A simple model for estimating the concentrations of natural estrogens in raw wastewater

Predicting micropollutant fate during wastewater treatment using refined classical kinetic model based on quantitative monitoring in multi-metropolitan regions of South Korea

This study aimed to implement an extensive prediction model for the fate of micropollutants (MPs) in wastewater treatment plants (WWTPs). Five WWTPs equipped with seven different biological treatment processes were monitored from 2020 to 2022 with three to four sampling events in each year, and 27 datasets for 20 MPs were collected. Among these datasets, 12 were used to investigate the behavior and fate of MPs in WWTPs in South Korea. Metformin, acetaminophen, caffeine, naproxen, and ibuprofen were the MPs with the highest influent concentrations (ranging from 3,933.3-187,637.0 ng L-1) at all WWTPs. More than 90% of MPs were removed by biological treatment processes in all WWTPs. The Kruskal-Wallis test verified that their efficacy did not differ statistically (p-value > 0.05). Meanwhile, to refine the performance of the prediction model, this study optimized the biodegradation rate constants (kbio) of each MP according to the variation of seasonal water temperature. As a result, compared to the original prediction model, the mean difference between the actual data and predicted results (MEAN) decreased by 6.77%, while the Nash-Sutcliffe efficiency (NSE) increased by 0.226. The final MEAN and NSE for the refined prediction model were calculated to be 5.09% and 0.964, respectively. The prediction model made accurate predictions, even for MPs exhibiting behaviors different from other cases, such as estriol and atrazine. Consequently, the optimization strategy proposed in this study was determined to be effective because the overall removal efficiencies of MPs were successfully predicted even with limited reference datasets.

Optimized fuzzy inference system to enhance prediction accuracy for influent characteristics of a sewage treatment plant

Sewage treatment plants (STPs) keep sewage contamination within safe levels and minimize the risk of environmental disasters. To achieve optimum operation of an STP, it is necessary for influent parameters to be measured or estimated precisely. In this research, six well-known influent chemical and biological characteristics, i.e., biochemical oxygen demand (BOD), chemical oxygen demand (COD), Ammoniacal Nitrogen (NH₃-N), pH, oil and grease (OG) and suspended solids (SS), were modeled and predicted using the Sugeno fuzzy logic model. The membership function range of the fuzzy model was optimized by ANFIS, the integrated Genetic algorithms (GA), and the integrated particle swarm optimization (PSO) algorithms. The results were evaluated by different indices to find the accuracy of each algorithm. To ensure prediction accuracy, outliers in the predicted data were found and replaced with reasonable values. The results showed that both integrated GA-FIS and PSO-FIS algorithms performed at almost the same level and both had fewer errors than ANFIS. As the GA-FIS algorithm predicts BOD with fewer errors than PSO-FIS and the aim of this study is to provide an accurate prediction of missing data, GA-FIS was only used to predict the BOD parameter; the other parameters were predicted by PSO-FIS algorithm. As a result, the model successfully could provide outstanding performance for predicting the BOD, COD, NH₃-N, OG, pH and SS with MAE equal to 3.79, 5.14, 0.4, 0.27, 0.02, and 3.16, respectively.

Bismuth impregnated biochar for efficient estrone degradation: The synergistic effect between biochar and Bi/Bi2O3 for a high photocatalytic performance

An innovative advanced oxidation process was successfully developed to photocatalytic-degradation of estrone through the synergistic effect of biochar and Bi/Bi₂O₃ in bismuth-containing photocatalytic biochar (BiPB). The highest reaction rate constant (k_obs) of estrone degradation by BiPB was 0.045 min^-1 under the conditions of initial concentration of estrone =10.4 μmol L^-1, [BiPB] =1 g L^-1, pH = 7.0. The k_obs was almost tenfold and more than 20 times than that of biochar without bismuth impregnation and pristine Bi/Bi₂O₃, respectively. The best photocatalytic performance of BiPB composites for the degradation of estrone was primarily attributed to generation of OH radicals. Impregnation of bismuth helped control the concentration of persistent free radicals (PFRs) and develop a hierarchical porous structure of biochar. The presence of biochar facilitated pre-concentration estrone on BiPB and improved the separation and transfer efficiency of charge carriers. The synergistic effect between biochar and Bi/Bi₂O₃ contributed to the generation of OH radicals for estrone degradation under neutral pH conditions. The transformation pathway of estrone was also proposed based on the measured transformation products in the presence of BiPB. The high efficiency of BiPB composites indicated that this easily-obtained material was promising for estrone-wastewater treatment applications as a low-cost composite photocatalyst.

