Model of an aquaponic system for minimised water, energy and nitrogen requirements.

Water and nutrient savings can be established by coupling water streams between interacting processes. Wastewater from production processes contains nutrients like nitrogen (N), which can and should be recycled in order to meet future regulatory discharge demands. Optimisation of interacting water systems is a complex task. An effective way of understanding, analysing and optimising such systems is by applying mathematical models. The present modelling work aims at supporting the design of a nearly emission-free aquaculture and hydroponic system (aquaponics), thus contributing to sustainable production and to food security for the 21st century. Based on the model, a system that couples 40 m(3) fish tanks and a hydroponic system of 1,000 m(2) can produce 5 tons of tilapia and 75 tons of tomato yearly. The system requires energy to condense and recover evaporated water, for lighting and heating, adding up to 1.3 GJ/m(2) every year. In the suggested configuration, the fish can provide about 26% of the N required in a plant cycle. A coupling strategy that sends water from the fish to the plants in amounts proportional to the fish feed input, reduces the standard deviation of the NO3(-) level in the fish cycle by 35%.

The urban harvest approach as framework and planning tool for improved water and resource cycles.

Water and resource availability in sufficient quantity and quality for anthropogenic needs represents one of the main challenges in the coming decades. To prepare for upcoming challenges such as increased urbanization and climate change related consequences, innovative and improved resource management concepts are indispensable. In recent years we have developed and applied the urban harvest approach (UHA). The UHA aims to model and quantify the urban water cycle on different temporal and spatial scales. This approach allowed us to quantify the impact of the implementation of water saving measures and new water treatment concepts in cities. In this paper we will introduce the UHA and its application for urban water cycles. Furthermore, we will show first results for an extension to energy cycles and highlight future research items (e.g. nutrients, water-energy-nexus).

Selective particle separation on centimeter scale using a dual frequency dynamic acoustic field.

This study investigated the application of dual-frequency type dynamic acoustic fields for size-selective particle separation on centimeter scale in a continuous flow. The 3D-printed X-shaped prototype has two inlets and two outlets. The dynamic acoustic field is generated by two transducers positioned under an angle of 60° and operating at slightly different frequencies. The acoustic reflections are eliminated by placing sound-absorbing material inside the prototype and the non-resonant operation is confirmed by the electrical admittance measurements. Numerical calculations suggested that pressure generated by each transducer does not need to have equal amplitude. Computer simulations and lab experiments were carried out for different frequency differences and flow rates. The results demonstrated the ability of dual-frequency dynamic acoustic fields for size-selective particle filtration on centimeter scale, with a total flow rate up to.1Lh-1.

Linear parameter estimation of rational biokinetic functions.

For rational biokinetic functions such as the Michaelis-Menten equation, in general, a nonlinear least-squares method is a good estimator. However, a major drawback of a nonlinear least-squares estimator is that it can end up in a local minimum. Rearranging and linearizing rational biokinetic functions for parameter estimation is common practice (e.g. Lineweaver-Burk linearization). By rearranging, however, the error is distorted. In addition, the rearranged model frequently leads to a so-called 'errors-in-variables' estimation problem. Applying the ordinary least squares (OLS) method to the linearly reparameterized function ensures a global minimum, but its estimates become biased if the regression variables contain errors and thus bias compensation is needed. Therefore, in this paper, a bias compensated total least squares (CTLS) method, which as OLS is a direct method, is proposed to solve the estimation problem. The applicability of a general linear reparameterization procedure and the advances of CTLS over ordinary least squares and nonlinear least squares approaches are shown by two simulation examples. The examples contain Michaelis-Menten kinetics and enzyme kinetics with substrate inhibition. Furthermore, CTLS is demonstrated with real data of an activated sludge experiment. It is concluded that for rational biokinetic models CTLS is a powerful alternative to the existing least-squares methods.

Dynamic modeling of sludge compaction and consolidation processes in wastewater secondary settling tanks.

The double exponential settling model is the widely accepted model for wastewater secondary settling tanks. However, this model does not estimate accurately solids concentrations in the settler underflow stream, mainly because sludge compression and consolidation processes are not considered. In activated sludge systems, accurate estimation of the solids in the underflow stream will facilitate the calibration process and can lead to correct estimates of particularly kinetic parameters related to biomass growth. Using principles of compaction and consolidation, as in soil mechanics, a dynamic model of the sludge consolidation processes taking place in the secondary settling tanks is developed and incorporated to the commonly used double exponential settling model. The modified double exponential model is calibrated and validated using data obtained from a full-scale wastewater treatment plant. Good agreement between predicted and measured data confirmed the validity of the modified model.

