Wastewater Treatment Plant Configurations Research Articles

A comprehensive carbon footprint analysis of different wastewater treatment plant configurations

With the growing concern of global warming, many water utilities are pioneering in mitigating greenhouse gas (GHG) emissions, with some water utilities aiming to achieve net-zero emissions operation in the next decade. However, for wastewater treatment plants (WWTPs), the carbon footprint of different treatment technologies and its contribution among various units within each treatment configuration is still unclear. This study evaluates the impacts of process design on the carbon footprint of WWTPs through the analysis of scope 1 (direct emission), scope 2 (indirect emission), and scope 3 (value chain emission) emissions. The comprehensive configuration design in this work considered three nutrient removal processes including typical aerobic and anaerobic wastewater treatment technologies. Emissions from the sludge management processes are also calculated, including aerobic and anaerobic sludge stabilization processes, short-term and long-term sludge storage, and three sludge disposal options. In total, 45 processes were analysed and the results were compared. The results showed the carbon footprints are highly dependent on the treatment configurations of WWTPs. Analysis suggested scope 2 & 3 emissions can be reduced by selecting suitable processes. In general, anaerobic wastewater and sludge stabilization technologies are more suitable than aerobic technologies to reduce scope 2 & 3 emissions, leading to a lower overall carbon footprint. In comparison, configuration design offers limited opportunities to reduce scope 1 emissions, which may be the future challenge for WWTP to achieve carbon neutrality.

Stochastic simulation-based superstructure optimization framework for process synthesis and design under uncertainty

Advances in simulation and optimization technologies coupled with the continued growth in computing power now increasingly pave the way for the development of advanced model-based engineering design frameworks. In this work, we propose an extensive computational framework, which brings together state-of-the-art engineering practices, such as high fidelity process simulation, superstructure-based conceptual design, global sensitivity analysis, Monte Carlo procedures for uncertainty quantification, and a stochastic simulation-based design space optimizer in order to foster decision making under uncertainty. The capabilities of the framework are highlighted in a case study, which addresses the challenges of how to synthesize and design wastewater treatment plant configurations under influent uncertainties. In order to handle multiple stochastic constraints, a black-box solver using a new infill criterion for surrogate-based optimization is also proposed. The results demonstrate the promising potential of the simulation and sampling-based framework for effectively addressing stochastic design problems arising in broader engineering domains.

Assessment of the fate of organic micropollutants in novel wastewater treatment plant configurations through an empirical mechanistic model.

Novel wastewater treatment plants (WWTPs) are expected to be less energetically demanding than conventional ones. However, scarce information is available about the fate of organic micropollutants (OMPs) in these novel configurations. Therefore, the objective of this work is to assess the fate of OMPs in three novel WWTP configurations by using a plant-wide simulation that integrates multiple units. The difference among the three configurations is the organic carbon preconcentration technology: chemically enhanced primary treatment (CEPT), high-rate activated sludge (HRAS) combined or not with a rotating belt filter (RBF); followed by a partial-nitritation (PN-AMX) unit. The simulation results show that the three selected novel configurations lead mainly to comparable OMPs removal efficiencies from wastewater, which were similar or lower, depending on the OMP, than those obtained in conventional WWTPs. However, the presence of hydrophobic OMPs in the digested sludge noticeably differs among the three configurations. Whereas the configuration based on sole HRAS to recover organic carbon leads to a lower presence of OMPs in digested sludge than the conventional WWTP, in the other two novel configurations this presence is noticeable higher. In conclusion, novel WWTP configurations do not improve the OMPs elimination from wastewater achieved in conventional ones, but the HRAS-based WWTP configuration leads to the lowest presence in digested sludge so it becomes the most efficient alternative.

