2‑Hydroxy-1,4-Naphthoquinone: A Promising Redox Mediator for Minimizing Dissolved Organic Nitrogen and Eutrophication Effects of Wastewater Effluent

Researchers and engineers are committed to finding effective approaches to reduce dissolved organic nitrogen (DON) to meet more stringent effluent total nitrogen limits and minimize effluent eutrophication potential. Here, we provided a promising approach by adding specific doses of 2-hydroxy-1,4-naphthoquinone (HNQ) to postdenitrification bioreactors. This approach of adding a small dosage of 0.03–0.1 mM HNQ effectively reduced the concentrations of DON in the effluent (ANOVA, p < 0.05) by up to 63% reduction of effluent DON with a dosing of 0.1 mM HNQ when compared to the control bioreactors. Notably, an algal bioassay indicated that DON played a dominant role in stimulating phytoplankton growth, thus effluent eutrophication potential in bioreactors using 0.1 mM HNQ dramatically decreased compared to that in control bioreactors. The microbe-DON correlation analysis showed that HNQ dosing modified the microbial community composition to both weaken the production and promote the uptake of labile DON, thus minimizing the effluent DON concentration. The toxic assessment demonstrated the ecological safety of the effluent from the bioreactors using the strategy of HNQ addition. Overall, HNQ is a promising redox mediator to reduce the effluent DON concentration with the purpose of meeting low effluent total nitrogen levels and remarkably minimizing effluent eutrophication effects

Effect of Solids Retention Time on Effluent Dissolved Organic Nitrogen in the Activated Sludge Process: Studies on Bioavailability, Fluorescent Components, and Molecular Characteristics

Wastewater-derived dissolved organic nitrogen (DON) should be minimized by municipal wastewater treatment plants (MWWTPs) to reduce its potential impact on receiving waters. Solids retention time (SRT) is a key control parameter for the activated sludge (AS) process; however, knowledge of its impact on effluent DON is limited. This study investigated the effect of SRT on the bioavailability, fluorescent components, and molecular characteristics of effluent DON in the AS process. Four lab-scale AS reactors were operated in parallel at different SRTs (5, 13, 26, and 40 days) for treatment of primary treated wastewater collected from an MWWTP. Results showed the positive effect of prolonged SRT on DON removal. AS reactors during longer SRTs, however, cannot sequester the bioavailable DON (ABDON) and occasionally contribute to greater amounts of ABDON in the effluents. Consequently, effluent DON bioavailability increased with SRT (R2 = 0.619, p < 0.05, ANOVA). Analysis of effluent DON fluorescent components and molecular characteristics indicated that the high effluent DON bioavailability observed at long SRTs is contributed by the production of microbially derived nitrogenous organics. The results presented herein indicate that operating an AS process with a longer SRT cannot control the DON forms that readily stimulate algal growth

Microbial Transformation of Dissolved Organic Sulfur during the Oxic Process in 47 Full-Scale Municipal Wastewater Treatment Plants

Dissolved organic sulfur (DOS) is a significant part of effluent organic matter of wastewater treatment plants (WWTPs) and poses a potential ecological risk for receiving waters. However, the oxic process is a critical unit of biological wastewater treatment for microorganisms performing organic matter removal, wherein DOS transformation and its mechanism are poorly understood. This study investigated the transformation of DOS during the oxic process in 47 full-scale municipal WWTPs across China from molecular and microbial aspects. Surprisingly, evident differences in DOS variations (ΔDOS) separated sampled WWTPs into two groups: 28 WWTPs with decreased DOS concentrations in effluents (ΔDOS < 0) and 19 WWTPs with increased DOS (ΔDOS > 0). These two groups also presented differences in DOS molecular characteristics: higher nitrogen/carbon (N/C) ratios (0.030) and more peptide-like DOS (8.2%) occurred in WWTPs with ΔDOS > 0, implying that peptide-like DOS generated from microbes contributed to increased DOS in effluents. Specific microbe–DOS correlations (Spearman correlation, p < 0.05) indicated that increased effluent DOS might be explained by peptide-like DOS preferentially being produced during copiotrophic bacterial growth and accumulating due to less active cofactor metabolisms. Considering the potential environmental issues accompanying DOS discharge from WWTPs with ΔDOS > 0, our study highlights the importance of focusing on the transformation and control of DOS in the oxic process

Carbon Source in Tertiary Denitrification Regulates Dissolved Organic Nitrogen in Wastewater Effluent

With global eutrophication and increasingly stringent nitrogen discharge restrictions, dissolved organic nitrogen (DON) holds considerable potential to upgrade advanced wastewater denitrification because of its large contribution to low-nitrogen effluents and stronger stimulation effect for algae. Here, we show that DON from the postdenitrification systems dominates effluent eutrophication potential under different carbon sources. Methanol resulted in significantly lower DON concentrations (0.84 ± 0.03 mg/L) compared with the total nitrogen removal-preferred acetate (1.11 ± 0.02 mg/L) (p < 0.05, ANOVA). With our well-developed mathematical model (R2 = 0.867–0.958), produced DON instead of shared (persist in both influent and effluent) and/or removed DON was identified as the key component for effluent DON variation (Pearson r = 0.992, p < 0.01). The partial least-squares path modeling analysis showed that it is the microbial community (r = 0.947, p < 0.01) rather than the predicted metabolic functions (r = 0.040, p > 0.1) that affected produced DON. Carbon sources rebuild the microorganism–DON interaction by affecting the structure of microbial communities with different abilities to generate and recapture produced DON to finally regulate effluent DON. This study revalues the importance of carbon source selection and overturns the current rationality of pursuing only the total nitrogen removal efficiency by emphasizing DON

Prediction of Adsorptive Activities of MOFs for Pollutants in Aqueous Phase Based on Machine Learning

Metal–organic frameworks (MOFs) have gained significant attention in the field of pollutant removal due to their rich pore structures and large specific surface areas. As the number of MOF structures continues to increase, machine learning methods have become a powerful tool for prediction of adsorptive activities of MOFs for pollutants. In this study, 16 models were constructed using published adsorption data, which included 28 MOFs and 30 pollutants, resulting in a dataset of 836 data points. The XGBoost model was determined to be the most effective model, achieving an average R2 of 0.953 during the 5-fold cross-validation. The model’s performance was influenced by a combination of MOF features, pollutant features, and adsorption conditions. Key parameters for the XGBoost model’s performance included the pollutant concentration, pH, solid–liquid ratio, and temperature. Different types of MOFs, including Zr-MOFs, Cr-MOFs, Al-MOFs, and Fe-MOFs, were observed to display distinct adsorption mechanisms through the machine learning model. These mechanisms included electrostatic interactions, π–π interactions, hydrogen bonding, and van der Waals force. The model’s predictions regarding the optimal MOFs and adsorption conditions for the 30 pollutants were partially validated through experimental data, demonstrating the feasibility of the model’s predictions. This study provides technical and theoretical support for the prediction and selection of optimal MOFs for pollutant removal in the aqueous phase