Adaptation in hindsight: dynamics and drivers shaping urban wastewater systems

Well-planned urban infrastructure should meet critical loads during its design lifetime. In order to proceed with design, engineers are forced to make numerous assumptions with very little supporting information about the development of various drivers. For the wastewater sector, these drivers include the future amount and composition of the generated wastewater, effluent requirements, technologies, prices of inputs such as energy or chemicals, and the value of outputs produced such as nutrients for fertilizer use. When planning wastewater systems, there is a lack of methods to address discrepancies between the timescales at which fundamental changes in these drivers can occur, and the long physical life expectancy of infrastructure (on the order of 25-80 years). To explore these discrepancies, we take a hindsight perspective of the long-term development of wastewater infrastructure and assess the stability of assumptions made during previous designs. Repeatedly we find that the drivers influencing wastewater loads, environmental requirements or technological innovation can change at smaller timescales than the infrastructure design lifetime, often in less than a decade. Our analysis shows that i) built infrastructure is continuously confronted with challenges it was not conceived for, ii) significant adaptation occurs during a structure's lifetime, and iii) "muddling-through" is the pre-dominant strategy for adaptive management. As a consequence, we argue, there is a need to explore robust design strategies which require the systematic use of scenario planning methods and instruments to increase operational, structural, managerial, institutional and financial flexibility. Hindsight studies, such as this one, may inform the development of robust design strategies and assist in the transition to more explicit forms of adaptive management for urban infrastructures.

Intermittent operation of ultra-low pressure ultrafiltration for decentralized drinking water treatment

River water was treated by ultrafiltration at a relatively low transmembrane pressure (40 mbar). As observed before, flux stabilization occurred after several days of operation although no back-flushing or cross flow was applied. Interruptions in flux were applied by temporary offset of the transmembrane pressure. After restoration of the transmembrane pressure, the initial flux was higher than the stable flux level, and the flux recovery depended on the standstill time. Furthermore, if a short cross flow was applied after standstill, the flux was restored to an even higher level. In all cases, the flux decreased again during operation to reach finally the same stable level as before standstill. In order to evaluate the influence of intermittent operation as practiced for water treatment on a household level, daily interruptions of flux were applied. An optimum of total daily water production rate was obtained at 21 h of operation and 3 h of standstill per day. A model was developed which can describe the impact of intermittent operation on the flux depending on the duration of the standstill and operating periods. This enables the prediction of production capacity of the system operated intermittently. The flux increase during standstill could be explained by a relaxation and expansion of the biofouling layer, while the higher flux after forward-flushing was caused by this layer being partially sloughed off. Household water treatment with the process presented here will generally be operated on a discontinuous basis. The results show that such operation schemes do not compromise the permeability of the system, but actually lead to higher fluxes after standstill.

Automatic reactor model synthesis with genetic programming

Successful modeling of wastewater treatment plant (WWTP) processes requires an accurate description of the plant hydraulics. Common methods such as tracer experiments are difficult and costly and thus have limited applicability in practice; engineers are often forced to rely on their experience only. An implementation of grammar-based genetic programming with an encoding to represent hydraulic reactor models as program trees should fill this gap: The encoding enables the algorithm to construct arbitrary reactor models compatible with common software used for WWTP modeling by linking building blocks, such as continuous stirred-tank reactors. Discharge measurements and influent and effluent concentrations are the only required inputs. As shown in a synthetic example, the technique can be used to identify a set of reactor models that perform equally well. Instead of being guided by experience, the most suitable model can now be chosen by the engineer from the set. In a second example, temperature measurements at the influent and effluent of a primary clarifier are used to generate a reactor model. A virtual tracer experiment performed on the reactor model has good agreement with a tracer experiment performed on-site.

Modelling biocide leaching from facades

Biocides leach from facades during rain events and subsequently enter the aquatic environment with storm water. Little is known about the losses of an entire settlement, since most studies referred to wash-off experiments conducted under laboratory conditions. Their results show a fast decrease of concentrations in the beginning, which subsequently slows down. The aim of this study is to develop a simple model to understand the mechanisms leading to these losses as well as to simulate losses under various rainfall and application conditions. We developed a four-box model based on the knowledge gained from fits of an exponential function to an existing experimental data set of a wash-off experiment. The model consists of two mobile stocks from which biocides are washed off during a rain event. These mobile stocks are supplied with biocides from storage stocks by diffusion-type processes. The model accurately reproduced the measured data of wash-off during single cycles as well as peak wash-offs over all cycles. Our model results for diuron losses showed that a large proportion (∼ 70%) of the applied biocides are still in the stocks even after a rain volume corresponding to several years (1100 mm y(-1), Swiss Plateau). Applications to realistic outdoor conditions showed that losses can not be neglected for urban environments and that knowledge about the amount of rainfall turned into runoff and the decay constants of the biocides in the facades are crucial. The model increased our understanding of the processes leading to the observed dynamic in laboratory experiments and was used to simulate losses for various rainfall and application conditions.

Using reactive tracers to detect flow field anomalies in water treatment reactors

The hydraulics of water and wastewater treatment reactors has a major impact on their performance and control. The residence time distribution as a measure for the hydraulics represents macroscopic mixing in an integrated way with no spatial information. However, with regard to optimal sensor location for process control and for process optimisation measures, spatial information about macro-mixing is helpful. Spatially distributed measurements of reactive tracers can provide this information. In this paper we generally discuss how reactive tracers can be used to detect and characterize distinct large scale flow structures. It is shown that tracer substances are particularly suited if their reaction time scale is similar to the time scale of the large scale flow structure. For nitrifying activated sludge systems, ammonium is identified to be a suitable tracer. In a comprehensive experimental study at a real aeration tank, two distinct large scale flow features were identified by distributed ammonium measurements. Flow velocity measurements using acoustic Doppler velocimetry clearly supported the nature of these flow field anomalies. Ion-selective electrodes are a well suited device for ammonium measurements providing the temporal resolution that is needed for such an analysis.

