● Hybrid deep-learning model is proposed for water quality prediction.

Anaerobic process is regarded as a green and sustainable process due to low carbon emission and minimal energy consumption in wastewater treatment plants (WWTPs). However, some water quality metrics are not measurable in real time, thus influencing the judgment of the operators and may increase energy consumption and carbon emission. One of the solutions is using a soft-sensor prediction technique. This article introduces a water quality soft-sensor prediction method based on Bidirectional Gated Recurrent Unit (BiGRU) combined with Gaussian Progress Regression (GPR) optimized by Tree-structured Parzen Estimator (TPE). TPE automatically optimizes the hyperparameters of BiGRU, and BiGRU is trained to obtain the point prediction with GPR for the interval prediction. Then, a case study applying this prediction method for an actual anaerobic process (2500 m³/d) is carried out. Results show that TPE effectively optimizes the hyperparameters of BiGRU. For point prediction of COD_eff and biogas yield, R² values of BiGRU, which are 0.973 and 0.939, respectively, are increased by 1.03%–7.61% and 1.28%–10.33%, compared with those of other models, and the valid prediction interval can be obtained. Besides, the proposed model is assessed as a reliable model for anaerobic process through the probability prediction and reliable evaluation. It is expected to provide high accuracy and reliable water quality prediction to offer basis for operators in WWTPs to control the reactor and minimize carbon emission and energy consumption.

● Salinity led to the elevation of NAR over 99.72%.

Biological treatment processes are critical for sewage purification, wherein microbial interactions are tightly associated with treatment performance. Previous studies have focused on assessing how environmental factors (such as salinity) affect the diversity and composition of the microbial community but ignore the connections among microorganisms. Here, we described the microbial interactions in response to elevated salinity in an activated sludge system by performing an association network analysis. It was found that higher salinity resulted in low microbial diversity, and small, complex, more competitive overall networks, leading to poor performance of the treatment process. Subnetworks of major phyla (Proteobacteria, Bacteroidetes, and Chloroflexi) and functional bacteria (such as AOB, NOB and denitrifiers) differed substantially under elevated salinity process. Compared with subnetworks of Nitrosomonadaceae, Nitrosomonas (AOB) made a greater contribution to nitrification under higher salinity (especially 3%) in the activated sludge system. Denitrifiers established more proportion of cooperative relationships with other bacteria to resist 3% salinity stress. Furthermore, identified keystone species playing crucial roles in maintaining process stability were dynamics and less abundant under salinity disturbance. Knowledge gleaned from this study deepened our understanding of microbial interaction in response to elevated salinity in activated sludge systems.

● A single particle observation was conducted in a high traffic flow road environment.

A single particle aerosol mass spectrometer (SPAMS) was used to accurately quantify the contribution of vehicle non-exhaust emissions to particulate matter at typical road environment. The PM_2.5, black carbon, meteorological parameters and traffic flow were recorded during the test period. The daily trend for traffic flow and speed on TEDA Street showed obvious “M” and “W” characteristics. 6.3 million particles were captured via the SPAMS, including 1.3 million particles with positive and negative spectral map information. Heavy Metal, High molecular Organic Carbon, Organic Carbon, Mixed Carbon, Elemental Carbon, Rich Potassium, Levo-rotation Glucose, Rich Na, SiO₃ and other categories were analyzed. The particle number concentration measured by SPAMS showed a good linear correlation with the mass concentrations of PM_2.5 and BC, which indicates that the particulate matter captured by the SPAMS reflects the pollution level of fine particulate matter. EC, ECOC, OC, HM and crustal dust components were found to show high values from 7:00–9:00 AM, showing that these chemical components are directly or indirectly related to vehicle emissions. Based on the PMF model, 7 major factors are resolved. The relative contributions of each factor were determined: vehicle exhaust emission (44.8 %), coal-fired source (14.5 %), biomass combustion (12.2 %), crustal dust (9.4 %), ship emission (9.0 %), tires wear (6.6 %) and brake pads wear (3.5 %). The results show that the contribution of vehicle non-exhaust to particulate matter at roadside environment is approximately 10.1 %. Vehicle non-exhaust emissions are the focus of future research in the vehicle pollutant emission control field.

