Electroconductive RGO-MXene membranes with wettability-regulated channels: improved water permeability and electro-enhanced rejection performance

● Electroconductive RGO-MXene membranes were fabricated. ● Wettable membrane channels were established between RGO and MXene nanosheets. ● Hydrophilic MXene reduces the resistance of water entering the membrane channels. ● Water permeance of RGO-MXene membrane is 16.8 times higher than that of RGO membrane. ● Electro-assistance can enhance the dye rejection performance of RGO-MXene membrane. Reduced graphene oxide (RGO) membranes are theoretically more conducive to the rapid transport of water molecules in their channels compared with graphene oxide (GO) membranes, as they have fewer oxygen-containing functional groups and more non-oxidized regions. However, the weak hydrophilicity of RGO membranes inhibits water entry into their channels, resulting in their low water permeability. In this work, we constructed wettable RGO-MXene channels by intercalating hydrophilic MXene nanosheets into the RGO membrane for improving the water permeance. The RGO-MXene composite membrane exhibits high pure water permeance of 62.1 L/(m²·h·bar), approximately 16.8 times that of the RGO membrane (3.7 L/(m²·h·bar)). Wettability test results and molecular dynamics simulations suggest that the improved water permeance results from the enhanced wettability of RGO-MXene membrane and increased rate of water molecules entering the RGO-MXene channels. Benefiting from good conductivity, the RGO-MXene membrane with electro-assistance exhibits significantly increased rejection rates for negatively charged dyes (from 56.0% at 0 V to 91.4% at 2.0 V for Orange G) without decreasing the permeate flux, which could be attributed to enhanced electrostatic repulsion under electro-assistance.     

Insights into the electron transfer mechanisms of permanganate activation by carbon nanotube membrane for enhanced micropollutants degradation

● A CNT filter enabled effective KMnO₄ activation via facilitated electron transfer. ● Ultra-fast degradation of micropollutants were achieved in KMnO₄/CNT system. ● CNT mediated electron transfer process from electron-rich molecules to KMnO₄. ● Electron transfer dominated organic degradation. Numerous reagents have been proposed as electron sacrificers to induce the decomposition of permanganate (KMnO₄) by producing highly reactive Mn species for micropollutants degradation. However, this strategy can lead to low KMnO₄ utilization efficiency due to limitations associated with poor mass transport and high energy consumption. In the present study, we rationally designed a catalytic carbon nanotube (CNT) membrane for KMnO₄ activation toward enhanced degradation of micropollutants. The proposed flow-through system outperformed conventional batch reactor owing to the improved mass transfer via convection. Under optimal conditionals, a > 70% removal (equivalent to an oxidation flux of 2.43 mmol/(h·m²)) of 80 μmol/L sulfamethoxazole (SMX) solution can be achieved at single-pass mode. The experimental analysis and DFT studies verified that CNT could mediate direct electron transfer from organic molecules to KMnO₄, resulting in a high utilization efficiency of KMnO₄. Furthermore, the KMnO₄/CNT system had outstanding reusability and CNT could maintain a long-lasting reactivity, which served as a green strategy for the remediation of micropollutants in a sustainable manner. This study provides new insights into the electron transfer mechanisms and unveils the advantages of effective KMnO₄ utilization in the KMnO₄/CNT system for environmental remediation.     

Enhancement of extracellular Cr(VI) reduction for anammox recovery using hydrazine: performance,pathways, and mechanism

