Autotrophic nitrogen removal for decentralized treatment of ammonia-rich industrial textile wastewater: process assessment, stabilization and modelling.

Digital textile printing (DTP) is a game-changer technology that is rapidly expanding worldwide. On the other hand, process wastewater is rich in ammoniacal and organic nitrogen, resulting in relevant issues for discharge into sewer system and treatment in centralized plants. The present research is focused on the assessment of the partial nitritation/anammox process in a single-stage granular sequencing batch reactor for on-site decentralized treatment. The technical feasibility of the process was assessed by treating wastewater from five DTP industries in a laboratory-scale reactor, in one case investigating long-term process stabilization. While experimental results indicated nitrogen removal efficiencies up to about 70%, complying with regulations on discharge in sewer system, these data were used as input for process modelling, whose successful parameter calibration was carried out. The model was applied to the simulation of two scenarios: (i) the current situation of a DTP company, in which wastewater is discharged into the sewer system and treated in a centralized plant, (ii) the modified situation in which on-site decentralized treatment for DTP wastewater is implemented. The second scenario resulted in significant improvements, including reduced energy consumption (- 15%), reduced greenhouse gases emission, elimination of external carbon source for completing denitrification at centralized WWTP and reduced sludge production (- 25%).

Towards an online mitigation strategy for N2O emissions through principal components analysis and clustering techniques.

Emission of N2O represents an increasing concern in wastewater treatment, in particular for its large contribution to the plant's carbon footprint (CFP). In view of the potential introduction of more stringent regulations regarding wastewater treatment plants' CFP, there is a growing need for advanced monitoring with online implementation of mitigation strategies for N2O emissions. Mechanistic kinetic modelling in full-scale applications, are often represented by a very detailed representation of the biological mechanisms resulting in an elevated uncertainty on the many parameters used while limited by a poor representation of hydrodynamics. This is particularly true for current N2O kinetic models. In this paper, a possible full-scale implementation of a data mining approach linking plant-specific dynamics to N2O production is proposed. A data mining approach was tested on full-scale data along with different clustering techniques to identify process criticalities. The algorithm was designed to provide an applicable solution for full-scale plants' control logics aimed at online N2O emission mitigation. Results show the ability of the algorithm to isolate specific N2O emission pathways, and highlight possible solutions towards emission control.

Modelling gas-liquid mass transfer in wastewater treatment: when current knowledge needs to encounter engineering practice and vice versa.

Gas-liquid mass transfer in wastewater treatment processes has received considerable attention over the last decades from both academia and industry. Indeed, improvements in modelling gas-liquid mass transfer can bring huge benefits in terms of reaction rates, plant energy expenditure, acid-base equilibria and greenhouse gas emissions. Despite these efforts, there is still no universally valid correlation between the design and operating parameters of a wastewater treatment plant and the gas-liquid mass transfer coefficients. That is why the current practice for oxygen mass transfer modelling is to apply overly simplified models, which come with multiple assumptions that are not valid for most applications. To deal with these complexities, correction factors were introduced over time. The most uncertain of them is the α-factor. To build fundamental gas-liquid mass transfer knowledge more advanced modelling paradigms have been applied more recently. Yet these come with a high level of complexity making them impractical for rapid process design and optimisation in an industrial setting. However, the knowledge gained from these more advanced models can help in improving the way the α-factor and thus gas-liquid mass transfer coefficient should be applied. That is why the presented work aims at clarifying the current state-of-the-art in gas-liquid mass transfer modelling of oxygen and other gases, but also to direct academic research efforts towards the needs of the industrial practitioners.

Tanks in series versus compartmental model configuration: considering hydrodynamics helps in parameter estimation for an N2O model.

The choice of the spatial submodel of a water resource recovery facility (WRRF) model should be one of the primary concerns in WRRF modelling. However, currently used mechanistic models are limited by an over-simplified representation of local conditions. This is illustrated by the general difficulties in calibrating the latest N2O models and the large variability in parameter values reported in the literature. The use of compartmental model (CM) developed on the basis of accurate hydrodynamic studies using computational fluid dynamics (CFD) can take into account local conditions and recirculation patterns in the activated sludge tanks that are important with respect to the modelling objective. The conventional tanks in series (TIS) configuration does not allow this. The aim of the present work is to compare the capabilities of two model layouts (CM and TIS) in defining a realistic domain of parameter values representing the same full-scale plant. A model performance evaluation method is proposed to identify the good operational domain of each parameter in the two layouts. Already when evaluating for steady state, the CM was found to provide better defined parameter ranges than TIS. Dynamic simulations further confirmed the CM's capability to work in a more realistic parameter domain, avoiding unnecessary calibration to compensate for flaws in the spatial submodel.

Multi-point monitoring of nitrous oxide emissions in three full-scale conventional activated sludge tanks in Europe.

The large global warming potential of nitrous oxide (N2O) is currently of general concern for the water industry, especially in view of a new regulatory framework concerning the carbon footprint of water resource recovery facilities (WRRFs). N2O can be generated through different biological pathways and from different treatment steps of a WRRF. The use of generic emission factors (EF) for quantifying the emissions of WRRFs is discouraged. This is due to the number of different factors that can affect how much, when and where N2O is emitted from WRRFs. The spatial and temporal variability of three WRRFs in Europe using comparable technologies is presented. An economically feasible and user-friendly method for accounting for the contribution of anoxic zones via direct gas emission measurements was proven. The investigation provided new insights into the contribution from the anoxic zones versus the aerobic zones of biological WRRF tanks and proved the unsuitability of the use of a single EF for the three WRRFs. Dedicated campaigns for N2O emissions assessment are to be advised. However, similarities in the EF magnitude can be found considering treatment strategy and influent water composition.