Comprehensive comparison of chemically enhanced primary treatment and high-rate activated sludge in novel wastewater treatment plant configurations

Novel wastewater treatment plants (WWTPs) are designed to be more energy efficient than conventional plants. One approach to becoming more energy efficient is the pre-concentration of organic carbon through chemically enhanced primary treatment (CEPT) or high-rate activated sludge (HRAS). This study compares these approaches in terms of energy demand, operational costs, organic micropollutants (OMP), and virus removal efficiency. A CEPT pilot-scale plant was operated at a hydraulic retention time (HRT) of 30 min, and a lab-scale HRAS reactor was operated at an HRT of 2 h and a solid retention time (SRT) of 1 d in continuous mode. A minimum dose of 150 mg/L ferric chloride (FeCl3) was required to achieve a threshold chemical oxygen demand (COD)-to-ammonium ratio below 2 g COD to 1 g of NH4+ –N (fulfilling the requirement for a partial nitritation-anammox reactor), reaching high phosphate (PO43−)-removal efficiency (>99%). A slightly lower COD recovery was attained in the HRAS reactor, due to the partial oxidation of the influent COD (15%). The lower PO43− removal efficiency achieved in the HRAS configuration (13%) was enhanced to a comparable value of that achieved in CEPT by the addition of 30 mg/L FeCl3 at the clarifier. The CEPT configuration was less energy-intensive (0.07 vs 0.13 kWh/m3 of wastewater) but had significantly higher operational costs than the HRAS-based configuration (6.0 vs 3.8 c€/m3 of wastewater). For OMPs with kbiol > 10 L/gVSS·d, considerably higher removal efficiencies were achieved in HRAS (80–90%) than in CEPT (4–55%). For the remaining OMPs, the biotransformation efficiencies were generally higher in HRAS than in CEPT but were below 55% in both configurations. Finally, CEPT was less efficient than HRAS for virus removal. HRAS followed by FeCl3 post-treatment appeared to be a more effective alternative than CEPT for COD pre-concentration in novel WWTPs.

Energetic and economic assessment of sludge thermal hydrolysis in novel wastewater treatment plant configurations

Novel wastewater treatment plants (WWTPs) are aimed to be more energetically efficient than conventional ones. Their first step is a chemical oxygen demand (COD) preconcentration stage with different alternatives, such as rotating belt filters (RBF), chemically enhanced primary treatment (CEPT), high-rate activated sludge (HRAS), or combinations thereof, in which energy requirements are substantially reduced. The COD recovered as sludge allows a noticeable increase of biogas production in anaerobic digestion (AD). In conventional WWTPs, sludge anaerobic biodegradability can be significantly enhanced by applying sludge pretreatment methods, such as thermal hydrolysis (TH), before AD. However, considering that novel-sludges are more anaerobically biodegradable than conventional ones, the impact of TH on their methane production is expected to result significantly lower. In this study, an energetic and economic assessment of applying TH in novel WWTPs was performed. We found that TH is only justified to reduce operational costs as long as sludge TS concentration in the feeding to the TH unit is higher than 1–2%. The HRAS-based WWTP is the scenario that leads to the lowest treatment costs (below 1c €/ m3 wastewater if sludge is thickened over 10% of TS). However, the WWTP based on CEPT for COD preconcentration leads to the lowest electricity consumption (below 0.01 kWh/m3 of wastewater), but even in the most favourable conditions the energy autarky was not achievable. Results show that the main impact of TH is mainly due to sludge disposal savings (270,000–430,000 €/year for a 500,000 inhabitants WWTP) rather than the increase of energy production (achieves maximum savings of 35,000–60,000 €/year). Payback time is very dependent on the WWTP size, ranging from 15 to 30 years for a 100,000 inhabitants WWTP and from 2 to 4 years for a 1,000,000 inhabitants WWTP.

Opportunities for rotating belt filters in novel wastewater treatment plant configurations

The combination of rotating belt filters and chemically enhanced settling allowed the production of suitable effluents for further stages and to generate enough methane to reach energy autarky.

