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.     

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.     

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.     

Current status of municipal wastewater treatment plants in North-east China: implications for reforming and upgrading

● The performance and costs of 20 municipal WWTPs were analyzed. ● Effluent COD and NH₄⁺-N effluent exceed the limits more frequently in winter. ● Nitrification and refractory pollutant removal are limited at low temperatures. ● To meet the national standards, electricity cost must increase by > 42% in winter. ● Anammox, granular sludge, and aerobic denitrification are promising technologies. Climate affects the natural landscape, the economic productivity of societies, and the lifestyles of its inhabitants. It also influences municipal wastewater treatment. Biological processes are widely employed in municipal wastewater treatment plants (WWTPs), and the prolonged cold conditions brought by the winter months each year pose obstacles to meeting the national standards in relatively cold regions. Therefore, both a systematic analysis of existing technical bottlenecks as well as promising novel technologies are urgently needed for these cold regions. Taking North-east China as a case, this review studied and analyzed the main challenges affecting 20 municipal WWTPs. Moreover, we outlined the currently employed strategies and research issues pertaining to low temperature conditions. Low temperatures have been found to reduce the metabolism of microbes by 58% or more, thereby leading to chemical oxygen demand (COD) and NH₄⁺-N levels that have frequently exceeded the national standard during the winter months. Furthermore, the extracellular matrix tends to lead to activated sludge bulking issues. Widely employed strategies to combat these issues include increasing the aeration intensity, reflux volume, and flocculant addition; however, these strategies increase electricity consumption by > 42% in the winter months. Internationally, the processes of anaerobic ammonium oxidation (anammox), granular sludge, and aerobic denitrification have become the focus of research for overcoming low temperature. These have inspired us to review and propose directions for the further development of novel technologies suitable for cold regions, thereby overcoming the issues inherent in traditional processes that have failed to meet the presently reformed WWTP requirements.     

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.     

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.     

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.     

Functional flax fiber with UV-induced switchable wettability for multipurpose oil-water separation

● A PAA-ZnO-HDTMS flax fiber with UV-induced switchable wettability was developed. ● The property of flax fiber could be switched from hydrophobicity to hydrophilicity. ● The mechanism of the acquired UV-induced switchable wettability was discussed. ● The developed flax fiber was successfully used for multipurpose oil-water separation. The large number of oily wastewater discharges and oil spills are bringing about severe threats to environment and human health. Corresponding to this challenge, a functional PAA-ZnO-HDTMS flax fiber with UV-induced switchable wettability was developed for efficient oil-water separation in this study. The developed flax fiber was obtained through PAA grafted polymerization and then ZnO-HDTMS nanocomposite immobilization. The as-prepared PAA-ZnO-HDTMS flax fiber was hydrophobic initially and could be switched to hydrophilic through UV irradiation. Its hydrophobicity could be easily recovered through being stored in dark environment for several days. To optimize the performance of the PAA-ZnO-HDTMS flax fiber, the effects of ZnO and HDTMS concentrations on its switchable wettability were investigated. The optimized PAA-ZnO-HDTMS flax fiber had a large water contact angle (~130°) in air and an extremely small oil contact angle (~0°) underwater initially. After UV treatment, the water contact angle was decreased to 30°, while the underwater oil contact angle was increased to more than 150°. Based on this UV-induced switchable wettability, the developed PAA-ZnO-HDTMS flax fiber was applied to remove oil from immiscible oil-water mixtures and oil-in-water emulsion with great reusability for multiple cycles. Thus, the developed flax fiber could be further fabricated into oil barrier or oil sorbent for oil-water separation, which could be an environmentally-friendly alternative in oil spill response and oily wastewater treatment.     

