WWTP dynamic disturbance modelling--an essential module for long-term benchmarking development

Modifications to the anaerobic digestion model no. 1 (ADM1) for enhanced understanding and application of the anaerobic treatment processes - A comprehensive review

Anaerobic digestion (AD) is a promising method for the recovery of resources and energy from organic wastes. Correspondingly, AD modelling has also been developed in recent years. The International Water Association (IWA) Anaerobic Digestion Model No. 1 (ADM1) is currently the most commonly used structured AD model. However, as substrates become more complex and our understanding of the AD mechanism grows, both systematic and specific modifications have been applied to the ADM1. Modified models have provided a diverse range of application besides AD processes, such as fermentation and biogas upgrading processes. This paper reviews research on the modification of the ADM1, with a particular focus on processes, kinetics, stoichiometry and parameters, which are the major elements of the model. The paper begins with a brief introduction to the ADM1, followed by a summary of modifications, including extensions to the model structure, modifications to kinetics (including inhibition functions) and stoichiometry, as well as simplifications to the model. The paper also covers kinetic parameter estimation and validation of the model, as well as practical applications of the model to a variety of scenarios. The review highlights the need for improvements in simulating AD and biogas upgrading processes, as well as the lack of full-scale applications to other substrates besides sludge (such as food waste and agricultural waste). Future research directions are suggested for model development based on detailed understanding of the anaerobic treatment mechanisms, and the need to recover of valuable products.

Modelling and techno-economic assessment of (bio)electrochemical nitrogen removal and recovery from reject water at full WWTP scale

At conventional wastewater treatment plants (WWTPs), reject waters originating from the dewatering of anaerobically digested sludge contain the highest nitrogen concentrations within the plant and thereby have potential for realising nitrogen recovery in a reusable form. At the same time, nitrogen removal from reject waters has potential to reduce the energetic and chemical demands of the WWTP due to a reduced nutrient load to the activated sludge process. In recent years, (bio)electrochemical methods have been extensively studied for nitrogen recovery from reject waters in laboratory-scale but not yet implemented in real WWTP environments, particularly due to concerns about the need for large capital investments. This study assessed the techno-economic feasibility of retrofitting a (bio)electrochemical nitrogen removal and recovery (NRR) unit into the reject water circulation line of a full-scale WWTP through modelling. Data from laboratory-scale (bio)electroconcentration ((B)EC) experiments was used to construct a simple, semi-empirical model block integrated into the Benchmark Simulation Model No. 2 (BSM2) simulating a generalised WWTP. The effects of nitrogen removal from the reject water on both the effluent quality and operational costs of the WWTP were assessed and compared to the BSM2 performance without an NRR unit. In all studied scenarios, the effluent quality index was improved by 4-11%, while both the aeration (7-19% decrease) and carbon (24-71%) requirements were reduced. The additional energy consumed by the NRR unit increased the total operational cost index by >18%, but the revenue assumed for the generated nutrient product (20 EUR kg_N^-1) was enough to make the BEC-NRR scenarios at realistically low current densities (1 and 5 A m^-2) economically attractive compared to the control. A sensitivity analysis revealed that electricity price and nutrient product value had the most notable effects on the feasibility of the NRR unit. The results suggest a key factor in making (bio)electrochemical NRR economically viable is to reduce its electricity consumption further, while the anticipated increases in nitrogen fertiliser prices can help accelerate the adoption of these methods in larger scale.

Mass and heat balances for biological nitrogen removal in an activated sludge process: to couple or not to couple?

Models adapt constantly, usually increasing the degree of detail describing physical phenomena. In water resource recovery facilities, models based on mass and/or heat balances have been used to describe and improve operation. While both mass and heat balances have proven their worth individually, the question arises to which extent their coupling, which entails increased model complexity, warrants the supposedly more precise simulation results. In order to answer this question, the need for and effects of coupling mass and heat balances in modelling studies were evaluated in this work for a biological nitrogen removal process treating highly concentrated wastewater. This evaluation consisted on assessing the effect of the coupling of mass and heat balances on the prediction of: (1) nitrogen removal efficiency; (2) temperature; (3) heat recovery. In general, mass balances are sufficient for evaluating nitrogen removal efficiency and effluent nitrogen concentrations. If one desires to evaluate the effect of temperature changes (e.g. daily, weekly, seasonally) on nitrogen removal efficiency, the use of temperature profiles as an input variable to a mass balance-based model is recommended over the coupling of mass and heat balances. In terms of temperature prediction, considering a constant biological heat generation term in the heat balance model provides sufficient information - i.e. without the coupling of mass and heat balances. Also, for evaluating the heat recovery potential of the system, constant biological heat generation values provide valuable information, at least under normal operating conditions, i.e. when the solids retention time is large enough to maintain nitrification.