● A 2D finite-element solute transport model, PRB-Trans, is developed.

The passive convergence-permeable reactive barrier (PC-PRB) was proposed to address the limitations of traditional PRB configurations. To evaluate the hydraulic and pollutant removal performance of the PC-PRB system, we developed a simulation code named PRB-Trans. This code uses the two-dimensional (2D) finite element method to simulate groundwater flow and solute transport. Case studies demonstrate that PC-PRB technology is more efficient and cost-effective than continuous permeable reactive barrier (C-PRB) in treating the same contaminated plume. Implementation of PC-PRB technology results in a 33.3% and 72.7% reduction in PRB length (L_PRB) and height (H_PRB), respectively, while increasing 2D horizontal and 2D vertical pollutant treatment efficiencies of PRB by 87.8% and 266.8%, respectively. In addition, the PC-PRB technology has the ability to homogenize the pollutant concentration and pollutant flux through the PRB system, which can mitigate the problems arising from uneven distribution of pollutants in the C-PRB to some extent. The L_PRB required for PC-PRB decreases as the water pipe length (L_p) increases, while the H_PRB required initially decreases and then increases with increasing L_p. The effect of passive well height (H_w) on H_PRB is not as significant as that of L_p on H_PRB. Overall, PC-PRB presents a promising and advantageous PRB configuration in the effective treatment of various types of contaminated plumes.

● Factor analysis of ammonium nitrate formation based on thermodynamic theory.

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.

● Fundamentals of membrane fouling are comprehensively reviewed.

Membrane technology is widely regarded as one of the most promising technologies for wastewater treatment and reclamation in the 21st century. However, membrane fouling significantly limits its applicability and productivity. In recent decades, research on the membrane fouling has been one of the hottest spots in the field of membrane technology. In particular, recent advances in thermodynamics have substantially widened people’s perspectives on the intrinsic mechanisms of membrane fouling. Formulation of fouling mitigation strategies and fabrication of anti-fouling membranes have both benefited substantially from those studies. In the present review, a summary of the recent results on the thermodynamic mechanisms associated with the critical adhesion and filtration processes during membrane fouling is provided. Firstly, the importance of thermodynamics in membrane fouling is comprehensively assessed. Secondly, the quantitative methods and general factors involved in thermodynamic fouling mechanisms are critically reviewed. Based on the aforementioned information, a brief discussion is presented on the potential applications of thermodynamic fouling mechanisms for membrane fouling control. Finally, prospects for further research on thermodynamic mechanisms underlying membrane fouling are presented. Overall, the present review offers comprehensive and in-depth information on the thermodynamic mechanisms associated with complex fouling behaviors, which will further facilitate research and development in membrane technology.

● Properties and performance relationship of CSBT photocatalyst were investigated.

Understanding the relationship between the properties and performance of black titanium dioxide with core-shell structure (CSBT) for environmental remediation is crucial for improving its prospects in practical applications. In this study, CSBT was synthesized using a glycerol-assisted sol-gel approach. The effect of different water-to-glycerol ratios (W:G = 1:0, 9:1, 2:1, and 1:1) on the semiconducting and physicochemical properties of CSBT was investigated. The effectiveness of CSBT in removing phenolic compounds (PHCs) from real agro-industrial wastewater was studied. The CSBT synthesized with a W:G ratio of 9:1 has optimized properties for enhanced removal of PHCs. It has a distinct core-shell structure and an appropriate amount of Ti³⁺ cations (11.18%), which play a crucial role in enhancing the performance of CSBT. When exposed to visible light, the CSBT performed better: 48.30% of PHCs were removed after 180 min, compared to only 21.95% for TiO₂ without core-shell structure. The CSBT consumed only 45.5235 kWh/m³ of electrical energy per order of magnitude and cost $2.4127 per unit volume of treated agro-industrial wastewater. Under the conditions tested, the CSBT demonstrated exceptional stability and reusability. The CSBT showed promising results in the treatment of phenols-containing agro-industrial wastewater.

