Conditions In Wastewater Treatment Plants Research Articles

Investigation of pharmaceutical bioaccumulation in Daphnia sp. living in a wastewater treatment plant

Non-steroidal anti-inflammatory drugs (NSAIDs) are among the most widely used pharmaceuticals. Their presence in natural waters is due to the low removal efficiency in conventional wastewater treatment plants (WWTPs). Interestingly, certain zooplankton species can survive the mixture of pollution and abnormal water conditions in WWTPs. In our study, for the first time, we tested the in-situ bioaccumulation of NSAIDs and their metabolites in Daphnia pulex, which were obtained in high numbers in one WWTP during the summer. It was found that diclofenac (DCF) and 4-hydroxy DCF were present in the studied clarifiers and ponds. Among these chemicals, only DCF was detected in daphnia. The bioaccumulation factor of DCF in daphnia was below 36 L kg−1ww and was lower than those obtained under experimental conditions for Daphnia magna. The tested daphnia adapted to chronic exposure to mixtures of drugs in μg L−1 level and could be implemented in biobased WWTPs. According to our data, there is a need to supplement the risk assessment of anthropogenic pollutants with in-situ cases to demonstrate the adaptation possibilities of wild-living organisms.

Energy efficiency assessment of wastewater treatment plants in China based on multiregional input–output analysis and data envelopment analysis

Wastewater treatment plants (WWTPs) play a pivotal role in natural water recycling and safeguarding the water security of approximately 42% of the world's population, yet they confront challenges posed by escalating energy consumption and regional energy constraints. In this study, we developed an evaluation framework that integrated regional energy scarcity with the operation conditions of WWTPs to quantify their energy efficiencies by applying multiregional input–output (MRIO) analysis and data envelopment analysis (DEA). A case study using this framework was conducted on 3776 WWTPs in 30 provinces in China. The results showed that the average scarcity-based energy efficiency level of WWTPs in China was low, of which those in northern provinces were higher compared to southeastern provinces. Furthermore, only 24 WWTPs in China attained the highest efficiency levels, while the rest had different degrees of input redundancy, indicating an energy-saving potential of 9.05 × 109 kWh. This paper enables the development of optimal efficiency strategies for WWTPs in different provinces considering the potential energy scarcity risks caused by trading activities.

Exposure of the static magnetic fields on the microbial growth rate and the sludge properties in the complete-mix activated sludge process (a Lab-scale study)

BackgroundIn this study, the effect of static magnetic fields (SMFs) on improving the performance of activated sludge process to enhance the higher rate of microbial growth biomass and improve sludge settling characteristics in real operation conditions of wastewater treatment plants has been investigated. The effect of SMFs (15 mT), hydraulic retention time, SRT, aeration time on mixed liquor suspended solids (MLSS) concentrations, mixed liquor volatile suspended solids (MLVSS) concentrations, α-factor, and pH in the complete-mix activated sludge (CMAS) process during 30 days of the operation, were evaluated.ResultsThere were not any differences between the concentration of MLSS in the case (2148.8 ± 235.6 mg/L) and control (2260.1 ± 296.0 mg/L) samples, however, the mean concentration of MLVSS in the case (1463.4 ± 419.2 mg/L) was more than the control samples (1244.1 ± 295.5 mg/L). Changes of the concentration of MLVSS over time, follow the first and second-order reaction with and without exposure of SMFs respectively. Moreover, the slope of the line and, the mean of α-factor in the case samples were 6.255 and, − 0.001 higher than the control samples, respectively. Changes in pH in both groups of the reactors were not observed. The size of the sluge flocs (1.28 µm) and, the spectra of amid I' (1440 cm−1) and II' (1650 cm−1) areas related to hydrogenase bond in the case samples were higher than the control samples.ConclusionsSMFs have a potential to being considered as an alternative method to stimulate the microbial growth rate in the aeration reactors and produce bioflocs with the higher density in the second clarifiers.

