Arsanilic acid (p-ASA), an organoarsenic additive found in livestock wastewater, can release toxic inorganic arsenic into the environment. While bioelectrochemical systems have proven effective in decomposing organoarsenics, managing the resulting inorganic arsenic remains a challenge. This study demonstrated the feasibility of a two-stage bioelectrochemical process designed to facilitate p-ASA degradation and in situ recover inorganic arsenic from contaminated livestock wastewater. It consisted of two sequential stages: (I) anodic stimulation for p-ASA degradation and (II) reversing electrode polarities for the cathodic reduction of inorganic arsenic. In Stage I, the anode significantly enhanced the degradation of p-ASA, resulting in 18 μg/L of As(III) and 700 μg/L of As(V) released into the bulk solution. In Stage II, the cathode further reduced the As(III) and As(V) to 8.9 and 35.5 μg/L, respectively, through the synergistic action of the cathode and suspended microbes. The inorganic arsenic was recovered as a layer of As(V)-O on the cathode. Microbial analysis indicated that Alcaligenes was responsible for the degradation of p-ASA, while Anaerobacillus and Desulfitibacter played key roles in reducing As(V) and As(III) on the cathode, respectively. This study provided a promising alternative approach for the removal of organoarsenics and in situ recovery of inorganic arsenic from organoarsenic-bearing wastewater.
Effective treatment of blackwater is critical for sustainable water management and environmental protection. This study investigated the performance of a novel two-stage anoxic-oxic moving bed biofilm reactor (A/O-MBBR) over an operational period of 82 d to enhance the treatment efficiency of blackwater. With an HRT of 25.5 h, the MBBR achieved removal rates of 94.4% for COD, 99.7% for NH3-N, 84.0% for TN, and 74.6% for TP. Even at reduced HRT, the system maintained consistently high removal efficiencies for both COD and TN, highlighting its robust performance under varying operational conditions. This study underscored the superior nitrification activity of attached biofilm compared to the suspended biomass. Predominant microbial genera identified within the biofilm included Thiothrix, Azospira, Acinetobacter, and Thauera genera, which played a critical role in nutrient removal processes. Notably, at low operational temperatures ranging from 8 to 15 °C, facultative anaerobic species contributed significantly to sustaining nitrogen removal efficiencies, hence demonstrating the adaptability of the microbial community to varied environmental conditions. Furthermore, an advanced machine learning model, eXtreme Gradient Boosting (XGBoost), was developed and applied to predict pollutant concentrations across different A/O-MBBR chambers. The model exhibited exceptional predictive accuracy, highlighting the potential of integrating computational intelligence with biological treatment systems to optimize wastewater treatment processes.
The extensive application of quaternary ammonium compounds (QACs) has led to a significant increase in their mass load in wastewater treatment plants (WWTPs). However, little is known about how QACs contribute to the emergence of resistance against different antibiotics. This study aims to reveal the structure- and dose–response relationships between various QACs and their induced antibiotic resistance and sensitivity patterns. 16 QACs were tested for their capacity in inducing multidrug resistance in activated sludge (AS) and AS-isolated E. coli. For AS, the exposure to three representative QACs resulted in up to a 32-fold increase in resistance against norfloxacin, tetracycline, kanamycin and gentamicin. However, the resistance to cefepime (CEF), azithromycin, and rifampicin remained largely unchanged. As a representative strain isolated from AS, the exposure of E. coli to QACs at 1 mg/L exhibited no induced resistance, whereas the MIC for CEF showed a decrease by 62.5%–87.5%. This was likely attributed to downregulation of proton motive force and efflux pump, which promoted the intracellular accumulation of CEF. Additionally, we identified the high-risk structural characteristics of QACs and emphasized the critical importance of determining the threshold concentrations for QACs risk management. This study provides valuable guidance for the assessment and management of environmental resistance risks caused by increased QACs in diverse environments.
High-molecular-weight disinfection byproducts (HMW DBPs) have been increasingly recognized as contaminants that pose potential hazards to human health. However, reliable analytical methods for exploring the properties and structures of these DBPs remain limited. This study presents a novel approach for detecting and identifying HMW DBPs via matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The experimental conditions were optimized by selecting super-2,5-dihydroxybenzoic acid (super-DHB) as the matrix and sodium trifluoroacetate as the cationization agent and employing the sandwich deposition method in reflection-positive ion mode with 90% laser intensity, resulting in the highest peak intensity for HMW DBPs. These optimized conditions enhanced peak reproducibility, yielding a signal-to-noise ratio of 134.9 and a coefficient of variation of 3.8%. With the new approach, five HMW DBPs were detected in simulated drinking water and identified as oligosaccharide carboxylic acids via isotopic pattern analysis, tandem mass spectrometry analysis in laser-induced dissociation mode, and database verification.