Selective Particle Filtering in a Large Acoustophoretic Serpentine Channel.

The objective of this study is to investigate the performance of a serpentine channel for acoustically driven selective particle filtering. The channel consists of sharp corners and straight sections, and the acoustic field is affecting the particles throughout the channel. A prototype of the separator channel is manufactured using 3D printing. Acoustic waves are generated by a piezoelectric transducer operating near 2 MHz. Computer simulations are carried out to explore and visualize the flow field and acoustic field in the separator. Selective particle trapping is aimed to be achieved in the hairpin sections, which is confirmed by experiments. Spherical polyethylene particles of 34 µm, 70 µm and 100 µm diameter are used to demonstrate selective trapping by adjusting the flow rate in the channel or voltage input to the transducer. In addition, wheat beer containing yeast up to 20 µm size is selectively filtered by adjusting the flow rate to the channel. Experiments demonstrate that selective particle filtering is possible in the serpentine channel as both methods yield clear separation thresholds.

On-line estimation of the dissolved zinc concentration during ZnS precipitation in a continuous stirred tank reactor (CSTR).

In this paper a method is presented to estimate the reaction term of zinc sulphide precipitation and the zinc concentration in a CSTR, using the read-out signal of a sulphide selective electrode. The reaction between zinc and sulphide is described by a non-linear model and therefore classical observer theory cannot be applied directly, as this theory was initially developed for linear systems. However, by linear reparametrization of this non-linear system, the linear observer theory can be applied in an effective way. This is illustrated by a zinc sulphide example using real data.

Production ecology of agroforestry systems: a minimal mechanistic model and analytical derivation of the land equivalent ratio.

In this paper, the yield and the land equivalent ratio (LER) of a silvo-arable agroforestry (SAF) system, containing one tree and one crop species, is analyzed analytically using a minimal mechanistic model describing the system dynamics. Light competition between tree and crop is considered using light extinction functions. The tree leaf area is driven by annual increase in the number of leaf-bearing shoots with a seasonal cycle of bud burst, leaf expansion and senescence. The crop leaf area dynamics is driven by the solar radiation, heat sum and the dry matter allocation to the leaves. As a consequence of this, the model consists of six state equations expressing the temporal dynamics of: (1) tree biomass; (2) tree leaf area; (3) number of shoots per tree; (4) crop biomass; (5) crop leaf area index, and (6) heat sum. The main outputs of the model are the growth dynamics and final yields of trees and crops. Daily inputs are temperature and radiation. Planting densities, initial biomass of tree and crop species and growth parameters must be specified. The main parameters are those describing light interception, conversion to dry matter and leaf area. Given the crop cover and the tree parameters, it is shown that under potential growing conditions the land equivalent ratio can be explicitly expressed in terms of these parameters.

Theory of pH changes in water desalination by capacitive deionization.

In electrochemical water desalination, a large difference in pH can develop between feed and effluent water. These pH changes can affect the long-term stability of membranes and electrodes. Often Faradaic reactions are implicated to explain these pH changes. However, quantitative theory has not been developed yet to underpin these considerations. We develop a theory for electrochemical water desalination which includes not only Faradaic reactions but also the fact that all ions in the water have different mobilities (diffusion coefficients). We quantify the latter effect by microscopic physics-based modeling of pH changes in Membrane Capacitive Deionization (MCDI), a water desalination technology employing porous carbon electrodes and ion-exchange membranes. We derive a dynamic model and include the following phenomena: I) different mobilities of various ions, combined with acid-base equilibrium reactions; II) chemical surface charge groups in the micropores of the porous carbon electrodes, where electrical double layers are formed; and III) Faradaic reactions in the micropores. The theory predicts small pH changes during desalination cycles in MCDI if we only consider phenomena I) and II), but predicts that these pH changes can be much stronger if we consider phenomenon III) as well, which is in line with earlier statements in the literature on the relevance of Faradaic reactions to explain pH fluctuations.

Forward and backward uncertainty propagation: an oxidation ditch modelling example.