Enhanced estrogen removal in activated sludge processes through the optimization of the hydraulic flow pattern

The removal of β-estradiol (E2) and α-ethinylestradiol (EE2) in biological wastewater treatment plants (WWTP) would need to be improved in order to comply with prospective Environmental Quality Standards (EQS) of 0.4 and 0.035 ng.L^-1 respectively. The effluent concentration of a micropollutant in an activated sludge process is a function of the removal rate, the hydraulic retention time (HRT) and the flow pattern, which is usually overlooked. In order to better understand this aspect, we carried out tracer studies in eight WWTPs in the UK and found that relatively modest changes in aeration tanks would translate into tangible improvements in their flow pattern. We further evaluated the degradation rates for E1 (estrone), E2, E3 (estriol) and EE2 in each WWTP and we estimated that the modification of the flow pattern would be sufficient to place effluent concentrations of E2 (23.2 L∙g_VSS^-1∙d^-1<k_bio<210 L∙g_VSS^-1∙d^-1) far below the prospective EQS, while EE2 (0.3 L∙g_VSS^-1∙d^-1<k_bio<2.9 L∙g_VSS^-1∙d^-1) would have to rely on river dilution for compliance. Regarding E1 and E3, with no prospective legislation, the modifications would place E3 (9.9 L∙g_VSS^-1∙d^-1<k_bio<39.5 L∙g_VSS^-1∙d^-1) effluent concentrations easily below its predicted no-effect concentrations (PNEC = 60 ng.L^-1) while for E1, (2.6 L∙g_VSS^-1∙d^-1<k_bio<19.2 L∙g_VSS^-1∙d^-1) it would very much depend on the degradation rates of the specific WWTP (PNEC = 6 ng.L^-1). Improvement in flow pattern had the additional benefit of improving the effectiveness of other plausible changes in HRT or biological removal rates. Managing the flow pattern of existing WWTPs is a cost-efficient tool for managing the fate of estrogens.

Double strand DNA functionalized Au@Ag Nps for ultrasensitive detection of 17β-estradiol using surface-enhanced raman spectroscopy

A detection method for 17β-estradiol (E2) using surface-enhanced Raman scattering (SERS)-based aptamer sensor was presented. Raman reporter molecule Cy3 labeled E2-aptamer and DNA functionalized gold-silver core-shell nanoparticles (Au@Ag CS NPs) offered SERS with high sensitivity and selectivity. Based on the fabricated double strand DNA-immobilized gold-silver core-shell nanoparticles (Au@Ag NPs), SERS signal intensity of Raman reporter changed with the number of Cy3-labeled aptamer attached to the core-shell nanoparticles due to the strong binding affinity between the aptamers and E2 with different concentrations. A wide linear range from 1.0 × 10^-13 to 1.0 × 10^-9 was obtained for the detection of E2, with a low detection limit of 2.75 fM. This proposed method showed highly sensitive and selective for detecting E2, and could be used to determine E2 in actual samples.

Estimation of human-origin estrone and 17β-estradiol concentrations in the Han River, Seoul, South Korea and its uncertainty-based ecological risk characterization

Estrogens originated from humans can reach ambient water and possibly cause significant ecological risks. In this study, the quantities of human-origin estrone (E1) and 17β-estradiol (E2) in the influent and effluent of four sewer treatment plants (STPs) in Seoul, South Korea were estimated using a demographic model. A Monte Carlo simulation was used to assess the quantitative uncertainty of estimated E1 and E2 concentrations. Mean concentrations of E1 and E2 estimated for STP influents ranged from 29.5 to 38.4 and 7.5 to 9.7ng/L, respectively. Meanwhile, mean concentrations of E1 and E2 estimated for STP effluents were 4.9 to 6.6 and 0.28 to 0.36ng/L, respectively. These estimated values are similar to measured data as reported in the literatures within the range of uncertainty based on the Monte Carlo simulation. The hazard quotient (HQ) value in the main stem of the Han River was calculated to be far less than 1 because of the dilution effect of the Han River's abundant flow, indicating that most of the Han River ecosystem will not be influenced by these endogenous estrogens. With a 95% cumulative probability, HQ values in the main stem of the Han River for the Jungrang, Nanji, Tanchun, and Seonam STPs were less than 0.18, 0.07, 0.08, and 0.15, respectively. Nevertheless, HQ values >1 were observed in the vicinity of the STP outlets when using the numerical modeling. Our results show that the endocrine disruption potential of E1 and E2 around STP outlets in the main stem of the Han River must be monitored carefully.