Strategies for achieving energy neutrality in biological nutrient removal systems - a case study of the Slupsk WWTP (northern Poland)

Insights into current bio-processes and future perspectives of carbon-neutral treatment of industrial organic wastewater: A critical review

With the rise of the concept of carbon neutrality, the current wastewater treatment process of industrial organic wastewater is moving towards the goal of energy conservation and carbon emission reduction. The advantages of anaerobic digestion (AD) processes in industrial organic wastewater treatment for bio-energy recovery, which is in line with the concept of carbon neutrality. This study summarized the significance and advantages of the state-of-the-art AD processes were reviewed in detail. The application of expanded granular sludge bed (EGSB) reactors and anaerobic membrane bioreactor (AnMBR) were particularly introduced for the effective treatment of industrial organic wastewater treatment due to its remarkable prospect of engineering application for the high-strength wastewater. This study also looks forward to the optimization of the AD processes through the enhancement strategies of micro-aeration pretreatment, acidic-alkaline pretreatment, co-digestion, and biochar addition to improve the stability of the AD system and energy recovery from of industrial organic wastewater. The integration of anaerobic ammonia oxidation (Anammox) with the AD processes for the post-treatment of nitrogenous pollutants for the industrial organic wastewater is also introduced as a feasible carbon-neutral process. The combination of AnMBR and Anammox is highly recommended as a promising carbon-neutral process for the removal of both organic and inorganic pollutants from the industrial organic wastewater for future perspective. It is also suggested that the AD processes combined with biological hydrogen production, microalgae culture, bioelectrochemical technology and other bio-processes are suitable for the low-carbon treatment of industrial organic wastewater with the concept of carbon neutrality in future.

Application of Machine Learning Methods for an Analysis of E-Nose Multidimensional Signals in Wastewater Treatment

The work represents a successful attempt to combine a gas sensors array with instrumentation (hardware), and machine learning methods as the basis for creating numerical codes (software), together constituting an electronic nose, to correct the classification of the various stages of the wastewater treatment process. To evaluate the multidimensional measurement derived from the gas sensors array, dimensionality reduction was performed using the t-SNE method, which (unlike the commonly used PCA method) preserves the local structure of the data by minimizing the Kullback-Leibler divergence between the two distributions with respect to the location of points on the map. The k-median method was used to evaluate the discretization potential of the collected multidimensional data. It showed that observations from different stages of the wastewater treatment process have varying chemical fingerprints. In the final stage of data analysis, a supervised machine learning method, in the form of a random forest, was used to classify observations based on the measurements from the sensors array. The quality of the resulting model was assessed based on several measures commonly used in classification tasks. All the measures used confirmed that the classification model perfectly assigned classes to the observations from the test set, which also confirmed the absence of model overfitting.

Modeling nutrient removal and energy consumption in an advanced activated sludge system under uncertainty

Activated sludge models are widely used to simulate, optimize and control performance of wastewater treatment plants (WWTP). For simulation of nutrient removal and energy consumption, kinetic parameters would need to be estimated, which requires an extensive measurement campaign. In this study, a novel methodology is proposed for modeling the performance and energy consumption of a biological nutrient removal activated sludge system under sensitivity and uncertainty. The actual data from the wastewater treatment plant in Slupsk (northern Poland) were used for the analysis. Global sensitivity analysis methods accounting for interactions between kinetic parameters were compared with the local sensitivity approach. An extensive procedure for estimation of kinetic parameters allowed to reduce the computational effort in the uncertainty analysis and improve the reliability of the computational results. Due to high costs of measurement campaigns for model calibration, a modification of the Generalized Likelihood Uncertainty method was applied considering the location of measurement points. The inclusion of nutrient measurements in the aerobic compartment in the uncertainty analysis resulted in percentages of ammonium, nitrate, ortho-phosphate measurements of 81%, 90%, 78%, respectively, in the 95% confidence interval. The additional inclusion of measurements in the anaerobic compartment resulted in an increase in the percentage of ortho-phosphate measurements in the aerobic compartment by 5% in the confidence interval. The developed procedure reduces computational and measurement efforts, while maintaining a high compatibility of the observed data and model predictions. This enables to implement activated sludge models also for the facilities with a limited availability of data.

The Influence of Co-Fermentation of Agri-Food Waste with Primary Sludge on Biogas Production and Composition of the Liquid Fraction of Digestate

Energy self-sufficiency is a current trend in wastewater treatment plants. This effect can be achieved by increasing the production of electricity from biogas and by reducing energy consumption for technological processes. One idea, in line with the circular economy concept, is the use of waste rich in organic matter as co-substrates for the fermentation process. The aim of this study was to determine the effect of waste co-fermentation on biogas production and nitrogen concentration in the reject water. A co-fermentation process with flotate or flotate and vegetables increased biogas production compared to primary sludge by 162 and 180%, respectively. During the tests, there was no inhibition of the fermentation process. Hydrolysis of organic compounds contained in flotate and vegetables resulted in a significant increase in ammonium nitrogen (by 80–100%) and dissolved organic nitrogen concentration (by 170–180%). The biogas and methane production rate as well as the ammonium and total nitrogen release rate were calculated. An energy balance was made, which took into account the variable amount of electric energy production depending on the efficiency of the cogeneration systems and energy consumption for supplying oxygen necessary to remove nitrogen contained in the reject water. A positive energy balance was obtained for all analyses.

