Effluent Violations Research Articles

Disintegrated Waste-Activated Sludge (NO2/FNA Method) as a Source of Carbon for Denitrification in the Mainstream of a WWTP

The deficiency of readily biodegradable organic carbon can be a significant limitation to effective nitrogen removal during wastewater denitrification. Waste-activated sludge (WAS) is a source of carbon produced directly at wastewater treatment plants (WWTPs). Raw WAS has a large molecular weight and complex chemical structure molecules that are not easily available for microorganisms. In this study, easily biodegradable organic fractions were released using pH control and/or nitrites and nitric acid (NO2/FNA). The obtained results indicated that WAS can be a sufficient carbon source for denitrification in WWTPs that are at risk of minor effluent violations. The implementation of WAS disintegration with the use of pH control and NO2/FNA allowed for the denitrification of an additional 0.5 and 0.8 mgN-NO3/L. WAS disintegration, besides being a source of carbon generation, reduces the volume of sludge and leads to the implementation of a closed-loop system.

Quantifying water effluent violations and enforcement impacts using causal AI

AbstractIn the landscape of environmental governance, controlling water pollution through the regulation of point sources is vital as it preserves ecosystems, protects human health, ensures legal compliance, and fulfills global environmental responsibilities. Under the Clean Water Act, the integrated compliance information system monitors the compliance and enforcement status of facilities regulated by the National Pollutant Discharge Elimination System (NPDES) permit program. This study assesses temporal and geographic trends for effluent violations within the United States and introduces a novel metric for quantifying violation trends at the facility level. Furthermore, we utilize a linear parametric approach for Conditional Average Treatment Effect (CATE) causal analysis to quantify the heterogeneous effects of EPA and state enforcement actions on effluent violation trends at facilities with NPDES permits. Our research reveals insights into national pollutant discharge trends, regional clustering of all pollutant violation types in Ohio ( Z‐score of 2.15), and priority pollutants in West Virginia ( Z‐score of 3.07). The trend metric identifies regulated facilities that struggle with severe and recurring violations. The causal model highlights variations in state compliance and enforcement effectiveness, underscoring the successful moderation of violation trends by states such as Montana and Maryland, among others.

Energy efficiency in activated sludge process using adaptive iterative learning control with PI ABAC

This paper proposed an iterative learning control (ILC) with a feedback regulator based on proportional integral ammonium-based aeration control (PI ABAC) to improve dissolved oxygen control through data learning of iteration data. The proposed controller's performance is evaluated using benchmark simulation model no. 1. (BSM1). The assessments focused on four main areas: effluent violation, effluent quality, aeration energy, and overall cost index. The proposed ILC PI ABAC controller's effectiveness is evaluated by comparing the performance of the activated sludge process to the BSM1 PI and feedback PI ABAC under three different weather conditions: dry, rain, and storm. The improvement of the proposed method over BSM1 PI is demonstrated by a reduction in aeration energy of up to 24%. In conclusion, if the proposed ILC PI ABAC controller is given enough information, it can be quite successful in achieving energy efficiency.

Enhancement of energy and cost efficiency in wastewater treatment plants using hybrid bio-inspired machine learning control techniques

Global population growth drives demand for clean water, energy, and wastewater production in urban areas. Most existing wastewater treatment plants (WWTPs) are energy- and cost-intensive. To achieve the UN Sustainable Development Goals (SDGs) by 2030, many regions have implemented strict policies for energy consumption and contaminated water discharge, promoting environmental sustainability. This paper attempts to enhance the achievement of SDGs in the wastewater treatment industry by proposing a novel method for hierarchical control of wastewater treatment plants to ensure energy and cost efficiency with less knowledge of the process model, fewer measurements, and fewer control loops. This controller is the combination of a machine learning control technique with a bio-inspired computational algorithm. To evaluate and validate the performance of the proposed controller on the WWTP, the benchmark simulation model no. 1 (BSM1) has been used. The most significant contributions of this paper show that 488.96 KWh/d, 3620.08 Kg/d, and 3454.55 KWh/d of aeration energy cost index, sludge production cost index, and operational cost index are respectively saved when compared to the default control strategy (DCS). Also, 893.69 Kg pollution units per day of effluent fine-related costs have been successfully recovered when compared to the DCS. The experimental results illustrate that the proposed control yields significant amelioration of the energy and cost profile of the WWTP with no effluent violation in dry, rain, and storm weather conditions.