Converting biomass materials to humic acid is a sustainable method for humic acid production and achieve biomass valorization. A two-step hydrothermal treatment method was adopted in this study to produce humic acid from corn stalks. In the first step of the process, hydrochar was prepared at different hydrothermal temperatures and pH values. Their chemical properties were then analyzed, and the hydrochar-derived humic acids were produced under alkaline hydrothermal conditions (denoted as HHA_alk). The hydrochar, prepared under high temperature (200 °C) and strong acidic (pH 0) conditions, achieved high HHA_alk yields (i.e., 67.9 wt% and 68.8 wt% calculated based on weight of hydrochar). The sources of HHA_alk formation were as follows: 1) production in the hydrochar preparation stage, and 2) increment under the alkaline hydrothermal treatment of hydrochar. The degree of hydrochar unsaturation was suggested as an indicator for evaluating the hydrochar humification potential under alkaline hydrothermal conditions. This study provides an important reference for the preparation of suitable hydrochar with high hydrothermal humification potential.

● A method based on ATR-FTIR and ML was developed to predict CHNS contents in waste.

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.

● A novel framework integrating quantile regression with machine learning is proposed.

The identification of factors that may be forcing ecological observations to approach the upper boundary provides insight into potential mechanisms affecting driver-response relationships, and can help inform ecosystem management, but has rarely been explored. In this study, we propose a novel framework integrating quantile regression with interpretable machine learning. In the first stage of the framework, we estimate the upper boundary of a driver-response relationship using quantile regression. Next, we calculate “potentials” of the response variable depending on the driver, which are defined as vertical distances from the estimated upper boundary of the relationship to observations in the driver-response variable scatter plot. Finally, we identify key factors impacting the potential using a machine learning model. We illustrate the necessary steps to implement the framework using the total phosphorus (TP)-Chlorophyll a (CHL) relationship in lakes across the continental US. We found that the nitrogen to phosphorus ratio (N׃P), annual average precipitation, total nitrogen (TN), and summer average air temperature were key factors impacting the potential of CHL depending on TP. We further revealed important implications of our findings for lake eutrophication management. The important role of N׃P and TN on the potential highlights the co-limitation of phosphorus and nitrogen and indicates the need for dual nutrient criteria. Future wetter and/or warmer climate scenarios can decrease the potential which may reduce the efficacy of lake eutrophication management. The novel framework advances the application of quantile regression to identify factors driving observations to approach the upper boundary of driver-response relationships.

● A review of machine learning (ML) for spatial prediction of soil contamination.

Soil pollution levels can be quantified via sampling and experimental analysis; however, sampling is performed at discrete points with long distances owing to limited funding and human resources, and is insufficient to characterize the entire study area. Spatial prediction is required to comprehensively investigate potentially contaminated areas. Consequently, machine learning models that can simulate complex nonlinear relationships between a variety of environmental conditions and soil contamination have recently become popular tools for predicting soil pollution. The characteristics, advantages, and applications of machine learning models used to predict soil pollution are reviewed in this study. Satisfactory model performance generally requires the following: 1) selection of the most appropriate model with the required structure; 2) selection of appropriate independent variables related to pollutant sources and pathways to improve model interpretability; 3) improvement of model reliability through comprehensive model evaluation; and 4) integration of geostatistics with the machine learning model. With the enrichment of environmental data and development of algorithms, machine learning will become a powerful tool for predicting the spatial distribution and identifying sources of soil contamination in the future.

● High fluorine is mainly HCO₃·Cl-Na and HCO₃-Na type.

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.

● Effects of AER adsorption and NF on DBP precursors, DBPs, and TOX were examined.