Evaluation of Control Strategies in Activated Sludge Process for Biological Wastewater Treatment

In this paper, benchmark simulation model no.1 (BSM1) of an activated sludge process is used to evaluate various control strategies. Control configurations such as feedback control and feed-forward plus feedback (FF-FB) control are applied and compared with respect to effluent discharge requirements under specified constraints and operating costs. Feed-forward control is incorporated in the PI control configuration for preventing the influent loading disturbance affecting the process. 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 influent load data are collected during the dry weather period. The influent fractionation is carried out using the activated sludge model no.1 (ASM1). The results of the dynamic simulation indicate that FF-FB control of the activated sludge process is more effective than feedback control in meeting the constraints, especially effluent ammonia concentration which is considered as very important. From the comparison of performance evaluation criteria, it is observed that FF-FB control has achieved almost the same operating costs as with feedback control.

Calibration and validation of a phenomenological influent pollutant disturbance scenario generator using full-scale data

The objective of this paper is to demonstrate the full-scale feasibility of the phenomenological dynamic influent pollutant disturbance scenario generator (DIPDSG) that was originally used to create the influent data of the International Water Association (IWA) Benchmark Simulation Model No. 2 (BSM2). In this study, the influent characteristics of two large Scandinavian treatment facilities are studied for a period of two years. A step-wise procedure based on adjusting the most sensitive parameters at different time scales is followed to calibrate/validate the DIPDSG model blocks for: 1) flow rate; 2) pollutants (carbon, nitrogen); 3) temperature; and, 4) transport. Simulation results show that the model successfully describes daily/weekly and seasonal variations and the effect of rainfall and snow melting on the influent flow rate, pollutant concentrations and temperature profiles. Furthermore, additional phenomena such as size and accumulation/flush of particulates of/in the upstream catchment and sewer system are incorporated in the simulated time series. Finally, this study is complemented with: 1) the generation of additional future scenarios showing the effects of different rainfall patterns (climate change) or influent biodegradability (process uncertainty) on the generated time series; 2) a demonstration of how to reduce the cost/workload of measuring campaigns by filling the gaps due to missing data in the influent profiles; and, 3) a critical discussion of the presented results balancing model structure/calibration procedure complexity and prediction capabilities.

Monitoring and modelling to support wastewater system management in developing mega-cities

Urban drainage system models can be useful to assess and manage system performance and to plan its development. However, due to data and computational costs, sophisticated, high-resolution contemporary models of the sewer system may not be applicable. This constraint is particularly marked in developing country mega-cities where catchments can be large, data tend to be scarce, and there are many unknowns, for example regarding sources, losses and wrong connections. This paper presents work undertaken over the last 7 years to develop a suitable monitoring and modelling framework to support operation and development of the wastewater system of Bogotá (Colombia). Components of the framework covered here are: (a) the flow and water quality database, (b) a wastewater pollution load generator, and (c) a semi-distributed sewer network model, which aims at a complexity that matches the information available from the previous two components. Results from a catchment within Bogotá, area 150 km(2) and with 2.5 million inhabitants, show that the model outputs capture the scale and dynamics of the observed concentrations and loads at various points on the sewer system. However uncertainty is high because much of variability of observed dry weather flow profiles is apparently random. Against this variability, the effects of in-sewer processes were not identifiable except where backwaters caused particularly high retention times. Hence the work has resulted in an operational model with a scientifically justified, yet useful, level of complexity for Bogotá. More generally, the work demonstrates the value of monitoring and modelling programmes, including having modellers actively involved in monitoring specification and operations; and the insights into suitable level of model complexity that may be gained by uncertainty and sensitivity analysis.

ICA and me--a subjective review

ICA - instrumentation, control and automation - is a hidden technology. It is ubiquitous in all industrial processes, including water and wastewater treatment systems. Still, as long as everything works fine, it is not noted but when things go wrong it will be observed. ICA has now about forty years of history in water and wastewater systems and is well recognized. One early attitude was that ICA will be a necessary burden to be added to a plant in order to correct for a poor design. However, the key reason for ICA is the fact that all processes are subject to disturbances, externally via the wastewater influent, from the customers in a water supply system, or from operations in one unit process that will propagate as a disturbance to another unit within a plant. This paper is an attempt to describe the development of ICA in water and wastewater systems. Most of it is based on personal experiences with all their limitations. No single paper can fairly describe the development that is documented in thousands of research papers, practiced by so many operators and process engineers and implemented in so many treatment systems. Still, the hope is that the paper can give a flavour of the most important ingredients of this fascinating development.