Identification of industrial wastewater by clustering wastewater treatment plant influent ultraviolet visible spectra

A procedure is proposed which allows the detection of industrial discharge events at the inlet of a wastewater treatment plant without the need for measurements performed at the industry, for special equipment and for exact knowledge of the industrial sewage. By performing UV/Vis measurements at the inlet of a plant and analyzing them with a two-staged clustering method consisting of the self-organizing map algorithm and the Ward clustering method, typical sewage clusters can be found. In an experiment performed at a mid-sized Swiss plant, one cluster of a cluster model with five clusters could be attributed to an industrial laundry. Out of 95 laundry discharging events measured in a validation period, 93 were correctly detected by the proposed algorithm, two were false positives and five were false negatives.

Effects of aeration patterns on the flow field in wastewater aeration tanks

Due to the high energy input of aeration, the spatial distribution of air diffusers largely determines the flow field in aeration tanks. This has consequences on the efficiency of the aeration system, the performance of the aeration tank and on tank operation and control. This paper deals with these effects applying both Computational Fluid Dynamics (CFD) enhanced with a biokinetic model and full scale validation using velocity and reactive tracer measurements with high temporal and spatial resolution. It is shown that small changes in the diffuser arrangement drastically change the overall flow field. Using different aeration patterns in the same tank may lead to large scale instabilities in the flow field that lower plant performance and produce strong variations in concentration signals impeding their use for plant control. CFD is a valuable tool to analyze the interaction of flow field and aeration and their effects on plant performance and operation. But, in complex flow situations experimental validation is needed and strongly suggested.

Is modeling of biological wastewater treatment a mature technology?

Based on three case studies it is demonstrated that the application of mathematical models in biological wastewater treatment has not yet reached its full potential. Model structure uncertainty and correlation of uncertain parameter values make up the first case. The combination of biokinetic and hydraulic models relates to the second case. The evolution of a full scale plant over its life expectancy is the frame for the third case. This paper was initially presented as a discussion starter and thus is raising questions rather than providing answers.

Global sensitivity analysis in wastewater treatment plant model applications: prioritizing sources of uncertainty

This study demonstrates the usefulness of global sensitivity analysis in wastewater treatment plant (WWTP) design to prioritize sources of uncertainty and quantify their impact on performance criteria. The study, which is performed with the Benchmark Simulation Model no. 1 plant design, complements a previous paper on input uncertainty characterisation and propagation (Sin et al., 2009). A sampling-based sensitivity analysis is conducted to compute standardized regression coefficients. It was found that this method is able to decompose satisfactorily the variance of plant performance criteria (with R(2) > 0.9) for effluent concentrations, sludge production and energy demand. This high extent of linearity means that the plant performance criteria can be described as linear functions of the model inputs under the defined plant conditions. In effect, the system of coupled ordinary differential equations can be replaced by multivariate linear models, which can be used as surrogate models. The importance ranking based on the sensitivity measures demonstrates that the most influential factors involve ash content and influent inert particulate COD among others, largely responsible for the uncertainty in predicting sludge production and effluent ammonium concentration. While these results were in agreement with process knowledge, the added value is that the global sensitivity methods can quantify the contribution of the variance of significant parameters, e.g., ash content explains 70% of the variance in sludge production. Further the importance of formulating appropriate sensitivity analysis scenarios that match the purpose of the model application needs to be highlighted. Overall, the global sensitivity analysis proved a powerful tool for explaining and quantifying uncertainties as well as providing insight into devising useful ways for reducing uncertainties in the plant performance. This information can help engineers design robust WWTP plants.

Struvite precipitation from urine - Influencing factors on particle size

Struvite crystallisation is a fast and reliable phosphorus removal and recovery process for concentrated waste streams - such as hydrolysed human urine. In order to optimise P-elimination efficiency, it is beneficial to obtain larger particle sizes: they are easier to separate and less prone to wash-out than smaller particles. This paper presents the results of a study on the effect of process parameters on particle size in a single step struvite precipitation. Crystals formed in batch experiments with real hydrolysed urine were shown to have an average size of >90 microm at pH 9 and 20 degrees C. This is reduced to 45 microm when changing stirrer type. Particle size increases with lower supersaturation. The results showed that under otherwise constant conditions, particle size decreases with lower temperature and has a minimum between pH 9 and 10. Deviating trends are observed at pH <8. Struvite formation in a CSTR (continuously stirred tank reactor) process was shown to be a reliable stable process that does not require any pH control. A method based on conductivity measurement is presented to estimate ionic strength, which is needed for equilibrium calculations.

Nitrification and me - a subjective review

Based on the subjective experience of the author it is discussed how the nitrification processes served as an important basis for the development of today's understanding and mathematical models for many wastewater treatment processes (activated sludge, biofilm reactors) and self-purification processes in rivers. Besides being an important process for the protection of receiving waters, nitrification served as a proxy for the understanding of the behavior of a narrowly defined group of microorganisms growing on known substrates under environmental conditions. Until the upcoming of readily available microbial genetic techniques, nitrification was the single most studied microbial process in environmental engineering.

The role of the flow pattern in wastewater aeration tanks

Reactor hydraulics is one of the key factors for plant performance and plant control. The residence time distribution is a good but limited indicator of reactor hydraulics. A more detailed view is obtained by direct observations within the reactor. Two different techniques (conservative tracer, reactive tracer) are discussed to detect major anomalies in the flow field of a wastewater aeration tank. Experiments with conservative tracers give valuable information over a very limited period of time making the analysis of the flow field difficult. On the other hand, reactive tracers can be monitored long term which helps identifying the flow pattern provided that a high spatial and temporal resolution of the measurements is applied. Experimental data is used to determine the structure and the parameters of a compartment model that corresponds well with the measurements.