In the field of water technology, forward uncertainty propagation is frequently used, whereas backward uncertainty propagation is rarely used. In forward uncertainty analysis, one moves from a given (or assumed) parameter subspace towards the corresponding distribution of the output or objective function. However, in the backward uncertainty propagation, one moves in the reverse direction, from the distribution function towards the parameter subspace. Backward uncertainty propagation, which is a generalisation of parameter estimation error analysis, gives information essential for designing experimental or monitoring programmes, and for tighter bounding of parameter uncertainty intervals. The procedure of carrying out backward uncertainty propagation is illustrated in this technical note by working example for an oxidation ditch wastewater treatment plant. Results obtained have demonstrated that essential information can be achieved by carrying out backward uncertainty propagation analysis.

Oxygen transfer rate estimation in oxidation ditches from clean water measurements.

Standard methods for the determination of oxygen transfer rate are based on assumptions that are not valid for oxidation ditches. This paper presents a realistic and simple new method to be used in the estimation of oxygen transfer rate in oxidation ditches from clean water measurements. The new method uses a loop-of-CSTRs model, which can be easily incorporated within control algorithms, for modelling oxidation ditches. Further, this method assumes zero oxygen transfer rates (KLa) in the unaerated CSTRs. Application of a formal estimation procedure to real data revealed that the aeration constant (k = KLaVA, where VA is the volume of the aerated CSTR) can be determined significantly more accurately than KLa and VA. Therefore, the new method estimates k instead of KLa. From application to real data, this method proved to be more accurate than the commonly used Dutch standard method (STORA, 1980).

Optimal parametric sensitivity control for the estimation of kinetic parameters in bioreactors.

In this paper the well-known problem of optimal input design is considered. In particular, the focus is on input design for the estimation of kinetic parameters in bioreactors. The problem is formulated as follows: given the model structure (f,g), which is assumed to be affine in the input, and the specific parameter of interest theta;(k) find a feedback law that maximizes the sensitivity of the model output to the parameter under different flow conditions in the bioreactor and, possibly, minimize the input or state costs. Analytical solutions to these problems are presented. As an example a bioreactor with a biomass that grows according to the well-known Monod kinetics is considered.

Respirometry-based on-line model parameter estimation at a full-scale WWTP.

This paper describes part of a project to develop a systematic approach to knowledge extraction from on-line respirometric measurements in support of wastewater treatment plant control and operation. The paper deals with the following issues: (1) test of the implementation of an automatic set-up consisting of a continuous laboratory respirometer integrated in a mobile trailer with sampling and dosing equipment, and data-acquisition and communication system; (2) assessment of activated sludge/sewage characteristics from sludge respirograms by model parameter estimation; (3) comparison of the parameter estimates with regular plant data and information obtained from supplementary wastewater respirograms. The paper describes the equipment and some of its measuring results from a period of one week at a large-scale wastewater treatment plant. The measurements were evaluated in terms of the common activated sludge modelling practice. The automatic set-up allowed reliable measurements during at least one week. The data were used to calibrate two different version of the model, and independent parameter estimates were obtained.

Parameter estimation procedure for complex non-linear systems: calibration of ASM No. 1 for N-removal in a full-scale oxidation ditch.

When applied to large simulation models, the process of parameter estimation is also called calibration. Calibration of complex non-linear systems, such as activated sludge plants, is often not an easy task. On the one hand, manual calibration of such complex systems is usually time-consuming, and its results are often not reproducible. On the other hand, conventional automatic calibration methods are not always straightforward and often hampered by local minima problems. In this paper a new straightforward and automatic procedure, which is based on the response surface method (RSM) for selecting the best identifiable parameters, is proposed. In RSM, the process response (output) is related to the levels of the input variables in terms of a first- or second-order regression model. Usually, RSM is used to relate measured process output quantities to process conditions. However, in this paper RSM is used for selecting the dominant parameters, by evaluating parameters sensitivity in a predefined region. Good results obtained in calibration of ASM No. 1 for N-removal in a full-scale oxidation ditch proved that the proposed procedure is successful and reliable.

Evaluation of control strategies using an oxidation ditch benchmark.

