Wastewater Treatment Plant Effluent Water Research Articles

A hybrid deep learning approach to improve real-time effluent quality prediction in wastewater treatment plant

Wastewater treatment plant (WWTP) operation is usually intricate due to large variations in influent characteristics and nonlinear sewage treatment processes. Effective modeling of WWTP effluent water quality can provide valuable decision-making support to facilitate their operations and management. In this study, we developed a novel hybrid deep learning model by combining the temporal convolutional network (TCN) model with the long short-term memory (LSTM) network model to improve the simulation of hourly total nitrogen (TN) concentration in WWTP effluent. The developed model was tested in a WWTP in Jiangsu Province, China, where the prediction results of the hybrid TCN-LSTM model were compared with those of single deep learning models (TCN and LSTM) and traditional machine learning model (feedforward neural network, FFNN). The hybrid TCN-LSTM model could achieve 33.1 % higher accuracy as compared to the single TCN or LSTM model, and its performance could improve by 63.6 % comparing to the traditional FFNN model. The developed hybrid model also exhibited a higher power prediction of WWTP effluent TN for the next multiple time steps within eight hours, as compared to the standalone TCN, LSTM, and FFNN models. Finally, employing model interpretation approach of Shapley additive explanation to identify the key parameters influencing the behavior of WWTP effluent water quality, it was found that removing variables that did not contribute to the model output could further improve modeling efficiency while optimizing monitoring and management strategies.

Comparison of economic benefits for the utilization of reclaimed resources from wastewater treatment plants: a case study in Beijing

Abstract The fate of resource recovery is significantly influenced by the standards of water quality and bio-dried excess sludge for various applications. These standards must be practically attainable while ensuring public and environmental health, safety, and economic advantages. The present study investigates a reclaimed wastewater treatment plant (WWTP) in Beijing that incorporates both reclaimed water utilization facility and bio-dried excess sludge treatment. The study elucidates the standards for reclaimed water quality and bio-dried excess sludge for diverse applications. Notably, reclaimed water demonstrates substantial market demand in terms of economic benefits. However, bio-dried excess faces challenges due to higher operational costs and lower TP content. The heat power of the WWTP effluent water source can not only be harnessed for the bio-drying process blowers but also be elevated air temperatures to expedite the bio-drying process.

Prediction of Wastewater Treatment Plant Effluent Water Quality Using Recurrent Neural Network (RNN) Models

Artificial Intelligence (AI) has recently emerged as a powerful tool with versatile applications spanning various domains. AI replicates human intelligence processes through machinery and computer systems, finding utility in expert systems, image and speech recognition, machine vision, and natural language processing (NLP). One notable area with limited exploration pertains to using deep learning models, specifically Recurrent Neural Networks (RNNs), for predicting water quality in wastewater treatment plants (WWTPs). RNNs are purpose-built for handling sequential data, featuring a feedback mechanism. However, standard RNNs may exhibit limitations in accommodating both short-term and long-term dependencies when addressing intricate time series problems. The solution to this challenge lies in adopting Long Short-Term Memory (LSTM) cells, known for their inherent memory management through a ‘forget gate’ mechanism. In general, LSTM architecture demonstrates superior performance. WWTP data represent a historical series influenced by fluctuating environmental conditions. This study employs simple RNNs and LSTM architecture to construct prediction models for effluent parameters, systematically assessing their performance through various training data scenarios and model architectures. The primary objective was to determine the most suitable WWTP dataset model. The study revealed that an epoch setting of 50 and a batch size of 100 yielded the lowest training time and root mean square error (RMSE) values for both RNN and LSTM models. Furthermore, when these models are applied to predict effluent parameters, they exhibit precise RMSE values for all parameters. The study results can be applied to detect potential upsets in WWTP operations.

Study of Adsorption Efficiency of Lignite, Biochar, and Polymeric Nanofibers for Veterinary Drugs in WWTP Effluent Water