Uncertainty analysis in WWTP model applications: a critical discussion using an example from design

This study focuses on uncertainty analysis of WWTP models and analyzes the issue of framing and how it affects the interpretation of uncertainty analysis results. As a case study, the prediction of uncertainty involved in model-based design of a wastewater treatment plant is studied. The Monte Carlo procedure is used for uncertainty estimation, for which the input uncertainty is quantified through expert elicitation and the sampling is performed using the Latin hypercube method. Three scenarios from engineering practice are selected to examine the issue of framing: (1) uncertainty due to stoichiometric, biokinetic and influent parameters; (2) uncertainty due to hydraulic behaviour of the plant and mass transfer parameters; (3) uncertainty due to the combination of (1) and (2). The results demonstrate that depending on the way the uncertainty analysis is framed, the estimated uncertainty of design performance criteria differs significantly. The implication for the practical applications of uncertainty analysis in the wastewater industry is profound: (i) as the uncertainty analysis results are specific to the framing used, the results must be interpreted within the context of that framing; and (ii) the framing must be crafted according to the particular purpose of uncertainty analysis/model application. Finally, it needs to be emphasised that uncertainty analysis is no doubt a powerful tool for model-based design among others, however clear guidelines for good uncertainty analysis in wastewater engineering practice are needed.

Compartmental models for continuous flow reactors derived from CFD simulations

Reactor modeling is of major interest in environmental technology. In this context, new contaminants with higher degradation requirements increase the importance of reactor hydraulics. CFD (Computational Fluid Dynamics) may meet this challenge but is expensive for everyday use. In this paper, we provide research and practice with a methodology designed to automatically reduce the complexity of such a high-dimensional flow model to a compartmental model. The derivation is based on the concentration field of a reacting species which is included in the steady state CFD simulation. While still capturing the most important flow features, the compartmental model is fast, easy to use, and open for process modeling with yet unknown compounds. The inherent overestimation of diffusion by compartmental models has been corrected by locally adjusting turbulent fluxes. We successfully applied the methodology to the ozonation process and experimentally verified it with tracer experiments. The loss of information was quantified as a deviation from CFD performance prediction for different reactions. With increasing discretisation of the compartmental model, these deviations diminish. General advice on the necessary discretisation is given.

Global sensitivity analysis for model-based prediction of oxidative micropollutant transformation during drinking water treatment

This study quantifies the uncertainty involved in predicting micropollutant oxidation during drinking water ozonation in a pilot plant reactor. The analysis is conducted for geosmin, methyl tert-butyl ether (MTBE), isopropylmethoxypyrazine (IPMP), bezafibrate, beta-cyclocitral and ciprofloxazin. These compounds are representative for a wide range of substances with second order rate constants between 0.1 and 1.9x10(4)M(-1)s(-1) for the reaction with ozone and between 2x10(9) and 8x10(9)M(-1)s(-1) for the reaction with OH-radicals. Uncertainty ranges are derived for second order rate constants, hydraulic parameters, flow- and ozone concentration data, and water characteristic parameters. The uncertain model factors are propagated via Monte Carlo simulation and the resulting probability distributions of the relative residual micropollutant concentrations are assessed. The importance of factors in determining model output variance is quantified using Extended Fourier Amplitude Sensitivity Testing (Extended-FAST). For substances that react slowly with ozone (MTBE, IPMP, geosmin) the water characteristic R(ct)-value (ratio of ozone- to OH-radical concentration) is the most influential factor explaining 80% of the output variance. In the case of bezafibrate the R(ct)-value and the second order rate constant for the reaction with ozone each contribute about 30% to the output variance. For beta-cyclocitral and ciprofloxazin (fast reacting with ozone) the second order rate constant for the reaction with ozone and the hydraulic model structure become the dominating sources of uncertainty.

Underestimation of uncertainty in statistical regression of environmental models: influence of model structure uncertainty

As the quality of sensors increases, systematic discrepancies between measurements and model outputs become more apparent Applying regression type analysis in these cases leads to autocorrelated residuals, biased parameter estimates, and underestimation of uncertainty. This paper examines how parameter estimates are affected by model structure uncertainty for an application from wastewater treatment. A Monod model is fitted to synthetic data generated by a reference system exhibiting predefined Tessier kinetics and a known error process. A range of methods are suggested to test if the resulting residuals fulfill the IID (independent and identically distributed)-requirement visual examination of time series, autocorrelation, and partial autocorrelation functions, the Jarque-Bera normality test, the Runs test for independence, and the BDS test for IID. The tests are shown to perform well at low measurement noise but not at higher levels of noise where transferring the parameter estimates gained from a batch system leads to erroneous estimation of steady state concentrations in a completely stirred tank reactor. Additional diagnostics are suggested which include second order autocorrelation functions of the residuals in the case of a single experiment and examination of moving averages of residuals in the case of multiple experiments.

Reactive tracers reveal hydraulic and control instabilities in full-scale activated sludge plant

The hydraulic characteristics of aeration tanks in WWTPs have a major impact on the degradation of pollutants, as well as on the control of the aeration. In particular in long reactors, which are not separated by baffles, hydraulic shortcuts or large scale recirculation can lead to a loss of performance. This work demonstrates that reactive tracers such as ammonium and oxygen can be used to investigate the hydraulics of aeration tanks in detail. With the use of electrochemical sensors it is possible to investigate effects in a broad range of time scales. In the present case study a slow oscillation of the aeration control loop was investigated. Large scale recirculation in the aeration tank and fast fluctuations of the ammonium concentrations close to the oxygen sensor were identified as the cause of these oscillations. Both, the recirculation as well as the fluctuation of the ammonium have a substantial influence on the performance of the aeration tank and the aeration control loop.

Sorption and high dynamics of micropollutants in sewers

Down-the-drain household chemicals are mostly discharged intermittently (i.e. with water pulses, e.g. pharmaceuticals from toilet flushing) and well soluble micropollutants can, therefore, be subject to significantly high short-term fluctuations. It is not known how these fluctuations are attenuated by sorption to sewer sediments or biofilm. First, we investigated in this paper the effect of sorption for substances with high, medium and low affinity to particulate matter based on computational experiments. For substances with high K(oc) we found that the additional attenuation of a load pattern due to sorption is in the same order of magnitude as caused by dispersion in a typical main sewer. The mass flux between wastewater and the first biofilm layer was identified as the most sensitive parameter. Furthermore, the interplay of systematic, slow diurnal variations does not affect short-term fluctuations. Second, during rain events partial erosion of the biofilm can lead to increased micropollutant loads for substances with high K(oc). This increase is in the same order of magnitude as diurnal variations of the loads in the liquid phase and the TSS.