● N₂H₄ addition enhanced and recovered anammox performance under Cr(VI) stress. ● N₂H₄ accelerated electron transfer of Cr(VI) reduction for detoxification. ● N₂H₄ enhanced anammox metabolism for activity recovery from Cr(VI) inhibition. ● Extracellular Cr(VI) reduction to less toxic Cr(III) was the dominant mechanism. The hexavalent chromium (Cr(VI)) would frequently impose inhibition to anaerobic ammonium oxidation (anammox) process, hindering the efficiency of nitrogen removal in wastewater treatment. Hydrazine (N₂H₄), which is an intermediate product of anammox, participates in intracellular metabolism and extracellular Cr(VI) reduction. However, the roles of N₂H₄-induced intracellular metabolism and extracellular reduction in nitrogen removal under Cr(VI) stress remain unclear. The addition of 3.67 mg/L of N₂H₄ increased the anammox activity by 17%. As an intermediate, N₂H₄ enhanced anammox metabolism by increasing the heme c content and electron transfer system activity. As a reductant, N₂H₄ accelerated the reduction of c-Cyts-mediated extracellular Cr(VI) to the less toxic Cr(III). Extracellular Cr(III) accounts for 74% of the total Cr in a Cr(VI)-stressed anammox consortia. These findings highlight that N₂H₄-induced extracellular Cr(VI) reduction is the dominant mechanism for the survival of anammox consortia. We also found that N₂H₄ increased the production of extracellular polymeric substances to sequester excessive Cr(VI) and produced Cr(III). Taken together, the study findings suggest a potential strategy for enhancing nitrogen removal from ammonium-rich wastewater contaminated with Cr(VI).     

Electroreduction of hexavalent chromium using a porous titanium flow-through electrode and intelligent prediction based on a back propagation neural network

● Titanium-based flow-through electrode achieved high Cr(VI) reduction efficiency. ● Flow-through pattern enhanced the mass transfer and reduced cathodic polarization. ● BPNN predicted the optimal electroreduction conditions of flow-through cell. Flow-through electrodes have been demonstrated to be effective for electroreduction of Cr(VI), but shortcomings are tedious preparation and short lifetimes. Herein, porous titanium available in the market was studied as a flow-through electrode for Cr(VI) electroreduction. In addition, the intelligent prediction of electrolytic performance based on a back propagation neural network (BPNN) was developed. Voltametric studies revealed that Cr(VI) electroreduction was a diffusion-controlled process. Use of the flow-through mode achieved a high limiting diffusion current as a result of enhanced mass transfer and favorable kinetics. Electroreduction of Cr(VI) in the flow-through system was 1.95 times higher than in a parallel-plate electrode system. When the influent (initial pH 2.0 and 106 mg/L Cr(VI)) was treated at 5.0 V and a flux of 51 L/(h·m²), a reduction efficiency of ~99.9% was obtained without cyclic electrolysis process. Sulfate served as the supporting electrolyte and pH regulator, as reactive CrSO₇²⁻ species were formed as a result of feeding HSO₄⁻. Cr(III) was confirmed as the final product due to the sequential three-electron transport or disproportionation of the intermediate. The developed BPNN model achieved good prediction accuracy with respect to Cr(VI) electroreduction with a high correlation coefficient (R² = 0.943). Additionally, the electroreduction efficiencies for various operating inputs were predicted based on the BPNN model, which demonstrates the evolutionary role of intelligent systems in future electrochemical technologies.     

Efficient production of hydrogen peroxide in microbial reverse-electrodialysis cells coupled with thermolytic solutions

● Appreciable H₂O₂ production rate was achieved in MRCs utilizing NH₄HCO₃ solutions. ● Carbon black outperformed activated carbon as the catalyst for H₂O₂ production. ● The optimum carbon black loading for H₂O₂ production on air-cathode was 10 mg/cm². ● The optimum number of cell pairs was determined to be three. ● A maximum power density of 980 mW/m² was produced by MRCs with 5 cell pairs. H₂O₂ was produced at an appreciable rate in microbial reverse-electrodialysis cells (MRCs) coupled with thermolytic solutions, which can simultaneously capture waste heat as electrical energy. To determine the optimal cathode and membrane stack configurations for H₂O₂ production, different catalysts, catalyst loadings and numbers of membrane cell pairs were tested. Carbon black (CB) outperformed activated carbon (AC) for H₂O₂ production, although AC showed higher catalytic activity for oxygen reduction. The optimum CB loading was 10 mg/cm² in terms of both the H₂O₂ production rate and power production. The optimum number of cell pairs was determined to be three based on a tradeoff between H₂O₂ production and capital costs. A H₂O₂ production rate as high as 0.99 ± 0.10 mmol/(L·h) was achieved with 10 mg/cm² CB loading and 3 cell pairs, where the H₂O₂ recovery efficiency was 52 ± 2% and the maximum power density was 780 ± 37 mW/m². Increasing the number of cell pairs to five resulted in an increase in maximum power density (980 ± 21 mW/m²) but showed limited effects on H₂O₂ production. These results indicated that MRCs can be an efficient method for sustainable H₂O₂ production.     

