New insights into the formation of ammonium nitrate from a physical and chemical level perspective

● Factor analysis of ammonium nitrate formation based on thermodynamic theory. ● Aerosol liquid water content has important role on the ammonium nitrate formation. ● Contribution of coal combustion and vehicle exhaust is significant in haze periods. High levels of fine particulate matter (PM_2.5) is linked to poor air quality and premature deaths, so haze pollution deserves the attention of the world. As abundant inorganic components in PM_2.5, ammonium nitrate (NH₄NO₃) formation includes two processes, the diffusion process (molecule of ammonia and nitric acid move from gas phase to liquid phase) and the ionization process (subsequent dissociation to form ions). In this study, we discuss the impact of meteorological factors, emission sources, and gaseous precursors on NH₄NO₃ formation based on thermodynamic theory, and identify the dominant factors during clean periods and haze periods. Results show that aerosol liquid water content has a more significant effect on ammonium nitrate formation regardless of the severity of pollution. The dust source is dominant emission source in clean periods; while a combination of coal combustion and vehicle exhaust sources is more important in haze periods. And the control of ammonia emission is more effective in reducing the formation of ammonium nitrate. The findings of this work inform the design of effective strategies to control particulate matter pollution.     

Stress response to nanoplastics with different charges in Brassica napus L. during seed germination and seedling growth stages

● Higher concentrations of PS, PS-NH₂ and PS-SO₃H inhibited seed germination. ● PS, PS-NH₂ and PS-SO₃H influenced seedling growth in a dose-dependent manner. ● PS, PS-NH₂ and PS-SO₃H reduced essential nutrients uptake and plant quality. ● PS, PS-NH₂ and PS-SO₃H increased antioxidant enzyme activities and MDA content. ● Nanoplastic toxicity was related to surface charges. Nanoplastic pollution has become a significant problem in farmland systems worldwide. However, research on the effects of nanoplastics (NPs) with different charges on field crops is still limited. In our study, NPs with different charges, including unmodified polystyrene nanoplastics (PS), positively charged polystyrene nanoplastics (PS-NH₂), and negatively charged polystyrene nanoplastics (PS-SO₃H), were investigated for their impacts on seed germination and seedling growth of rape. The results showed that seed water uptake (after 12 h), seed germination, seed vigour, and relative root elongation were all significantly reduced under exposure to NPs (200 mg/L). Similarly, remarkable decreases in plant biomass (root weight, shoot weight), growth (root length, plant height), photosynthesis ability (chlorophyll a, chlorophyll b, carotenoids), essential nutrient uptake (Fe, Mn, Zn, Cu), and plant quality (soluble protein, soluble sugar, crude fibre content) of rape seedlings were also observed after exposure to NPs. Among the three kinds of NPs, PS-NH₂ showed stronger effects. Moreover, superoxide dismutase, peroxidase, and catalase activities of rape seedlings were changed, and the content of malondialdehyde was significantly increased under exposure to NPs. Furthermore, positively charged PS-NH₂ showed stronger effects on the phenotype, physiology, biochemistry, nutrient uptake, and plant quality of rape. Notably, a comprehensive toxicity evaluation revealed that PS-NH₂ had the strongest toxicity to rape. The present study provides important implications for the interaction and risk assessment of NPs and crops in soil-plant systems.     

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.     

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.     

Is atmospheric oxidation capacity better in indicating tropospheric O3 formation?

● This study summarizes and evaluates different approaches that indicate O₃ formation. ● Isopleth and sensitivity methods are useful but have many prerequisites. ● AOC is a better indicator of photochemical reactions leading to O₃ formation. Tropospheric ozone (O₃) concentration is increasing in China along with dramatic changes in precursor emissions and meteorological conditions, adversely affecting human health and ecosystems. O₃ is formed from the complex nonlinear photochemical reactions from nitrogen oxides (NO_x = NO + NO₂) and volatile organic compounds (VOCs). Although the mechanism of O₃ formation is rather clear, describing and analyzing its changes and formation potential at fine spatial and temporal resolution is still a challenge today. In this study, we briefly summarized and evaluated different approaches that indicate O₃ formation regimes. We identify that atmospheric oxidation capacity (AOC) is a better indicator of photochemical reactions leading to the formation of O₃ and other secondary pollutants. Results show that AOC has a prominent positive relationship to O₃ in the major city clusters in China, with a goodness of fit (R²) up to 0.6. This outcome provides a novel perspective in characterizing O₃ formation and has significant implications for formulating control strategies of secondary pollutants.     

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.     