Confronting limitations: new solutions required for urban water management in Kunming City

Despite continuous investment and various efforts to control pollution, urban water environments are worsening in large parts of the developing world. In order to reveal potential constraints and limitations of current practices of urban water management and to stimulate proactive intervention, we conducted a material flow analysis of the urban water system in Kunming City. The results demonstrate that the current efficiency of wastewater treatment is only around 25% and the emission of total phosphorous from the city into its receiving water, Dianchi Lake, is more than 25 times higher than its estimated tolerance. With regard to the crisis of water quantity and quality, the goal of a sustainable urban water environment cannot be attained with the current problem-solving approach in the region due to the technical limitations of the conventional urban drainage and treatment systems. A set of strategies is therefore proposed. The urban drainage system in Zurich is used as a reference for a potential best-available technology for conventional urban water management (BAT) scenario in terms of its low combined frequency of sewer overflow.

Sources of parameter uncertainty in predicting treatment performance: the case of preozonation in drinking water engineering

This study investigates the factors that determine parameter uncertainty when applying predefined, existing models to predict the performance of a full scale treatment system from environmental engineering. The analysis is performed for ozonation of surface water, a technology applied in drinking water treatment for disinfection and oxidation of micropollutants. The pseudo first order rate constant of ozone decay k(O3) is characterized as a time dependent parameter and estimated from data obtained from three experimental setups representing upscaling stages in engineering design. To obtain meaningful uncertainty estimates, various factors need to be acknowledged: uncertainty about the model structure, uncertainty of other model parameters, uncertainty due to non-representative sampling, and errors in chemical analysis. It is concluded that an on-site automated sequencing batch reactor is best suited for estimating kinetics during operation of the full scale system. Furthermore, the transferability of information in upscaling from laboratory experiments to the full scale system is found to be critical. Although uncertainty analysis enhances the understanding of the system, it is also shown to be a subjective process depending on the knowledge and assumptions of the modeler and the availability and quality of data.

Uncertainty in prediction of disinfection performance

Predicting the disinfection performance of a full-scale reactor in drinking water treatment is associated with considerable uncertainty. In view of quantitative risk analysis, this study assesses the uncertainty involved in predicting inactivation of Cryptosporidium parvum oocysts for an ozone reactor treating lake water. A micromodel is suggested which quantifies inactivation by stochastic sampling from density distributions of ozone exposure and lethal ozone dose. The ozone exposure distribution is computed with a tank in series model that is derived from tracer data and measurements of flow, ozone concentration and ozone decay. The distribution of lethal ozone doses is computed with a delayed Chick-Watson model which was calibrated by Sivaganesan and Marinas [2005. Development of a Ct equation taking into consideration the effect of Lot variability on the inactivation of Cryptosporidium parvum oocysts with ozone. Water Res. 39(11), 2429-2437] utilizing a large number of inactivation studies. Parameter uncertainty is propagated with Monte Carlo simulation and the probability of attaining given inactivation levels is assessed. Regional sensitivity analysis based on variance decomposition ranks the influence of parameters in determining the variance of the model result. The lethal dose model turns out to be responsible for over 90% of the output variance. The entire analysis is re-run for three exemplary scenarios to assess the robustness of the results in view of changing inputs, differing operational parameters or revised assumptions about the appropriate model. We argue that the suggested micromodel is a versatile approach for characterization of disinfection reactors. The scheme developed for uncertainty assessment is optimal for model diagnostics and effectively supports the management of uncertainty.

Estimating sewer leakage from continuous tracer experiments

Direct measurements of sewer leakage with continuous dosing of tracers are often considered too imprecise for practical applications. However, no mathematical framework for data analysis is reported in literature. In this paper, we present an improved experimental design and data analysis procedure together with a comprehensive framework for uncertainty assessment. Test runs in a 700 m-long watertight sewer showed no significant bias and a very high precision of the methodology. The standard error in the results was assessed to 2.6% of the labeled flow with a simplified model. It could be reduced to 1.2% when a dynamic data analysis procedure was applied. The major error contribution was caused by transient transport phenomena, which suggests that careful choosing of the experimental time is more important than the choice of a very specific tracer substance. Although the method is not intended to replace traditional CCTV inspections, it can provide complementary information for rational rehabilitation planning.

The behaviour of pharmaceuticals and heavy metals during struvite precipitation in urine

Separating urine from wastewater at the source reduces the costs of extensive wastewater treatment. Recovering the nutrients from urine and reusing them for agricultural purposes adds resource saving to the benefits. Phosphate can be recovered in the form of struvite (magnesium ammonium phosphate). In this paper, the behaviour of pharmaceuticals and heavy metals during the precipitation of struvite in urine is studied. When precipitating struvite in urine spiked with hormones and non-ionic, acidic and basic pharmaceuticals, the hormones and pharmaceuticals remain in solution for more than 98%. For heavy metals, initial experiments were performed to study metal solubility in urine. Solubility is shown to be affected by the chemical conditions of stored and therefore hydrolysed urine. Thermodynamic modelling reveals low or very low equilibrium solute concentrations for cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), nickel (Ni) and lead (Pb). Experiments confirmed Cd, Cu and Pb carbonate and hydroxide precipitation upon metal addition in stored urine with a reaction half-life of ca. 7 days. For all metals considered, the maximum specific metal concentrations per gram phosphate or nitrogen showed to be typically several orders of magnitudes lower in urine than in commercially available fertilizers and manure. Heavy metals in struvite precipitated from normal stored urine could not be detected. Phosphate recovery from urine over struvite precipitation is shown to render a product free from most organic micropollutants and containing only a fraction of the already low amounts of heavy metals in urine.