Revealing the GHG reduction potential of emerging biomass-based CO2 utilization with an iron cycle system

● Greenhouse gas mitigation by biomass-based CO₂ utilization with a Fe cycle system. ● The system including hydrothermal CO₂ reduction with Fe and Fe recovery by biomass. ● The reduction potential quantified by experiments, simulations, and an ex-ante LCA. ● The greatest GHG reduction potential is −34.03 kg CO₂-eq/kg absorbed CO₂. ● Ex-ante LCA supports process optimization to maximize GHG reduction potential. CO₂ utilization becomes a promising solution for reducing anthropogenic greenhouse gas (GHG) emissions. Biomass-based CO₂ utilization (BCU) even has the potential to generate negative emissions, but the corresponding quantitative evaluation is limited. Herein, the biomass-based CO₂ utilization with an iron cycle (BCU-Fe) system, which converts CO₂ into formate by Fe under hydrothermal conditions and recovers Fe with biomass-derived glycerin, was investigated. The GHG reduction potential under various process designs was quantified by a multidisciplinary method, including experiments, simulations, and an ex-ante life-cycle assessment. The results reveal that the BCU-Fe system could bring considerable GHG emission reduction. Significantly, the lowest value is −34.03 kg CO₂-eq/kg absorbed CO₂ (−2.44 kg CO₂-eq/kg circulated Fe) with the optimal yield of formate (66%) and Fe (80%). The proposed ex-ante evaluation approach not only reveals the benefits of mitigating climate change by applying the BCU-Fe system, but also serves as a generic tool to guide the industrialization of emerging carbon-neutral technologies.     

Effectiveness of tertiary treatment processes in removing different classes of emerging contaminants from domestic wastewater

● Different advanced treatment processes were tested for ECs removal from wastewater. ● UV radiation showed low to moderate removal for 5 of the 38 micropollutants. ● Among tested membrane processes, nanofiltration showed the better performance. ● The use of PAC achieved high or partially removal for 31 out of the 38 compounds. ● The environmental and economical evaluation of a pilot-scale PAC unit is suggested. In this work, 38 different organic emerging contaminants (ECs), belonging to various chemical classes such as pharmaceuticals (PhCs), endocrine-disrupting chemicals (EDCs), benzotriazoles (BTRs), benzothiazoles (BTHs), and perfluorinated compounds (PFCs), were initially identified and quantified in the biologically treated wastewater collected from Athens’ (Greece) Sewage Treatment Plant (STP). Processes already used in existing STPs such as microfiltration (MF), nanofiltration (NF), ultrafiltration (UF), UV radiation, and powdered activated carbon (PAC) were assessed for ECs’ removal, under the conditions that represent their actual application for disinfection or advanced wastewater treatment. The results indicated that MF removed only one out of the 38 ECs and hence it was selected as pretreatment step for the other processes. UV radiation in the studied conditions showed low to moderate removal for 5 out of the 38 ECs. NF showed better results than UF due to the smaller pore sizes of the filtration system. However, this enhancement was observed mainly for 8 compounds originating from the classes of PhCs and PFCs, while the removal of EDCs was not statistically significant. Among the various studied technologies, PAC stands out due to its capability to sufficiently remove most ECs. In particular, removal rates higher than 70% were observed for 9 compounds, 22 were partially removed, while 7 demonstrated low removal rates. Based on our screening experiments, future research should focus on scaling-up PAC in actual conditions, combining PAC with other processes, and conduct a complete economic and environmental assessment of the treatment.     

