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In recent years, there has been significant interest in photocatalytic technologies utilizing semiconductors and photosensitizers responsive to solar light, owing to their potential for energy and environmental applications. Current efforts are focused on enhancing existing photocatalysts and developing new ones tailored for environmental uses. Anthraquinones (AQs) serve as redox-active electron transfer mediators and photochemically active organic photosensitizers, effectively addressing common issues such as low light utilization and carrier separation efficiency found in conventional semiconductors. AQs offer advantages such as abundant raw materials, controlled preparation, excellent electron transfer capabilities, and photosensitivity, with applications spanning the energy, medical, and environmental sectors. Despite their utility, comprehensive reviews on AQs-based photocatalytic systems in environmental contexts are lacking. In this review, we thoroughly describe the photochemical properties of AQs and their potential applications in photocatalysis, particularly in addressing key environmental challenges like clean energy production, antibacterial action, and pollutant degradation. However, AQs face limitations in practical photocatalytic applications due to their low electrical conductivity and solubility-related secondary contamination. To mitigate these issues, the design and synthesis of graphene-immobilized AQs are highlighted as a solution to enhance practical photocatalytic applications. Additionally, future research directions are proposed to deepen the understanding of AQs' theoretical mechanisms and to provide practical applications for wastewater treatment. This review aims to facilitate mechanistic studies and practical applications of AQs-based photocatalytic technologies and to improve understanding of these technologies.

The carbon–neutral target presents a significant challenge for the sewage sludge treatment and disposal (SSTD) industry, necessitating strategic planning for a low-carbon transition. However, flexible and comprehensive carbon emission analysis tools to support this goal remain lacking. This study presents a carbon emission analysis tool to evaluate the carbon emission characteristics and future mitigation potentials of SSTD. The tool integrates life cycle inventory (LCI) modeling-based analysis, sensitivity analysis, regression analysis, and scenario analysis. Carbon emissions are dynamically calculated based on sludge properties, technological level, and industry external parameters, providing a foundation for adaptable evaluation tailored to local conditions. The framework considers the potential effects of multi-parameter and multi-aspect changes in scene design, both within and outside the industry, to achieve dynamic and comprehensive simulations. A case study conducted in Wuhan, China, demonstrated the usability and application processes of the framework. The results indicated that carbon emissions from SSTD are projected to more than double from 2021 to 2060 without interventions. Among the mitigation measures, energy and chemical savings would yield the largest reduction potential, followed by the technical layout adjustment and the promotion of energy efficiency. Operational optimization in the sludge industry and outside the industry would contribute the least. With all mitigation measures applied, emissions could decrease to –82.91 kt CO2-eq in 2060, equivalent to 13.03% compensation for emissions from the sewage treatment line. Among all the processes, incineration routes are recommended due to their current and future low carbon emissions. The cooperative resource route of anaerobic digestion and land use also shows promise as it progressively demonstrates superior performance with increasing organic matter and nutrient content of sludge. Critical factors, sub-processes, and emission types for different routes were identified and can be optimized accordingly. The developed method demonstrates sufficient flexibility to be applied to other cities and larger-scale regions, thereby offering technical and strategic support for SSTD towards carbon–neutral operation.

