Sidestream bio-P and mainstream anammox in a BNR process with upstream carbon capture.

The integration of biological phosphorus removal (bio-P) and shortcut nitrogen removal (SNR) processes is challenging because of the conflicting demands on influent carbon: SNR allows for upstream carbon diversion, but this reduction of influent carbon (especially volatile fatty acids [VFAs]) prevents or limits bio-P. The objective of this study was to achieve SNR, either via partial nitritation/anammox (PNA) or partial denitrification/anammox (PdNA), simultaneously with biological phosphorus removal in a process with upstream carbon capture. This study took place in a pilot scale A/B process with a sidestream bio-P reactor and tertiary anammox polishing. Despite low influent rbCOD concentrations from the A-stage effluent, bio-P occurred in the B-stage thanks to the addition of A-stage WAS fermentate to the sidestream reactor. Nitrite accumulation occurred in the B-stage via partial denitrification and partial nitritation (NOB out-selection), depending on operational conditions, and was removed along with ammonia by the tertiary anammox MBBR, with the ability to achieve effluent TIN less than 2 mg/L. PRACTITIONER POINTS: A sidestream reactor with sufficient fermentate addition enables biological phosphorus removal in a B-stage system with little-to-no influent VFA. Enhanced biological phosphorus removal is not inhibited by intermittent aeration and is stable at a wide range of process SRTs. Partial nitritation and partial denitrification are viable routes to produce nitrite within an A/B process with sidestream bio-P, for downstream anammox in a polishing MBBR.

Effects of ferric-phosphate forms on phosphorus release and the performance of anaerobic fermentation of waste activated sludge.

Five ferric-phosphate (Fe(III)Ps) with amorphous or crystalline structures were added to waste activated sludge (WAS) for anaerobic fermentation, aiming to investigate effects of Fe(III)Ps forms on phosphorus (P) release and the performance of WAS fermentation. The results revealed that the Fe(III) reduction rate of hexagonal-FePO4 was faster than that of monoclinic-FePO4·2H2O, thanks to its lower crystal field stabilization energy. FePO4·nH2O was reduced to vivianite and part of the phosphate was released as orthophosphate (PO4-P). Giniite (Fe5(PO4)4(OH)3·2H2O) as an iron hydroxyphosphate was transformed to ßFe(III)Fe(II)(PO4)O-like compounds without PO4-P release. In addition, Fe(III)Ps had an adverse effect on the anaerobic fermentation of WAS. The specific hydrolysis rate constant and volatile fatty acids (VFAs) yield decreased by 38.4% and 41.9%, respectively, for the sludge sample with amorphous-FePO4·3H2O, which dropped the most. This study provides new insights into various forms of Fe(III)Ps performance during anaerobic fermentation and is beneficial to enhancing P recovery efficiency.

Optimization of P compounds recovery from aerobic sludge by chemical modeling and response surface methodology combination.

Phosphorus recovery has drawn much attention during recent years, due to estimated limited available quantities, and to the harmful environmental impact that it may have when freely released into aquatic environments. Struvite precipitation from wastewater or biological sludge is among the preferred approaches applied for phosphorus recovery, as it results in the availability of valuable fertilizer materials. This process is mostly affected by pH and presence of competitive ions in solution. Modeling and optimization of the precipitation process may help understanding the optimal conditions under which the most efficient recovery could be achieved. In this study, a combination of chemical equilibrium modeling and response surface methodology (RSM) was applied to this aim to aerobic sludge from a plant in Italy. The results identify optimum chemical parameters values for best phosphorus precipitation recovery and removal efficiencies, respectively. Identification of optimal conditions for process control is of great importance for implementing pilot scale struvite precipitation and achieve efficient phosphorus recovery.

Optimizing the configuration of integrated nutrient and energy recovery treatment trains: A new application of global sensitivity analysis to the generic nutrient recovery model (NRM) library.

This paper describes the use of global sensitivity analysis (GSA) for factor prioritization in nutrient recovery model (NRM) applications. The aim was to select the most important factors influencing important NRM model outputs such as biogas production, digestate composition and pH, ammonium sulfate recovery, struvite production, product purity, particle size and density, air and chemical requirements, scaling potential, among others. Factors considered for GSA involve: 1) input waste stream characteristics, 2) process operational factors, and 3) kinetic parameters incorporated in the NRMs. Linear regression analyses on Monte Carlo simulation outputs were performed, and the impact of the standardized regression coefficients on major performance indicators was evaluated. Finally, based on the results, the paper describes the original use of GSA to obtain insight in complex nutrient recovery systems and to propose an optimal nutrient and energy recovery treatment train configuration that maximizes resource recovery and minimizes energy and chemical requirements.

Nutrient recovery from digested waste: Towards a generic roadmap for setting up an optimal treatment train.