This paper presents validation and implementation results of a benchmark developed for a specific full-scale oxidation ditch wastewater treatment plant. A benchmark is a standard simulation procedure that can be used as a tool in evaluating various control strategies proposed for wastewater treatment plants. It is based on model and performance criteria development. Testing of this benchmark, by comparing benchmark predictions to real measurements of the electrical energy consumptions and amounts of disposed sludge for a specific oxidation ditch WWTP, has shown that it can (reasonably) be used for evaluating the performance of this WWTP. Subsequently, the validated benchmark was then used in evaluating some basic and advanced control strategies. Some of the interesting results obtained are the following: (i) influent flow splitting ratio, between the first and the fourth aerated compartments of the ditch, has no significant effect on the TN concentrations in the effluent, and (ii) for evaluation of long-term control strategies, future benchmarks need to be able to assess settlers' performance.

Sulfide response analysis for sulfide control using a pS electrode in sulfate reducing bioreactors.

Step changes in the organic loading rate (OLR) through variations in the influent chemical oxygen demand (CODin) concentration or in the hydraulic retention time (HRT) at constant COD/SO4(2-) ratio (0.67) were applied to create sulfide responses for the design of a sulfide control in sulfate reducing bioreactors. The sulfide was measured using a sulfide ion selective electrode (pS) and the values obtained were used to calculate proportional-integral-derivative (PID) controller parameters. The experiments were performed in an inverse fluidized bed bioreactor with automated operation using the LabVIEW software version 2009(®). A rapid response and high sulfide increment was obtained through a stepwise increase in the CODin concentration, while a stepwise decrease to the HRT exhibited a slower response with smaller sulfide increment. Irrespective of the way the OLR was decreased, the pS response showed a time-varying behavior due to sulfide accumulation (HRT change) or utilization of substrate sources that were not accounted for (CODin change). The pS electrode response, however, showed to be informative for applications in sulfate reducing bioreactors. Nevertheless, the recorded pS values need to be corrected for pH variations and high sulfide concentrations (>200 mg/L).

Selective precipitation of Cu from Zn in a pS controlled continuously stirred tank reactor.

Copper was continuously and selectively precipitated with Na(2)S to concentrations below 0.3 ppb from water containing around 600 ppm of both Cu and Zn in a Continuously Stirred Tank Reactor. The pH was controlled at 3 and the pS at 25 (pS=-log(S(2-))) by means of an Ag(2)S sulfide selective electrode. Copper's recovery and purity were about 100%, whereas the total soluble sulfide concentration was below 0.02 ppm. X-ray diffraction (XRD) analysis showed that copper precipitated as hexagonal CuS (covellite). The mode of the particle size distribution (PSD) of the CuS precipitates was around 36 microm. The PSD increased by high pS values and by the presence of Zn. Depending on the turbulence, the CuS precipitates can grow up to 200 microm or fragment in particles smaller than 3 microm in a few seconds. Zn precipitation with Na(2)S at pH 3 and 4, in batch, always lead to Zn concentrations above 1 ppm. Zn precipitated as cubic ZnS (spharelite).

Endogenous model state and parameter estimation from an extensive batch experiment.

In this paper an extensive batch experiment of endogenous process behavior in an aerobic biodegradation process is presented. From these experimental data, comprising measurements of MLVSS (mixed liquor volatile suspended solids) and respiration rate, in a first step the states and unknown parameters in a four-compartmental model are reconstructed analytically. Subsequently, for a selected set of states and parameters, using the results of the previous step, a recursive state estimation procedure, in particular an Extended Kalman filter-based observer, is applied to deal with the noise properties of the data appropriately. From this it appears that the initially proposed model structure, and especially the hydrolysis term, has to be modified.

Analysis of endogenous process behavior in activated sludge.

In this article, an autonomous four-compartment model that describes the endogenous respiration in an aerobic biodegradation process is proposed and analyzed theoretically. First, the multi-time scale of the system's behavior, to be taken into account in subsequent analyses, is emphasized. Then, an identifiability and observability study, given measurements of MLVSS (mixed liquor volatile suspended solids) and respiration rate, is performed for use under practical circumstances, such as in state and parameter estimation. It appears that the process is observable, but not fully identifiable. Hence, for the identification of some of the model parameters, additional measurements or experiments, also indicated here, have to be performed. Furthermore, it is shown that, under quasi-steady state conditions which, in general, appear shortly after initialization of an endogenous respiration experiment, the model can be reduced significantly. Finally, results of parameter estimation from available data are presented and discussed.