Evaluation of activated sludge properties’ changes in industrial-wastewater pre-treatment: role of residual aluminum hydrolyzed species with different polymerization degree

● Medium poly Al salts dominated the PAC residual salts with a rational dosage. ● Settlement flocculation effect under medium poly Al salts showed a better trend. ● Complex of medium poly Al salts and enzymes promoted cell activity. ● Medium poly Al salts were beneficial to the effluent indexes. With the widespread introduction of pre-coagulation prior to the biological unit in various industrial wastewater treatments, it is noteworthy that long-term accumulation of residual coagulants has certains effect on both micro and macro characteristics of activated sludge (AS). In this study, the morphology distributions of residual aluminum salts (RAS) and their effects on the removal efficiency of AS were investigated under different PAC concentrations. The results showed that the dominance of medium polymeric RAS, formed under an appropriate PAC dose of 20 mg/L enhanced the hydrophobicity, flocculation, and sedimentation performances of AS, as well as the enzymatic activity in cells in the sludge system, improving the main pollutants removal efficiency of the treatment system. Comparatively the species composition with monomer and dimer / high polymer RAS as the overwhelming parts under an over-dosed PAC concentration of 55 mg/L resulted in excessive secretion of EPS with loose flocs structure and conspicuous inhibition of cellular activity, leading to the deterioration of physico-chemical and biological properties of AS. Based on these findings, this study can shed light on the role of the RAS hydrolyzed species distributions, closely relevant to Al dosage, in affecting the comprehensive properties of AS and provide a theoretical reference for coagulants dosage precise control in the pretreatment of industrial wastewater.     

Identification of pollution sources in rivers using a hydrodynamic diffusion wave model and improved Bayesian-Markov chain Monte Carlo algorithm

● A hydrodynamic-Bayesian inference model was developed for water pollution tracking. ● Model is not stuck in local optimal solutions for high-dimensional problem. ● Model can estimate source parameters accurately with known river water levels. ● Both sudden spill incident and normal sewage inputs into the river can be tracked. ● Model is superior to the traditional approaches based on the test cases. Water quality restoration in rivers requires identification of the locations and discharges of pollution sources, and a reliable mathematical model to accomplish this identification is essential. In this paper, an innovative framework is presented to inversely estimate pollution sources for both accident preparedness and normal management of the allowable pollutant discharge. The proposed model integrates the concepts of the hydrodynamic diffusion wave equation and an improved Bayesian-Markov chain Monte Carlo method (MCMC). The methodological framework is tested using a designed case of a sudden wastewater spill incident (i.e., source location, flow rate, and starting and ending times of the discharge) and a real case of multiple sewage inputs into a river (i.e., locations and daily flows of sewage sources). The proposed modeling based on the improved Bayesian-MCMC method can effectively solve high-dimensional search and optimization problems according to known river water levels at pre-set monitoring sites. It can adequately provide accurate source estimation parameters using only one simulation through exploration of the full parameter space. In comparison, the inverse models based on the popular random walk Metropolis (RWM) algorithm and microbial genetic algorithm (MGA) do not produce reliable estimates for the two scenarios even after multiple simulation runs, and they fall into locally optimal solutions. Since much more water level data are available than water quality data, the proposed approach also provides a cost-effective solution for identifying pollution sources in rivers with the support of high-frequency water level data, especially for rivers receiving significant sewage discharges.     

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).     

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.     

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.     

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.     

Microplastics in municipal wastewater treatment plants: a case study of Denizli/Turkey

● High amounts of microplastics are released to receiving media from WWTPs. ● The effect of classical treatment processes on MP removal is important. ● MP load in the effluent of WWTPs is important for developing treatment technology. ● Additional physical treatment could help further reduce MP discharge. Plastic particles smaller than 5 mm are microplastics. They are among the significant pollutants that recently attracted attention. Great quantities of microplastics enter the sewage system daily and reach wastewater treatment plants (WWTPs). As a result, WWTPs are potential microplastic sources. Hence, they create a pathway for microplastics to reach aquatic environments with treated wastewater discharge. Studies on microplastic characterization in WWTPs have gained momentum in academia. This study investigates the abundance, size, shape, color, polymer type, and removal efficiencies of microplastics in a municipal wastewater treatment plant (WWTP) in Denizli/Turkey. The results showed that the dominant microplastic shape in wastewater samples was fibers (41.78%–60.77%) in the 100–500 µm (58.57%–80.07%) size range. Most of the microplastics were transparent-white (32.86%–58.93%). The dominant polymer types were polyethylene (54.05%) and polyethylene vinyl acetate (37.84%) in raw wastewater. Furthermore, the microplastic removal efficiencies of the Denizli Central WWTP as a whole and for individual treatment units were evaluated. Although the microplastic pollution removal efficiency of the Denizli Central WWTP was over 95%, the microplastic concentration discharged daily into the receiving environment was considerably high (1.28 × 10¹⁰ MP/d). Thus, Denizli Central WWTP effluents result in a high volume of emissions in terms of microplastic pollution with a significant daily discharge to the Çürüksu Stream.     

