in formulating appropriate safety management measures to mitigate fire risk.

The low utilization of nitrogen (N) and phosphorus (P) fertilizers causes resource waste and water eutrophication. To address this, novel biochar composites (Mg-ZSBC and CS-Mg-ZSBC) were prepared via co-pyrolysis of corn stover with zeolite, magnesium modification, and chitosan coating. Adsorption experiments showed that Mg-ZSBC efficiently immobilized N/P through struvite precipitation, achieving removal rates of 90.05% for P and 55.73% for N, with maximum adsorption capacities of 106.61 mg/g for NH4+-N and 170.55 mg/g for PO43--P. Release kinetics revealed that chitosan-coated CS-Mg-ZSBC had cumulative release rates of only 10.22% for N and 15.27% for P over 35 days in soil. Pot experiments demonstrated that compared to traditional compound fertilizers, CS-Mg-ZSBC increased Chinese cabbage height and root length by 10-15%, and boosted biomass by 28.7%. It also improved soil cation exchange capacity and microbial community structure. This study provides a feasible strategy for recovering wastewater nitrogen and phosphorus and developing low-carbon, eco-friendly biochar-based slow-release fertilizers.

Copper-based persulfate activation is an effective approach for degrading phenolic pollutants, but its practical application is often constrained by the agglomeration of nano-CuO and the associated copper leaching. In this study, a CuO-loaded Miscanthus lutarioriparius (CuO-ML) activator was developed by exploiting the intrinsic three-dimensional (3D) closed-cell structure of ML, a natural wetland biomass, and in situ immobilizing nanoCuO on its inner pore walls. The preparation process was simple without any fixer required, and the obtained CuO-ML had a macroscopic structure, being readily recoverable. In the CuO-ML/PDS/NaHCO3 system, NaHCO3 was introduced to suppress Cu2+ leaching by regulating the solution pH. Under the optimized conditions, the system achieved the complete degradation of 2-chlorophenol (2-CP) within 50 min and 71 % removal of total organic carbon at 60 min. The degradation performance kept stability in the presence of coexisting anions (Cl-, SO4 2-and NO3- ) and was well maintained over five successive cycles. Acute toxicity assays confirmed that the treated solution showed no obvious biological toxicity. The 2-CP degradation proceeded through a surfacedominated process involving the joint participation of SO4 center dot-ads, center dot OHads, O2 center dot- and 1O2. The surface functional groups on the ML and the 2-CP acted as the electron donors for activating PDS. The degradation pathway of 2-CP was first dechlorinated to form pyrocatechnol, then gradually oxidized to 2,4-hexadienedioic acid, maleic acid/ fumaric acid and oxalic acid/propanedioic acid, and finally mineralized to CO2 and H2O. Overall, this study integrated nano-CuO with a cost-effective wetland plant, offering a sustainable approach for phenolic wastewater treatment.

The core of heterogeneous catalytic systems is to design high-performance heterogeneous catalysts. In the present study, CuO-PEI-JE was synthesized via in situ precipitation of CuO on the 3D structure of PEI-JE prepared by a cross-linking method. It possessed a macro-size and 3D open-cell structure, being easily separated and having super-performance for PDS activation. Compared to PDS alone (0.0017 min- 1), the CuO-PEI-JE + PDS + NaHCO3 system increased the kobs (0.3526 min- 1) by a factor of 207 with 100% phenol degradation within 20 min and 87% TOC removal at 30 min. It outperformed many other published heterogeneous persulfate systems in phenol degradation. Meanwhile, the developed system displayed a good anti-interference ability in the coexistence of anions or different water matrixes. After five successive cycles, the degradation rate still kept 100%, exhibiting the excellent reusability of CuO-PEI-JE. Furthermore, the preparation of CuO-PEI-JE had the advantages with moderate preparation conditions (60 degrees C) and readily available raw materials. The activation mechanism was mainly involved in the formation of active PDS and its further decomposition into & sdot;OHads, SO4ads, O2 and 1O2. Surface functional groups and phenol acted as electron donors for active PDS. Phenol was first degraded into hexadienedioic acid, then oxidized to propane diacid and oxalic acid, and finally mineralized into CO2 and H2O. This work provides a new strategy for preparing effective heterogeneous persulfate activators and has high potential for the treatment of phenol-containing wastewater.