This paper aims to develop a generic roadmap for setting up strategies for nutrient recovery from digested waste (digestate). First, a guideline-based decision-tree is presented for setting up an optimal bio-based fertilization strategy as function of local agronomic and regulatory criteria. Next, guidelines and evaluation criteria are provided to determine the feasibility of bio-based fertilizer production as function of the input digestate characteristics. Finally, a conceptual decision making algorithm is developed aiming at the configuration and optimization of nutrient recovery treatment trains. Important input digestate characteristics to measure, and essential factors for monitoring and control are identified. As such, this paper provides a useful decision-support guide for wastewater and residuals processing utilities aiming to implement nutrient recovery strategies. This, in turn, may stimulate and hasten the global transition from wastewater treatment plants to water resource recovery facilities. On top of that, the proposed roadmap may help adjusting the choice of nutrient recovery strategies to local fertilizer markets, thereby speeding up the transition from a fossil-reserve based to a bio-based circular nutrient economy.

Including Life Cycle Assessment for decision-making in controlling wastewater nutrient removal systems.

This paper focuses on the use of Life Cycle Assessment (LCA) to evaluate the performance of seventeen control strategies in wastewater treatment plants (WWTPs). It tackles the importance of using site-specific factors for nutrient enrichment when decision-makers have to select best operating strategies. Therefore, the LCA evaluation is repeated for three different scenarios depending on the limitation of nitrogen (N), phosphorus (P), or both, when evaluating the nutrient enrichment impact in water bodies. The LCA results indicate that for treated effluent discharged into N-deficient aquatic systems (e.g. open coastal areas) the most eco-friendly strategies differ from the ones dealing with discharging into P-deficient (e.g. lakes and rivers) and N&P-deficient systems (e.g. coastal zones). More particularly, the results suggest that strategies that promote increased nutrient removal and/or energy savings present an environmental benefit for N&P and P-deficient systems. This is not the case when addressing N-deficient systems for which the use of chemicals (even for improving N removal efficiencies) is not always beneficial for the environment. A sensitivity analysis on using weighting of the impact categories is conducted to assess how value choices (policy decisions) may affect the management of WWTPs. For the scenarios with only N-limitation, the LCA-based ranking of the control strategies is sensitive to the choice of weighting factors, whereas this is not the case for N&P or P-deficient aquatic systems.

Biological nitrogen and phosphorus removal in membrane bioreactors: model development and parameter estimation.

Membrane bioreactors (MBR) are being increasingly used for wastewater treatment. Mathematical modeling of MBR systems plays a key role in order to better explain their characteristics. Several MBR models have been presented in the literature focusing on different aspects: biological models, models which include soluble microbial products (SMP), physical models able to describe the membrane fouling and integrated models which couple the SMP models with the physical models. However, only a few integrated models have been developed which take into account the relationships between membrane fouling and biological processes. With respect to biological phosphorus removal in MBR systems, due to the complexity of the process, practical use of the models is still limited. There is a vast knowledge (and consequently vast amount of data) on nutrient removal for conventional-activated sludge systems but only limited information on phosphorus removal for MBRs. Calibration of these complex integrated models still remains the main bottleneck to their employment. The paper presents an integrated mathematical model able to simultaneously describe biological phosphorus removal, SMP formation/degradation and physical processes which also include the removal of organic matter. The model has been calibrated with data collected in a UCT-MBR pilot plant, located at the Palermo wastewater treatment plant, applying a modified version of a recently developed calibration protocol. The calibrated model provides acceptable correspondence with experimental data and can be considered a useful tool for MBR design and operation.

Single-objective vs. multi-objective autocalibration in modelling total suspended solids and phosphorus in a small agricultural watershed with SWAT.

To obtain greater precision in modelling small agricultural watersheds, a shorter simulation time step is beneficial. A daily time step better represents the dynamics of pollutants in the river and provides more realistic simulation results. However, with a daily evaluation performance, good fits are rarely obtained. With the Shuffled Complex Evolution (SCE) method embedded in the Soil and Water Assessment Tool (SWAT), two calibration approaches are available, single-objective or multi-objective optimization. The goal of the present study is to evaluate which approach can improve the daily performance with SWAT, in modelling flow (Q), total suspended solids (TSS) and total phosphorus (TP). The influence of weights assigned to the different variables included in the objective function has also been tested. The results showed that: (i) the model performance depends not only on the choice of calibration approach, but essentially on the influential parameters; (ii) the multi-objective calibration estimating at once all parameters related to all measured variables is the best approach to model Q, TSS and TP; (iii) changing weights does not improve model performance; and (iv) with a single-objective optimization, an excellent water quality modelling performance may hide a loss of performance of predicting flows and unbalanced internal model components.