Photo-induced surface frustrated Lewis pairs for promoted photocatalytic decomposition of perfluorooctanoic acid

● Terminal carboxylate group activation is PFOA degradation’s rate-limiting step. ● Bi₃O(OH)(PO₄)₂ with surface frustrated Lewis pairs (SFLPs) efficiently degrade PFOA. ● Photo-induced Lewis acidic sites and proximal surface hydroxyls constitute SFLPs. ● SFLPs act as collection centers to effectively adsorb PFOA. ● SFLPs endow accessible pathways for photogenerated holes rapid transfer to PFOA. Heterogeneous photocatalysis has gained substantial research interest in treating per- and polyfluoroalkyl substances (PFAS)-contaminated water. However, sluggish degradation kinetics and low defluorination efficiency compromise their practical applications. Here, we report a superior photocatalyst, defected Bi₃O(OH)(PO₄)₂, which could effectively degrade typical PFAS, perfluorooctanoic acid (PFOA), with high defluorination efficiency. The UV light irradiation could in situ generate oxygen vacancies on Bi₃O(OH)(PO₄)₂ through oxidation of the lattice hydroxyls, which further promotes the formation of Lewis acidic coordinately unsaturated bismuth sites. Then, the Lewis acidic sites couple with the proximal surface hydroxyls to constitute the surface frustrated Lewis pairs (SFLPs). With the in-depth spectroscopic analysis, we revealed that the photo-induced SFLPs act as collection centers to effectively adsorb PFOA and endow accessible pathways to transfer photogenerated holes to PFOA rapidly. Consequently, activation of the terminal carboxyl, a rate-limiting step for PFOA decomposition, could be easily achieved over the defected Bi₃O(OH)(PO₄)₂ photocatalyst. These results suggest that SFLPs exhibit great potential in developing highly efficient photocatalysts to degrade persistent organic pollutants.     

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.     

Electrocatalytic reduction of nitrate using Pd-Cu modified carbon nanotube membranes

● Pd-Cu modified CNT membranes were prepared successfully by electrodeposition method. ● The deposition voltage and deposition time were optimized for Pd-Cu co-deposition. ● NO₃⁻-N was removed efficiently from water by Pd-Cu modified CNT membranes. ● The presence of dissolved oxygen did not affect the nitrate reduction performance. ● Mass transfer rate was promoted significantly with the increase in membrane flux. Excessive nitrate in water is harmful to the ecological environment and human health. Electrocatalytic reduction is a promising technology for nitrate removal. Herein, a Pd-Cu modified carbon nanotube membrane was fabricated with an electrodeposition method and used to reduce nitrate in a flow-through electrochemical reactor. The optimal potential and duration for codeposition of Pd and Cu were −0.7 V and 5 min, respectively, according to linear scan voltammetry results. The membrane obtained with a Pd:Cu ratio of 1:1 exhibited a relatively high nitrate removal efficiency and N₂ selectivity. Nitrate was almost completely reduced (~99 %) by the membrane at potentials lower than −1.2 V. However, −0.8 V was the optimal potential for nitrate reduction in terms of both nitrate removal efficiency and product selectivity. The nitrate removal efficiency was 56.2 %, and the N₂ selectivity was 23.8 % for the Pd:Cu=1:1 membrane operated at −0.8 V. Nitrate removal was enhanced under acidic conditions, while N₂ selectivity was decreased. The concentrations of Cl⁻ ions and dissolved oxygen showed little effect on nitrate reduction. The mass transfer rate constant was greatly improved by 6.6 times from 1.14 × 10⁻³ m/h at a membrane flux of 1 L/(m²·h) to 8.71 × 10⁻³ m/h at a membrane flux of 15 L/(m²·h), which resulted in a significant increase in the nitrate removal rate from 13.6 to 133.5 mg/(m²·h). These findings show that the Pd-Cu modified CNT membrane is an efficient material for nitrate reduction.     

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.     

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.     

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.     

Effects of sulfur on variations in the chemical speciation of heavy metals from fly ash glass

● A higher sulfur content reduced the curing rate of Cr in glass. ● Depolymerization increased the amounts of heavy metals in the carbonate bound state. ● Reducing the CaO/SiO₂ ratio increased the proportion of stable heavy metals. This work designed a new CaO-Al₂O₃-SiO₂-SO₃ glass for the immobilization of multiple heavy metals found in dechlorinated fly ash having high amounts of calcium and sulfur. Increasing the (CaO + SO₃)/SiO₂ mass ratio (M(CS/S)) from 0.28 to 0.85 was found to lower the proportions of Mn, Ni and Zn in an unstable state, while an M(CS/S) ratio of 0.51 gave the lowest proportions of unstable Cr and Pb. Decreasing the degree of polymerization of the glassy network increased the proportions of Mn, Cr, Ni, Pb and Zn in the carbonate bound state. The leaching out of metals in this state was the primary cause of degradation of Q³ structural units in the glassy network. The amount of Mn in the iron-manganese oxide bound state was increased by increasing the number of Q² units in the silicate network. Decreasing the CaO/SiO₂ mass ratio (M(C/S)) raised the proportions of Mn, Ni and Zn in the unstable state. An M(C/S) value of 0.43 lowered the proportions of unstable Cr and Pb. A principal components analysis determined that the leaching of toxic heavy metals from the glass was primarily related to the proportions of these metals in the unstable state while there were no evident correlations between leaching and the proportions in stable states.     