Urban fire risks intensify owing to rapid urbanization, increasing population density, and concentrated infrastructure. Traditional fire risk assessment models, such as Multi-scale Geographically Weighted Regression (MGWR), often overlook spatial heterogeneity and lack interpretability. This study applied an eXplainable Artificial Intelligence (XAI) framework integrating eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP) for predictive modeling and for feature attribution, respectively, to assess the urban fire risk in Qingyang District in Chengdu, China. A key challenge was to address the spatial complexity of fire risks and ensure model interpretability for decision-makers. To overcome this challenge, we integrated spatial autocorrelation metrics and kernel density analysis to analyze the spatial patterns of key features. The framework outperformed MGWR in terms of prediction accuracy, with R2 values of 0.998 for fire occurrence and 0.935 for fire loss, compared to the 0.995 and 0.856 obtained for MGWR, respectively. The mean squared error was 4.447 for fire occurrence and 0.00027 for fire loss, while 10.297 and 0.00055 were obtained for MGWR, respectively. Notably, the SHAP values proved to be effective in explaining the spatial heterogeneity of urban fire risk features. The main contributions of this study are as follows: (1) the integration of XGBoost and SHAP for interpretable urban fire risk prediction, (2) the application of spatial analysis to enhance model transparency, and (3) the development of a framework that provides actionable, spatially explicit insights for urban safety planning. This study provides a data-driven tool for policymakers that offers quantitative guidance for urban fire risk mitigation.

Lanthanum (La)-based hydroxide materials are considered promising candidates for phosphate removal, but their adsorption efficiency is often limited by the hydroxide (OH-) release and slow mass transfer. In this study, we synthesized lanthanum hydroxyl carbonate supported onto magnetic porous biochar (La-FPBC0.5) for advanced phosphate removal from actual secondary effluent of wastewater. La-FPBC0.5 significantly enhanced phosphate removal by releasing more carbonate (CO32-) rather than hydroxy (-OH) during adsorption. Density functional theory calculations revealed that the absolute value of absorb adsorption energy for ion exchange in La-FPBC0.5 is 4.48 eV, higher than that for ligand exchange (3.11 eV). The adsorption kinetic rate constant of La-FPBC0.5 reached 1.7 x 10-3 g/(mg-1 min), which is 1.8 times that of La(CO3)(OH). Furthermore, La-FPBC0.5 removed up to 151.5 mg P/g of phosphate from wastewater, representing a 1.6-fold increase compared to La(CO3)(OH), surpassing not only commercial La-based materials but also most reported adsorbents. It maintained over 85 % of its phosphate adsorption capacity in the presence of anions or humic acid and showed effective adsorption across various water sources, including river, campus lake, and tap water, with a capacity exceeding 120 mg P/g. La-FPBC0.5 also exhibited excellent stability, retaining 95 % of its capacity after five adsorption-desorption cycles. Notably, La-FPBC0.5 treated approximately 1800 bed volumes of phosphate-containing wastewater to below 0.1 mg/L in a fixed-bed adsorption mode, with the recovered phosphate suitable for plant growth. These results suggest that La-FPBC0.5 is an ideal candidate for phosphate removal in practical applications.

Singlet oxygen (O-1(2)) is attractive in water decontamination because of its high selectivity to remove organic pollutants, but its oriented generation in peroxymonosulfate (PMS) activation is still challenging, especially using metal catalysts. In this study, it was found that simple sulfuration of FeCo layered double hydroxide (FeCo-LDH-S-10) can achieve efficient O-1(2) generation in PMS activation, and SO5- is the precursor of O-1(2). Density functional theory calculations revealed that sulfuration of FeCo-LDH positively shifts the d-band center of Co 3d to enhance the interaction between Co site and PMS, thus reducing the free energy barrier for O-1(2) formation from 1.02 eV to 0.61 eV. With norfloxacin (NOR) as the target pollutant, FeCo-LDH-S-10 not only has much higher catalytic activity than the original FeCo-LDH but also most of the reported catalysts. In the continuous-flow reactor containing FeCo-LDH-S-10, a high removal rate of NOR (>90 %) can be kept for more than 132 h. Importantly, the activity of the used FeCo-LDH-S-10 in the continuous-flow reactor can be easily in-situ regenerated through simple sulfuration again. Furthermore, various antibiotics in actual secondary effluent of wastewater treatment plants can be effectively removed by FeCo-LDH-S-10/PMS system, leading to a significant decrease of toxicity. This work emphasizes the feasibility of enhancing actual water decontamination by modulating the O-1(2) formation in PMS-based advanced oxidation processes.