Glocal assessment of integrated wastewater treatment and recovery concepts using partial nitritation/Anammox and microalgae for environmental impacts

This study explored the feasibility and estimated the environmental impacts of two novel wastewater treatment configurations. Both include combined bioflocculation and anaerobic digestion but apply different nutrient removal technologies, i.e. partial nitritation/Anammox or microalgae treatment. The feasibility of such configurations was investigated for 16 locations worldwide with respect to environmental impacts, such as net energy yield, nutrient recovery and effluent quality, CO2 emission, and area requirements. The results quantitatively support the applicability of partial nitritation/Anammox in tropical regions and some locations in temperate regions, whereas microalgae treatment is only applicable the whole year round in tropical regions that are close to the equator line. Microalgae treatment has an advantage over the configuration with partial nitritation/Anammox with respect to aeration energy and nutrient recovery, but not with area requirements. Differential sensitivity analysis points out the dominant influence of microalgal biomass yield and wastewater nutrient concentrations on area requirements and effluent quality. This study provides initial selection criteria for worldwide feasibility and corresponding environmental impacts of these novel municipal wastewater treatment plant configurations.

Optimal flow sensor placement on wastewater treatment plants

Obtaining high quality data collected on wastewater treatment plants is gaining increasing attention in the wastewater engineering literature. Typical studies focus on recognition of faulty data with a given set of installed sensors on a wastewater treatment plant. Little attention is however given to how one can install sensors in such a way that fault detection and identification can be improved. In this work, we develop a method to obtain Pareto optimal sensor layouts in terms of cost, observability, and redundancy. Most importantly, the resulting method allows reducing the large set of possibilities to a minimal set of sensor layouts efficiently for any wastewater treatment plant on the basis of structural criteria only, with limited sensor information, and without prior data collection. In addition, the developed optimization scheme is fast. Practically important is that the number of sensors needed for both observability of all flows and redundancy of all flow sensors is only one more compared to the number of sensors needed for observability of all flows in the studied wastewater treatment plant configurations.

Towards a comprehensive greenhouse gas emissions inventory for biosolids

Effective handling and treatment of the solids fraction from advanced wastewater treatment operations carries a substantial burden for water utilities relative to the total economic and environmental impacts from modern day wastewater treatment. While good process-level data for a range of wastewater treatment operations are becoming more readily available, there remains a dearth of high quality operational data for solids line processes in particular. This study seeks to address this data gap by presenting a suite of high quality, process-level life cycle inventory data covering a range of solids line wastewater treatment processes, extending from primary treatment through to biosolids reuse in agriculture. Within the study, the impacts of secondary treatment technology and key parameters such as sludge retention time, activated sludge age and primary-to-waste activated sludge ratio (PS:WAS) on the life cycle inventory data of solids processing trains for five model wastewater treatment plant configurations are presented. BioWin® models are calibrated with real operational plant data and estimated electricity consumption values were reconciled against overall plant energy consumption. The concept of “representative crop” is also introduced in order to reduce the uncertainty associated with nitrous oxide emissions and soil carbon sequestration offsets under biosolids land application scenarios. Results indicate that both the treatment plant biogas electricity offset and the soil carbon sequestration offset from land-applied biosolids, represent the main greenhouse gas mitigation opportunities. In contrast, fertiliser offsets are of relatively minor importance in terms of the overall life cycle emissions impacts. Results also show that fugitive methane emissions at the plant, as well as nitrous oxide emissions both at the plant and following agricultural application of biosolids, are significant contributors to the overall greenhouse gas balance and combined are higher than emissions associated with transportation. Sensitivity analyses for key parameters including digester PS:WAS and sludge retention time, and assumed biosolids nitrogen content and agricultural availability also provide additional robustness and comprehensiveness to our inventory data and will facilitate more customised user analyses.

A Guide to Net-Zero Energy Solutions for Water Resource Recovery Facilities

The overall goal of this energy project is to aid water resource recovery facilities in quickly assessing their energy management performances (benchmarking) to move toward “net-zero” energy use through proven and available practices and technologies in the areas of energy conservation, demand reduction, and enhanced production. This project provides WERF subscribers with information on baseline energy performance for common wastewater treatment plant configurations and on opportunities for demand reduction, energy efficiency, and energy recovery/onsite energy production.The guiding principle behind net-zero energy was that neutrality had to be achieved by harnessing the energy contained in the wastes treated. Following this principle removed wind and solar power from consideration. These energy sources may contribute to a facility's energy performance, but they are unrelated to the embedded energy contained in waste streams at a water resource recovery facility (WRRF).The results from this project confirm the hypothesis that energy-neutral wastewater treatment is within reach for a significant number of facilities via proven and available technologies.This title belongs to WERF Research Report SeriesISBN: 9781780407685 (eBook)