Disinfection byproducts (DBPs) are emerging pollutants in drinking water with high health risks. Precursor reduction before disinfection is an effective strategy to control the formation of DBPs. In this study, three types of anion exchange resins (AERs) and two types of nanofiltration (NF) membranes were tested for their control effects on DBP precursors, DBPs, and total organic halogen (TOX). The results showed that, for AER adsorption, the removal efficiencies of DBP precursors, DBPs, and TOX increased with the increase of resin dose, and the strong basic macroporous anion exchange resin (M500MB) had the highest removal efficiencies. For NF, the highest removal efficiencies were achieved at an operating pressure of 4 bar, and the membrane (NF90) with a smaller molecular weight cut-off, had a better control efficiency. However, AER adsorption was inefficient in removing dissolved organic carbon (DOC); NF was inefficient in removing Br⁻ resulting in insufficient control of Br-DBPs. Accordingly, a sequential approach of AER (M500MB) adsorption followed by NF (NF90) was developed to enhance the control efficiency of DBPs. Compared with single AER adsorption and single NF, the sequential approach further increased the removal efficiencies of DOC by 19.4%–101.9%, coupled with the high Br⁻ removal efficiency of 92%, and thus improved the reduction of cyclic DBPs and TOX by 3.5%–4.9%, and 2.4%–8.4%, respectively; the sequential approach also reduced the cytotoxicity of the water sample by 66.4%.

● Efficient carbon methanation and nitrogen removal was achieved in AnMBR-PN/A system.

An AnMBR-PN/A system was developed for mainstream sewage treatment. To verify the efficient methanation and subsequent chemolitrophic nitrogen removal, a long-term experiment and analysis of microbial activity were carried out. AnMBR performance was less affected by the change of hydraulic retention time (HRT), which could provide a stable influent for subsequent PN/A units. The COD removal efficiency of AnMBR was > 93% during the experiment, 85.5% of COD could be recovered in form of CH₄. With the HRT of PN/A being shortened from 10 to 6 h, nitrogen removal efficiency (NRE) of PN/A increased from 60.5% to 80.4%, but decreased to 68.8% when the HRT_PN/A further decreased to 4 h. Microbial analysis revealed that the highest specific ammonia oxidation activity (SAOA) and the ratio of SAOA to specific nitrate oxidation activity (SNOA) provide stable NO₂⁻-N/NH₄⁺-N for anammox, and anammox bacteria (mainly identified as Candidatus Brocadia) enriched at the bottom of Anammox-UASB might play an important role in nitrogen removal. In addition, the decrease of COD in Anammox-UASB indicated partial denitrification occurred, which jointly promoted nitrogen removal with anammox.

● The main direct seal up carbon options and challenges are reviewed.

Carbon capture and storage (CCS) technology is an imperative, strategic, and constitutive method to considerably reduce anthropogenic CO₂ emissions and alleviate climate change issues. The ocean is the largest active carbon bank and an essential energy source on the Earth’s surface. Compared to oceanic nature-based carbon dioxide removal (CDR), carbon capture from point sources with ocean storage is more appropriate for solving short-term climate change problems. This review focuses on the recent state-of-the-art developments in offshore carbon storage. It first discusses the current status and development prospects of CCS, associated with the challenges and uncertainties of oceanic nature-based CDR. The second section outlines the mechanisms, sites, advantages, and ecologic hazards of direct offshore CO₂ injection. The third section emphasizes the mechanisms, schemes, influencing factors, and recovery efficiency of ocean-based CO₂-CH₄ replacement and CO₂-enhanced oil recovery are reviewed. In addition, this review discusses the economic aspects of offshore CCS and the preponderance of offshore CCS hubs. Finally, the upsides, limitations, and prospects for further investigation of offshore CO₂ storage are presented.

● A higher sulfur content reduced the curing rate of Cr in glass.

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.

● Cr self-catalysis behaviors during Cr-initiated AOPs were described.

Chromium (Cr), as a transition metal material with multiple redox states, has exhibited the catalysis toward Fenton-like reactions over a wide pH range. Although it is not sensible to add Cr reagents as catalysts due to its toxicity, it is highly promising to remediate Cr-containing wastewater through Cr-initiated advanced oxidation processes (Cr-initiated AOPs), which are clean and low-cost. Moreover, the widely concerned Cr-complexes, considered as obstacles in the remediation process, can be effectively destroyed by AOPs. Cr self-catalysis is defined as Cr species is both substrate and catalyst. However, the full understanding of Cr self-catalysis, including the generation of intermediates Cr(IV)/Cr(V), the synergetic effects with co-existing ions, and the accumulation of toxic Cr(VI), remains a challenge for the practical application of Cr-initiated AOPs. In this review, relevant researches on Cr self-catalysis during Cr-initiated AOPs are summarized. Specifically, the Cr-Fenton-like reaction, Cr substituted materials, and Cr-sulfite reactions are explored as key mechanisms contributing to Cr self-catalysis. Moreover, Cr transformation processes, including synchronously Cr removal, Cr redox reactions, and Cr(VI) accumulation, in AOPs-based synergistic systems are systematically analyzed. Detailed approaches for the detection of active species in AOPs-based systems are also presented. The primary objective of this review is to explore the application of AOPs for Cr-containing wastewater remediation based on Cr self-catalysis, and provide fundamental insights and valuable information for future research on Cr-initiated AOPs.