Long-term exposure to air pollution and cerebrovascular disease: findings from Beijing Health Management Cohort study

● This study explored the long-term association by double robust additive models. ● Individual exposure concentrations were assessed by integrating GAM, LUR and BPNN. ● PM_2.5, SO₂ and NO₂ are positively associated with cerebrovascular disease. ● CO could reduce the risk of cerebrovascular disease with the highest robustness. ● The elderly, women and people with normal BMI are at higher risk for air pollution. The relationship between air pollution and cerebrovascular disease has become a popular topic, yet research findings are highly heterogeneous. This study aims to investigate this association based on detailed individual health data and a precise evaluation of their exposure levels. The integrated models of generalized additive model, land use regression model and back propagation neural network were used to evaluate the exposure concentrations. And doubly robust additive model was conducted to explore the association between cerebrovascular disease and air pollution after adjusted for demographic characteristics, physical examination, disease information, geographic and socioeconomic status. A total of 25097 subjects were included in the Beijing Health Management Cohort from 2013 to 2018. With a 1 μg/m³ increase in the concentrations of PM_2.5, SO₂ and NO₂, the incidence risk of cerebrovascular disease increased by 1.02 (95% CI: 1.008–1.034), 1.06 (95% CI: 1.034–1.095) and 1.02 (95% CI: 1.010–1.029) respectively. Whereas CO exposure could decrease the risk, with an odds ratio of 0.38 (95% CI: 0.212–0.626). In the subgroup analysis, individuals under the age of 50 with normal BMI were at higher risk caused by PM_2.5, and SO₂ was considered more hazardous to women. Meanwhile, the protective effect of CO on women and those with normal BMI was stronger. Successful reduction of long-term exposure to PM_2.5, SO₂ and NO₂ would lead to substantial benefits for decrease the risk of cerebrovascular disease especially for the health of the susceptible individuals.     

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.     

Adsorption and desorption of steroid hormones on saline soil

● Organic matter content significantly affected adsorption of E2/EE2 on saline soil. ● EE2 possessed higher competition intensity for adsorption sites than E2. ● The adsorption of E2/EE2 on saline soil was a spontaneous exothermic process. ● Desorption capacity of EE2/E2 accounted for 40%/78% of the total adsorption capacity. Soil organic matter content was the main driving factor affecting adsorption and desorption process of 17β-estradiol (E2) and 17α-ethynylestradiol (EE2) on saline soil. The adsorption and desorption of E2 and EE2 on three saline soils showed the similar behavior that soil with the highest organic content possessed the highest adsorption capacity and the lowest desorption capacity for E2 and EE2. The adsorption capacity of untreated soil samples (with organic matter) was larger than that of soil samples without organic matter. For soil with the largest adsorption capacity, adsorption capacity of E2/EE2 on the untreated soil and soil colloid (with organic matter) respectively reached 0.15/0.30 μg/g and 0.16/0.33 μg/g while the soil and soil colloid without organic matter hardly adsorbed pollutants. The adsorption capacity of E2/EE2 at the initial concentration of 100 μg/L was 25/15 times higher than that at the initial concentration of 5 μg/L. E2 and EE2 had the same adsorption sites on saline soil while EE2 possessed higher competition intensity for adsorption sites than E2. Pseudo-first-order model (R² = 0.995–0.986) and Langmuir model (R² = 0.989–0.999) could better fit the adsorption process of E2 or EE2. The thermodynamic study further showed that the adsorption of E2/EE2 on saline soil was a spontaneous exothermic process. The desorption capacity of EE2/E2 accounted for 40%/78% of the total adsorption capacity to possibly exert potential risk to the groundwater. The variation of the salinity led to the variation of soil organic carbon which subsequently changed the adsorption and desorption behaviors of endocrine disrupting chemicals in coastal saline soil. This study provides a new insight on the interfacial behavior of endocrine disrupting chemicals on saline soil.     

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.     

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.