Smart-Plant Decision Support System (SP-DSS): Defining a multi-criteria decision-making framework for the selection of WWTP configurations with resource recovery

The development of the Smart-Plant Decision Support System (SP-DSS) is presented, which helps to find the optimal water resource recovery facility (WRRF) configuration for a specific case. A general plant superstructure is defined to allow the evaluation of different combinations among the available process unit options, considering technical, economic, and environmental impact criteria. The complete evaluation is based on a five-step framework: (i) design problem set-up, (ii) wastewater inflow generation, (iii) superstructure generation and plant-wide model simulation under dynamic conditions, (iv) estimation of multi-criteria objective values (greenhouse gas emissions, accumulation of effluent violations, effluent quality index, net present value, system readiness level and plant land area), and (v) design configuration multi-criteria sorting with the technique for order of preference by similarity to ideal solution (TOPSIS). SP-DSS application is shown comparing the mainstream shortcut enhanced phosphorus and polyhydroxyalkanoate (PHA) recovery (SCEPPHAR) technology with a conventional anaerobic/anoxic/aerobic (A2O) configuration for a medium size WWTP (Manresa, Spain). The comparison shows both configurations allow meeting discharge limits, and among other criteria, the SCEPPHAR novel configuration, with respect to A2O, shows higher pollutant contents in the effluent (3.30 vs 2.34 gPoll/m3), higher capital expenditures (CAPEX 0.191 vs 0.130 €/m3), lower operational expenditures (OPEX 0.397 vs 0.515 €/m3), lower required tariff (0.654 vs 0.674 €/m3) and higher greenhouse gas emissions (GHG 0.19 vs 0.14 kgCO2/m3). Overall, TOPSIS sorting indicates A2O is still the best configuration for this specific case.

Decentralized proportional-integral control with carbon addition for wastewater treatment plant

Two main challenges in activated sludge wastewater treatment plant (WWTP) are cost and effluent quality, which has forced the wastewater treatment operator to find an alternative to improve the existing control strategy. The Benchmark Simulation Model No. 1 (BSM1) is applied as operational settings for this study. In BSM1, the standard control variables are the internal recirculation flow rate and the oxygen transfer rate. To improve the existing control strategy of BSM1, three alternative control handles are proposed, which are the individual aeration intensity control, carbon source addition and combination of both. The effect of each control handles in terms of the effluent violation, effluent quality, aeration cost, and total operational cost index are examined. The simulation result has shown that the individual control of aeration intensity improved the effluent quality index, and reduced the aeration, pumping, and total operational cost index when compared to the standard BSM1 control handle. Nonetheless, the addition of a fixed external carbon source has shown a significantly improved effluent quality with a lower number of total nitrogen violations as compared to the standard BSM1 control handles. Thus, the proposed control handles may be beneficial if applied in a real WWTP.

Model Based Control of a Full-Scale Biological Wastewater Treatment Plant

In the present contribution, different combinations of control strategies based on PI, MPC and Fuzzy controllers are implemented with a prime concern of improving the quality of the discharge and reducing the operational expenditure in a full scale wastewater treatment plant. The Benchmark Simulation Model No.2 (BSM2) is used as the working platform. The control objective is to maintain the dissolved oxygen concentration in the fourth tank by manipulating the oxygen transfer coefficients of third, fourth and fifth tanks in the biological wastewater treatment. PI and MPC are used at the lower level whereas MPC and Fuzzy controllers are used at the higher level. The effluent violations are reduced for all the proposed control schemes. It is also observed that PI-MPC results in best Effluent Quality Index (EQI) and PI-Fuzzy results in best Operational Cost Index (OCI).

Factors affecting SVI in small scale WWTPs

This paper analyses factors associated with bulking in 195 small scale wastewater treatment plants (WWTPs) in Estonia. Operational data from each plant were collected and analysed statistically. The key factors associated with bulking were infiltration into sewage pipes, the type and purpose of process reactor, operational practices and influent characteristics. Both anaerobic fraction and volumetric fraction of the anaerobic reactor compared to the aerobic reactor resulted in a positive correlation with sludge volume index (SVI) <150 ml/g values. Good operation and maintenance practice as well as an operator's competence play a crucial role in bulking prevention. Using the 30 minute settling test (V30) as the single process control parameter can mislead an operator's judgement in process control strategies and cause effluent violations. Misjudgements in process control decisions can lead to unwanted conditions in small WWTPs (e.g. excessive chemical addition favoured bulking). Use of instrumentation, control and automation helped to keep the process conditions more stable and reduce the probability of bulking. Analyses of variance showed that the factors associated with Microthrix parvicella growth were long solids retention time (SRT), low food-to-microorganism ratio (F/M) and lack of carbon content compared against nitrogen and phosphorus contents.