Comparative Analysis of Greenhouse Gas Emissions from Domestic Wastewater Treatment Processes by Modeling: Existing Estimation Methods vs Modeling

This study examined the existing methodologies and the applicability of process modeling concerning the estimation of nitrous oxide (N<sub>2</sub>O) emissions from wastewater treatment processes. The method of extimating N<sub>2</sub>O emissions from wastewater occurring during biological nitrification and denitrification processes can be divided into those before and after legal nitrogen effluent quality enhancement for domestic wastewater treatment plant. Initial IPCC guidelines such as IPCC 1996 GL, GPG 2000, and IPCC 2006 GL, provided methods for estimating N<sub>2</sub>O emissions throughout domestic wastewater, while the revised version, IPCC 2019 RF, proposed methods for estimating each N<sub>2</sub>O emission by distinguishing wastewater treatment and effluent after the advancement of wastewater treatment plants. The National Greenhouse Gas Inventory Report (NIR) in Korea adopted the methodology of GPG 2000, and the Emissions Trading System (ETS) applies the estimation method of IPCC 2006 GL in the wastewater treatment plants. This study utilized process modeling to consider the process characteristics and operating conditions of wastewater treatment plants. IPCC, NIR, and ETS estimate N<sub>2</sub>O emissions based on nitrogen behavior activity data and emissions factors. On the other hand, process modeling estimates N<sub>2</sub>O emissions in each unit process of the wastewater treatment plant using a 4-step AOB nitrification/4-step denitrification model and a liquid/gas transfer model. The estimation results of N<sub>2</sub>O emissions from modeling method were compared with the estimation results of IPCC, NIR, and ETS to analyze the suitability of the estimation method. Through this, it was evaluated how appropriate process modeling is for estimating N<sub>2</sub>O emissions in domestic wastewater treatment plants.

Activity- and gene-based quantification of enteric viruses, F- specific RNA phage genogroups, pepper mild mottle virus, and Escherichia coli in surface water

Polymerase chain reaction (PCR) is widely applied for the monitoring of pathogenic viruses in water environments. To date, several pretreatments to selectively detect genes from infectious viruses via PCR have been developed. This study was aimed to characterize and validate methods for quantifying active viruses and indicators and to evaluate the proportion of their active fractions in surface water (n = 42). Active E. coli and F-specific RNA phage (FRNAPH) genogroups were quantified using culture assays. In addition to these microbes, norovirus genogroups I (GI) and II, Aichi virus 1, and pepper mild mottle virus (PMMoV) were quantified by (reverse transcription)-quantitative PCR (RT-qPCR) with and without cis-dichlorodiammineplatinum (CDDP) treatment to exclude genes in inactive viruses. CDDP-RT-qPCR showed concentrations and detection frequencies comparable to or higher than culture assays. Consequently, although CDDP-RT-qPCR can suggest the presence of an inactive virus, it can also overestimate the activity of the virus in the environment. Differences between culture and CDDP-RT-qPCR and between CDDP-RT-qPCR and RT-qPCR varied among the viruses. CDDP-RT-qPCR showed a concentration comparable to the culture assay (within 1 log10 difference) in 93 % of positive samples for GI-FRNAPH but in <63 % of positive samples for GII- and GIII-FRNAPHs. GII-NoV was detected from 5 and 30 out of 42 samples via CDDP-RT-qPCR and RT-qPCR, respectively, and was suggested as inactivated by 2.0 log10 or higher in most of the samples. By contrast, concentrations of PMMoV determined by these two assays were not notably different. It is suggested that the operational conditions of wastewater treatment plants around the sites, rather than environmental stresses, affected the microbial inactivation. To better understand the infectivity of viruses in the environment, it is important to investigate them using sensitive detection methods at various sites, including the source of contamination.