● The performance and costs of 20 municipal WWTPs were analyzed.

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.

● Bioaugmentation and low-dose persulfate were effective in degrading PAHs.

Polycyclic aromatic hydrocarbon (PAH)-contaminated soils are usually complex and characterized by a lack of nutrition and soil salinization, resulting in difficulties in soil remediation. In this study, bioaugmentation with a PAH-degrading Bacillus PheN7 (BA) and low-dose persulfate oxidation (PS), along with natural biodegradation, were utilized to remediate alkaline PAH-contaminated soil. The soil used in the study had a pH of 9.35, and the total PAH content was 568.8 ± 31.0 mg/kg dry soil. After 42 d of remediation, the degradation efficiency of PAHs was 96.72% and 93.88% using persulfate oxidation and bioaugmentation, respectively, whereas 38.66% of PAHs were degraded in natural attenuation (NA). Bacillus was the dominant genera throughout the process of bioremediation with the relative abundance of 79.3% on day 42 in the BA system, whereas, Alcanivorax was enriched and became the dominant genera in PS systems. In the meantime, PAH degradation genes were detected with remarkably higher level in the BA system than in PS system during the remediation. In addition to the degradation of contaminants, persulfate oxidation promotes microbial bioremediation efficiency mainly by lowering the pH to neutral and increasing the active phosphorus content in the soil. Microbial species and ecological niches were less reduced in the PS system than in the BA system. Collectively, persulfate oxidation had a better impact on the soil microbiome and is more suitable for long-term soil health than bioaugmentation through PheN7 addition.

● A new adsorption-membrane separation strategy is used for phosphate removal.

Enhanced phosphorus treatment and recovery has been continuously pursued due to the stringent wastewater discharge regulations and a phosphate supply shortage. Here, a new adsorption-membrane separation strategy was developed for rational reutilization of phosphate from sea cucumber aquaculture wastewater using a Zr-modified-bentonite filled polyvinyl chloride membrane. The as-obtained polyvinyl chloride/Zr-modified-bentonite membrane was highly permeability (940 L/(m²·h)), 1–2 times higher than those reported in other studies, and its adsorption capacity was high (20.6 mg/g) when the phosphate concentration in water was low (5 mg/L). It remained stable under various conditions, such as different pH, initial phosphate concentrations, and the presence of different ions after 24 h of adsorption in a cross-flow filtration system. The total phosphorus and phosphate removal rate reached 91.5% and 95.9%, respectively, after the membrane was used to treat sea cucumber aquaculture wastewater for 24 h and no other water quality parameters had been changed. After the purification process, the utilization of the membrane as a new source of phosphorus in the phosphorus-free f/2 medium experiments indicated the high cultivability of economic microalgae Phaeodactylum tricornutum FACHB-863 and 1.2 times more chlorophyll a was present than in f/2 medium. The biomass and lipid content of the microalgae in the two different media were similar. The innovative polyvinyl chloride/Zr-modified-bentonite membrane used for phosphorus removal and recovery is an important instrument to establish the groundwork for both the treatment of low concentration phosphate from wastewater as well as the reuse of enriched phosphorus in required fields.

● A global snapshot of plastic waste generation and disposal is analysed.