This study determined the optimal preparation temperature and time of Mg–BC, which has excellent synergistic adsorption capacity for NH 4 + and PO 4 3− . Furthermore, NP@Mg–BC can serve as a fertilizer to facilitate the resource utilization of N and P.

Developing high-performance heterogeneous catalysts was the core for constructing efficiently heterogeneous catalytic system. In this study, CuO-loaded chitosan hydrogel spheres (CuO/CS) were prepared via one-step method where the shaping of CS spheres and the in-situ precipitation of CuO happened simultaneously. The obtained CuO/CS was employed as an efficient heterogeneous activator of PDS for phenol degradation in the coexistence of NaHCO3. The introduction of NaHCO3 not only promoted phenol degradation, but also effectively inhibited the Cu2+ leaching. With 15 g/L of CuO/CS, 500 mg/L of PDS and 5 mmol/L of NaHCO3, 50 mg/L of phenol reached 100 % degradation rate and 73.09 % TOC removal within 120 min, meanwhile the Cu2+ leaching concentration was only 0.18 mg/L. The coexisting ions experiment and the spiked experiment in real water samples exhibited the excellent anti-interference of the developed system. After five consecutive cycles, the degradation rate of phenol still had 95.33 %, suggesting the good reusability of the CuO/CS. center dot OHads, SO4ads-center dot, O-2(-center dot), O-1(2) and Cu(III) were identified as the main active species. During the degradation process, phenol was first degraded into hexadienedioic acid, then converted to propane diacid and oxalic, and finally to CO2 and H2O. This study provides an efficient heterogeneous catalytic system for the treatment of phenol-containing wastewater.

As one of the attractive phosphate adsorption materials, layered double hydroxide (LDH) is frequently used in the form of nanomaterials, which makes LDH suffer from weak recyclability and agglomeration. Powder immobilization is applicable for separation, though usually sacrifices the adsorption capacity. In this investigation, Two types of rare earth-based layered double hydroxide/chitosan (CS) hydrogel beads were fabricated, namely LaCa-LDH/CS and CeCa-LDH/CS. The results demonstrate that the combination of CS and LDH exhibits superior adsorption performance than individual LDH, primarily due to the incorporation of -NH2 and the uniform dispersion of LDH in CS. The maximum adsorption capacities for phosphate on LaCa-LDH/CS and CeCa-LDH/CS are 149.5 and 174.6 mg P/g at 200 mg P/L and pH 5, respectively, surpassing the powder form of LaCa-LDH (107.9 mg P/g), CeCa-LDH (105.0 mg P/g), and pure CS beads (10.2 mg P/g). Furthermore, both LaCa-LDH/CS and CeCa-LDH/CS exhibit steady phosphate removal performance at a wide pH range, and the adsorption capacities only experience a decrease of 20.0 % and 28.4 % from pH 3–7, outperforming previous reports. The co-existing anions effect experiments proved excellent selectivity of LDH/CS to phosphate. The stable binding of phosphate on LDH/CS is confirmed through a long-term adsorption stability test lasting for 10 days. Moreover, two LDH/CS could remove 96 % phosphate from natural water. After five cycles, the adsorption capacities of two LDH/CS were maintained at over 95 %. The primary adsorption mechanism involves electrostatic attraction as pH < pHpzc and ligand exchange as pH > pHpzc. Ion exchange and hydrogen bonding also contribute to a certain extent.

Layered double hydroxide (LDH) is frequently used for phosphate removal in water, while a desirable LDH adsorbent should have sufficiently high adsorption capacity and selectivity.