The Uptake of Engineered Nanoparticles by Sludge Particulates

The aim of the study was to understand the removal characteristics of engineered nanoparticles (ENP) from sludge treatment processes in wastewater treatment plants (WWTP). Removal of ENP (TiO2, ZnO) was tested on primary and secondary sludge, using differential sedimentation experiments to quantify the attachment of ENP to sludge particulates. To better understand the attachment characteristics, aquatic conditions such as mixed liquid suspended solid concentration, and Ionic strength of the wastewater, were varied to replicate different field conditions of WWTPs. Results showed different degrees of multilayer attachment to sludge surfaces based on the experimental conditions. To verify the effect of ENP surface characters with the sludge attachment, SiO2, ZnO, and TiO2 were tested, showing SiO2 with the highest amount of attachment regardless of its surface charge. With the variation of sludge concentration, up to four degrees of magnitude in sorption was observed. Salt concentrations also showed high impacts on the sorption, where the sorption is decreased by half when doubling the salt concentration. The findings of the current research may aid in understanding the fate of engineered nanoparticles in wastewater treatment plants.

Application of Multispectral Images from Unmanned Aerial Vehicles to Analyze Operations of a Wastewater Treatment Plant

The main task of a wastewater treatment plant (WWTP) is to reduce pollutants that adversely affect the receiving environment in which the effluent is discharged. The operation of a WWTP is a complex task due to the number of different processes that take place in its process facilities. In order to maintain the high efficiency of a WWTP, it is necessary to control the quality of the effluent at the outlet and monitor the processes taking place there. The main objective of the research presented in this study was to evaluate the possibility of using unmanned aerial vehicle (UAV) technology and multispectral images acquired with a Micasense Red-Edge MX camera to analyse the performance of an activated sludge bioreactor using the example of a municipal WWTP in Poland. Remote sensing analyses were carried out to check the relationships between the calculated spectral indices and the quality parameters in the bioreactor. The spectral indices assessed were the normalised difference vegetation index (NDVI), green normalised difference vegetation index (GNDVI), optimised soil adjusted vegetation index (OSAVI), and their derived indices, after substitution of the red or near-infrared channel with the red edge channel. In this study, the sensitivity of the NDVI and GNDVIRED-EDGE indexes to changes in the nutrient content (NUC) of the bioreactor was observed. The presented research may find application in the design of a new soft sensor for monitoring the operating conditions of wastewater treatment plants.

China's enhanced urban wastewater treatment increases greenhouse gas emissions and regional inequality

Sustainable water pollution control requires understanding of historical trajectories and spatial characteristics of greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs), which remains inadequately studied. Here, we establish plant-level monthly operational emissions inventories of China's WWTPs in 2009–2019. We show that urban wastewater treatment has been enhanced with 80% more chemical oxygen demand being removed annually. However, this progress is associated with 180% more GHG emissions at the national level, up to 58.3 Mt CO2 eq in 2019. We found significant seasonality in GHG emissions. Increasing sludge yield and electricity intensity became primary drivers after 2015 because of stricter standards, causing GHG emissions increase 12.9 and 8.3% until 2019. GHG emissions from urban wastewater treatment show high spatial difference at province, city and plant levels, with different sludge disposal and energy mix approaches combined with different influent and effluent conditions in WWTPs across China. Stricter effluent standard resulted in similar GHG emissions growth pattern in cities. We argue WWTPs focus on resource recovery in developed areas and higher operational efficiency in developing areas.

Sustainable Energy Management Benchmark at Wastewater Treatment Plant

Urban wastewater effluents bring large amounts of nutrients, organic matter, and organic microcontaminants into freshwater ecosystems. Ensuring the quality of wastewater treatment (WWT) is one of the main challenges facing the management of wastewater treatment plants (WWTPs). However, achievement of high-quality standards leads towards significant energy consumption: usually the more intensive WWT process requires additional energies. Energy efficiency at WWTP is actual mainstream on the current sustainable development agenda. The WWTP processes and methods can be considered from the standpoint of material and energy flows according to circular economy paradigm, which offers great possibilities to reuse waste originating from WWT in order to receive renewable energy. The correlation between energy and quality issues to evaluate WWTP efficiency is of a great scientific and practical interest. The main goal of the paper is to check the dependency between these two main issues in WWTP management—WWT quality and energy efficiency—and to determine possible limits of such relation. The municipal sewerage system of Ekaterinburg, Russia was studied within this paper. The total length of centralized sewerage system in Ekaterinburg is over 1500 km of pipes within two main sewerage basins: northern and southern. The methodological framework for the current research consisted of three steps: (i) WWT quality evaluation, (ii) energy efficiency evaluation, and (iii) WWTP Quality/Energy (Q/E) efficiency dependency matrix. For the purpose of research, authors investigated the 2015–2018 period. The results showed that the outputs correlate with the technical conditions of WWTPs and the implementation of the best available techniques (BATs): most of the northern WWTP values are referred to the green zone (good rank), while the southern WWTP values are situated generally in the orange zone (unsatisfactory rank). The proposed methodological approach for Q/E dependency of WWT process creates a strong but simple tool for managers to evaluate the current success of the operation of WWTP and progress towards circular economy practices implementation.