Plastic is considered one of the most indispensable commodities in our daily life. At the end of life, the huge ever-growing pile of plastic waste (PW) causes serious concerns for our environment, including agricultural farmlands, groundwater quality, marine and land ecosystems, food toxicity and human health hazards. Lack of proper infrastructure, financial backup, and technological advancement turn this hazardous waste plastic management into a serious threat to developing countries, especially for Bangladesh. A comprehensive review of PW generation and its consequences on environment in both global and Bangladesh contexts is presented. The dispersion routes of PW from different sources in different forms (microplastic, macroplastic, nanoplastic) and its adverse effect on agriculture, marine life and terrestrial ecosystems are illustrated in this work. The key challenges to mitigate PW pollution and tackle down the climate change issue is discussed in this work. Moreover, way forward toward the design and implementation of proper PW management strategies are highlighted in this study.

● Data-driven approach was used to simulate VFA production from WAS fermentation.

Riboflavin is a redox mediator that promotes volatile fatty acids (VFAs) production from waste activated sludge (WAS) and is a promising method for WAS reuse. However, time- and labor-consuming experiments challenge obtaining optimal operating conditions for maximal VFA production. In this study, three machine learning (ML) models were developed to predict the VFAs production from riboflavin-mediated WAS fermentation systems. Among the three tested ML algorithms, eXtreme Gradient Boosting (XGBoost) presented the best prediction performance and excellent generalization ability, with the highest testing coefficient of determination (R² of 0.93) and lowest root mean square error (RMSE of 0.070). Feature importance analysis and their interactions using the Shepley Additive Explanations (SHAP) method indicated that pH and soluble protein were the top two input features for the modeling. The intrinsic correlations between input features and microbial communities corroborated this deduction. On the optimized ML model, genetic algorithm (GA) and particle swarm optimization (PSO) solved the optimal solution of VFA output, predicting the maximum VFA output as 650 mg COD/g VSS. This study provided a data-driven approach to predict and optimize VFA production from riboflavin-mediated WAS fermentation.

● Nitrifiers in WWTP were investigated at large spatial scale.

Ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB) play crucial roles in removing nitrogen from sewage in wastewater treatment plants (WWTPs) to protect water resources. However, the differences in ecological properties and putative interactions of AOB and NOB in WWTPs at a large spatial scale remain unclear. Hence, 132 activated sludge (AS) samples collected from 11 cities across China were studied by utilizing 16S rRNA gene sequencing technology. Results indicated that Nitrosomonas and Nitrosospira accounted for similar ratios of the AOB community and might play nearly equal roles in ammonia oxidation in AS. However, Nitrospira greatly outnumbered other NOB genera, with proportions varying from 94.7% to 99.9% of the NOB community in all WWTPs. Similar compositions and, hence, a low distance–decay turnover rate of NOB (0.035) across China were observed. This scenario might have partly resulted from the high proportions of homogenizing dispersal (~13%). Additionally, drift presented dominant roles in AOB and NOB assembling mechanisms (85.2% and 81.6% for AOB and NOB, respectively). The partial Mantel test illustrated that sludge retention time and temperature were the primary environmental factors affecting AOB and NOB communities. Network results showed that NOB played a leading role in maintaining module structures and node connections in AS. Moreover, most links between NOB and other microorganisms were positive, indicating that NOB were involved in complex symbioses with bacteria in AS.

● Better packing density and higher early strength of SS-rich geopolymer.

Geopolymer is a material with high early strength. However, the insufficient durability properties, such as long-term strength, acid-base resistance, freeze–thaw resistance, leaching toxicity, thermal stability, sulfate resistance and carbonation resistance, restrain its practical application. Herein, a long-term stable geopolymer composite with high final strength (ASK1) was synthesized from shell coal gasification fly ash (SFA) and steel slag (SS). Additionally, a geopolymer composite with high early strength (ASK2) was also synthesized for comparison. The results showed that ASK1 exhibited better performance on freezing-thawing resistance, carbonization resistance and heavy metals stabilization compared to the ASK2 at long-term curing. Raising the curing temperature could accelerate the unconfined compressive strength (UCS) development at initial curing ages of 3 to 7 d. Both ASK1 and ASK2 exhibited excellent acid-base and sulfate corrosion resistance. An increase for UCS was seen under KOH solution and MgSO₄ solution corrosion for ASK1. All leaching concentrations of heavy metals out of the two geopolymers were below the standard threshold, even after 50 freezing-thawing cycles. Both ASK1 and ASK2 geopolymer concrete exhibited higher sustainability and economic efficiency than Portland cement concrete. The result of this study not only provides a suitable way for the utilization of industrial solid waste in civil and environmental engineering, but also opens a new approach to improve the long-term stabilities of the geopolymers.