Plastic packaging is mostly produced in a composite way, and its waste is difficult to be recycled, resulting in plastic pollution has become a major problem in the current global environmental pollution control. This paper presents a summary of the rationale behind the global approach to controlling plastic packaging pollution, as well as an overview of the developments in China’s strategy for tackling this issue. Concurrently, the findings of the comprehensive life cycle assessment indicate that the primary sources of carbon emissions within China’s plastic packaging manufacturing sector are the production of virgin resin and the disposal of waste, while the manufacturing process of plastic packaging is not a significant contributor to overall emissions. Additionally, alternative materials for plastic packaging do not demonstrate a more substantial reduction in carbon footprint than traditional plastic packaging materials. The objective of this study is to provide a reference point for the enhancement of the entire chain management of plastic packaging pollution, thereby guiding relevant industries and research toward the development of a circular economy.
With industrialization accelerating and carbon emissions rising in recent years, the treatment of industrial wastewater containing refractory organic compounds must align with goals of energy conservation and emission reduction under the principle of carbon neutrality. Integrating anaerobic digestion (AD) with biochar (BC) presents a promising biological approach to mitigating the inhibitory effects of pollutants in wastewater treatment. By simultaneously utilizing waste biomass resources, the integration of these two sustainable biotechnologies within the biochar-anaerobic digestion (BC-AD) process not only enhances bioenergy recovery but also contributes substantially to the reduction of carbon emissions. This study addresses key challenges in the anaerobic treatment of industrial wastewater and introduces BC in terms of its functional applications, modification techniques, performance benefits, and prospects for achieving carbon neutrality. Experimental findings demonstrate that BC contributes significantly to maintaining neutral pH by regulating hydraulic retention time (HRT) and organic loading rate (OLR). The study presents a novel framework for the BC-AD process in treating industrial wastewater, emphasizing its potential to suppress refractory organics and eliminate toxic inorganics. By examining practical applications and identifying the challenges associated with large-scale implementation, this study improves the development and deployment of this integrated biotechnology. The primary objective is to encourage further investigation and industrial adoption of the BC-AD approach for low-carbon and environmentally sustainable wastewater treatment. Special emphasis is placed on the modification and application of BC to improve pollutant degradation and bioenergy recovery within AD systems, thereby underscoring its promise as an innovative solution aligned with carbon neutrality goals.
Antibiotic resistance genes (ARGs) are emerging environmental contaminants, with vertical gene transfer (VGT) in Escherichia coli (E. coli) contributing significantly to their spread. In this study, we sought to predict amino acid mutations in the DNA gyrase subunit A protein of E. coli, simulating resistance scenarios and evaluating the binding efficacy of quinolones (QNs), based on molecular docking analyses. To optimize QNs, we designed a three-dimensional quantitative structure–activity relationship model, thereby enabling the design of 153 substitutes. By screening for environmental friendliness and functional stability, we identified PM-55 and PM-58 as pharmacodynamically stable alternatives, using which the inhibition of VGT was enhanced by 65.52% and 75.86%, respectively. Furthermore, drug synergy experiments revealed that when combined with colistin sulfate E, this promoted the binding affinity of PM-58 to mutant proteins by 77.71%, mediated by an intensification of hydrophobic interactions and shorter hydrogen bonds. In addition, a machine learning-based random forest regression model was used to identify key molecular descriptors influencing drug synergy and the inhibition of ARGs, thereby providing a framework for designing sustainable antibiotic alternatives. This dual approach, which combines molecular modifications with drug synergy, offers practical solutions for mitigating the environmental dissemination of ARGs and will contribute to a more effective inhibition of antimicrobial resistance.