Predicting influent biochemical oxygen demand: Balancing energy demand and risk management

Ready access to comprehensive influent information can help water reclamation plant (WRP) operators implement better real-time process controls, provide operational reliability and reduce energy consumption. The five-day biochemical oxygen demand (BOD5), a critical parameter for WRP process control, is expensive and difficult to measure using hard-sensors. An alternative approach based on a soft-sensor methodology shows promise, but can be problematic when used to predict high BOD5 values. Underestimating high BOD5 concentrations for process control could result in an insufficient amount of aeration, increasing the risk of an effluent violation. To address this issue, we tested a hierarchical hybrid soft-sensor approach involving multiple linear regression, artificial neural networks (ANN), and compromise programming. While this hybrid approach results in a slight decrease in overall prediction accuracy relative to the approach based on ANN only, the underestimation percentage is substantially lower (37% vs. 61%) for predictions of carbonaceous BOD5 (CBOD5) concentrations higher than the long-term average value. The hybrid approach is also flexible and can be adjusted depending on the relative importance between energy savings and managing the risk of an effluent violation.

Model calibration and feed‐forward control of the wastewater treatment plant – case study for CLUJ‐Napoca WWTP

AbstractAlthough the activated sludge models for waste water treatment plants (WWTPs) offer comprehensive description of their involved biochemical and physical processes, it is a challenging task to calibrate the model for the operational plant. The article first presents a systematic calibrating procedure applied to the Activated Sludge Model No.1 (ASM 1), showing its potential to be extended to other WWTPs. It particularly addresses cases when comprehensive knowledge on the WWTP influent composition does not exist. An optimisation‐based approach is used for the WWTP model calibration and for finding the partially unknown influent composition. Dynamic model validation shows good match between model predicted values and WWTP measured data. Second, a new feed‐forward control strategy is designed for the WWTP and compared with the conventional nitrate‐nitrite nitrogen and dissolved oxygen control. The evaluation based on the effluent quality index, pumping and aeration energy and the number of effluent violations assessment tools, demonstrates incentives for the proposed control approach.

Enhanced control of activated sludge process using predetermined set-points

The performance of activated sludge process (ASP) is evaluated by the effluent quality which is determined by five different variables of the treated wastewater such as ammonia, total nitrogen, COD, BOD5 and TSS. To keep these five variables within the limits as per environmental regulations, nitrate and nitrite concentration (SNO) in the second anoxic reactor and the dissolved oxygen concentration (SO) in the last aerobic reactor of the ASP should be maintained at prescribed levels. To do that, a closed-loop control configuration is required and proper set-points for these closed-loop control configurations are needed. In this paper, the optimal values of controller set-points are determined for nitrogen removal in the activated sludge process. Effluent quality limits have been considered to evaluate the optimal set-points for the Indian climatic conditions. Once the optimal set-points are determined, PI controllers are used to control SNO in the second anoxic reactor and SO in the last aerobic reactor of the ASP. Further, feed-forward control is incorporated to minimize the effect of disturbances, which enters along with the influent. No case studies of BSM1 model have been reported in the literature for the Indian wastewater. In this work, the dynamic simulation of an activated sludge process is performed using the data collected from the sewage treatment plant, located in India. The results of the simulation showed that feed-forward with PI control strategy, ASP can be efficiently controlled without any effluent violations, when compared to BSM1.

Advanced decision control system for effluent violations removal in wastewater treatment plants

This paper presents the application of control strategies for wastewater treatment plants with the goal of effluent limits violations removal as well as achieving a simultaneous improvement of effluent quality and reduction of operational costs. The evaluation is carried out with the Benchmark Simulation Model No. 2. The automatic selection of the suitable control strategy is based on risk detection of effluent violations by Artificial Neural Networks. Fuzzy Controllers are implemented to improve the denitrification or nitrification process based on the proposed objectives. Model Predictive Control is applied for the improvement of dissolved oxygen tracking.