Implementation of a knowledge-based methodology in a decision support system for the design of suitable wastewater treatment process flow diagrams

In light of rapid global change, the demand for wastewater treatment is increasing rapidly and will continue to do so in the near future. Wastewater management is a complex puzzle for which the proper pieces must be combined to achieve the desired solution, requiring the simultaneous consideration of technical, economic, social and environmental issues. In this context, a knowledge-based methodology (KBM) for the conceptual design of wastewater treatment plant (WWTP) process flow diagrams (PFDs) and its application for two scenarios is presented in this paper. The core of the KBM is composed of two knowledge bases (KBs). The first, a specification knowledge base (S-KB), summarizes the main features of the different treatment technologies: pollutants removal efficiency, operational costs and technical reliability. The second, a compatibility knowledge base (C-KB), contains information about the different interactions amongst the treatment technologies and determines their degree of compatibility. The proposed methodology is based on a decision hierarchy that uses the information contained in both KBs to generate all possible WWTP configurations, screening and selecting appropriate configurations based on user-specified requirements and scenario characteristics. The design of the most adequate treatment train for small and medium sized wastewater treatment plants (2000 and 50,000 p.e. respectively) according to different restrictions (space constraints, operation simplicity and cost optimization) was the example in order to show the usefulness of the KBM.

A knowledge management methodology for the integrated assessment of WWTP configurations during conceptual design

The current complexity involved in wastewater management projects is arising as the XXI century sets new challenges leading towards a more integrated plant design. In this context, the growing number of innovative technologies, stricter legislation and the development of new methodological approaches make it difficult to design appropriate flow schemes for new wastewater projects. Thus, new tools are needed for the wastewater treatment plant (WWTP) conceptual design using integrated assessment methods in order to include different types of objectives at the same time i.e. environmental, economical, technical, and legal. Previous experiences used the decision support system (DSS) methodology to handle the specific issues related to wastewater management, for example, the design of treatment facilities for small communities. However, tools developed for addressing the whole treatment process independently of the plant size, capable of integrating knowledge from many different areas, including both conventional and innovative technologies are not available. Therefore, the aim of this paper is to present and describe an innovative knowledge-based methodology that handles the conceptual design of WWTP process flow-diagrams (PFDs), satisfying a vast number of different criteria. This global approach is based on a hierarchy of decisions that uses the information contained in knowledge bases (KBs) with the aim of automating the generation of suitable WWTP configurations for a specific scenario. Expert interviews, legislation, specialized literature and engineering experience have been integrated within the different KBs, which indeed constitute one of the main highlights of this work. Therefore, the methodology is presented as a valuable tool which provides customized PFD for each specific case, taking into account process unit interactions and the user specified requirements and objectives.

Observability of reduced order models - application to a model for control of Alpha process

This paper describes the theoretical basis and some applications of a identifiability/observability test for state-space models based on the recursive calculation of the numerical condition of the observability matrix. This test evaluates the possibility of estimating the unknown states and parameters of a mathematical model under defined experimental conditions and available information. The numerical value of the proposed “observability parameter” is also an index of uncertainty propagation through the model. As examples of the utility of the proposed test, the paper presents the analysis of a reduced-order model for two wastewater treatment plant configurations (D-N and Alpha process), evaluating the on-tine information that is theoretically indispensable in distinguishing each one of the unknown states and parameters under steady or dynamic conditions.

Observability of reduced order models - application to a model for control of alpha process

This paper describes the theoretical basis and some applications of a identifiability/observability test for state-space models based on the recursive calculation of the numerical condition of the observability matrix. This test evaluates the possibility of estimating the unknown states and parameters of a mathematical model under defined experimental conditions and available information. The numerical value of the proposed “observability parameter” is also an index of uncertainty propagation through the model. As examples of the utility of the proposed test, the paper presents the analysis of a reduced-order model for two wastewater treatment plant configurations (D-N and Alpha process), evaluating the on-line information that is theoretically indispensable in distinguishing each one of the unknown states and parameters under steady or dynamic conditions.