Towards improved accuracy in modeling aeration efficiency through understanding bubble size distribution dynamics.

Aeration is the largest energy consumer in most water and resource recovery facilities, which is why oxygen transfer optimization is fundamental to improve energy efficiency. Although oxygen transfer is strongly influenced by the bubble size distribution dynamics, most aeration efficiency models currently do not include this influence explicitly. In few cases, they assume a single average bubble size. The motivation of this work is to investigate this knowledge gap, i.e. a more accurate calculation of the impact of bubble size distribution dynamics on oxygen transfer. Experiments were performed to study bubble size distribution dynamics along the height of a bubble column at different air flow rates for both tap water and solutions that mimic the viscosity of activated sludge at different sludge concentrations. Results show that bubble size is highly dynamic in space and time since it is affected by hydrodrynamics and the viscosity of the liquid. Consequently, oxygen transfer also has a dynamic character. The concept of a constant overall volumetric oxygen transfer coefficient, KLa, can thus be improved. A new modeling approach to determine the KLa locally based on bubble size distribution dynamics is introduced as an alternative. This way, the KLa for the entire column is calculated and compared to the one measured by a traditional method. Results are in good agreement for tap water. The modeled KLa based on the new approach slightly overestimates the experimental KLa for solutions that mimic the viscosity of activated sludge. The difference appears to be lower when the air flow rate increases. This work can be considered as a first step towards more accurate and rigorous mechanistic aeration efficiency models which are based on in-depth mechanism knowledge. This is key for oxygen transfer optimization and consequently energy savings.

Towards advanced aeration modelling: from blower to bubbles to bulk.

Aeration is an essential component of aerobic biological wastewater treatment and is the largest energy consumer at most water resource recovery facilities. Most modelling studies neglect the inherent complexity of the aeration systems used. Typically, the blowers, air piping, and diffusers are not modelled in detail, completely mixed reactors in a series are used to represent plug-flow reactors, and empirical correlations are used to describe the impact of operating conditions on bubble formation and transport, and oxygen transfer from the bubbles to the bulk liquid. However, the mechanisms involved are very complex in nature and require significant research efforts. This contribution highlights why and where there is a need for more detail in the different aspects of the aeration system and compiles recent efforts to develop physical models of the entire aeration system (blower, valves, air piping and diffusers), as well as adding rigour to the oxygen transfer efficiency modelling (impact of viscosity, bubble size distribution, shear and hydrodynamics). As a result of these model extensions, more realistic predictions of dissolved oxygen profiles and energy consumption have been achieved. Finally, the current needs for further model development are highlighted.

Monitoring the aeration efficiency and carbon footprint of a medium-sized WWTP: experimental results on oxidation tank and aerobic digester.

The efficiency of aeration systems should be monitored to guarantee suitable biological processes. Among the available tools for evaluating the aeration efficiency, the off-gas method is one of the most useful. Increasing interest towards reducing greenhouse gas (GHG) emissions from biological processes has resulted in researchers using this method to quantify N2O and CO2 concentrations in the off-gas. Experimental measurements of direct GHG emissions from aerobic digesters (AeDs) are not available in literature yet. In this study, the floating hood technique was used for the first time to monitor AeDs. The floating hood technique was used to evaluate oxygen transfer rates in an activated sludge (AS) tank of a medium-sized municipal wastewater treatment plant located in Italy. Very low values of oxygen transfer efficiency were found, confirming that small-to-medium-sized plants are often scarcely monitored and wrongly managed. Average CO2 and N2O emissions from the AS tank were 0.14 kgCO2/kgbCOD and 0.007 kgCO2,eq/kgbCOD, respectively. For an AeD, 3 × 10-10 kgCO2/kgbCOD direct CO2 emissions were measured, while CO2,eq emissions from N2O were 4 × 10-9 kgCO2,eq/kgbCOD. The results for the AS tank and the AeD were used to estimate the net carbon and energy footprint of the entire plant.

Experimental investigation of granule size and shape dynamics in twin-screw granulation.

A twin-screw granulator (TSG), a promising equipment for continuous high shear wet granulation (HSWG), achieves the desired level of mixing by a combination of the appropriate screw configuration and a suitable set of process settings (e.g. feed rate, screw speed, etc.), thus producing a certain granule size and shape distribution (GSSD). However, the primary sizing and shaping mechanism behind the resulting distribution is not well understood due to the opacity of the multiphase system in the granulator. This study experimentally characterised the GSSD dynamics along the TSG barrel length in order to understand the function of individual screw modules and process settings, as well as their interaction. Particle size analysis of granules collected at the outlet of the TSG suggested significant interaction between the process and screw configuration parameters influencing the heterogeneity in the GSSD. By characterising the samples collected along the screw length, a variable influence of the screw modules at different process conditions was observed. At low liquid-to-solid ratio (L/S), the first kneading module seemed to play a significant role in mixing, whereas the second kneading module was found to be more involved in reshaping the granules. At high L/S and high throughput, aggregation mainly took place in the second kneading module changing the GSSD. The results obtained from this study will be further used for the calibration and validation of a mechanistic model and, hence, support future development of a more detailed understanding of the HSWG process in a TSG.