● Haze formation in China is highly correlated with iron and steel industry.

Recent years have witnessed significant improvement in China’s air quality. Strict environmental protection measures have led to significant decreases in sulfur dioxide (SO₂), nitrogen oxides (NO_x), and particulate matter (PM) emissions since 2013. But there is no denying that the air quality in 135 cities is inferior to reaching the Ambient Air Quality Standards (GB 3095–2012) in 2020. In terms of temporal, geographic, and historical aspects, we have analyzed the potential connections between China’s air quality and the iron and steel industry. The non-target volatile organic compounds (VOCs) emissions from iron and steel industry, especially from the iron ore sinter process, may be an underappreciated index imposing a negative effect on the surrounding areas of China. Therefore, we appeal the authorities to pay more attention on VOCs emission from the iron and steel industry and establish new environmental standards. And different iron steel flue gas pollutants will be eliminated concurrently with the promotion and application of new technology.

● Screened 8862 metal-organic frameworks for I₂ capture via molecular simulation.

We performed large-scale molecular simulation to screen and identify metal-organic framework materials for gaseous iodine capture, as part of our ongoing effort in addressing management and handling issues of various radionuclides in the grand scheme of spent nuclear fuel reprocessing. Starting from the computation-ready experimental (CoRE) metal-organic frameworks (MOFs) database, grand canonical Monte Carlo simulation was employed to predict the iodine uptake values of the MOFs. A ranking list of MOFs based on their iodine uptake capabilities was generated, with the Top 10 candidates identified and their respective adsorption sites visualized. Subsequently, machine learning was used to establish structure-property relationships to correlate MOFs’ various structural and chemical features with their corresponding performances in iodine capture, yielding interpretable common features and design rules for viable MOF adsorbents. The research strategy and framework of the present study could aid the development of high-performing MOF adsorbents for capture and recovery of radioactive iodine, and moreover, other volatile environmentally hazardous species.

● Catalytic combustion in fluidized bed realizes efficient heat and mass transfer.

A micro fluidized bed reactor was used to study the self-sustaining catalytic combustion of carbon monoxide (CO). The Cu_1−xCe_xO_y catalyst, as well as the pure CuO and CeO₂, are used to investigate the contributing mechanism of different active sites including dispersed CuO and Cu–Ce solid solutions. The ignition temperature (T_i) of CO over these catalysts at a flow rate of 2000 mL/min followed the order: 74 °C (Cu_0.5Ce_0.5O_y) < 75 °C (Cu_0.25Ce_0.75O_y) < 84 °C (Cu_0.75Ce_0.25O_y) < 105 °C (CuO) < 500 °C (CeO₂). Furthermore, the lean combustion limits (equivalence ratio ϕ) over these catalysts under the flow rates of 750–3000 mL/min (through fixed, bubbling, and fluidized bed) were also measured, which are Cu_0.5Ce_0.5O_y < Cu_0.25Ce_0.75O_y < Cu_0.75Ce_0.25O_y < CuO < CeO₂. The fluidized bed was simulated using the Eulerian two-fluid model (TFM) coupled with a diffusion/kinetic-limited reaction model to evaluate the influence of operation conditions on the self-sustained combustion of CO. The predicted maximum temperature agreed with the experimental measurements, demonstrating the validity of the kinetic model and simulation parameters. The results of catalytic combustion with increasing CO concentrations suggest that the catalytic combustion reaction could co-exist with the flamed combustion. When a high concentration of CO is used, a blue-purple flame caused by CO combustion appears in the upper part of the fluidized bed, indicating that the range of CO-containing exhaust gas purification could be expanded to a larger range using the fluidized-bed catalytic combustion technique.

● EE2 photodegradation behavior in the presence of four WWTPs’ DOM was explored.