Struvite precipitation thermodynamics in source-separated urine

Struvite (MgNH(4)PO(4).6H(2)O) precipitation eliminates phosphate efficiently from urine, a small but highly concentrated stream in the total flux of domestic wastewater. Precipitation experiments with hydrolysed urine evaluated the solubility product of struvite. The stored and fully hydrolysed urine had an ionic strength of between 0.33 and 0.56M and required the estimation of activity coefficients. From our data, we identified the Davies approximation with the two constants A=0.509 and B=0.3 as agreeing best with our laboratory results. The standard solubility product K(s)(0)=f(1)[NH4(+)]f(2)[Mg2+]f(3)[PO(4)(3-)] ([ ]=concentration of the species; f(x)=corresponding activity coefficient) of struvite in urine was found to be 10(-13.26+/-0.057) at 25 degrees C and the enthalpy of struvite formation DeltaH was 22.6(+/-1.1) kJmol(-1). The equilibrium calculations required the following dissolved complexes: [MgCO(3)](aq), [MgHCO(3)](+), [MgPO(4)](-), [NH4HPO4and [NaHPO(4)](-) and to a lesser extent [MgSO(4)](aq) and [NH(4)SO(4)](-). Organic complexes do not seem to influence the solubility product substantially. For practical purposes, a conditional solubility product K(s)(cond)=[Mg(aq)].[NH(4)(+)+NH(3)].[P(ortho)]=10(-7.57)M(3) was derived to calculate struvite solubility in urine at 25 degrees C, pH=9.0 and ionic strength I=0.4M directly from measured concentrations.

Exploring temporal variations of oxygen saturation constants of nitrifying bacteria

Activated sludge models (ASM) are generally accepted as state-of-the-art in modeling wastewater treatment plants. In this paper, we assess the temporal variability of an ASM parameter-the oxygen half-saturation constant of autotrophic bacteria (K(O),(AUT)). A series of respirometric experiments is performed for conventional activated sludge and sludge from a membrane bioreactor. K(O) values are estimated for both ammonium-oxidizing and nitrite-oxidizing bacteria. For parameter estimation, the Monod kinetic model structure is extended by a sensor model. Still remaining systematic deviations between data and model are considered by a thorough residual analysis: (1) uncertainty estimates of K(O) are corrected to reflect model structure deficiencies and (2) the inter-experimental cross-correlation of residuals is taken into account to assess temporal changes. We conclude that K(O),(AUT) is a time variable parameter and should be considered accordingly.

Discrete event simulation for exploring strategies: an urban water management case

This paper presents a model structure aimed at offering an overview of the various elements of a strategy and exploring their multidimensional effects through time in an efficient way. It treats a strategy as a set of discrete events planned to achieve a certain strategic goal and develops a new form of causal networks as an interfacing component between decision makers and environment models, e.g., life cycle inventory and material flow models. The causal network receives a strategic plan as input in a discrete manner and then outputs the updated parameter sets to the subsequent environmental models. Accordingly, the potential dynamic evolution of environmental systems caused by various strategies can be stepwise simulated. It enables a way to incorporate discontinuous change in models for environmental strategy analysis, and enhances the interpretability and extendibility of a complex model by its cellular constructs. It is exemplified using an urban water management case in Kunming, a major city in Southwest China. By utilizing the presented method, the case study modeled the cross-scale interdependencies of the urban drainage system and regional water balance systems, and evaluated the effectiveness of various strategies for improving the situation of Dianchi Lake.

Decay processes of nitrifying bacteria in biological wastewater treatment systems

A knowledge of the decay rates of autotrophic bacteria is important for reliably modeling nitrification in activated sludge plants. The introduction of nitrite to activated sludge models also requires the separate determination of the kinetics of ammonia- and nitrite-oxidizing bacteria. Batch experiments were carried out in order to study the effects of different oxidiation-reduction potential conditions and membrane separation on the separate decay of these bacteria. It was found that decay is negligible in both cases under anoxic conditions. No significant differences were detected between the membrane and conventional activated sludge. The aerobic decay of these two types of bacteria did not diverge significantly either. However, the measured loss of autotrophic activity was only partly explained by the endogenous respiration concept as incorporated in activated sludge model no. 3 (ASM3). In contrast to nitrite-oxidizing bacteria, ammonia-oxidizing bacteria needed 1-2 h after substrate addition to reach their maximum growth rate measured as a maximum OUR. This pattern could be successfully modeled using the ASM3 extended by enzyme kinetics. The significance of these findings on wastewater treatment is discussed on the basis of the extended ASM3.

Evolution of a wastewater treatment plant challenges traditional design concepts

Traditional design and upgrade concepts for wastewater treatment plants (WWTPs) are based on the forecasting of load parameters over a period of 25-40 years. This approach is adequate as long as the environment of a WWTP is stable or predictable over this long time period. However, these conditions are usually not met, as the catchment area, discharge requirements, available technology and institutional conditions of a WWTP may change drastically over time. The complexity and consequences of these dynamics are shown exemplary in a case study analyzing the historical development of a plant from the initial planning steps to the current date. We conclude that the dynamics and complexity of the wastewater system makes reliable predictions impossible, and therefore question the current design and upgrade approach. Instead, we propose to improve the planning and design of wastewater infrastructures through methodologies that systematically account for future uncertainty, like, e.g. scenario planning.

Sampling for representative micropollutant loads in sewer systems

Most commercially available auto-sampling devices do not support a continuous flow-proportional sampling mode, which would conceptually be the best for collecting representative composite samples. Instead different discrete sampling modes are available. Household chemicals can show considerable random short-term variations. With the anticorrosive benzotriazole, relating to a middle-frequent household activity, we show that, besides an accurate flow meter, mainly three factors are decisive for the representativeness of a substance's average load: the substance's load pattern, the sampling frequency and the length of the composite sample. When the sampling intervals are 10 minutes or longer, errors in the order of +/-40% (standard deviation) or more have to be accepted, if the substance of interest is contained in a low number of wastewater pulses (i.e., the level of household activity). This particularly holds true for specific pharmaceuticals e.g. carbamazepine. Ammonium would be less critical, because it relates to a larger number of sources in the same catchment.