Including greenhouse gas emissions during benchmarking of wastewater treatment plant control strategies

The main objective of this paper is to demonstrate how greenhouse gas (GHG) emissions can be quantified during the evaluation of control strategies in wastewater treatment plants (WWTP). A modified version of the IWA Benchmark Simulation Model No 2 (BSM2G) is hereby used as a simulation case study. Thus, the traditional effluent quality index (EQI), operational cost index (OCI) and time in violation (TIV) used to evaluate control strategies in WWTP are complemented with a new dimension dealing with GHG emissions. The proposed approach is based on a set of comprehensive models that estimate all potential on-site and off-site sources of GHG emissions. The case study investigates the overall performance of several control strategies and demonstrates that substantial reductions in effluent pollution, operating costs and GHG emissions can be achieved when automatic control is implemented. Furthermore, the study is complemented with a scenario analysis that examines the role of i) the dissolved oxygen (DO) set-point, ii) the sludge retention time (SRT) and iii) the organic carbon/nitrogen ratio (COD/N) as promoters of GHG emissions. The results of this study show the potential mechanisms that promote the formation of CO2, CH4 and N2O when different operational strategies are implemented, the existing synergies and trade-offs amongst the EQI, the OCI and TIV criteria and finally the need to reach a compromise solution to achieve an optimal plant performance.

Multiple-objective evaluation of wastewater treatment plant control alternatives

Besides the evaluation of the environmental issues, the correct assessment of wastewater treatment plants (WWTP) should take into account several objectives such as: economic e.g. operation costs; technical e.g. risk of suffering microbiology-related TSS separation problems; or legal e.g. accomplishment with the effluent standards in terms of the different pollution loads. For this reason, the main objective of this paper is to show the benefits of complementing the environmental assessment carried out by life cycle assessment with economical, technical and legal criteria. Using a preliminary version of the BSM2 as a case study, different combinations of controllers are implemented, simulated and evaluated. In the following step, the resulting multi-criteria matrix is mined using multivariate statistical techniques. The results showed that the presence of an external carbon source addition, the type of aeration system and the TSS controller are the key elements creating the differences amongst the alternatives. Also, it was possible to characterize the different control strategies according to a set of aggregated criteria. Additionally, the existing synergies amongst different objectives and their consequent trade-offs were identified. Finally, it was discovered that from the initial extensive list of evaluation criteria, only a small set of five are really discriminant, being useful to differentiate within the generated alternatives.

Including the effects of filamentous bulking sludge during the simulation of wastewater treatment plants using a risk assessment model

The main objective of this paper is to demonstrate how including the occurrence of filamentous bulking sludge in a secondary clarifier model will affect the predicted process performance during the simulation of WWTPs. The IWA Benchmark Simulation Model No. 2 (BSM2) is hereby used as a simulation case study. Practically, the proposed approach includes a risk assessment model based on a knowledge-based decision tree to detect favourable conditions for the development of filamentous bulking sludge. Once such conditions are detected, the settling characteristics of the secondary clarifier model are automatically changed during the simulation by modifying the settling model parameters to mimic the effect of growth of filamentous bacteria. The simulation results demonstrate that including effects of filamentous bulking in the secondary clarifier model results in a more realistic plant performance. Particularly, during the periods when the conditions for the development of filamentous bulking sludge are favourable--leading to poor activated sludge compaction, low return and waste TSS concentrations and difficulties in maintaining the biomass in the aeration basins--a subsequent reduction in overall pollution removal efficiency is observed. Also, a scenario analysis is conducted to examine i) the influence of sludge retention time (SRT), the external recirculation flow rate (Q(r)) and the air flow rate in the bioreactor (modelled as k(L)a) as factors promoting bulking sludge, and ii) the effect on the model predictions when the settling properties are changed due to a possible proliferation of filamentous microorganisms. Finally, the potentially adverse effects of certain operational procedures are highlighted, since such effects are normally not considered by state-of-the-art models that do not include microbiology-related solids separation problems.

A time series model for influent temperature estimation: application to dynamic temperature modelling of an aerated lagoon

Thirty-nine linear regression and time series models were built and calibrated for influent temperature (Ti) estimation at the primary aerated facultative lagoon in a municipal wastewater treatment plant. The models were based on mean daily ambient air temperature (Ta) and/or daily rainfall (P), and-optionally-wastewater temperature autoregression. The best fits were achieved with some time series models involving Ta and P, and Ti autoregression. The best-fit model was able to estimate influent temperature with a root-mean-square-error of 0.5 degrees C, and an R2 of 0.925, for the calibration period of 10.5 months. In addition, a dynamic lagoon-temperature (Tw) model from the literature was modified in its terms of solar radiation and aeration latent heat, and applied to the primary lagoon. The model was fed with the estimated influent temperature, and five model parameters were identified by calibration against 10.5-month Tw data. Dynamic lagoon-temperature estimation results were comparable to or better than other results of long-term simulations found in the literature. Sensitivity analyses were run on both models. Further validation with independent sets of data is needed for verification of the predictive capability of the models.