Separation/degradation behavior and mechanism for cationic/anionic dyes by Ag-functionalized Fe3O4-PDA core-shell adsorbents

● PDA-Fe₃O₄-Ag was made by hydrothermal and oxidation self-polymerization method. ● PDA-Fe₃O₄-Ag had great magnetic separation performance. ● PDA-Fe₃O₄-Ag had good adsorption and degradation performance for ionic dyes. ● PDA-Fe₃O₄-Ag showed NR and MO degradation potential of 91.2% and 87.5%, respectively. High-performance adsorbents have been well-studied for the removal of organic dye pollutants to promote environment remediation. In this study, an Ag nanoparticle-functionalized Fe₃O₄-PDA nanocomposite adsorbent (PDA-Fe₃O₄-Ag) was synthesized, and the adsorption/separation performance of commonly used cationic and anionic organic dyes by the PDA-Fe₃O₄-Ag adsorbent were assessed. Overall, PDA-Fe₃O₄-Ag exhibited a significantly higher adsorption capacity for cationic dyes compared to anionic dyes, the highest of which was more than 110.0 mg/g (methylene blue (MB)), which was much higher than not only the adsorption capacities of the anionic dyes in this study but also other dye adsorption capacities reported in the literature. The dye adsorption kinetics data fitted well to both the pseudo second-order kinetics model and the Langmuir isotherm model, suggesting a monolayer-chemisorption-dominated adsorption mode. Thermodynamics analysis indicated that the adsorption process was both endothermic and spontaneous. Furthermore, the PDA-Fe₃O₄-Ag adsorbent achieved high photodegradation removal rates of the dyes, especially neutral red (NR) and methyl orange (MO), which were 91.2% and 87.5%, respectively. With the addition of PDA-Fe₃O₄-Ag, the degradation rate constants of NR and MO increased from 0.08 × 10⁻² and 0 min⁻¹ to 2.11 × 10⁻² and 1.73 × 10⁻² min⁻¹, respectively. The high adsorption and photocatalytic degradation performance of the PDA-Fe₃O₄-Ag adsorbent make it an excellent candidate for removing cationic and anionic dyes from the industrial effluents.     

Unveiling the interaction mechanisms of key functional microorganisms in the partial denitrification-anammox process induced by COD

● The availability of PD-anammox was investigated with higher NO₃^––N concentration. ● NO₃^––N concentration affects NO₃^––N accumulation during denitrification. ● COD concentration is determinant for N removal pathways in PD-anammox process. ● The synergy/competition mechanisms between denitrifiers and anammox was explored. Partial denitrification-anammox (PD-anammox) is an innovative process to remove nitrate (NO₃^––N) and ammonia (NH₄⁺–N) simultaneously from wastewater. Stable operation of the PD-anammox process relies on the synergy and competition between anammox bacteria and denitrifiers. However, the mechanism of metabolic between the functional bacteria in the PD-anammox system remains unclear, especially in the treatment of high-strength wastewater. The kinetics of nitrite (NO₂^––N) accumulation during denitrification was investigated using the Michaelis-Menten equation, and it was found that low concentrations of NO₃^––N had a more significant effect on the accumulation of NO₂^––N during denitrification. Organic matter was a key factor to regulate the synergy of anammox and denitrification, and altered the nitrogen removal pathways. The competition for NO₂^––N caused by high COD concentration was a crucial factor that affecting the system stability. Illumina sequencing techniques demonstrated that excess organic matter promoted the relative abundance of the Denitratesoma genus and the nitrite reductase gene nirS, causing the denitrifying bacteria Denitratisoma to compete with Cadidatus Kuenenia for NO₂^––N, thereby affecting the stability of the system. Synergistic carbon and nitrogen removal between partial denitrifiers and anammox bacteria can be effectively achieved by controlling the COD and COD/NO₃^––N.     

Non-toxic,high selectivity process for the extraction of precious metals from waste printed circuit boards