Modelling seasonal dynamics of "Microthrix parvicella"

The filamentous bacteria "Microthrix parvicella" can cause serious bulking and scumming in wastewater treatment plants (WWTPs) all over the world. Decades of research have identified Microthrix as a specialized lipid consumer but could not clarify the processes that allow this organism to successfully compete in activated sludge systems. In this study we developed a model, based on ASM3, that describes the pronounced seasonal variations of Microthrix abundance observed in a full-scale WWTP. We hypothesize that low temperatures reduce the solubility of lipids and inhibit their uptake by non-specialized bacteria. The presented model structure and parameters successfully fit the measured data; however they do not necessarily reflect the only and true selection mechanism for Microthrix. This model is not yet to be used for prediction; it is rather a valuable research tool to coordinate the discussion and plan future research activities in order to identify the relevant selection mechanisms favoring Microthrix in activated sludge systems.

Fate of major compounds in source-separated urine

Urine separation is a promising alternative to present-day waste water management. It can help to manage our nutrient flows in a sustainable way. Currently, techniques are being developed to recycle and treat source-separated urine. These techniques, however, must consider the spontaneous processes that change the separated urine. The initial cause of changes is the contamination with microorganisms, which can hardly be avoided in urine-collecting systems. The most important transformation processes are microbial urea hydrolysis, mineral precipitation and ammonia volatilisation. Additionally, a variety of microorganisms may grow in source-separated urine, because the content of biodegradable organic compounds is very high. These microorganisms may also include pathogens. In this paper we give an overview of the effects that the spontaneous transformation processes may have. We focus on nitrogen, phosphorus, magnesium, calcium, potassium, sulphur, organic substances, pathogens and the buffering capacity. The discussion is based on own experiences and literature reviews. This overview will help to develop appropriate technologies for urine recycling.

Modelling of aeration systems at wastewater treatment plants

A model for the response time of aeration systems at WWTPs is proposed. It includes the delays caused by the air supply system (consisting of blowers, throttles and pipes), the rise time of the air bubbles and all control loops except the master DO controller. Beside a description of the required step-change experiments, different approaches for model calibration are given depending on the available data. Moreover, the parameters for the oxygen transfer and the response time of the aeration system model are not clearly identifiable. The model can be used for simulation studies which compare different types of controllers under changing loading and process conditions. The results from full-scale experiments at three different plants show that the response times of the aeration systems are in the range of 4-5 min. Taking all processes and time constants into account, some 30 min are needed to reach a new steady state after a step change of the airflow rate.

Activated sludge modelling: past, present and future

Model complexity in activated sludge modelling has increased over 30 years in parallel with the computational power of computers. Today, the complexity of biokinetics has reached a practical limit. Future advances may be in the direction of enhanced spacial resolution (CFD, single organisms) respectively, in repetitive computations (MC simulation, parameter identification). Further model development may be in niches such as population dynamics, micropollutants, etc.

Using decision analysis to determine optimal experimental design for monitoring sewer exfiltration with tracers

The tracer methods developed to assess exfiltration from sewers in the European project APUSS (assessment of the performance of sewer systems) have a high degree of freedom with regard to the choice of tracer and the dosing strategy. These can lead to very different degrees of uncertainty in the measured exfiltration ratio. In this study, we demonstrate how to select an optimal experimental design using decision analysis, which accounts for this uncertainty and its associated costs. Although the results are site-specific, we can conclude generally that, when NaCl is used as the tracer, the accuracy of the exfiltration estimate is most sensitive to the amount of tracer used and the starting time of the experiment.

Quantifying the uncertainty of on-line sensors at WWTPs during field operation

It remains an ongoing task to quantify the uncertainty of continuous measuring systems at WWTPs during field operation. The commonly used methods are based on lab experiments under standardized conditions and are only suitable for characterizing the measuring device itself. For measuring devices under field conditions, a knowledge of the response time, trueness and precision is equally important. A method is proposed which can be used to characterize newly installed on-line sensors or to evaluate monitoring data which may contain systematic errors. The concept is based on comparative measurements between the sensor and a reference. A linear regression is used to differentiate between trueness and precision. Various statistical tests are conducted to validate the preconditions of linear regression. The information about the trueness and precision of the measuring system under field conditions helps to adapt control strategies more effectively to the relevant processes and permits sophisticated control concepts. Moreover, the concept can help to define guidelines for evaluating the uncertainties of effluent quality monitoring to overcome the concerns about on-line sensors, improve the trust in these systems and to allow the use of continuously measuring systems for legislative purposes. The approach is discussed in detail in this paper and all statistical tests and formulas are listed in the Appendix.

Consequences of mass transfer effects on the inetics of nitrifiers

The influence of membrane separation and mass transfer effects on the kinetics of nitrifiers was evaluated by running a membrane bioreactor (MBR) and a conventional activated sludge (CAS) plant in parallel. Both pilot plants were operated at the same sludge age and treated the same domestic wastewater. The half-saturation constants for the substrate were low in both MBR and CAS and did not differ significantly between the two processes (K(NH(4))) and 0.14+/-0.10 g(N)m(-3) and (K(NO(2))) and 0.28+/-0.20 g(N)m(-3) for the MBR and CAS, respectively). However, the half-saturation constants for oxygen exhibited a major difference between the two processes for both the ammonia-oxidizing (AOB) and nitrite-oxidizing (NOB) bacteria. The experiments yielded K(O,AOB)=0.18+/-0.04 and 0.79+/-0.08 g(O2) as well as K(O,NOB)=0.13+/-0.06 and 0.47+/-0.04 g(O2) m(-3) (substrate only NO(2)) for the MBR and CAS, respectively. The higher K(0) values of the CAS were attributed to mass transfer effects within the large flocs prevailing in the conventional system. In contrast, the sludge from the MBR consisted of very small flocs for which the diffusion resistance can be neglected. On the basis of these results, the implementation of mass transfer effects in activated sludge models is discussed and consequences for the operation of MBRs are highlighted.