Towards an Energy Self-Sufficient Resource Recovery Facility by Improving Energy and Economic Balance of a Municipal WWTP with Chemically Enhanced Primary Treatment

The recent trend of turning wastewater treatment plants (WWTPs) into energy self-sufficient resource recovery facilities has led to a constant search for solutions that fit into that concept. One of them is chemically enhanced primary treatment (CEPT), which provides an opportunity to increase biogas production and to significantly reduce the amount of sludge for final disposal. Laboratory, pilot, and full-scale trials were conducted for the coagulation and sedimentation of primary sludge (PS) with iron sulphate (PIX). Energy and economic balance calculations were conducted based on the obtained results. Experimental trials indicated that CEPT contributed to an increase in biogas production by 21% and to a decrease in sludge volume for final disposal by 12% weight. Furthermore, the application of CEPT may lead to a decreased energy demand for aeration by 8%. The removal of nitrogen in an autotrophic manner in the side stream leads to a further reduction in energy consumption in WWTP (up to 20%). In consequence, the modeling results showed that it would be possible to increase the energy self-sufficiency for WWTP up to 93% if CEPT is applied or even higher (up to 96%) if, additionally, nitrogen removal in the side stream is implemented. It was concluded that CEPT would reduce the operating cost by over 650,000 EUR/year for WWTP at 1,000,000 people equivalent, with a municipal wastewater input of 105,000 m3/d.

The Use of Organic Coagulants in the Primary Precipitation Process at Wastewater Treatment Plants

Measurements for determining the effect of chemically enhanced primary treatment (CEPT) on the efficiency of pollutant removal from wastewater were carried out using conventional inorganic coagulants PIX113 with polymer A110 (Kemipol, Police, Poland) and unconventional cationic organic coagulants Cofloc (Attana, Coalville, UK) C29510 (Kemipol, Police, Poland) and Sedifloc 575 (3F Chimica, Sandrigo, Italy). The average removal efficiency in the 2-h sedimentation process was 46%, 34%, 8%, 12% for the total suspended solids, organic matter (COD), total nitrogen, and total phosphorus, respectively. The use of organic coagulants contributed to 14–81% increase of pollutant removal efficiency. Substantial discrepancies in biological nutrient removal processes were not discovered in two-phase (anaerobic-anoxic) experiments without and with the addition of the organic coagulants. The increase in organic matter removal efficiency as a result of the CEPT process may contribute to a 65–80% increase in biogas production. The conducted research confirms the possibility of using organic coagulants in the primary precipitation process in wastewater treatment plants (WWTPs) in accordance with the principles of maximum energy recovery, thereby promoting renewable energy sources. Additionally, organic coagulants, as opposed to inorganic ones, do not cause a significant increase of chloride and sulfate ion concentrations, which facilitates the use of treated wastewater in the water reuse systems, such as irrigation of agricultural crops.

Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning

The paper presented the methodology for the construction of a soft sensor used for activated sludge bulking identification. Devising such solutions fits within the current trends and development of a smart system and infrastructure within smart cities. In order to optimize the selection of the data-mining method depending on the data collected within a wastewater treatment plant (WWTP), a number of methods were considered, including: artificial neural networks, support vector machines, random forests, boosted trees, and logistic regression. The analysis conducted sought the combinations of independent variables for which the devised soft sensor is characterized with high accuracy and at a relatively low cost of determination. With the measurement results pertaining to the quantity and quality of wastewater as well as the temperature in the activated sludge chambers, a good fit can be achieved with the boosted trees method. In order to simplify the selection of an optimal method for the identification of activated sludge bulking depending on the model requirements and the data collected within the WWTP, an original system of weight estimation was proposed, enabling a reduction in the number of independent variables in a model—quantity and quality of wastewater, operational parameters, and the cost of conducting measurements.

Strategies for mitigating nitrous oxide production and decreasing the carbon footprint of a full-scale combined nitrogen and phosphorus removal activated sludge system

Nitrous oxide (N₂O) emitted from biological nutrient removal activated sludge systems contributes significantly to the total carbon footprint of modern wastewater treatment plants. In the present study, N₂O production and emissions were experimentally determined in a large-scale plant (220,000 PE) employing combined nitrogen (N) and phosphorus (P) removal. As a modelling tool, the Activated Sludge Model 2d (ASM2d) was extended with modules describing multiple N₂O production pathways and N₂O liquid-gas transfers. The new model was calibrated and validated using the results of laboratory experiments and full-scale measurements. Different operational strategies were evaluated following the proposed model-based procedure. Heterotrophic denitrification was found to be the predominant pathway of N₂O production under both anoxic and aerobic conditions. This behaviour could primarily be attributed to the predominant abundance of heterotrophic denitrifiers over nitrifiers. Simulations revealed that the optimal solution for minimizing liquid N₂O production is to set the dissolved oxygen concentration in the aerobic zone from 1 to 2 mg O₂/L and to enhance the mixed liquor recirculation rate (MLR) (>500% of the influent flowrate) while not compromising effluent standards. Regarding the actual conditions, the potential reduction in the carbon footprint was estimated to be 10% by applying the proposed operational strategy. The results suggest that considerable improvements can be achieved without substantial upgrades and increased costs.