There is an interaction between public fire safety awareness and fire direct economic loss, while how to quantify public fire safety awareness is still a challenge. Driven by the rapid development of Internet networks and information technology, Internet search engine query data provides an opportunity for quantifying the level of public fire safety awareness. Based on the fire-related Baidu Search Volume (BSV) data, this paper investigates the relationship between public fire safety awareness and fire direct economic loss with an integration machine learning method. Firstly, the fire-related keywords selection framework is constructed based on the analysis of the fire safety demand generated at different responding stages of fire accidents. Then, the most important keywords associated with fire direct economic losses are identified by correlation analysis. Finally, four types of assessing models, including multiple regression model, principal component analysis model, vector auto-regression model, and artificial neural network model are developed to simulate the ability of fire-related keywords to assess fire direct economic losses. The results show that the fire-related keywords BSV data have a strong correlation with the fire direct economic loss. Meanwhile, BSV data presents a good applicability in evaluating the fire direct economic loss. The artificial neural network model presents the best assessment performance in this work. This research could contribute to quantifying the public awareness of fire safety, indirectly present the public fire safety behavior, and also provide a new solution for how to assess urban fire risk.

Hydrothermal carbonization is highly applicable to high moisture biomass upgrading due to fact that moisture involved can be directly used as reaction media under subcritical-water region. With this, value-added utilization of hydrochar as solid fuel with high carbon and energy density is one of the important pathways for biomass conversion. In this review, the dewatering properties of hydrochar after the hydrothermal carbonization of biowaste, coalification degree with elemental composition and evolution, pelletization of hydrochar to enhance the mechanical properties and density, coupled with the combustion properties of hydrochar biofuel were discussed with various biomass and carbonization parameters. Potential applications for the co-combustion with coal, cleaner properties and energy balance for biowaste hydrothermal carbonization were presented as well as the challenges.

Phosphorus (P) is a nutrient element triggering eutrophication. Therefore, the removal of excess phosphorus has become an emergent demand. In this study, lanthanum-loaded biochar (La-BC) was prepared via a simple one-step pyrolysis method. Its surface properties and structural characteristics were analyzed by SEM, XRD, FTIR and pHpzc. The phosphate removal by the La-BC was systematically investigated in batch mode. Results showed that the phosphorus adsorption obeyed the pseudo-second-order model and Langmuir isotherm. The calculated maximum adsorption capacities were 31.94, 33.06 and 33.98 mg/g at 25, 35 and 45°C, respectively. Except for SO42− and CO32−, phosphate adsorption by the La-BC showed strong anti-interference to coexisting ions. For real water samples, the phosphate concentrations in the effluents were below 0.02 mg/L after treatment. The P loaded the La-BC was difficult to be desorbed, suggesting that the La-BC was not only a P-capping agent but also a P-immobilizing agent. More interestingly, a large number of stable LaPO4 nanofibers were formed on the La-BC surface via the reaction between the dissolved phosphate anions and La(OH)3 loaded on the adsorbent. Their intertwining facilitated the formation of the floc, which was conducive to the solid–liquid separation. Hence, the developed La-BC can be used as a potential adsorbent for natural waterbody remediation.

Decorative wood boards are common combustible materials and have been utilized in lots of buildings, which could bring serious property loss and casualties due to fires. In order to analyze fire hazard of decorative wood boards, horizontal flame spread characteristics and combustion traces were studied on six typical decorative wood boards though the tunnel furnace test in this paper. It was found that the flame spread distance of all the samples were in power function with time. With the increase of ambient temperature and ambient wind speed, the combustion was more intense, the crack length increased, the flame spread distance, and the flame spread rate (V) all increased, the cracks got wider, the micro appearance damage and the degree of carbonization got more serious. Among them, the relationship between V and the initial temperature difference (T-v-T-i) between solid pyrolysis temperature and the ambient temperature could be expressed as V similar to(T-v-T-i)(theta) and the exponent of the power law theta was -6.24 for the decorative wood boards; the relationship between V and the ambient wind speed (U-infinity) could be expressed as V similar to U-infinity(delta) and delta was 9.0 for the decorative wood boards. In addition, the change rules of C, P and S elements on the combustion residues were similar, which were opposite to the change rule of O.