Stochastic modeling of total suspended solids (TSS) in urban areas during rain events

The load of total suspended solids (TSS) is one of the most important parameters for evaluating wet-weather pollution in urban sanitation systems. In fact, pollutants such as heavy metals, polycyclic aromatic hydrocarbons (PAHs), phosphorous and organic compounds are adsorbed onto these particles so that a high TSS load indicates the potential impact on the receiving waters. In this paper, a stochastic model is proposed to estimate the TSS load and its dynamics during rain events. Information on the various simulated processes was extracted from different studies of TSS in urban areas. The model thus predicts the probability of TSS loads arising from combined sewer overflows (CSOs) in combined sewer systems as well as from stormwater in separate sewer systems in addition to the amount of TSS retained in treatment devices in both sewer systems. The results of this TSS model illustrate the potential of the stochastic modeling approach for assessing environmental problems.

Rapid quantification of bacteria in activated sludge using fluorescence in situ hybridization and epifluorescence microscopy

A rapid quantification method for bacteria in activated sludge has been developed, based on fluorescence in situ hybridization (FISH) and epifluorescence microscopy. Samples are hybridized on slides and analyzed by direct microscopic observation. Abundance categories were designed based on digital images of the target organisms. These rating systems were developed for the filamentous bacteria Microthrix parvicella and for different morphotypes of nocardioform actinomycetes, but can easily be adapted to other types of microorganisms. Due to the quantification by direct microscopic observation, this method is suitable for samples that are difficult to be processed by semi-automated image analysis techniques, such as samples containing fluorescent debris, cells of different fluorescence intensities and target organisms that need partial enzymatic digestion prior to FISH. In contrast to commonly used rating systems consisting of photographs, the newly developed categories allow to quantitatively compare results of different categories and different organisms. The uncertainties of the results were calculated by a non-parametric bootstrap procedure; a thorough uncertainty analysis was performed including sample variability and operator subjectivity.

Chemical nitrite oxidation in acid solutions as a consequence of microbial ammonium oxidation

In long-term experiments with membrane aerated biofilm reactors we observed complete nitrite oxidation in highly concentrated ammonium nitrite solutions with a contaminant pH decrease to values below 3. The maximum initial concentration for ammonium was 42 mM and for nitrite was 41 mM. We hypothesized that (1) acid-tolerant ammonium oxidizing bacteria were responsible for the pH decrease, and (2) chemical processes caused complete nitrite oxidation at low pH values. To test this hypothesis we set up a mechanistic computer model based on kinetic data from literature and we validated the model with additional experiments. The simulations fitted the measurements very well. Additionally, an experiment with the inhibitor allylthiourea showed that ammonium-oxidizing bacteria were active at pH values far below 5.5. Experiments in a sterile reactor confirmed the chemical nitrite oxidation to nitrate. Nitrogen balances revealed that 8 +/- 4% of the initial nitrogen (ammonium, nitrite, and nitrate) were lost during the cycles. On the basis of measurements and simulations we concluded that volatilization was responsible for the significant nitrogen loss. We estimated that about half of the lost nitrogen volatilized as nitrous acid HNO2. The rest mainly volatilized as dinitrogen N2 and nitrous oxide N2O.

A rapid method to quantify nitrifiers in activated sludge

Quantification of bacteria using Fluorescence In Situ Hybridization (FISH), confocal laser scanning microscopy (CLSM) and image analysis is very time consuming and requires the availability of an expensive microscope. Therefore, a rapid method to quantify nitrifying bacteria in activated sludge using FISH and epifluorescence microscopy was developed. The quantification of the biovolume is based on manual counting of the aggregates formed by nitrifying bacteria and determination of their size. The overall uncertainty of the method was evaluated as a function of the number of analyzed microscopic fields. It was found that 10-15 microscopic fields for ammonia-oxidizing bacteria and 6-8 microscopic fields for nitrite-oxidizing bacteria per sample were optimal regarding effort and accuracy. Accordingly, the time needed for one sample was only 5-15 min, compared to about 1h for the quantification with CLSM and image analysis. As a consequence, this method also allows for the measurement of extended time series with a reasonable effort. The comparison of the determined biovolume and the measured activity showed an explicit correlation.

Quantification of infiltration into sewers based on time series of pollutant loads

We introduce the concepts of a novel approach that allows for the quantification of infiltrating non-polluted waters by a combined analysis of time series of pollutant concentrations and discharged wastewater volume. The methodology is based on the use of automated sensors for the recording of the pollutant concentrations. This provides time series in a high temporal resolution that are suitable for a detailed data analysis and discussion on the underlying assumptions. The procedure is demonstrated on two examples from recent measurement campaigns in Switzerland.

Dispersion coefficients of sewers from tracer experiments

In this paper, 60 tracer experiments in 37 different sewer reaches have been analyzed for longitudinal dispersion under dry weather flow conditions. It was found that dispersion coefficients of sewers are two to three orders of magnitude smaller than those measured in rivers and do not differ much from system to system. Suitable equations were identified to predict reasonable dispersion coefficients in sewer reaches with uniform geometry and stable flow conditions. For engineering applications that require a high degree of accuracy the performance of tracer measurements is recommended.

Membrane bioreactor versus conventional activated sludge system: population dynamics of nitrifiers

Although membrane bioreactors have attracted increasing attention in recent years, little research has been undertaken on the influence of the membrane separation on the microbial community composition. This paper compares the startup behaviour and the performance of the subsequent eight months of a membrane bioreactor with a conventional activated sludge pilot plant. Both plants were operated in parallel at the same sludge age and treated the same domestic wastewater. The identification of the nitrifying community composition using fluorescent in situ hybridization revealed only minor differences between the two reactors for both ammonia-oxidizing bacteria and nitrite-oxidizing bacteria. Accordingly, both systems exhibited the same maximum nitrification rates. Confocal laser scanning microscopy showed that the aggregates formed by nitrifying bacteria were located mostly in the inner part of the flocs and were overgrown by heterotrophic bacteria. It is concluded that the membrane separation itself does affect neither the nitrifying community composition nor the nitrification performance. However, impacts on kinetic parameters are emphasized.