Dissolved organic matter (DOM) from each treatment process of wastewater treatment plants (WWTPs) contains abundant photosensitive substances, which could significantly affect the photodegradation of 17α-ethinylestradiol (EE2). Nevertheless, information about EE2 photodegradation behavior mediated by DOM from diverse WWTPs and the photosensitivity sources of such DOM are inadequate. This study explored the photodegradation behavior of EE2 mediated by four typical WWTPs’ DOM solutions and investigated the photosensitivity sources of DOM in the anaerobic-anoxic-oxic (A²/O) process. The parallel factor analysis identified three varying fluorescing components of these DOM, tryptophan-like substances or protein-like substances, microbial humus-like substances, and humic-like components. The photodegradation rate constants of EE2 were positively associated with the humification degree of DOM (P < 0.05). The triplet state substances were responsible for the degradation of EE2. DOM extracted from the A²/O process, especially in the secondary treatment process had the fastest EE2 photodegradation rate compared to that of the other three processes. Four types of components (water-soluble organic matter (WSOM), extracellular polymeric substance, humic acid, and fulvic acid) were separated from the A²/O process DOM. WSOM had the highest promotion effect on EE2 photodegradation. Fulvic acid-like components and humic acid-like organic compounds in WSOM were speculated to be important photosensitivity substances that can generate triplet state substances. This research explored the physicochemical properties and photosensitive sources of DOM in WWTPs, and explained the fate of estrogens photodegradation in natural waters.

● Urban water systems are challenged by climate change.

Urban water systems are facing various challenges against climate change, impacting cities’ security and their sustainable development. Specifically, there are three major challenges: submersion risk of coastal cities as glaciers melt and sea level rises, more and severe urban flooding caused by extreme weather like intensified storm surge and heavy precipitation, and regional water resource patterns challenged by alteration of spatial distribution of precipitation. Regarding this, two strategies including proactive adaptation and positive mitigation were proposed in this article to realize the reconstruction and optimization of urban water systems, to enhance their resilience, and eventually increase their adaptability and coping ability to climate change. The proactive adaptation strategy consists of 1) construction of sponge cities to accommodate the increased regular rainfall and to balance the alterations of spatial redistribution of precipitation; 2) reconstruction of excess stormwater discharge and detention system to increase capability for extreme precipitation events based on flood risk assessment under future climate change; 3) deployment of forward-looking, ecological, and integrated measures to improve coastal protection capability against inundation risks caused by climate change and sea level rise. The positive mitigation strategy is to employ the systematic concept in planning and design and to adopt advanced applicable energy-saving technologies, processes, and management practices, aiming at reduction in flux of urban water systems, reinforcement in energy conservation and carbon reduction in both water supply systems and wastewater treatment systems, and thus a reduction of greenhouse gas emission from urban water systems.

● Microplastics (MPs) undergo photoaging in natural water under light irradiation.

Plastic products widespread in natural water can be broken into smaller-sized microplastics (MPs, < 5 mm) under light irradiation, thermal degradation and biodegradation, posing a serious threat to aquatic ecosystems and human health. This perspective concludes that MPs can generate reactive oxygen species (ROS) through initiation, propagation and termination steps, which can attack the polymer resulting in the photoaging and breakdown of C–C and C–H bonds under ultraviolet (UV) irradiation. Free radical generation and weathering degree of MPs depend on their physicochemical properties and environmental conditions. In general, UV irradiation and co-existed MPs can significantly accelerate MP photoaging. With plentiful chromophores (carbonyl, carboxyl and benzene rings, Dissolved organic matter (DOM) mainly absorbs photons (300–500 nm) and generates hydrated electrons, ³DOM* and ROS, which may affect MP photoaging. However, whether DOM may transfer the electron and energy to MPs under UV irradiation, affect ROS generation of MPs and their photoaging pathway are inadequately studied. More studies are needed to elucidate MP photoaging pathways and mechanisms, consider the influence of stabilization capacity, photosensitization and photoionization of DOM as well as their competitive light absorption with MPs, which provides valuable insights into the environmental behavior and ecological risk of MPs in natural water.