Optimization of TiO2-P25 photocatalyst dose and H2O2 concentration for advanced photo-oxidation using smartphone-based colorimetry.

Color images taken by a smartphone camera were used to estimate the rate of advanced photo-oxidation reaction of Direct Red 23 (DR23) azo dye as a model organic pollutant. The red, green, blue color coordinates were tested to quantify the dye. Images of the reaction mixture were taken at specified intervals to obtain kinetic lines and reaction rate constants. Both the reaction rate constant and the final degree of degradation were plotted as functions of the photocatalyst dose and the concentration of H2O2. The smartphone measurements are fully consistent with the reference spectrophotometry data. The maximum degradation efficiency of the DR23 dye was recorded at C0(H2O2) = 2.5 mM and photocatalyst dose equal to 1.0 mg/L. Higher H2O2 concentrations reduce the degradation rate as a result of the side reaction of H2O2 with OH radicals. A two-factor experimental design was used to study the effects of photocatalyst dose and H2O2 concentration with five and seven levels, respectively. The analysis of variance results indicated that the concentration of H2O2 had the greater influence. The smartphone provides quick and easy measurement of the photodegradation rate directly in the solutions without sampling. The proposed approach can be applied under field conditions in wastewater treatment plants.

Modelling atmospheric emissions from wastewater treatment plants: Implications of land-to-water roughness change

Atmospheric emissions from passive liquid surfaces, such as wastewater treatment plants (WWTP), are common sources of impacts to the environment and to the health of communities, due to odours, greenhouse gases and other air pollutants. Emission models have been broadly employed for assessing these emissions, with the wind friction velocity (u∗) being a key variable. The usual practice in the context of WWTP is to parametrise u∗ based on reference wind speeds measured over the land, without considering the internal boundary layer (IBL) development due to the change in aerodynamic roughness as the wind blows from the land to the liquid surface, nor the stability of the wind flow. The potential consequences of these conceptual inconsistencies are major knowledge gaps in emission modelling. Addressing these, a customised computation was implemented to couple the wind friction parametrisation with the evolution of the IBL downwind of the land-to-water roughness change. A sensitivity analysis with different emission models, considering ranges of fetch, wind speed and surface roughness encompassing typical conditions in WWTP, showed that not incorporating the roughness change leads to systematic overestimation of u∗ and the overall mass transfer coefficient KL for two compounds analysed (liquid phase and gas phase-controlled volatilisation). A modelling approach was devised, comprising the u∗ parametrisation that incorporate the roughness change combined with the Prata-Brutsaert emission model and alternative calculation of the gas-side mass transfer coefficient kG from local IBL variables. Evaluation against experimental data and physical considerations support the adoption of this approach for modelling the volatilisation of compounds from passive liquid surfaces in WWTP. A simplified equation to approximate u∗ after a change in roughness is presented, which can be used for quick emission modelling of liquid phase-controlled compounds. Furthermore, a preliminary exploration demonstrated that the effects of atmospheric stability on the response of u∗ to the land-to-water roughness change can be substantial under certain conditions.

Characterization of Environmental and Cultivable Antibiotic-Resistant Microbial Communities Associated with Wastewater Treatment.

