Resource recovery from wastewater and sludge: modelling and control challenges

Wastewater treatment plants (WWTPs) have been renamed water resource recovery facilities (WRRFs). Our industry is quickly moving from an end-of-pipe environmental protection service to an economic producer of valued products for society. Based on a critical review of resource recovery technologies that are currently applied or in advanced development, it became obvious that most of these technologies are based on physicochemical unit processes (precipitation, volatilization, sorption, …). Current industrial practice for the design and operation of WRRFs is based on mathematical models describing the traditional biological processes. The modeling challenge therefore is to provide practice with proper models for the physicochemical resource recovery processes. The fact that the WRRFs aim at delivering valued products that can partially replace those produced by other means (typically in the chemical industry) leads to a paradigm shift in specifications of the outputs of the facility: no longer treated wastewater and biosolids, but products that have to compete with what is already on the market. The tighter specifications will thus impose a challenge on the process control systems that will be required to guarantee the quality of the products of the WRRFs

Nutrient recovery from biodigestion waste (water) streams and reuse as renewable fertilizers: a two-year field experiment

The aim of this study was to evaluate the impact of using bio-digestion waste derivatives as substitute for synthetic fertilizers and/or as P-poor equivalent for animal manure on soil and crop production. In a field trial, nutrient balances were assessed and the physicochemical soil fertility and quality were evaluated. The biogas yield of the harvested energy crops was also determined. An economical and ecological evaluation was conducted. The highest biomass yields were obtained when the liquid fraction of digestate was used as P-poor fertilizer in addition to animal manure. Furthermore, the complete substitution of synthetic fertilizer N by air scrubber waste water resulted in the highest N and P use efficiencies. Finally, for all reuse scenarios the calculated economical and ecological benefits were significantly higher as compared to the common practice using animal manure and synthetic fertilizers

Forecasting Techniques Applied To Water Quality Time Series In View Of Data Quality Assessment

The main advantage of continuous water quality measurement systems is the ability to capture dynamics in water and wastewater systems, which allows for the identification of critical events, the evaluation of impacts on receiving water bodies, the identification of cause and effect relationships and the ability to discern trends. However, the challenge associated with automatic monitoring systems is the collection of data with sufficient quality for the intended application. That is, useful monitoring is dependent on cautious data quality assessment. With particular attention to its practical implementation, this paper presents a method for data quality assessment that attempts to extract useful information from individual water quality measurement time series. Based on forecasting techniques that make use of the historical behavior of the data, raw measurements are evaluated for the detection of doubtful data and outliers. Posterior treatment is then applied to remove noise and detect potential sensor faults. The proposed tool has been successfully tested on water quality time series collected from different water and wastewater systems

Considering The Effect Of Uncertainty And Variability In The Synthetic Generation Of Influent Wastewater Time Series

The availability of influent wastewater time series is crucial for assessing the performance of a wastewater treatment plant (WWTP) under dynamic flow and loading conditions. Given the difficulty of collecting sufficient data, synthetic generation may be the only option. Usually, the main constituents of the influent time series (e.g. flow, COD, TSS, TKN) show periodic, auto-correlation, and cross-correlation structures in time. Therefore researchers have used statistical models (e.g. auto-regressive time series models) for random generation of the influent time series. However, these regular patterns in time could be significantly distorted during rain events (wet weather flow (WWF) conditions) in which the amount and frequency of rainfall affects the flow and other constituents of the influent. To tackle this problem, a hybrid of statistical and conceptual modeling techniques was adopted. The time series of rainfall and influent in DWF conditions (i.e. inputs to the conceptual model) were generated using two types of statistical models (a periodic-multivariate time series model for influent in DWF conditions and a two-state Markov chain-exponential model for rainfall). These two time series serve as inputs to a conceptual model for generation of influent time series during WWF conditions. The effect of total model uncertainty on the generated outputs was also taken into account through a Bayesian calibration and communicated to the user by constructing uncertainty bands with a desired level of confidence. The proposed influent generator is a powerful tool for realistic generation of the influent time series and is well-suited for probabilistic design of WWTPs as it considers both the effect of input variability (i.e. time variation in rainfall and influent composition during DWF) and total model uncertainty in the generation of the influent

Modélisation dynamique du comportement des métaux lourds dans des stations d’épuration

Le but de ce travail était de développer un modèle permettant de décrire le comportement des métaux lourds, en plus des polluants traditionnels, dans une station d’épuration par boues activées et pouvant être utilisé pour sa conception et son optimisation. Le modèle, qui considère la sorption des métaux lourds sur des matières en suspension comme processus réactionnel, a été évalué à partir de données recueillies durant dix jours dans un système réel de traitement par boues activées. Les résultats démontrent la sensibilité du modèle face aux importantes variations instantanées des concentrations de métaux lourds dans l’affluent. Il est néanmoins capable de prévoir l’évolution des concentrations de métaux lourds à l’intérieur de la station et à l’effluent.The aim of this work was to develop a model which simultaneously describes the fate of heavy metals and traditional pollutants in an activated sludge wastewater treatment plant. The model could then be used to design and optimize WWTPs. The evaluation of the model, which considers the sorption of heavy metals onto suspended solids as the reactive process, was done with a set of data obtained during a 10-day monitoring period in an activated sludge plant. The results show a significant sensitivity of the model towards the important variations in heavy metal concentrations in the influent. Nonetheless, the model is able to describe the heavy metal concentration dynamics inside the WWTP, as well as in the effluent

Construction, start-up and operation of a continuously aerated laboratory-scale SHARON reactor in view of coupling with an Anammox reactor

In this study practical experiences during start-up and operation of a laboratory-scale SHARON reactor are discussed, along with the construction of the reactor. Special attention is given to the start-up in view of possible toxic effects of high nitrogen concentrations (up to 4 000 mgN(.)l(-1)) on the nitrifier population and because the reactor was inoculated with sludge from an SBR reactor operated under completely different conditions. Because of these considerations, the reactor was first operated as an SBR to prevent biomass washout and to allow the selection of a strong nitrifying population. A month after the inoculation the reactor was switched to normal chemostat operation. As a result the nitrite oxidisers were washed out and only the ammonium oxidisers persisted in the reactor. In this contribution also some practical considerations concerning the operation of a continuously aerated SHARON reactor, such as mixing, evaporation and wall growth are discussed. These considerations are not trivial, since the reactor will be used for kinetic characterisation and modelling studies. Finally the performance of the SHARON reactor under different conditions is discussed in view of its coupling with an Anammox unit. Full nitrification was proven to be feasible for nitrogen loads up to 1.5 gTAN-N(.)l(-1.)d(-1), indicating the possibility of the SHARON process to treat highly loaded nitrogen streams. Applying different influent concentrations led to different effluent characteristics indicating the need for proper control of the SHARON reactor