Evaluating the effect of different operational strategies on the carbon footprint of wastewater treatment plants - case studies from northern Poland

Nowadays, low greenhouse gas (GHG) emission is expected at wastewater treatment plants (WWTPs). However, emission quantification and evaluation still faces difficulties related to data availability and uncertainty. The objective of this study was to perform carbon footprint (CF) analysis for two municipal WWTPs located in northern Poland. Slupsk WWTP is a large biological nutrient removal (BNR) facility (250,000 PE) which benefits from on-site electricity production from biogas. The other studied plant is a medium-size BNR facility in Starogard (60,000 PE). In this WWTP, all the required electricity was provided from the grid. Both wastewater systems were composed of activated sludge, with differences in the nutrient removal efficiency and sludge treatment line. The CF calculations were based on empirical models considering various categories of input parameters, afterwards summing up the emissions expressed in CO₂ equivalents (CO_2e). After sensitivity analysis, significant contributors to GHG emissions were identified. The total specific CF of the Slupsk and the Starogard WWTP was 17.3 and 38.8 CO_2e per population equivalent (PE), respectively. In both cases, sludge management, electricity consumption and direct emissions from wastewater treatment were found to significantly influence the CF. A substantial share of the total CF originated from indirect emissions, primarily caused by the energy consumption. This negative impact can be partially overcome by increasing the share of renewable energy sources. Reduction of over 30% in the total CF could be achieved while applying energy recovery from biogas by combined heat and power plants. Farmland and farmland after composting were found to be the most appropriate strategies for sludge management. They could create a CF credit (8% of the total CF) as a result of substituting a synthetic fertilizer. Reliable full-scale measurements of N₂O emissions from wastewater treatment are recommended due to high uncertainty in CF estimation based on fixed emission factors (EFs). While applying the lowest and the highest N₂O EFs reported in the literature, the total CF would change even by 2-3 times.

Aeration Process in Bioreactors as the Main Energy Consumer in a Wastewater Treatment Plant. Review of Solutions and Methods of Process Optimization

Due to the key role of the biological decomposition process of organic compounds in wastewater treatment, a very important thing is appropriate aeration of activated sludge, because microorganisms have to be supplied with an appropriate amount of oxygen. Aeration is one of the most energy-consuming processes in the conventional activated sludge systems of wastewater treatment technology (may consume from 50% to 90% of electricity used by a plant), which makes it the most cost-generating process incurred by treatment plants. The paper presents the construction of aeration systems, their classification as well as parameters and factors that significantly affect the aeration process e.g., oxygen transfer efficiency, diffuser fouling, methods of dealing with diffuser fouling, diffuser selection. Additionally, there are briefly presented “smart control” systems in wastewater treatment and effect of application control strategy based on Supervisory Control and Data Acquisition system connected with the decrease in the energy consumption for aeration of bioreactors with activated sludge. It is noted that before the process is optimized, the system should be equipped with suitable metering devices. Only when relevant data is available, the improvements can be carried out. However, it’s important, that the operator should regularly maintain good condition and high efficiency of diffusers.

Pilot plant demonstration of stable and efficient high rate biological nutrient removal with low dissolved oxygen conditions

Aeration in biological nutrient removal (BNR) processes accounts for nearly half of the total electricity costs at many wastewater treatment plants. Even though conventional BNR processes are usually operated to have aerated zones with high dissolved oxygen (DO) concentrations, recent research has shown that nitrification can be maintained using very low-DO concentrations (e.g., below 0.2 mg O₂/L), and therefore, it may be possible to reduce energy use and costs in BNR facilities by decreasing aeration. However, the effect of reduced aeration on enhanced biological phosphorus removal (EBPR) is not understood. In this study, we investigated, at the pilot-scale level, the effect of using minimal aeration on the performance of an EBPR process. Over a 16-month operational period, we performed stepwise decreases in aeration, reaching an average DO concentration of 0.33 mg O₂/L with stable operation and nearly 90% phosphorus removal. Under these low-DO conditions, nitrification efficiency was maintained, and nearly 70% of the nitrogen was denitrified, without the need for internal recycling of high nitrate aeration basin effluent to the anoxic zone. At the lowest DO conditions used, we estimate a 25% reduction in energy use for aeration compared to conventional BNR operation. Our improved understanding of the efficiency of low-DO BNR contributes to the global goal of reducing energy consumption during wastewater treatment operations.