Wastewater treatment plants (WWTPs) are important and energy-intensive municipal infrastructures. High energy consumption and relatively low operating performance are major challenges from the perspective of carbon neutrality. However, water–energy nexus analysis and models for WWTPs have rarely been reported to date. In this study, a cloud-model-based energy consumption analysis (CMECA) of a WWTP was conducted to explore the relationship between influent and energy consumption by clustering its influent’s parameters. The principal component analysis (PCA) and K-means clustering were applied to classify the influent condition using water quality and volume data. The energy consumption of the WWTP is divided into five standard evaluation levels, and its cloud digital characteristics (CDCs) were extracted according to bilateral constraints and golden ratio methods. Our results showed that the energy consumption distribution gradually dispersed and deviated from the Gaussian distribution with decreased water concentration and quantity. The days with high energy efficiency were extracted via the clustering method from the influent category of excessive energy consumption, represented by a compact-type energy consumption distribution curve to identify the influent conditions that affect the steady distribution of energy consumption. The local WWTP has high energy consumption with 0.3613 kW·h·m−3 despite low influent concentration and volumes, across four consumption levels from low (I) to relatively high (IV), showing an unsatisfactory operation and management level. The average oxygenation capacity, internal reflux ratio, and external reflux ratio during high energy efficiency days recognized by further clustering were obtained (0.2924–0.3703 kg O2·m−3, 1.9576–2.4787, and 0.6603–0.8361, respectively), which could be used as a guide for the days with low energy efficiency. Consequently, this study offers a water–energy nexus analysis method to identify influent conditions with operational management anomalies and can be used as an empirical reference for the optimized operation of WWTPs.

Effective management of large basins necessitates pinpointing the spatial and temporal drivers of primary index exceedances and urban risk factors, offering crucial insights for basin administrators. Yet, comprehensive examinations of multiple pollutants within the Yangtze River Basin remain scarce. Here we introduce a pollution inventory for urban clusters surrounding the Yangtze River Basin, analyzing water quality data from 102 cities during 2018–2019. We assessed the exceedance rates for six pivotal indicators: dissolved oxygen (DO), ammonia nitrogen (NH3–N), chemical oxygen demand (COD), biochemical oxygen demand (BOD), total phosphorus (TP), and the permanganate index (CODMn) for each city. Employing random forest regression and SHapley Additive exPlanations (SHAP) analyses, we identified the spatiotemporal factors influencing these key indicators. Our results highlight agricultural activities as the primary contributors to the exceedance of all six indicators, thus pinpointing them as the leading pollution source in the basin. Additionally, forest coverage, livestock farming, chemical and pharmaceutical sectors, along with meteorological elements like precipitation and temperature, significantly impacted various indicators' exceedances. Furthermore, we delineate five core urban risk components through principal component analysis, which are (1) anthropogenic and industrial activities, (2) agricultural practices and forest extent, (3) climatic variables, (4) livestock rearing, and (5) principal polluting sectors. The cities were subsequently evaluated and categorized based on these risk components, incorporating policy interventions and administrative performance within each region. The comprehensive analysis advocates for a customized strategy in addressing the discerned risk factors, especially for cities presenting elevated risk levels.

Sulfamethoxazole (SMX) is a significant environmental concern due to its adverse effects and ecological risks. SMX elimination in aquatic environments via photocatalysis presents a viable solution, given its high oxidation potential. However, such a solution remains controversial, primarily due to a lack of selectivity. Here we introduce a molecularly imprinted TiO2@Fe2O3@g-C3N4 (MFTC) photocatalyst designed for the selective degradation of SMX. To assess MFTC's selectivity, we applied it to degrade synthetic wastewater containing SMX alongside interfering species sulfadiazine (SDZ), ibuprofen (IBU), and bisphenol A (BPA). The results demonstrated a selective degradation efficiency rate of 96.8%, nearly twice that of competing pollutants. The molecularly imprinted sites within the catalyst played a crucial role by selectively capturing SMX and enhancing its adsorption, thereby improving catalytic efficiency. The degradation process involved •OH and •O2− free radicals, with a newly proposed double Z-scheme mechanism and potential pathway for SMX degradation by the MFTC photocatalytic system. This study enriches the application of photocatalysis using molecularly imprinted nanocomposite materials for treating complex pollutant mixtures in water.