On the potential of iPhone significant location data to characterize individual mobility for air pollution health studies

● We evaluated the accuracy of iPhone data in capturing time-activity patterns. ● iPhone data captured the most important microenvironments and time spent in them. ● iPhone data also accurately captured daily exposure to ambient PM pollution. ● A considerable fraction of the population in the USA may have iPhone data available. ● iPhone data has great potential in air pollution health studies. In many air pollution health studies, the time-activity pattern of individuals is often ignored largely due to lack of data. However, a better understanding of this location-based information is expected to decrease uncertainties in exposure estimation. Here, we showcase the potential of iPhone’s Significant Location (iSL) data in capturing the user’s historical time-activity patterns in order to estimate exposure to ambient air pollutants. In this study, one subject carried an iPhone in tandem with a reference GPS tracking device for one month. The GPS device recorded locations in 10 second intervals while the iSL recorded the time spent in locations the subject visited frequently. Using GPS data as a reference, we then evaluated the accuracy of iSL data in capturing the subject’s time-activity patterns and time-weighted air pollution concentration within the study time period. We found the iSL data accurately captured the time the subject spent in 16 microenvironments (i.e. locations the subject visited more than once), which was 93% of the time during the study period. The average error of time-weighted aerosol optical depth value, a surrogate of particle pollution, is only 0.012%. To explore the availability of iSL data among iPhone users, an online survey was conducted. Among the 349 surveyed participants, 72% of them have iSL data available. Considering the popularity of iPhones, iSL data may be available for a significant portion of the general population. Our results suggest iSL data have great potential for characterizing historical time-activity patterns to improve air pollution exposure estimation.     

Data quality assessment for studies investigating microplastics and nanoplastics in food products: Are current data reliable?

● Data quality assessment criteria for MP/NPs in food products were developed. ● Data quality of 71 data records (69 of them only focused on MPs) was assessed. ● About 96% of the data records were considered unreliable in at least one criterion. ● Improvements need to be made regarding positive controls and polymer identification. ● A mismatch between MP/NPs used in toxicity studies and those in foods was recorded. Data on the occurrence of microplastics and nanoplastics (MP/NPs) in foods have been used to assess the human health risk caused by the consumption of MP/NPs. The reliability of the data, however, remains unclear because of the lack of international standards for the analysis of MP/NPs in foods. Therefore, the data quality needs to be assessed for accurate health risk assessment. This study developed 10 criteria applicable to the quality assessment of data on MP/NPs in foods. Accordingly, the reliability of 71 data records (69 of them only focused on MPs) was assessed by assigning a score of 2 (reliable without restrictions), 1 (reliable but with restrictions), or 0 (unreliable) on each criterion. The results showed that only three data records scored 2 or 1 on all criteria, and six data records scored 0 on as many as six criteria. A total of 58 data records did not include information on positive controls, and 12 data records did not conduct the polymer identification, which could result in the overestimation or underestimation of MP/NPs. Our results also indicated that the data quality of unprocessed foods was more reliable than that of processed foods. Furthermore, we proposed a quality assurance and quality control protocol to investigate MP/NPs in foods. Notably, the characteristics of MP/NPs used in toxicological studies and those existing in foods showed a remarkable discrepancy, causing the uncertainty of health risk assessment. Therefore, both the estimated exposure of MP/NPs and the claimed potential health risks should be treated with caution.     

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).     

Water quality prediction of copper-molybdenum mining-beneficiation wastewater based on the PSO-SVR model