Modeling stochastic load variations in sewer systems

In wastewater treatment and environmental risk assessments increasing attention is paid to the fate of micropollutants. These are time-consuming, expensive and difficult to detect and quantify. If a substance's load or concentration is subject to high dynamic fluctuations, it is demanding to take representative samples, especially when the "variation" is unknown. Therefore, we developed a concept to model stochastic load variations in sewer systems. We gathered readily available information from existing databases (population and consumption data) and combined it with the characteristics of household activities and appliances. We succeeded in predicting realistic short-term variations of benzotriazole (contained in dishwasher detergents) and validated them with a high-frequency measuring campaign. Benzotriazole stands as an example for other household chemicals, which cannot be measured so easily. All required information used within this case study is also available for other substances and catchments. This allows the forecast of stochastic load variations for many chemical compounds of interest. It helps to plan measuring campaigns, to estimate discharged loads from combined sewer overflows and to have a characteristic input for modeling purposes.

Uncertainty in predicting riverbed erosion caused by urban stormwater discharge

Ecologically based criteria require an integrated modeling approach. Due to the complexity of the system, the stochastic nature of loads, and the model abstractions, many uncertainties are involved. In this study, a simple integrated model is applied, which Swiss engineers employ to assess the impact of urban stormwater discharges on riverbed stability. In the course of a case study, an uncertainty analysis is carried out focusing on parameter uncertainties. The underlying context of the uncertainties is evaluated, and a variance-based sensitivity analysis is presented estimating the local uncertainty contribution of each parameter. The results reveal that the largest contributions stem from the model components describing the natural system. An experimental design is proposed that manages to reduce the output uncertainty significantly. Finally, we discuss the benefits of following the proposed procedure.

Reaeration in sewers

The sewer system is a very dynamic system with an abundance of mass transfer processes and transformations. A key process is the mass exchange between the wastewater and the sewer atmosphere. An equation that describes the gas-liquid mass transfer under different hydrodynamic conditions is essential when sewer processes are to be quantified or modelled. In this work, a calibrated reaeration equation is proposed. It is based on the shear Reynolds and the Froude number to correct the increased gas-liquid interface roughness to higher flow rates. The equation was calibrated with previously published data and with new data. This data was obtained with a safe and environmentally friendly gas tracer method for gravity sewers based on the inert gas sulphur hexafluoride (SF6), a new method for the sewer system. Measurements were conducted in four channels under different conditions. The resulting equation will allow for more accurate simulations of the sewer system. Finally, the effect of reaeration with regard to the oxygen consuming processes for different hydrodynamic conditions is discussed.

Quantification of oxygen fluxes in a long gravity sewer

Quantification of the oxygen fluxes in the sewer system is at present the optimal methodology to obtain information about the influence of sewers on transformations and mass balances in the urban drainage system. However, the relative and absolute values of these fluxes are practically unknown. In this work, the oxygen fluxes were quantified experimentally in a full-scale aerobic main sewer. The sewer biofilm respiration was determined with an in situ flow cell, a method that has not been used before in the sewer. The surface reaeration was determined with a gas tracer method based on the inert, non-radio-active and non-toxic gas tracer sulphur hexafluoride. In addition, the wastewater biomass respiration rate was measured. The validity of the applied methods was verified with redundant oxygen balances over a 2-km-long section. Measurement campaigns under different hydrodynamic conditions showed that the relative contribution of the biofilm, the wastewater, the reaeration and the in- and outflow with the water, all contributed significantly. However, the absolute contributions varied extensively and depended especially on the discharge. The COD conversion in the sewer could be estimated from the aerobic activity. The aerobic total degradation in the study reach was 3%. However, when extrapolated to the entire sewer net of the catchment area with 5000 PE, the COD conversion was estimated as high as 30% of the dissolved COD during the night. This indicates that the wastewater composition at the treatment plant will be strongly affected by the sewer system.

Systems analysis in environmental engineering: how far should we go?

Systems analysis is identified as a unifying topic of environmental engineering. Based on a questionnaire sent out to peers and based on the experience with an advanced systems analysis course the possible content and association of the content with bachelor and master's programs is discussed. At the bachelor's level it is concluded that an array of topics should be introduced more in an inductive way, going along with the discussion of examples. At the master's level it is suggested that a substantial course, which systematically introduces a broad variety of systems analysis tools, is provided. Such a course should go along with the introduction of a simulation tool, which supports application of systems analysis methods.

Computer-aided monitoring and operation of continuous measuring devices

Extended studies of measuring and control systems in activated sludge plants at EAWAG revealed that the measuring devices remain the weakest point in control applications. To overcome this problem, a software package was developed which analyses and evaluates the residuals between a reference measurement and the sensor and collects the information in a database. The underlying monitoring concept is based on a two-step evaluation of the residuals by means of statistical evaluations using control charts with two different sets of criteria. The first step is a warning phase in which hints on probable errors trigger an increase in the monitoring frequency. In the second step, the alarm phase, the error hypothesis has to be validated and should allow immediate and targeted reactions from the operator. This procedure enables an optimized and flexible monitoring effort combined with an increased probability of early detection of systematic measuring errors. Beside the monitoring concept, information about the measuring device, the performed servicing actions and the responsibilities is stored. Statistical values for the quantitative characterization of the measuring system during operation will be given. They are needed to parameterise controllers or to guarantee the accuracy of the instrument in order to allow reliable calculations of effluent tax. In contrast to other concepts, not only is the measuring device examined under standard conditions, but so is the entire measuring chain from the liquid to be analysed to the value stored in the database of the supervisory system. The knowledge of the response time of the measuring system is then required in order to allow a comparison of the corresponding values.