The spectral fingerprint is a significant concept in nontarget screening of environmental samples to direct identification efforts to relevant and important features. Surface-enhanced Raman scattering (SERS) has long been recognized as an optical method that can provide fingerprint-like chemical information at the single-molecule level. Here, the advanced one-dimensional convolutional neural network (1D-CNN) approach was applied to accurately identify the SERS spectral signature of industrial wastewaters for source tracing. A total of 66,000 SERS spectra were acquired from wastewaters of 22 factories across 10 industrial categories at three excitation wavelengths after data augmentation. The dataset was used to train a 1D-CNN model consisting of three convolutional layers to achieve adequate feature extraction of SERS spectra. As a proof-of-concept, multimixed wastewater samples were used to simulate practical pollution scenarios and evaluate the application potential of the model. The SERS-1D-CNN platform can identify the amount and factory information of wastewaters in multimixed samples, which achieves a recognition accuracy rate of 97.33%. The results suggest that even in a complex and unknown water environment, the 1D-CNN model can accurately identify industrial wastewaters in precollected datasets, exhibiting excellent potential in pollution source tracing.

La2O3 and CeO2, as main rare earth oxides, with unique physical and chemical properties have been widely used in catalyst and grinding industry. In this study, the effects of La2O3 and CeO2 on the anaerobic process were investigated. The biological methane production tests showed that 0-0.05 g/L La2O3 and 0-0.05 g/L CeO2 enhanced anaerobic methanogenesis process. The result showed maximum specific methanogenic rates of La2O3 and CeO2 were 56.26 mL/(h center dot gVSS) and 49.43 mL/(h center dot gVSS) and, compared with the control, increased 4% and 3%, respectively. La2O3 significantly reduced the accumulation of volatile fatty acids (VFAs), whereas CeO2 had no similar effect. Dissolution experiments demonstrated that the content of extracellular La in the anaerobic granular sludge reached 404 mu g-La/g volatile suspended solid (VSS), which was 134 times higher than that of extracellular Ce (3 mu g-Ce/gVSS). The content of intracellular La reached 206 mu g-La/gVSS, which was 19 times higher than that of intracellular Ce (11 mu g-Ce/gVSS). The different stimulation between La3+ and Ce3+ could be attributed to the different dissolution of La2O3 and CeO2. The result of this work is helpful to optimize anaerobic processes and to develop novel additives. Practitioner PointsNovel anaerobic additives were developed.La2O3 and CeO2 in 0-0.05 g/L enhanced organics degradation and methane production.The addition of La2O3 significantly reduced the accumulation of volatile fatty acids.The solubilization of La2O3 was stronger than CeO2.The promoting effects of low concentrations of La2O3 and CeO2 were derived from dissolved La and Ce.

Polyurethane is widely used in building facades as a good energy-saving and environment-friendly organic material, and the U-shaped structure is a common facade form as it could improve indoor lighting and ventilation. Through numerical simulation and theoretical analysis, this study found the flame spread rate of polyurethane foam over a U-shaped facade was affected by the structural dimensions due to three main factors: lateral air entrainment restriction, bottom air entrainment restriction, and flame fusion between the back wall flame and side wall flame. The average flame spread rate was negative linearly correlated with the back wall width and positive exponentially correlated with the side wall length. This was due to that the side walls caused lateral air entrainment restriction, reduced the heat loss, enhanced the thermal feedback, generated an upward induced airflow close to the back wall, elongated the flame, and also caused the flame fusion between side walls and the back wall, thus accelerated the flame spread process compared to the flat structures.

In this paper, experiments focus on the fire smoke flow characteristics under different slopes in a vaulted tunnel and no-mechanical ventilation conditions. Explored the smoke back-layering length Lb and ceiling temperature, with the main research factors tunnel slope and heat release rate (HRR). Research showed that the influences of HRR on the length Lb decreases with increasing slope (especially after 10%) for all slopes where the lengths Lb are present (4%–35%). The slope will also intensify the flow of smoke in the downstream ceiling and the heat exchange between the smoke-wall, resulting in a decrease in the ceiling temperature, while the decay trend remains consistent at the three heat release rates. Combined with the dimensional analysis, the respective dimensionless expressions were established. The results indicated dimensionless smoke back-layering length (Lb*) and the 0.12 power of the normalized HRR decrease with the slope as a power function, while dimensionless ceiling temperature rise and the 3/5 power of the dimensionless HRR decrease exponentially with the slope. These conclusions can provide useful suggestions for engineering practice.