● Data acquisition and pre-processing for wastewater treatment were summarized. ● A PSO-SVR model for predicting COD_eff in wastewater was proposed. ● The COD_eff prediction performances of the three models in the paper were compared. ● The COD_eff prediction effects of different models in other studies were discussed. The mining-beneficiation wastewater treatment is highly complex and nonlinear. Various factors like influent quality, flow rate, pH and chemical dose, tend to restrict the effluent effectiveness of mining-beneficiation wastewater treatment. Chemical oxygen demand (COD) is a crucial indicator to measure the quality of mining-beneficiation wastewater. Predicting COD concentration accurately of mining-beneficiation wastewater after treatment is essential for achieving stable and compliant discharge. This reduces environmental risk and significantly improves the discharge quality of wastewater. This paper presents a novel AI algorithm PSO-SVR, to predict water quality. Hyperparameter optimization of our proposed model PSO-SVR, uses particle swarm optimization to improve support vector regression for COD prediction. The generalization capacity tested on out-of-distribution (OOD) data for our PSO-SVR model is strong, with the following performance metrics of root means square error (RMSE) is 1.51, mean absolute error (MAE) is 1.26, and the coefficient of determination (R²) is 0.85. We compare the performance of PSO-SVR model with back propagation neural network (BPNN) and radial basis function neural network (RBFNN) and shows it edges over in terms of the performance metrics of RMSE, MAE and R², and is the best model for COD prediction of mining-beneficiation wastewater. This is because of the less overfitting tendency of PSO-SVR compared with neural network architectures. Our proposed PSO-SVR model is optimum for the prediction of COD in copper-molybdenum mining-beneficiation wastewater treatment. In addition, PSO-SVR can be used to predict COD on a wide variety of wastewater through the process of transfer learning.     

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.     

Tailoring the simultaneous abatement of methanol and NOx on Sb-Ce-Zr catalysts via copper modification

● Cu addition enhances CH₃OH oxidation and alleviates its inhibitory effect on SCR. ● Cu addition improves the activation of SCR reactants in the presence of methanol. ● Damaged structure by more Cu addition decreases specific surface area and acidity. ● Excessive Cu addition would lead to the narrowing of SCR temperature window. Simultaneously removal of NO_x and VOCs over NH₃-SCR catalysts have attracted lots of attention recently. However, the presence of VOCs would have negative effect on deNO_x efficiency especially at low temperature. In this study, copper modification onto Sb_0.5CeZr₂O_x (SCZ) catalyst were performed to enhance the catalytic performance for simultaneous control of NO_x and methanol. It was obtained that copper addition could improve the low-temperature activity of both NO_x conversion and methanol oxidation, where the optimal catalyst (Cu_0.05SCZ) exhibited a deNO_x activity of 96% and a mineralization rate of 97% at 250 °C, which are around 10% higher than that of Cu free sample. The characterization results showed that copper addition could obviously enhance the redox capacity of the catalysts. As such, the inhibition effect of methanol incomplete oxidation on NO adsorption and NH₃ activation were then lessened and the conversion of surface formamide species were also accelerated, resulting in the rising of NO_x conversion at low temperature. However, excessive copper addition would damage the Sb-Ce-Zr oxides solid solution structure owing to Cu-Ce strong interactions, decreasing the surface area and acidity. Meanwhile, due to easier over-oxidation of NH₃ with more Cu addition, the temperature window for NO_x conversion would become quite narrow. These findings could provide useful guidelines for the synergistic removal of VOCs over SCR catalyst in real application.     

Biodegradation of waste refrigerator polyurethane by mealworms

● Waste refrigerator polyurethane (WRPU) was ingested and biodegraded by mealworms. ● The carbon in WRPU-based frass was lower than that in WRPU. ● Urethane groups in WRPU were broken down after ingestion by mealworms. ● Thermal stability of WRPU-based frass were deteriorated compared to that of WRPU. ● Gut microbiomes of mealworms fed using WRPU were distinct from that fed using bran. Refrigerator insulation replacement results in discarding a large amount of waste refrigerator polyurethane (WRPU). Insect larvae like mealworms have been used to biodegrade pristine plastics. However, knowledge about mealworms degrading WRPU is scarce. This study presents an in-depth investigation of the degradation of WRPU by mealworms using the micro-morphology, composition, and functional groups of WRPU and the egested frass characteristics. It was found that the WRPU debris in frass was scoured, implying that WRPU was ingested and degraded by mealworms. The carbon content of WRPU-based frass was lower than that of WRPU, indicating that mealworms utilized WRPU as a carbon source. The urethane groups in WRPU were broken, and benzene rings’ C=C and C–H bonds in the isocyanate disappeared after being ingested by mealworms. Thermal gravimetric-differential thermal gravimetry analysis showed that the weight loss temperature of WRPU-based frass was 300 °C lower than that of WRPU, indicating that the thermal stability of WRPU deteriorated after being ingested. The carbon balance analysis confirmed that carbon in the ingested WRPU released as CO₂ increased from 18.84 % to 29.80 %, suggesting that WRPU was partially mineralized. The carbon in the mealworm biomass ingesting WRPU decreased. The possible reason is that WRPU does not supply sufficient nutrients for mealworm growth, and the impurities and odor present in WRPU affect the appetite of the mealworms. The microbial community analysis indicated that WRPU exerts a considerable effect on the gut microorganism of mealworms. These findings confirm that mealworms degrade WRPU.