● Au, Ag and Pd were recovered from WPCBs with high efficiencies. ● Au leaching is strictly dependent on WPCB size and reagent concentration. ● High Ag extraction efficiencies are achieved regardless of the WPCB size. ● Pd leaching works better with small and medium WPCB sizes. ● The leaching results suggest the possibility of selective recovery of metals. The work presented here focused on the extraction of gold (Au), silver (Ag) and palladium (Pd) from electronic waste using a solution of ammonium thiosulfate. Thiosulfate was used as a valid alternative to cyanide for precious metal extractions, due to its non-toxicity and high selectivity. The interactions between sodium thiosulfate, total ammonia/ammonium, precious metal concentrations and the particle size of the waste printed circuit boards (WPCBs) were studied by the response surface methodology (RSM) and the principal component analysis (PCA) to maximize precious metal mobilization. Au extraction reached a high efficiency with a granulometry of less than 0.25 mm, but the consumption of reagents was high. On the other hand, Ag extraction depended neither on thiosulfate/ammonia concentration nor granulometry of WPCBs and it showed efficiency of 90% also with the biggest particle size (0.50 < Ø < 1.00 mm). Pd extraction, similarly to Au, showed the best efficiency with the smallest and the medium WPCB sizes, but required less reagents compared to Au. The results showed that precious metal leaching is a complex process (mainly for Au, which requires more severe conditions in order to achieve high extraction efficiencies) correlated with reagent concentrations, precious metal concentrations and WPCB particle sizes. These results have great potentiality, suggesting the possibility of a more selective recovery of precious metals based on the different granulometry of the WPCBs. Furthermore, the high extraction efficiencies obtained for all the metals bode well in the perspective of large-scale applications.     

Nonpolar cross-stacked super-aligned carbon nanotube membrane for efficient wastewater treatment

● A novel nonpolar super-aligned carbon nanotube (SACNT) membrane was prepared. ● SACNT membranes achieved smoother and more uniform structures. ● SACNT membranes have inert chemistry and unique nonpolar wetting feature. ● SACNT membranes exhibit superior separation and antifouling capabilities. ● SACNT membranes achieved superior oil/water separation efficiency. Membrane separation technology has made great progress in various practical applications, but the unsatisfactory separation performance of prevailing membrane materials hampers its further sustainable growth. This study proposed a novel nonpolar super-aligned carbon nanotube (SACNT) membrane, which was prepared with a layer-by-layer cross-stacking method. Through controlling the number of stacked SACNT layers, three kinds of SACNT membranes (SACNT_200, SACNT_300, and SACNT_400) were prepared. Systematic characterizations and filtration tests were performed to investigate their physico-chemical properties, surface wetting behavior, and filtration performance. Compared with two commercial membranes (Com_0.22 and Com_0.45), all the SACNT membranes achieved smoother and more uniform structures. Due to the hexagonal graphene structure of CNTs, the surface chemistry of the SACNT membranes is simple and inert, thereby potentially eliminating the covalent-bonding-induced membrane fouling. Besides, the SACNT membranes exhibited a typical nonpolar wetting behavior, with high contact angles for polar liquids (water: ~124.9°–126.5°; formamide: ~80.0°–83.9°) but low contact angles for nonpolar diiodomethane (~18.8°–20.9°). This unique nonpolar feature potentially leads to weak interactions with polar substances. Furthermore, compared with the commercial membranes, the SACNT membranes obtained a significantly higher selectivity while achieving a comparable or higher permeability (depending on the number of stacked layers). Moreover, the SACNT membranes exhibited superior separation performance in various application scenarios, including municipal wastewater treatment (> 2.3 times higher cleaning efficiency), electro-assistant fouling inhibition (or even self-cleaning), and oil/water separation (> 99.2 % of separation efficiency), suggesting promising application prospects in various fields.     

Fluorescence detection of phosphate in an aqueous environment by an aluminum-based metal-organic framework with amido functionalized ligands

● A novel Al-MOF was successfully synthesized by a facile solvothermal method. ● Al-MOF showed superior performance for phosphate detection. ● High selectivity and anti-interference for detection were demonstrated. ● The high coordination between Al-O and PO₄³⁻ was the key in fluorescence sensing. The on-site monitoring of phosphate is important for environmental management. Conventional phosphate detection methods are not appropriate to on-site monitoring owing to the use of complicated detection procedures, and the consequent high cost and maintenance requirements of the detection apparatus. Here, a highly sensitive fluorescence-based method for phosphate detection with a wide detection range was developed based on a luminescent aluminum-based metal-organic framework (Al-MOF). The Al-MOF was prepared by introducing amine functional groups to conventional MIL to enhance phosphate binding, and exhibited excellent fluorescence properties that originated from the ligand-to-metal charge transfer (LMCT). The detection limit was as low as 3.25 μmol/L (0.10 mg/L) and the detection range was as wide as 3–350 μmol/L (0.10–10.85 mg/L). Moreover, Al-MOF displayed specific recognition toward phosphate over most anions and metal cations, even for a high concentration of the co-existent ions. The mechanism of phosphate detection was analyzed through the characterization of the combination of Al-MOF and phosphate, and the results indicated the high affinity between Al-O and phosphate inhibited that the LMCT process and recovered the intrinsic fluorescence of NH₂-H₂BDC. The recovery of the developed detection method reached a satisfactory range of 85.1%–111.0%, and the feasibility of on-site phosphate detection was verified using a prototype sensor for tap water and lake water samples. It was demonstrated that the prepared Al-MOF is highly promising for on-site detection of phosphate in an aqueous environment.     