Bacterial resistance to antibiotics is a growing global concern, threatening human and environmental health, particularly among urban populations. Wastewater treatment plants (WWTPs) are thought to be “hotspots” for antibiotic resistance dissemination. The conditions of WWTPs, in conjunction with the persistence of commonly used antibiotics, may favor the selection and transfer of resistance genes among bacterial populations. WWTPs provide an important ecological niche to examine the spread of antibiotic resistance. We used heterotrophic plate count methods to identify phenotypically resistant cultivable portions of these bacterial communities and characterized the composition of the culturable subset of these populations. Resistant taxa were more abundant in raw sewage and wastewater before the biological aeration treatment stage. While some antibiotic-resistant bacteria (ARB) were detectable downstream of treated wastewater release, these organisms are not enriched relative to effluent-free upstream water, indicating efficient removal during treatment. Combined culture-dependent and -independent analyses revealed a stark difference in community composition between culturable fractions and the environmental source material, irrespective of culturing conditions. Higher proportions of the environmental populations were recovered than predicted by the widely accepted 1% culturability paradigm. These results represent baseline abundance and compositional data for ARB communities for reference in future studies addressing the dissemination of antibiotic resistance associated with urban wastewater treatment ecosystems.

Technology for biological treatment of urban wastewater and sludge treatment with deep removal of nitrogen and phosphorus

This article is dedicated to increasing of removing of nitrogen and phosphorus in DENIFO technology, and the removing of phosphorus by reagents. Removal of nitrogen and phosphorus from municipal wastewater prevents eutrophication of open water, which has become a global problem. A list of conditions that provide maximum efficiency of the processes of wastewater treatment and sludge treatment is completed. Functions of primary settlers, air tanks (based on technology DENIFO), and secondary settlers is reviewed. Pre-denitrification of the returned active sludge with the partial flow of waste water improves anaerobiosis in the anaerobic zone of biological block, and promotes intensive dephosphorization. The work was made under normal conditions of wastewater treatment plant. Unfavorable periods (snowmelt, torrential rains, floods) are not taken into consideration. Mathematical equations are made for the average flow of wastewater during dry weather. Combined dehydratation of the sludge and sediments (the long stay in the tank) leads to rapid displacement phosphorus phosphate to drain water, and a corresponded increase the content of phosphorus in the treated water. Also recommendations for changing the operating mode of the block of sludge treatment given. The important results included in article was taken on the really functioned wastewater treatment plants of Saint Petersburg. This work is aimed at a comprehensive assessment, development and improvement of technology of removing nitrogen and phosphorus from municipal wastewater, including from secondary pollution coming from the return flow from the sludge treatment units.

WHAT IS HIDDEN BEHIND ACTIVATED SLUDGE SUPERNATANT? FLUORESCENT STAINING AND LASER GRANULOMETRY INVESTIGATION SUPPORTED BY MACHINE LEARNING

Studies on the biological composition of activated sludge flocs in the operating conditions of wastewater treatment plants are generally limited to the estimation of respiratory activity or to the analysis of images made with optical microscopy. The results of these studies indirectly provide information on the microbiological composition. To date, molecular methods, although very promising, have not found a wider application in operational monitoring of wastewater treatment plants. In this paper, the supernatant was under discussion as a potential source of sampling for analyzing microbial quality changes. The results of 270 activated sludge and treated wastewater samples showed that the smallest flocs leaching to the outflow constitute a group of microorganisms that is most numerous. The studies carried out using the fluorescence in situ hybridization method have shown that the microorganisms responsible for the nitrification processes occur both in activated sludge and supernatant. Image analysis of microorganisms from activated sludge and supernatant stained with Live/DEAD reagent indicate that microflocs and bacteria in the outer flocs, which are relatively loosely attached to the flocculent matrix are more exposed to external factors. The results suggest that it is advisable to find information about the condition of the whole community especially for group of particles in the supernatant. In addition, the authors recommend using machine learning methods to evaluate predicting anomalies in biological composition of activated sludge flocs.