The increased consumption, overuse, and subsequent difficult removal of pharmaceuticals using conventional processes lead to their rising prevalence in the environment. Adsorption belongs to the most efficient approaches to pharmaceuticals’ removal from wastewater. This study provides insight into the sorption properties of biochar, lignite, and polyamide nanofibers (PA-nanofibers) for sulfamethoxazole, trimethoprim, clarithromycin, azithromycin, and amoxicillin in ultrapure and wastewater treatment plant (WWTP) effluent water. The negative effect of WWTP effluent water was reflected in a reduction of the sorption capacity of biochar by 6.31–72.15%, 25.58–98.55% for lignite, and 4.21–67.71% for PA-nanofibers. Simultaneously, this study investigates the impact of the experimental setup. The sorption capacities were recorded in the range from 0.65 to 2.84 mg g−1 for biochar, 0.04 to 75.73 μg·g−1 for lignite, and 0.53 to 30.54 μg·g−1 for PA-nanofibers during the fixed-bed column tests with WWTP effluent water. Based on the results, biochar appears to be a suitable sorbent for selected pharmaceuticals in field conditions with running water. Lignite and PA represent complementary treatment technology or can act as a carrier for microbial degraders. Performed batch tests with ultrapure and WWTP effluent water and subsequent column tests highlighted the importance of conducting tests with the appropriate matrix and experimental setup to gain a realistic insight into the behavior of the sorbents under environmentally relevant conditions.Graphical

Performance of Pd/Sn catalysts supported by chelating resin prestoring reductant for nitrate reduction in actual water

Catalytic hydrogen reduction has appeared as a promising strategy for chemical denitrification with advantages of high activity and simple operation. However, the risk and low utilization of H2 is the disadvantage of catalytic hydrogen reduction. In recent years, catalytic reduction reactions in the presence of sodium borohydride (NaBH4) have been extensively studied. NaBH4 can be used as an electron source to generate electrons on the surface of the catalyst and can catalyze the reduction of pollutants. But it makes commercialization costly and causes significant environmental pollution if widely use NaBH4. In this study, we prepared supported Pd/Sn bimetallic nanoparticles which could adsorb NaBH4 during the preparation of the Pd/Sn bimetallic catalyst as the prestoring reductant. No additional reducing agent is required during nitrate reduction process. The performance and mechanism for nitrate reduction by using Pd/Sn bimetallic nanoparticles were discussed. Moreover, the catalyst D-Pd1/Sn1 reached a complete nitrate removal in the municipal wastewater treatment plant effluent water within 3 h. The results provide a prospect for denitrification in biological wastewater treatment plants.

Early and differential bacterial colonization on microplastics deployed into the effluents of wastewater treatment plants

Microbial colonization of microplastics (MPs) in aquatic ecosystems is a well-known phenomenon; however, there is insufficient knowledge of the early colonization phase. Wastewater treatment plant (WWTP) effluents have been proposed as important pathways for MPs entry and transport in aquatic environments and are hotspots of bacterial pathogens and antibiotic resistance genes (ARGs). This study aimed at characterizing bacterial communities in the early stage of biofilm formation on seven different types of MPs deployed in two different WWTPs effluents as well as measuring the relative abundance of two ARGs (sulI and tetM) on the tested MPs. Illumina Miseq sequencing of the 16S rRNA showed significant higher diversity of bacteria on MPs in comparison with free-living bacteria in the WWTP effluents. β-diversity analysis showed that the in situ environment (sampling site) and hydrophobicity, to a lesser extent, had a role in the early bacterial colonization phase. An early colonization phase MPs-core microbiome could be identified. Furthermore, specific core microbiomes for each type of polymer suggested that each type might select early attachment of bacteria. Although the tested WWTP effluent waters contained antibiotic resistant bacteria (ARBs) harboring the sulI and tetM ARGs, MPs concentrated ARBs harboring the sulI gene but not tetM. These results highlight the relevance of the early attachment phase in the development of bacterial biofilms on different types of MP polymers and the role that different types of polymers might have facilitating the attachment of specific bacteria, some of which might carry ARGs.

Leachates from Helophyte Leaf-Litter Enhance Nitrogen Removal from Wastewater Treatment Plant Effluents.

Bioengineering techniques are currently used in a wide variety of wastewater treatment systems. Aquatic plants (i.e.,helophytes)used in these techniques reduce excess nitrogen (N) from water column via assimilation. Moreover, leachates from plant leaf-litter can serve as an additional source of labile dissolved organic matter (DOM), which can promote aerobic respiration and N removal via denitrification. We tested the influence of leaf-litter leachates from Iris pseudacorus and Phragmites australis on the structure and activity of freshwater biofilms grown in flumes fed by effluent from a wastewater treatment plant (WWTP). The responses of the epilithic biofilm to the inputs of leaf-litter leachates were compared to those measured using a brewery byproduct rich in sugars and to the WWTP effluent water (i.e., control). All DOM sources significantly enhanced aerobic respiration and denitrification of the biofilm when compared to the controls, with increases in total microbial abundance but not in denitrifier abundance. The results suggest that metabolic activity of biofilms may be limited by bioavailability of DOM in WWTP effluent; and leaf-litter leachates of helophytes used in bioengineering techniques could alleviate this limitation by enhancing microbial N and C uptake.

