A waste characterisation procedure for ADM1 implementation based on degradation kinetics.

In this study, a procedure accounting for degradation kinetics was developed to split the total COD of a substrate into each input state variable required for Anaerobic Digestion Model n°1. The procedure is based on the combination of batch experimental degradation tests ("anaerobic respirometry") and numerical interpretation of the results obtained (optimisation of the ADM1 input state variable set). The effects of the main operating parameters, such as the substrate to inoculum ratio in batch experiments and the origin of the inoculum, were investigated. Combined with biochemical fractionation of the total COD of substrates, this method enabled determination of an ADM1-consistent input state variable set for each substrate with affordable identifiability. The substrate to inoculum ratio in the batch experiments and the origin of the inoculum influenced input state variables. However, based on results modelled for a CSTR fed with the substrate concerned, these effects were not significant. Indeed, if the optimal ranges of these operational parameters are respected, uncertainty in COD fractionation is mainly limited to temporal variability of the properties of the substrates. As the method is based on kinetics and is easy to implement for a wide range of substrates, it is a very promising way to numerically predict the effect of design parameters on the efficiency of an anaerobic CSTR. This method thus promotes the use of modelling for the design and optimisation of anaerobic processes.

Anaerobic co-digestion of waste activated sludge and greasy sludge from flotation process: batch versus CSTR experiments to investigate optimal design.

In this study, the maximum ratio of greasy sludge to incorporate with waste activated sludge was investigated in batch and CSTR experiments. In batch experiments, inhibition occurred with a greasy sludge ratio of more than 20-30% of the feed COD. In CSTR experiments, the optimal greasy sludge ratio was 60% of the feed COD and inhibition occurred above a ratio of 80%. Hence, batch experiments can predict the CSTR yield when the degradation phenomenon are additive but cannot be used to determine the maximum ratio to be used in a CSTR configuration. Additionally, when the ratio of greasy sludge increased from 0% to 60% of the feed COD, CSTR methane production increased by more than 60%. When the greasy sludge ratio increased from 60% to 90% of the feed COD, the reactor yield decreased by 75%.

Two-phase flow modelling for oxygen renewal estimation in vertical flow filter: luxury or necessity?

Scientists and practitioners exhibit an increasing interest on effluent transfer and degradation modelling in Vertical Flow Sand Filters (VFSF) and Vertical Flow Constructed Wetland (VFCW). Modelling software used to this purpose is mainly monophasic: in the unsaturated zone, only water flow is taken into account and air phase influence is assumed to be negligible. In hydrology, many studies have point out the limitations of this assumption in order to quantify air phase movement but little has been done in the modelling of vertical flow filter. Despite its complexity, two-phase flow modelling allows to overcome these difficulties. In this work, we describe the complex air and water flows in the particular case of vertical flow filter fed intermittently using both numerical and experimental results. Complete different behaviour is observed depending on ponding occurs or not. If it does, flow is clearly influenced by air entrapment which is responsible of a reduction of the infiltration speed and of the drainage of a part of the water kept at the interface between the sand and the drainage layer. Finally, we study the dependency of oxygen income by convection on hydraulic load and compare numerical results with experimental results obtained on oxygen consumption.

Use of 3D modelling and several ultrasound sensors to assess overflow rate.

A new instrumentation mode has been put in place in order to determine the overflow rate of five complex CSOs of the system in Sélestat (French), which are subject to self monitoring. 3D and 1D models have made it possible to predict the shapes of the water lines and suggest a location for the ultrasound sensors. In order to validate the instrumentation principle, three overhead sensors were placed on a weir. The overflow laws suggested are of the type Q(overflow) = a1h1b1 + a2h2b2 + a3h3b3. Early results of the overflow rate that have been obtained by applying the law are close to 10 % of the flow measured in the physical test bench. On the actual site, the ultrasound sensors were assembled on a rail covering the entire weir in order to be able to change their position in future after models calibration.

Activated sludge wastewater treatment plants optimisation to face pollution overloads during grape harvest periods.

The principal objective of our study was to optimise a municipal activated sludge wastewater treatment plant (WWTP) to face high organic flows due to viticulture effluents inputs. Treatment file optimization consisted in testing different treatment lines, changing the number and volume of biological basins and clarifiers, with or without a buffer basin upstream, with a view to achieving a better reduction of COD. The actual WWTP biological stage is composed of two aerated basins whose total volume is 1365 m3. The studied cases are successively, the installation of a single basin of 1365 m3, then of several basins whose total volume remains constant and equal to 1365 m3. Another case was also considered, that of an aerated basin followed by a first clarifier and then, by another aerated basin and a second clarifier. All scenarios presented below were evaluated, for standard dry weather conditions and for high organic load conditions, as encountered during the grape harvest period. The method used was to carry out various simulations, using numerical modelling, and to compare the impact of different process line scenarios and management strategies on the activated sludge WWTP efficiencies.