Fuzzy Control and Model Predictive Control Configurations for Effluent Violations Removal in Wastewater Treatment Plants

In this paper the following new control objectives for biological wastewater treatment plants (WWTPs) have been established: to eliminate violations of total nitrogen in the effluent (Ntot,e) or ammonium and ammonia nitrogen concentration (NH) in the effluent (NHe) and at the same time handle the customary requirements of improving effluent quality and reducing operational costs. The Benchmark Simulation Model No. 1 (BSM1) is used for evaluation, and the control is based on Model Predicitive Control (MPC) and fuzzy logic. To improve effluent quality and to reduce operational costs, a hierarchical control structure is implemented to regulate the dissolved oxygen (DO) on the three aerated tanks. The high level of this hierarchical structure is developed with a fuzzy controller that adapts the DO set points of the low level based on the NH concentration in the fifth tank (NH5). The low level is composed of three MPC controllers with feedforward control (MPC + FF). For avoiding violations of Ntot,e, a second fuzzy controller is used to manipulate the external carbon flow rate in the first tank (qEC1) based on nitrate nitrogen in the fifth tank (NO5) plus NH5. For avoiding violations of NHe, a third fuzzy controller is applied to manipulate the internal recirculation flow rate (Qrin) based on NH5 and NH in the influent. Simulation results show the benefit of the proposed approach.

Evaluation and improvement of wastewater treatment plant performance using BioWin

In this study, the activated sludge model implemented in the BioWin® software was validated against full-scale wastewater treatment plant data. Only two stoichiometric parameters (Yp/acetic and the heterotrophic yield (YH)) required calibration. The value 0.42 was used for Yp/acetic in this study, while the default value of the BioWin® software is 0.49, making it comparable with the default values of the corresponding parameter (yield of phosphorus release to substrate uptake \((Y_{PO_4 } )\)) used in ASM2, ASM2d, and ASM3P, respectively. Three scenarios were evaluated to improve the performance of the wastewater treatment plant, the possibility of wasting sludge from either the aeration tank or the secondary clarifier, the construction of a new oxidation ditch, and the construction of an equalization tank. The results suggest that construction of a new oxidation ditch or an equalization tank for the wastewater treatment plant is not necessary. However, sludge should be wasted from the aeration tank during wet weather to reduce the solids loading of the clarifiers and avoid effluent violations. Therefore, it is recommended that the design of wastewater treatment plants (WWTPs) should include flexibility to operate the plants in various modes. This is helpful in selection of the appropriate operating mode when necessary, resulting in substantial reductions in operating costs.

Improvement of Activated Sludge Process Using Enhanced Nonlinear PI Controller

Wastewater treatment plant is a large-scale system and highly known with the nonlinearity of the parameters, making them a challenge to be controlled. In this paper, enhanced nonlinear PI (EN-PI) controller is developed for activated sludge process where a sector-bounded nonlinear gain with automatic gain adjustment is cascaded to conventional static-gain PI. The importance in controlling the dissolved oxygen concentration and the improvement of nitrogen removal process are discussed. The effectiveness of the proposed EN-PI controller is validated by comparing the performance of local control loops and the activated sludge process to the benchmark PI under three different weathers. The EN-PI controller is effectively applied in improving the performances of the static-gain PI, hence controlling the dynamic natures of the plant. Itwas proved by significant improvement in effluent violations, effluent quality index and energy saving of the Benchmark Simulation Model No.1.

Mathematical modeling and modification of an activated sludge benchmark process evaluated by multiple performance criteria

Optimal modification of an activated sludge process (ASP) evaluated by multiple performance criteria was studied. A benchmark process in BSM1 was taken as a target process. Four indexes of percentage of effluent violation (PEV), energy consumption (OCI), total volume of tanks (TV) and total suspended solid in tank5 (TSSa5), were criteria and eleven process parameters were decision variables, making up the multiple criteria optimization model, which was solved by non-dominated sorting genetic algorithm II (NSGA-II) in MATLAB. Pareto solutions were obtained; one solution (opt1) was selected based on the authors’ decision for a further analysis. Results show that the process with opt1 strategy exhibits much better performance of PEV and OCI than with the default, being improved by 74.17% and 9.97% specifically under dry influent and without control. These results indicated that the multiple criterion optimization method is very useful for modification of an ASP.

Optimal design activated sludge process by means of multi-objective optimization: case study in Benchmark Simulation Model 1 (BSM1).