A Novel Method to Characterise Levels of Pharmaceutical Pollution in Large-Scale Aquatic Monitoring Campaigns

Much of the current understanding of pharmaceutical pollution in the aquatic environment is based on research conducted in Europe, North America and other select high-income nations. One reason for this geographic disparity of data globally is the high cost and analytical intensity of the research, limiting accessibility to necessary equipment. To reduce the impact of such disparities, we present a novel method to support large-scale monitoring campaigns of pharmaceuticals at different geographical scales. The approach employs the use of a miniaturised sampling and shipping approach with a high throughput and fully validated direct-injection High-Performance Liquid Chromatography-Tandem Mass Spectrometry method for the quantification of 61 active pharmaceutical ingredients (APIs) and their metabolites in tap, surface, wastewater treatment plant (WWTP) influent and WWTP effluent water collected globally. A 7-day simulated shipping and sample stability assessment was undertaken demonstrating no significant degradation over the 1–3 days which is typical for global express shipping. Linearity (r2) was consistently ≥0.93 (median = 0.99 ± 0.02), relative standard deviation of intra- and inter-day repeatability and precision was <20% for 75% and 68% of the determinations made at three concentrations, respectively, and recovery from Liquid Chromatography Mass Spectrometry grade water, tap water, surface water and WWTP effluent were within an acceptable range of 60–130% for 87%, 76%, 77% and 63% of determination made at three concentrations respectively. Limits of detection and quantification were determined in all validated matrices and were consistently in the ng/L level needed for environmentally relevant API research. Independent validation of method results was obtained via an interlaboratory comparison of three surface-water samples and one WWTP effluent sample collected in North Liberty, Iowa (USA). Samples used for the interlaboratory validation were analysed at the University of York Centre of Excellence in Mass Spectrometry (York, UK) and the U.S. Geological Survey National Water Quality Laboratory in Denver (Colorado, USA). These results document the robustness of using this method on a global scale. Such application of this method would essentially eliminate the interlaboratory analytical variability typical of such large-scale datasets where multiple methods were used.

Influencing factors on the removal of pharmaceuticals from water with micro-grain activated carbon

The removal efficiency of 6 micro-grain AC (μGAC) was examined for 23 selected pharmaceutical compounds, usually found at trace level in municipal wastewater treatment plant (WWTP) effluents. Two different sets of experiments were carried out using distilled water and a real WWTP secondary effluent in order to understand the adsorption mechanisms of pharmaceuticals, including the role of the presence of background organic matter. Physical and chemical properties of μGACs and target pollutants were checked for their potential to predict the pharmaceutical removal. Textural properties of μGACs, and especially the mesopore volume, seemed to play the most important role during the adsorption without background organic matter whereas the chemistry of the μGACs, such as the presence of surface oxygen groups and the point of zero charge, could have more influence in the experiments with WWTP effluent water. Positively charged molecules are better adsorbed due to the influence of the background organic matter and the presence of oxygenated groups in the surface of the μGACs. The UV254 removal correlated well with the pharmaceutical removal and it is confirmed as an indicator to control the performance of pharmaceuticals adsorption with μGACs in tertiary treatment.

Pharmaceuticals in Wastewater Treatment Plant Effluent Waters

Pharmaceuticals in Wastewater Treatment Plant Effluent Waters

Biomass production and nutrient removal by Chlorella sp. as affected by sludge liquor concentration

The use of microalgae for biomass production and nutrient removal from the reject water produced in the dewatering process of anaerobically digested sludge, sludge liquor, was investigated. The sludge liquor was characterized by a high content of total suspended solids (1590 mg L−1), a high nitrogen concentration (1210 mg L−1), and a low phosphorus concentration (28 mg L−1). Chlorella sp. was grown in sludge liquor diluted with wastewater treatment plant effluent water to different concentrations (12, 25, 40, 50, 70, and 100%) using batch mode. The environmental conditions were 25 °C, a continuous lightning of 115 μmol m−2 s−1, and a CO2 concentration of 3.0%. The highest biomass production (0.42–0.45 g dry weight L−1 Day−1) was achieved at 40–50% sludge liquor, which was comparable to the production of the control culture grown with an artificial fertilizer. The biomass production was 0.12 and 0.26 g dry weight L−1 Day−1 at 12% and 100% sludge liquor, respectively. The percentage of nitrogen in the algal biomass increased from 3.6% in 12% sludge liquor and reached a saturation of ∼10% in concentrations with 50% sludge liquor and higher. The phosphorus content in the biomass increased linearly from 0.2 to 1.5% with increasing sludge liquor concentrations. The highest nitrogen removal rates by algal biosynthesis were 33.6–42.6 mg TN L−1 Day−1 at 40–70% sludge liquor, while the highest phosphorus removal rates were 3.1–4.1 mg TP L−1 Day−1 at 50–100% sludge liquor.

