Evaluating the potential impact of energy-efficient ammonia control on the carbon footprint of a full-scale wastewater treatment plant.

An assessment was performed for elucidating the possible impact of different aeration strategies on the carbon footprint of a full-scale wastewater treatment plant. Using a calibrated model, the impact of different aeration strategies was simulated. The ammonia controller tested showed its ability in ensuring effluent ammonia concentrations compliant with regulation along with significant savings on aeration energy, compared to fixed oxygen set point (DOsp) control strategies. At the same time, nitrous oxide emissions increased due to accumulation of nitrification intermediates. Nevertheless, when coupled with the carbon dioxide emissions due to electrical energy consumption for aeration, the overall carbon footprint was only marginally affected. Using the local average CO2 emission factor, ammonia control slightly reduced the carbon footprint with respect to the scenario where DOsp was fixed at 2 mg·L-1. Conversely, no significant change could be detected when compared against the scenarios where the DOsp was fixed. Overall, the actual impact of ammonia control on the carbon footprint compared to other aeration strategies was found to be strictly connected to the sources of energy employed, where the larger amount of low CO2-emitting energy is, the higher the relative increase in the carbon footprint will be.

Improving the quality of wastewater treatment plant monitoring by adopting proper sampling strategies and data processing criteria.

Monitoring is a crucial operation for plant management. However, proper sampling procedures and data processing criteria are not always adopted. Wastewater treatment plants work under dynamic conditions, which poses a challenge for a correct performance assessment. The aim of this work is to analyse some important aspects of wastewater sampling and data processing, to identify case by case methods which should to be adopted in order to obtain reliable and consistent information on plant performance. The study was conducted through simulations and real data analyses. It turned out that: a) the preferable 24-hour composite sampling procedure is the flow-proportional mode; in addition, the required sampling frequency (i.e. the number of sub-samples to be taken to make the 24-h composite sample) increases as the percentage of population discontinuously discharging the monitored substance decreases; b) a Variability Index was defined to help find the minimum sampling frequency (i.e. the number of 24-h composite samples per year) for the calculation of annual mass flows with an acceptable uncertainty; and c) criteria were proposed for the identification of pseudo-steady state periods needed to calculate reliable mass balances and plant performance indicators.

A novel fuzzy-logic control strategy minimizing N2O emissions.

A novel control strategy for achieving low N2O emissions and low effluent NH4+ concentration is here proposed. The control strategy uses the measurements of ammonium and nitrate concentrations in inlet and outlet of the aerobic zone of a wastewater treatment plant to calculate a ratio indicating the balance among the microbial groups. More specifically, the ratio will indicate if there is a complete nitrification. In case nitrification is not complete, the controller will adjust the aeration level of the plant in order to inhibit the production of N2O from AOB and HB denitrification. The controller was implemented using the fuzzy logic approach. It was comprehensively tested for different model structures and different sets of model parameters with regards to its ability of mitigating N2O emissions for future applications in real wastewater treatment plants. It is concluded that the control strategy is useful for those plants having AOB denitrification as the main N2O producing process. However, in treatment plants having incomplete NH2OH oxidation as the main N2O producing pathway, a cascade controller configuration adapting the oxygen supply to respect only the effluent ammonium concentration limits was found to be more effective to ensure low N2O emissions.

Systematic design of membership functions for fuzzy-logic control: A case study on one-stage partial nitritation/anammox treatment systems.

A methodology is developed to systematically design the membership functions of fuzzy-logic controllers for multivariable systems. The methodology consists of a systematic derivation of the critical points of the membership functions as a function of predefined control objectives. Several constrained optimization problems corresponding to different qualitative operation states of the system are defined and solved to identify, in a consistent manner, the critical points of the membership functions for the input variables. The consistently identified critical points, together with the linguistic rules, determine the long term reachability of the control objectives by the fuzzy logic controller. The methodology is highlighted using a single-stage side-stream partial nitritation/Anammox reactor as a case study. As a result, a new fuzzy-logic controller for high and stable total nitrogen removal efficiency is designed. Rigorous simulations are carried out to evaluate and benchmark the performance of the controller. The results demonstrate that the novel control strategy is capable of rejecting the long-term influent disturbances, and can achieve a stable and high TN removal efficiency. Additionally, the controller was tested, and showed robustness, against measurement noise levels typical for wastewater sensors. A feedforward-feedback configuration using the present controller would give even better performance. In comparison, a previously developed fuzzy-logic controller using merely expert and intuitive knowledge performed worse. This proved the importance of using a systematic methodology for the derivation of the membership functions for multivariable systems. These results are promising for future applications of the controller in real full-scale plants. Furthermore, the methodology can be used as a tool to help systematically design fuzzy logic control applications for other biological processes.