Designing efficient and sustainable catalyst for peroxymonosulfate (PMS) activation and refractory 2,4,6-trichlorophenol (2,4,6-TCP) removal is an imminent task. This study synthesized a novel γ-MnO2/NF catalyst, which has advantages in saving manganese dioxide demand and reducing manganese leaching. The γ-MnO2/NF + PMS oxidation system achieved a 0.219 min−1 2,4,6-TCP apparent rate constant at 20 °C, and removed > 90% of 2,4,6-TCP at the 5th cycle. Both free radical identification and DFT calculations revealed that •OH and SO4•−, rather than 1O2, were the dominant reactive species during γ-MnO2/NF + PMS oxidation. The results indicated that the inner-sphere complexation between γ-MnO2/NF and PMS facilitated the formation of •OH and SO4•−. To fill the research gap in the molecular-level dissimilarities between •OH and SO4•− in 2,4,6-TCP degradation mechanism, experimental testing and quantum chemical analysis methods were used. The DFT calculation found that the HAA reaction at H13 site and RAF reaction at C1 site were more favorable for both •OH and SO4•−. For most reaction sites, SO4•− demonstrates greater energy barriers and substrate selectivity than •OH, attributed to steric constraints. The •OH acted as the predominant oxidative agents responsible for 2,4,6-TCP decomposition. Combining DFT calculation and intermediate identification, potential degradation routes of 2,4,6-TCP were proposed. The ecotoxicity assays verified a substantial reduction in acute toxicity of the treated 2,4,6-TCP solution. This study opens up new avenues for activating PMS with γ-MnO2/NF, and helps to select preferred radical oxidation processes for optimal 2,4,6-TCP removal in practical engineering.
Utilization of carbon-based materials is crucial for mitigating CO2 emissions. However, practical materials for CO2 capture remain challenging due to limitations in adsorption capacity and rate. Inspired by the unique structural features of biomass materials, high-performance hierarchical porous carbon was prepared using vascular plants. The ordered arrangement structure effectively improved the adsorption capacity and rate of the material by optimizing the pore structure. Potassium hydroxide (KOH) was used as an activator to synthesize microporous carbon with an ordered hierarchical structure. The properties of hierarchical porous carbon were characterized. The experimental results indicate that porous carbon prepared from loofah complex has excellent CO2 adsorption capacity. The highest adsorption capacity is 4.09 mmol/g when the activation temperature is 700 °C. The selectivity (15/85) for the binary gas mixture CO2/N2 was 20, and the recoverability was good after 10 cycles. The hierarchical porous carbon derived from loofah showed excellent adsorption performance and has potential in various applications.
Boron carbon nitride (BCN) is a promising adsorbent for removing antibiotics in aquatic environments. However, its practical application in complex aqueous environments is limited by insufficient resistance to pH fluctuations and ion competition. In this study, a novel Ce2O2S-doped tubular boron carbon nitride adsorbent (Ce2O2S-TBCN) was synthesized via a straightforward in situ temperature-controlled self-assembly method. As the temperature increased from 700 to 1000 °C, the carbon derived from P123 improved the flexibility of BCN and facilitated sulfur retention from Ce(SO4)2, leading to the formation of Ce2O2S. During this process, interactions between B-OH groups and Ce2O2S particles induced the bending of the lamellar structure, ultimately forming a tubular morphology that increased the specific surface area by a factor of 2.8. This structural modification, combined with the incorporation of Ce2O2S, synergistically increased the adsorption capacity of Ce2O2S-TBCN by 58.9% compared to pristine BCN. The adsorption kinetics of tetracycline by Ce2O2S-TBCN followed a pseudo-second-order kinetic model. Isotherm analysis revealed a transition from multilayer to monolayer adsorption as the adsorbent dose increased. The spontaneous and exothermic adsorption process was verified by thermodynamic analysis. Moreover, Ce2O2S-TBCN demonstrated remarkable stability under ion coexistence conditions and across a wide pH range, with its performance declining by only 2.4% after 10 cycles. This exceptional stability was attributed to multiple adsorption forces, including hydrogen bonding, Lewis acid-base interactions, and M-π complexation. Ce2O2S-TBCN with high adsorption capacity and resistance to interference holds great potential for application in complex aquatic environments.