Comparative analysis of effluent water quality from a municipal treatment plant and two on-site wastewater treatment systems

Though decentralized on-site technologies are extensively employed for wastewater treatment around the globe, an understanding of effluent water quality impairments associated with these systems remain less understood than effluent discharges from centralized municipal wastewater treatment facilities. Using a unique experimental facility, a novel comparative analysis of effluent water quality was performed from model decentralized aerobic (ATS) and septic (STS) on-site wastewater treatment systems and a centralized municipal wastewater treatment plant (MTP). The ATS and STS units did not benefit from further soil treatment. Each system received common influent wastewater from the Waco, Texas, USA Metropolitan Area Regional Sewerage System. We tested the hypothesis that MTP effluent would exhibit higher water quality than on-site effluents, based on parameters selected for study. A tiered testing approach was employed to assess the three effluent discharges: select routine water quality parameters (Tier I), whole effluent toxicity (Tier II), and select endocrine-active compounds (Tier III). Contrary to our hypothesis, ATS effluent was not statistically different from MTP effluents, based on Tier I and III parameters, but reproductive responses of Daphnia magna were slightly more sensitive to ATS than MTP effluents. STS effluent water quality was identified as most degraded of the three wastewater treatment systems. Parameters used to assess centralized wastewater treatment plant effluent water quality such as whole effluent toxicity and endocrine active substances appear useful for water quality assessments of decentralized discharges. Aerobic on-site wastewater treatment systems may represent more robust options than traditional septic systems for on-site wastewater treatment in watersheds with appreciable groundwater – surface water exchange.

Multi-residue Screening Method To Quantify Mycotoxins in Aqueous Environmental Samples

Mycotoxins are naturally occurring secondary metabolites of fungi colonizing agricultural products on the field or during storage. In earlier work, we have shown that two common mycotoxins, i.e., zearalenone and deoxynivalenol, can be present at significant levels in the aquatic environment. This raises the question about the relevance of a wider range of mycotoxins in natural waters. In this investigation, we present the first validated method for analysis of some additional 30 mycotoxins in drainage, river, and wastewater treatment plant effluent water. The method includes solid-phase extraction over Oasis HLB cartridges, followed by liquid chromatography with electrospray ionization triple quadrupole mass spectrometry. Absolute method recoveries for 13 of the 33 mycotoxins were higher than 70% in wastewater treatment plant effluent (at 25 ng/L), and 27 compounds had method detection limits (MDLs) below 10 ng/L. The applicability of this method is illustrated with selected data from our ongoing monitoring campaigns. Specifically and for the first time, beauvericin and nivalenol were quantified in drainage and river water samples with mean concentrations of 6.7 and 4.3 ng/L and 6.1 and 5.9 ng/L, respectively. These compounds thus add to the complex mixture of natural and anthropogenic micropollutants in natural waters, where their ecotoxicological risk remains to be evaluated.

Determination of estrogens in water by HPLC–UV using cloud point extraction

A method based on cloud point extraction was developed to determine four kinds of estrogens: estriol (E3), estradiol (E2), estrone (E1), and progesterone (P) in water by high performance liquid chromatography separation and ultraviolet detection (HPLC–UV). The non-ionic surfactant Triton X-114 was chosen as extractant solvent. The parameters affecting extraction efficiency, such as concentrations of Triton X-114 and Na 2SO 4, equilibration temperature, equilibration time and centrifugation time were evaluated and optimized. Under the optimum conditions, preconcentration factors of 99 for E3, 73 for E2, 152 for E1 and 86 for P were obtained for 10 mL water sample. The detection of limitation was 0.23 ng mL −1 for E3, 0.32 ng mL −1 for E2, 0.25 ng mL −1 for E1 and 5.0 ng mL −1 for P. The proposed method was successfully applied to the determination of trace amount of estrogens in wastewater treatment plant (WWTP) effluent water and exposure water with 10 ng mL −1 E2 for toxicological study in our lab. For the case of WWTP effluent water samples, no estrogen was found. The accuracy of the proposed method was tested by recovery measurements of spiked samples and good recoveries of 81.2–99.5% were obtained.