Study of Industrial Black Water Treatment Plant Installation Planning System Based on Sewage Treatment Plant

Wastewater in general is water, in general, is a liquid that comes from households, industries, or other public places that usually contain materials or substances that can endanger human life and disturb the environment. Quid comes from households, industries, or other public places that usually contain materials or substances that can endanger human life and disturb the environment. This study to plan, analyze, and assess the performance conditions of wastewater treatment plants (IPAL) at PT XYZ Bekasi Regency on environmental quality standards. Data and information used are data on the amount of wastewater, sources of wastewater, and behavior of water use as well as secondary data in the form of data that the authors surveyed directly at the research location. The processing method of the output value of WWTP uses the research method of the laboratories from the research method in which the output value exceeds the quality standard of LHK Regulation No. 68 the Year 2016 and has exceeded its planning capacity. And what is identified is not safe. An alternative solution to the problem of unsafe output values ??is by planning a new wastewater treatment plant.

Optimization and scale-up of an LED-illuminated microalgal photobioreactor for wastewater treatment.

The use of light-emitting diode (LED)-illuminated photobioreactors with microalgae has been extensively studied for wastewater treatment. Most studies have used isolated microalgae species; however, this practice does not match the reality of conditions in wastewater treatment plants. Operational conditions that promote greater growth of algal biomass and that remove pollutants most effectively are disputed in the literature. In this context, LED-illuminated photobioreactors with microalgae were evaluated using multivariate analysis in order to optimize removal of pollutants (nitrogen, phosphorus, and carbonaceous organic matter). Three variables were evaluated: operating time, LED wavelength, and luminous flux intensity. A microalgae consortium was used in the photobioreactor. In addition to the LED-illuminated photobioreactors, control photobioreactors illuminated by sunlight were also operated. Using the results obtained in the optimization, a scaled-up reactor approximately 8.5 times larger in volume was operated to evaluate if the behavior would be maintained. The best operational conditions for the removal of pollutants were observed in LED-illuminated photobioreactors operated under a light intensity of 700 μmol·m-2s-1 for 15 days. Under these conditions, it was possible to remove 89.97% of carbonaceous organic matter, 86.50% of nitrogen, and 30.64% of phosphorus. The scaled-up photobioreactor operated with similar performance.

Rapid removal of acesulfame potassium by acid-activated ferrate(VI) under mild alkaline conditions

Acesulfame potassium (ACE) is a widely used artificial sweetener that has consistently been detected in wastewater and surface waters. The high-valent iron-based green oxidant known as ferrate(VI) (potassium ferrate(VI); Fe(VI)) had low reactivity with ACE (i.e. 4 h (or 240 min) contact time removed only ∼ 67% ACE) at a molar ratio of 6.0 ([Fe(VI)]:[ACE]). Comparatively, it took 60 s (or 1 min) to remove ∼94% ACE when HCl (786 μM) was added to a mixture of Fe(VI)-ACE at the same molar ratio of 6.0 (or acid-activated Fe(VI)). Significantly, the final pH (i.e. 7.6–8.1) was similar for Fe(VI) and acid-activated Fe(VI). An empirical model using response surface methodology was developed that could describe reasonably well the removal efficiency of ACE. Inorganic constituents of wastewater (Cl−, Na+, Ca2+, and Mg2+) had no significant effect on the oxidation of ACE by acid-activated Fe(VI). The degradation efficiency of ACE decreased in the presence of 10 mg/L of natural organic matter (NOM) but remained unchanged at 5 mg NOM/L. Sulfamic acid as the oxidized product of ACE was identified by liquid chromatography high resolution mass spectrometry method. Reaction pathways include ring opening of ACE through hydrolytic transformation. Acid-activated Fe(VI) has advantage of rapid removal of ACE under mild alkaline conditions of wastewater treatment plants compared to other oxidation processes such as chlorination, ozonation, and light-based processes.

The Proteome of Tetrasphaera elongata is adapted to Changing Conditions in Wastewater Treatment Plants.