In this study, the influence of Fe3+ on N removal, microbial assembly, and species interactions in a biofilm system was determined. The results showed that maximum efficiencies of ammonia nitrogen (NH4+-N), total nitrogen (TN), phosphorus (P), and chemical oxygen demand (COD) removal were achieved using 10 mg/L Fe3+, reaching values of 100, 78.85, 100, and 95.8%, respectively, whereas at concentrations of 15 and 30 mg/L Fe3+ suppressed the removal of NH4+-N, TN, and COD. In terms of absolute abundance, the expression of bacterial amoA, narG, nirK, and napA was maximal in the presence of 10 mg/L Fe3+ (9.18 × 105, 8.58 × 108, 1.09 × 108, and 1.07 × 109 copies/g dry weight, respectively). Irrespective of Fe3+ concentrations, the P removal efficiency remained at almost 100%. Candidatus_Competibacter (10.26–23.32%) was identified as the most abundant bacterial genus within the system. Determinism (50%) and stochasticity (50%) contributed equally to microbial community assembly. Co-occurrence network analysis revealed that in the presence of Fe3+, 60.94% of OTUs in the biofilm system exhibited positive interactions, whereas 39.06% exhibited negative interactions. Within the OTU-based co-occurrence network, fourteen species were identified as key microbes. The stability of the system was found to be predominantly shaped by microbial cooperation, complemented by competition for resources or niche incompatibility. The results of this study suggested that during chemical P removal in wastewater treatment plants using biofilm methods, the concentration of supplemental Fe3+ should be maintained at 10 mg/L, which would not only contribute to P elimination, but also enhance N and COD removal.

IntroductionPharmaceutical wastewater frequently contains high levels of toxic pollutants. If they are discharged untreated, they pose a threat to the environment. The traditional activated sludge process and the advanced oxidation process do not sufficiently remove toxic and conventional pollutants from pharmaceutical wastewater treatment plants (PWWTPs).MethodsWe designed a pilot-scale reaction system to reduce toxic organic pollutants and conventional pollutants from pharmaceutical wastewater during the biochemical reaction stage. This system included a continuous stirred tank reactor (CSTR), microbial electrolysis cells (MECs), an expanded sludge bed reactor (EGSB), and a moving bed biofilm reactor (MBBR). We used this system to further investigate the benzothiazole degradation pathway.Results and discussionThe system effectively degraded the toxic pollutants (benzothiazole, pyridine, indole, and quinoline) and the conventional chemicals (COD, NH4+-N, TN). During the stable operation of the pilot-scale plant, the total removal rates of benzothiazole, indole, pyridine, and quinoline were 97.66, 94.13, 79.69, and 81.34%, respectively. The CSTR and MECs contributed the most to the removal of toxic pollutants, while the EGSB and MBBR contributed less to the removal of the four toxic pollutants. Benzothiazoles can be degraded via two pathways: the benzene ring-opening reaction and the heterocyclic ring-opening reaction. The heterocyclic ring-opening reaction was more important in degrading the benzothiazoles in this study.ConclusionThis study provides feasible design alternatives for PWWTPs to remove both toxic and conventional pollutants at the same time.

An effective sponge city construction evaluation system plays a crucial role in evaluating sponge city construction schemes. The construction of a sponge city evaluation system still faces challenges related to incomplete index selection and unscientific weight division. Limited studies have focused on the comprehensive assessment of sponge city construction in the early stages. This study constructed a scientific assessment indicator system and a quantitative indicator weight at all levels by literature review and statistical analysis methods from an objective perspective. To demonstrate how to utilize our evaluation methods, three construction schemes randomly generated by MATLAB were evaluated under evaluation states of constant weight and variable weight, respectively. Scheme 3 had the highest score of 0.638 under the constant weight assessment, but it cannot practically be the final construction scheme due to the imbalance between indicators. Compared to the constant weight assessment, a variable weight assessment can effectively balance the states of the evaluation index with changes in the decision variable. Among the three schemes, Scheme 2 is the best choice with a value of 0.0355 under variable weight evaluation due to punishment and incentives in the variable weight method. The concept of “punishing” a disadvantageous indicator and “motivating” an advantageous indicator increases the relative advantages of the indices, ultimately affecting the assessment results of schemes and leading to a more balanced state. This study provides reasonable analysis and decision-making mechanisms to support decision-making and guide the scientific selection of a construction scheme.