Distribution,enrichment mechanism and risk assessment for fluoride in groundwater: a case study of Mihe-Weihe River Basin,China

● High fluorine is mainly HCO₃·Cl-Na and HCO₃-Na type. ● F⁻ decreases with the increase of depth to water table. ● High fluoride is mainly affected by fluorine-containing minerals and weak alkaline. ● Fluorine pollution is mainly in the north near Laizhou Bay (wet season > dry season). ● Groundwater samples have a high F⁻ health risk (children > adults). Due to the unclear distribution characteristics and causes of fluoride in groundwater of Mihe-Weihe River Basin (China), there is a higher risk for the future development and utilization of groundwater. Therefore, based on the systematic sampling and analysis, the distribution features and enrichment mechanism for fluoride in groundwater were studied by the graphic method, hydrogeochemical modeling, the proportionality factor between conventional ions and factor analysis. The results show that the fluorine content in groundwater is generally on the high side, with a large area of medium-fluorine water (0.5–1.0 mg/L), and high-fluorine water is chiefly in the interfluvial lowlands and alluvial-marine plain, which mainly contains HCO₃·Cl-Na- and HCO₃-Na-type water. The vertical zonation characteristics of the fluorine content decrease with increasing depth to the water table. The high flouride groundwater during the wet season is chiefly controlled by the weathering and dissolution of fluorine-containing minerals, as well as the influence of rock weathering, evaporation and concentration. The weak alkaline environment that is rich in sodium and poor in calcium during the dry season is the main reason for the enrichment of fluorine. Finally, an integrated assessment model is established using rough set theory and an improved matter element extension model, and the level of groundwater pollution caused by fluoride in the Mihe-Weihe River Basin during the wet and dry seasons in the Shandong Peninsula is defined to show the necessity for local management measures to reduce the potential risks caused by groundwater quality.     

Porous silica synthesis out of coal fly ash with no residue generation and complete silicon separation

● Both amorphous and crystalline silicon are completely separated from coal fly ash. ● Porous silica is synthesized out of coal fly ash. ● No residues is produced during the whole synthesis process. ● The one-step method to synthesize silica don’t need long-time reaction and aging. Ordered mesoporous silica materials exhibit enormous potential in industrial production. Since coal fly ash (CFA) is abundant in Si, it has become a green and promising way to utilize CFA by synthesizing porous silica materials. However, the stable crystalline structure of CFA limits the extraction of Si, and the residue is generated during the process of extracting Si. In this work, we proposed a no-residue method to synthesize ordered mesoporous silica out of CFA. Sodium carbonate (Na₂CO₃) was used to reconstruct the crystals of the CFA, and the calcined mixture then directly reacted with the precipitators. This method combined the process of Si extraction and porous material synthesis. In this method, no residue was generated and the silicon in both amorphous and crystalline phases of CFA was fully utilized. By this method, the extraction efficiency of Si was increased from 31.75% to nearly 100%. The as-synthesized mesoporous silica had a highly-ordered pore structure with a space group of la-3d, a surface area of 663.87 m²/g, a pore volume of 0.41 cm³/g, and an average pore diameter of 2.73 nm. The mechanism of crystalline transformation and material structure formation were systematically studied. This method provides a new idea to dispose of CFA and synthesize porous silica materials.     

