Quantitative risk model to estimate the level of antimicrobial residues that can be transferred to soil via manure, due to oral treatments of pigs.

Veterinary antimicrobials can spread via manure onto agricultural fields, representing an emission of these products or their active metabolites into the environment. This causes concerns regarding the role of antimicrobial residues in the development, selection and spread of resistance. Aiming to approach this issue quantitatively, first a literature review was performed on the bioavailability and extent of in vivo biotransformation of twelve antimicrobials commonly used in pigs orally, and on the level of their persistence in manure. This information was then used in a model estimating the level of each of these administered antimicrobials that is present in manure at the end of common storage durations in pits and, thus, readily applied onto soil. From the studied antimicrobials, the highest level of residues in stored manure was estimated for doxycycline (55% of the initial amount of doxycycline administered orally to pigs after six months of manure storage), as a combining result of its high use in pigs, low bioavailability and high stability in manure. Other antimicrobials (e.g. amoxicillin) are readily degraded and therefore pose less threat. The results of this study highlight the importance of rational antimicrobial use and of further research on pharmacokinetics of antimicrobials and their degraded products in different environmental compartments, to efficiently control the spread of residues and/or resistance genes from manure to these matrices.

Application of automated measurement stations for continuous water quality monitoring of the Dender river in Flanders, Belgium.

During the summer of 1999, two automated water quality measurement stations were installed along the Dender river in Belgium. The variables dissolved oxygen, temperature, conductivity, pH, rain-intensity, flow and solar radiation were measured continuously. In this paper these on-line measurement series are presented and interpreted using also additional measurements and ecological expert-knowledge. The purpose was to demonstrate the variability in time and space of the aquatic processes and the consequences of conducting and interpreting discrete measurements for river quality assessment and management. The large fluctuations of the data illustrated the importance of continuous measurements for the complete description and modelling of the biological processes in the river.

A quantitative risk analysis tool for design/simulation of wastewater treatment plants.

Uncertainty is a central concept in the decision-making process, especially when dealing with biological systems subject to large natural variations. In the design of activated sludge systems, a conventional approach in dealing with uncertainty is implicitly translating it into above-normal safety factors, which in some cases may even increase the capital investments by an order of magnitude. To obviate this problem, an alternative design approach explicitly incorporating uncertainty is herein proposed. A probabilistic Monte Carlo engine is coupled to deterministic wastewater treatment plant (WWTP) models. The paper provides a description of the approach and a demonstration of the general adequacy of the method. The procedure is examined in an upgrade of a conventional WWTP towards stricter effluent standards on nutrients. The results suggest that the procedure can support the decision-making process under uncertainty conditions and that it can enhance the likelihood of meeting effluent standards without entailing above-normal capital investments. The analysis led to reducing the capital investment by 43%, producing savings of more than 1.2 million euro.

Model reduction through boundary relocation to facilitate real-time control optimisation in the integrated urban wastewater system.

Real time control is one of the possibilities to minimise the impact of the integrated urban wastewater system (sewer system and treatment plant) on the receiving water quality. Integrated control uses information about the river state to act in the sewer system or in treatment plant. In order to test and tune these integrated controllers, a simplified integrated model is needed. Even with these simplified models, the simulation times may be too long and further model reduction is needed. In this paper, dependency-structure based model reduction is proposed as a technique to further reduce model complexity. Three steps are proposed: relocation of the upstream system boundaries to just upstream of the first control point, relocation of the downstream boundaries to just downstream of the last measurement point, and third, a further model simplification based on an analysis of the sensitivity of the control actions on submodel elimination. The effect of applying the different reduction approaches on the control strategy and on the resulting river water quality is discussed on the basis of a case study of the catchment of Tielt.

Real time control of the integrated urban wastewater system using simultaneously simulating surrogate models.

The urban wastewater system (sewer and treatment plant) has a major impact on the river water quality of urban streams. To minimise this impact, real time control is a valuable option. Since the ultimate goal of any control strategy is to optimise the quality of the river system, it is useful to take pollutant immissions into account when determining the control strategy and/or the setpoints of the controller. However, a simultaneously simulating model of the complete system is needed in order to allow design and evaluation of such control strategies. In this work an integrated model of the urban wastewater system is created. This has been accomplished by implementing surrogate models of the three subsystems within a single software platform. The coupled submodels are subsequently used in a semi-hypothetical case study to optimise the resulting river water quality. An ammonia sensor in the river has been used to control the amount of water treated biologically in the treatment plant. It was shown that this integrated control could lower the peak ammonia concentration in the part of the river downstream of the treatment plant. Hence, a proof of principle has been given that the use of measurements in the river to perform control actions in the sewer system and the treatment plant is a promising option.

Development of a risk assessment based technique for design/retrofitting of WWTPs.

Up to now, within the design/retrofit of wastewater treatment plants (WWTPs), deterministic models were used to evaluate different scenarios on their merits in terms of effluent compliance. This paper describes an approach in which a Monte Carlo engine is coupled to a deterministic treatment plant model, followed by risk interpretation in the form of concentration-duration-frequency (cdf) curves of norm exceedance. The combination of probabilistic modelling techniques with the currently available deterministic models allows to determine the probability of exceeding the effluent limits of a WWTP. This percentage of exceedance is accompanied by confidence intervals resulting from the inherent uncertainty of influent characteristics and model parameters. The approach is illustrated for a hypothetical case study, consisting of a denitrifying plant model inspired by the benchmark model described by Spanjers et al.

Fast, simultaneous simulation of the integrated urban wastewater system using mechanistic surrogate models.

The urban wastewater system components (sewer, treatment plant, and river) are often modelled using complex mechanistic models. Mechanistic surrogate models are introduced here as simplified models that still contain some physical knowledge. Surrogate models are faster, but are less but still sufficiently accurate, and require more data to be calibrated. The possibilities of replacing actual field data by virtual data generated with a complex mechanistic model for calibration of the surrogate model are examined. As an example, a series of tanks with variable volume is shown to approximate sufficiently well the flow propagation in the river Zwalm (Belgium) as predicted by the "de Saint-Venant" equations. The three surrogate models can be implemented in the WEST simulator, which makes a simultaneous simulation of the system possible. In this work a connection is made between the ASM1 and the new IWA River Model No. 1 (RWOM1) by using a translator between the models in such a way that both mass and elemental balances remain closed for the overall system. This approach is illustrated with a case study on the river Lambro (Italy). The dispersion process in this river with steady flow could be modelled by using a tanks in series model, while the water quality in the river was predicted to improve substantially with an increase in hydraulic capacity of the treatment plant. The simulation results with the upgraded plant still need to be checked by field data.

An overview of the posters presented at Watermatex 2000. I. New models/integrated urban wastewater systems/time series analysis.

This paper presents an overview of the posters presented in the sessions 1, 6 and 9 of the Watermatex 2000 conference. The first session focused on the development of new models in different areas of environmental technology, e.g. wastewater, ground pollution, sewers, etc. The sixth session dealt with integrated urban wastewater systems. Session 9 focused on the application of neural network modeling and principal component analysis in time series analysis. Rewarded posters are mentioned and selected for full paper publication in this issue of Wat. Sci. Tech.