Due to increasingly stringent discharge standards for total nitrogen (TN) in wastewater treatment plant effluents and presence of residual organic pollutants (e.g., humic acid, HA, a typical refractory organic) in secondary effluents, new challenges have emerged for water reclamation. These residual organics contribute to membrane fouling in subsequent microfiltration units and serve as precursors to disinfection by-products, making the simultaneous and efficient removal of nitrate and refractory organic contaminants critical for improving reclaimed water quality. In this study, we employed iron-carbon micro-electrolysis (IC-ME) to achieve synchronous removal of nitrate and HA in a continuous-flow reactor system. The reactor was operated for 233 d, including 32 d of validation with real wastewater. With synthetic wastewater containing 20 mg/L NO3−−N and 15 mg/L HA, the system achieved 96.3% ± 3.6% TN and 97.1% ± 4.6% HA removal. During real wastewater treatment (influent: 24.1 ± 0.9 mg/L NO3−−N and 5.9 ± 0.6 mg/L HA), HA and TN removal efficiencies reached 94.6% ± 7.3% and 92.8% ± 2.9%, respectively, with effluent TN consistently below 2 mg/L. Three-dimensional fluorescence analysis confirmed that HA was effectively degraded from the reactor bottom to top. HA addition facilitated the transformation of Fe3O4 precipitates into FeO(OH) and Fe(OH)3, suggesting reduced passivation film formation. Moreover, NapA gene abundance increased and f_Rhodocyclaceae and f_Methanobacteriaceae were the dominant microbes. Thus, IC-ME is a robust technique for treating complex real wastewater, thus providing an environmentally benign solution for concurrent nitrogen and refractory organics removal in advanced wastewater treatment.
Nitrite- and nitrate-coupled anaerobic oxidation of methane (AOM), mediated by Candidatus Methylomirabilis-like bacteria and Methanoperedens-like archaea, respectively, are two recent additions of freshwater carbon and nitrogen cycles. However, the quantitative roles of the two AOM processes in CH4 emission reduction in lakes have not yet been characterized. Here, we explored vertical (0–10, 10–20, and 20–30 cm) variation in nitrite- and nitrate-coupled AOM activity, as well as the abundance and community structure of Methylomirabilis- and Methanoperedens-like methanotrophs in freshwater lake sediment. The potential rates of nitrite- and nitrate-coupled AOM quantified via 13CH4 isotopic experiments were 0.41–3.84 and 0.32–3.88 nmol CH4/(g·d), respectively. The rates of AOM exhibited significant and consistent depth-related variation across different sampling sites, with both peaking in the 10–20 cm layer. The abundance of Methylomirabilis-like bacteria and Methanoperedens-like archaea quantified via quantitative PCR was 3.34 × 105–9.17 × 106 and 1.27 × 106–9.46 × 106 copies/g, respectively. There was no consistent depth-related variation in the abundance of bacteria or archaea. The community composition of both Methylomirabilis- and Methanoperedens-like methanotrophs remained relatively stable along the sediment profile, while the composition significantly changed across sampling sites. Sediment pH and the content of NH4+ and organic carbon were key variables influencing the community structure of Methylomirabilis- and Methanoperedens-like methanotrophs. Overall, we characterized vertical variation in nitrite- and nitrate-coupled AOM processes in lake sediment, which helps quantify their role in CH4 consumption in freshwater aquatic ecosystems.
China’s inland waterway transport sector is facing the challenge of achieving carbon neutrality goals amidst its rapid development. However, the carbon mitigation potential of targeted interventions within inland waterway transport networks remains poorly understood. We construct a port-to-port carbon emission inventory for the inland waterway transport sector from 2019 to 2050. Jiangxi province, a typical dynamically developing region, is selected as the study area given its plans for the large-scale construction of new inland waterways in the future. Our results reveal that while waterway optimization improves cargo transport efficiency, it may lead to higher carbon emissions by 2030. However, with intensified mitigation efforts, it can contribute to significant emission reductions by 2050. In terms of strategic interventions, prioritizing transport technology upgrades (e.g., improve energy efficiency) in the short-term, while transitioning to alternative fuels in the long-term, could reduce to 0.76 Mt emissions by 2050, representing a 72% decrease compared to 2019 levels. Our findings from the typical complex waterway transport network in China offer valuable insights for managing carbon emissions in inland waterways globally, especially in regions contemplating the expansion of their inland waterway systems.
The global water treatment industry urgently demands improved efficiency, energy conservation, and resource recovery. In response to these pressing challenges, artificial intelligence (AI) is rapidly emerging as a driving force for advancing water treatment technology and industry innovation, demonstrating unprecedented potential in data analysis, process prediction, strategy optimization, and resource allocation. However, the application of AI in water treatment currently lacks a systematic theoretical framework and empirical research. In particular, there is a significant gap in the implementation of AI-driven water treatment processes and the evaluation of the water industry, which urgently requires further exploration and resolution. This paper systematically sorts out the transformative logic of AI-driven water treatment technology and industry, analyzing frontier topics in the field from the perspectives of technology development paradigms, engineering application methods, and industry ecosystem models. It also proposes future research priorities and action recommendations, to provide empirical insights for the strategic deployment and execution of smart water management.