Predicting the elemental compositions of solid waste using ATR-FTIR and machine learning

● A method based on ATR-FTIR and ML was developed to predict CHNS contents in waste. ● Feature selection methods were used to improve models’ prediction accuracy. ● The best model predicted C, H, and N contents with accuracy R ² ≥ 0.93, 0.87, 0.97. ● Some suitable models showed insensitivity to spectral noise. ● Under moisture interference, the models still had good prediction performance. Elemental composition is a key parameter in solid waste treatment and disposal. This study has proposed a method based on infrared spectroscopy and machine learning algorithms that can rapidly predict the elemental composition (C, H, N, S) of solid waste. Both noise and moisture spectral interference that may occur in practical application are investigated. By comparing two feature selection methods and five machine learning algorithms, the most suitable models are selected. Moreover, the impacts of noise and moisture on the models are discussed, with paper, plastic, textiles, wood, and leather as examples of recyclable waste components. The results show that the combination of the feature selection and K-nearest neighbor (KNN) approaches exhibits the best prediction performance and generalization ability. Particularly, the coefficient of determination (R²) of the validation set, cross validation and test set are higher than 0.93, 0.89, and 0.97 for predicting the C, H, and N contents, respectively. Further, KNN is less sensitive to noise. Under moisture interference, the combination of feature selection and support vector regression or partial least-squares regression shows satisfactory results. Therefore, the elemental compositions of solid waste are quickly and accurately predicted under noise and moisture disturbances using infrared spectroscopy and machine learning algorithms.     

Same stimuli,different responses: a pilot study assessing air pollution visibility impacts on emotional well-being in a controlled environment

● Emotional responses to visibility-reducing haze was assessed in a controlled lab. ● Valence and arousal have non-linear responses to pollution-caused low visibility. ● Repetitive exposure aggravates negative emotions in severely polluted conditions. ● Emotional bias to pollution relates with gender, decisiveness, attitude to clean air. A growing number of studies have shown that impaired visibility caused by particulate matter pollution influences emotional wellbeing. However, evidence is still scant on how this effect varies across individuals and over repetitive visual exposure in a controlled environment. Herein, we designed a lab-based experiment (41 subjects, 6 blocks) where participants were presented with real-scene images of 12 different PM_2.5 concentrations in each block. Emotional valence (negative to positive) and arousal (calm to excited) were self-rated by participants per image, and the response time for each rating was recorded. We find that as pollution level increases from 10 to 260 µg/m³, valence scores decrease, whereas arousal scores decline first and then bounce back, following a U-shaped trend. When air quality deteriorates, individual variability decreases in hedonic valence but increases in arousal. Over blocks, repetitive visual exposure increases valence at a moderate pollution level but aggravates negative emotions in severely polluted conditions (> 150 µg/m³). Finally, we find females, people who are slow in making responses, and those who are highly aroused by clean air tend to express more negative responses (so-called negativity bias) to ambient pollution than their respective counterparts. These results provide deeper insights into individual-level emotional responses to dirty air in a controlled environment. Although the findings in our pilot study should only be directly applied to the conditions assessed herein, we introduce a framework that can be replicated in different regions to assess the impact of air pollution on local emotional wellbeing.     

NiB2O4 (B = Mn or Co) catalysts for NH3-SCR of NOx at low-temperature in microwave field

● Microwave-assisted catalytic NH₃-SCR reaction over spinel oxides is carried out. ● SCR reaction temperature is tremendously lowered in microwave field. ● NO conversion of NiMn₂O₄ is highly up to 90.6% at 70°C under microwave heating. Microwave-assisted selective catalytic reduction of nitrogen oxides (NO_x) was investigated over Ni-based metal oxides. The NiMn₂O₄ and NiCo₂O₄ catalysts were synthesized by the co-precipitation method and their activities were evaluated as potential candidate catalysts for low-temperature NH₃-SCR in a microwave field. The physicochemical properties and structures of the catalysts were characterized by X-ray diffraction (XRD), Scanning electron microscope (SEM), N₂-physisorption, NO adsorption-desorption in the microwave field, H₂-temperature programmed reduction (H₂-TPR) and NH₃-temperature programmed desorption (NH₃-TPD). The results verified that microwave radiation reduced the reaction temperature required for NH₃-SCR compared to conventional heating, which needed less energy. For the NiMn₂O₄ catalyst, the catalytic efficiency exceeded 90% at 70 °C and reached 96.8% at 110 °C in the microwave field. Meanwhile, the NiMn₂O₄ also exhibited excellent low-temperature NH₃-SCR reaction performance under conventional heating conditions, which is due to the high BET specific surface area, more suitable redox property, good NO adsorption-desorption in the microwave field and rich acidic sites.     