The activated sludge in wastewater treatment plants (WWTP) designed for enhanced biological phosphorus removal (EBPR) experiences periodically changing nutrient and oxygen availability. Tetrasphaera is the most abundant genus in Danish WWTP and represents up to 20–30% of the activated sludge community based on 16S rRNA amplicon sequencing and quantitative fluorescence in situ hybridization analyses, although the genus is in low abundance in the influent wastewater. Here we investigated how Tetrasphaera can successfully out-compete most other microorganisms in such highly dynamic ecosystems. To achieve this, we analyzed the physiological adaptations of the WWTP isolate T. elongata str. LP2 during an aerobic to anoxic shift by label-free quantitative proteomics and NMR-metabolomics. Escherichia coli was used as reference organism as it shares several metabolic capabilities and is regularly introduced to wastewater treatment plants without succeeding there. When compared to E. coli, only minor changes in the proteome of T. elongata were observed after the switch to anoxic conditions. This indicates that metabolic pathways for anaerobic energy harvest were already expressed during the aerobic growth. This allows continuous growth of Tetrasphaera immediately after the switch to anoxic conditions. Metabolomics furthermore revealed that the substrates provided were exploited far more efficiently by Tetrasphaera than by E. coli. These results suggest that T. elongata prospers in the dynamic WWTP environment due to adaptation to the changing environmental conditions.

The use of respirometry as a tool for the diagnosis of waste water treatment plants. A real case study in Southern Spain

The influence of operating conditions of wastewater treatment plants in microbial composition of activated sludge should be controlled to evaluate the efficiency of the plant. Respirometry has been widely applied as a useful tool for a better understanding of the processes taking place in activated sludge system. In the present study, respirometry tests have provided relevant information about possible faults in the plant and potential improvements. With this aim, experimental tests were applied to a real wastewater treatment plant serving an equivalent population of 730,000. To evaluate the sludge activated process, the samples of mixed liquor studied were: those collected from inlet and outlet flow of reactor system and the laboratory prepared samples from mixing those from the influent/effluent wastewater to/from reactor with the returned activated sludge. The comparison of reference values with experimental results of factor charge (0.9–1.5), organic loading rate (>0.5 gBODgMLVSS−1 d−1) and specific oxygen uptake rate in mixed liquor for outlet samples from reactor (mainly > 10 mgO2 g-1 h−1) obtained from respirometry tests revealed that the plant was operated at low efficiency and at overload. These conditions have a direct influence on the efficiency of biological treatment and the secondary clarifier operation. The sedimentation of activated sludge was evaluated through the determination of the sludge volume index during 10 months obtaining an average value of 208 mL g−1. Respirometry tests also revealed that the decrease of biomass activity was associated with the wastewater instead of with the biomass.

Monitoring Influent Conditions of Wastewater Treatment Plants by Nonlinear Data-Based Techniques

To operate wastewater treatment plants (WWTPs) with optimized efficiency, influent conditions (ICs) as initial states of inflow fed to WWTPs were monitored to identify potential anomalies that would trigger adverse events or system crash. To employ voluminous measurements for data-driven decisions, the non-linear, non-Gaussian, non-stationary, auto-correlated, cross-correlated, hetero-skedastic, case-specific nature of multivariate environmental datasets must be considered. This research proposed kernel machine learning models, the kernel principal components analysis based one-class support vector machine (KPCA-OCSVM) with various kernels, to learn anomaly-free training set then classify the testing set. A seven-years multivariate ICs time series was introduced with exploratory analysis performed to reveal temporal behaviors and statistical properties. KPCA with polynomial kernels sufficiently output representative features, based on which OCSVM with Gaussian kernels sensitively and specifically identified anomalies in ICs that were previously omitted by WWTP operators. The proposed kernel algorithms surpassed previous linear PCA-based K-nearest-neighbors models, and improved outcomes with limited increase in computation cost. Without requiring linear, Gaussian, stationary, independent, and homo-skedastic qualities from data, the proposed flexible environmental data science approach could be transferred, rebuilt, and tuned conveniently for ICs from different WWTPs.