Optimal design of activated sludge process (ASP) using multi-objective optimization was studied, and a benchmark process in Benchmark Simulation Model 1 (BSM1) was taken as a target process. The objectives of the study were to achieve four indexes of percentage of effluent violation (PEV), overall cost index (OCI), total volume and total suspended solids, making up four cases for comparative analysis. Models were solved by the non-dominated sorting genetic algorithm in MATLAB. Results show that: ineffective solutions can be rejected by adding constraints, and newly added objectives can affect the relationship between the existing objectives; taking Pareto solutions as process parameters, the performance indexes of PEV and OCI can be improved more than with the default process parameters of BSM1, especially for N removal and resistance against dynamic NH4(+)-N in influent. The results indicate that multi-objective optimization is a useful method for optimal design ASP.

Nonlinear PI Control with Adaptive Interaction Algorithm for Multivariable Wastewater Treatment Process

The wastewater treatment plant (WWTP) is highly known with the nonlinearity of the control parameters, thus it is difficult to be controlled. In this paper, the enhancement of nonlinear PI controller (ENon-PI) to compensate the nonlinearity of the activated sludge WWTP is proposed. The ENon-PI controller is designed by cascading a sector-bounded nonlinear gain to linear PI controller. The rate variation of the nonlinear gainknis automatically updated based on adaptive interaction algorithm. Initiative to simplify the ENon-PI control structure by adaptingknhas been proved by significant improvement under various dynamic influents. More than 30% of integral square error and 14% of integral absolute error are reduced compared to benchmark PI for DO control and nitrate in nitrogen removal control. Better average effluent qualities, less number of effluent violations, and lower aeration energy consumption resulted.

Cost-performance analysis of nutrient removal in a full-scale oxidation ditch process based on kinetic modeling

A full-scale oxidation ditch process for treating sewage was simulated with the ASM2d model and optimized for minimal cost with acceptable performance in terms of ammonium and phosphorus removal. A unified index was introduced by integrating operational costs (aeration energy and sludge production) with effluent violations for performance evaluation. Scenario analysis showed that, in comparison with the baseline (all of the 9 aerators activated), the strategy of activating 5 aerators could save aeration energy significantly with an ammonium violation below 10%. Sludge discharge scenario analysis showed that a sludge discharge flow of 250–300 m3/day (solid retention time (SRT), 13-15 days) was appropriate for the enhancement of phosphorus removal without excessive sludge production. The proposed optimal control strategy was: activating 5 rotating disks operated with a mode of “111100100” (“1” represents activation and “0” represents inactivation) for aeration and sludge discharge flow of 200 m3/day (SRT, 19 days). Compared with the baseline, this strategy could achieve ammonium violation below 10% and TP violation below 30% with substantial reduction of aeration energy cost (46%) and minimal increment of sludge production (< 2%). This study provides a useful approach for the optimization of process operation and control.

Improving wastewater mixing and oxygenation efficiency with solar-powered circulation

Electrical grid-powered aeration is used in most pond-based systems and equalization basins at activated sludge wastewater treatment plants to provide the mixing and oxygenation that enables bacteria to digest organic-matter. Oxygen also is needed in the near-surface water of all ponds and basins to provide an “odor cap” by oxidizing malodorous sulfur compounds, preventing their release to air. Much more aeration typically is needed to mix than oxygenate the wastewater. This imbalance causes an operational inefficiency in that grid-power is used to supply more oxygen than needed. The U.S. Environmental Protection Agency concluded that the use of solar-powered circulation (SPC) technology reduces the need to aerate, operational costs, and greenhouse gas emissions associated with electrical power generation. However, the Agency did not quantify electrical, water quality, or other parameters. The New Hampshire Department of Environmental Services directed a 3-site study to quantify the ability of SPC to replace some or all aeration while maintaining good effluent water quality. Water quantity and quality, odor event, and kilowatt-hour consumption and expenditure data were collected 1 year prior to, and 2 years during, SPC treatment at pond-based treatment plants in Pittsfield and Exeter, and at the activated sludge treatment plant in Rochester. Final effluent water quality was maintained, no effluent violations or odor events occurred, and sludge buildup was minimal during the SPC study period. Electricity usage and costs declined by about 38% in Pittsfield and Exeter, and by about 87% in Rochester, resulting in carbon dioxide emission reductions of 273,161, 918,183, and 1,082,509 kg, respectively. Payback periods ranged from 1.9 to 3.7 years. SPC improved operational efficiency at the plants by reducing grid-power consumption while operational objectives were met. The 25-year expected lifetime of SPC units with minimal maintenance requirements indicated long-term reductions in operational expenses and greenhouse gas emissions.