Prediction of high-density polyethylene pyrolysis using kinetic parameters based on thermogravimetric and artificial neural networks

● Reducting the sampling frequency can enhance the modelling process. ● The pyrolysis of HDPE was investigated at three different heating rates. ● The average E_a and k₀ were calculated by Friedman, KAS, FWO, and CR methods. ● ANN was employed to predict the HDPE weight loss with the optimal MSE and R². Pyrolysis is considered an attractive option and a promising way to dispose waste plastics. The thermogravimetric experiments of high-density polyethylene (HDPE) were conducted from 105 °C to 900 °C at different heating rates (10 °C/min, 20 °C/min, and 30 °C/min) to investigate their thermal pyrolysis behavior. We investigated four methods including three model-free methods and one model-fitting method to estimate dynamic parameters. Additionally, an artificial neural network model was developed by providing the heating rates and temperatures to predict the weight loss (wt.%) of HDPE, and optimized via assessing mean squared error and determination coefficient on the test set. The optimal MSE (2.6297 × 10⁻²) and R² value (R² > 0.999) were obtained. Activation energy and pre-exponential factor obtained from four different models achieves the acceptable value between experimental and predicted results. The relative error of the model increased from 2.4 % to 6.8 % when the sampling frequency changed from 50 s to 60 s, but showed no significant difference when the sampling frequency was below 50 s. This result provides a promising approach to simplify the further modelling work and to reduce the required data storage space. This study revealed the possibility of simulating the HDPE pyrolysis process via machine learning with no significant accuracy loss of the kinetic parameters. It is hoped that this work could potentially benefit to the development of pyrolysis process modelling of HDPE and the other plastics.     

Impacts of backwashing on micropollutant removal and associated microbial assembly processes in sand filters

● Backwashing in sand filters with 2-h and 4-h EBCTs was simulated. ● Removal efficiency of five micropollutants recovered within 2 d at 2-h EBCT. ● Active biomass of sand filters recovered within 2 d under two EBCTs. ● Microbial composition gradually recovered to pre-backwashing level at 2-h EBCT. ● Recovered microbes only accounted for 15.55 %–25.69 % in the sand filters at 4-h EBCT. Backwashing is crucial for preventing clogging of sand filters. However, few studies have investigated the effect of backwashing on micropollutant removal and the dynamic changes in the microbial community in sand filters. Here, we used a series of manganese and quartz sand filters under empty bed contact times (EBCTs) of 2 h and 4 h to explore variations in micropollutant degradation and temporal dynamics of the microbial community after backwashing. The results showed that the removal efficiencies of caffeine, sulfamethoxazole, sulfadiazine, trimethoprim, atrazine, and active biomass recovered within 2 d after backwashing in both types of sand filters at 2-h EBCT, but the recovery of sulfadiazine and trimethoprim was not observed at 4-h EBCT. Moreover, the removal efficiency of atenolol increased after backwashing in the manganese sand filters, whereas maintained almost complete removal efficiency in the quartz sand filters at both EBCTs. Pearson correlation analysis indicated that microbial community composition gradually recovered to the pre-backwashing level (R increased from 0.53 to 0.97) at 2-h EBCT, but shifted at 4-h EBCT (R < 0.25) after backwashing. Furthermore, the compositions of the recovered, depleted, and improved groups of microbes were distinguished by applying hierarchical clustering to the differentially abundant amplicon sequence variants. The cumulative relative abundance of recovered microbes at 2-h EBCT was 82.76 % ± 0.43 % and 46.82 % ± 4.34 % in the manganese and quartz sand filters, respectively. In contrast, at 4-h EBCT, the recovered microbes dropped to 15.55 %–25.69 % in both types of sand filters.