An integrated mechanistic modeling of a facultative pond: Parameter estimation and uncertainty analysis.

Imitating natural lakes, pond treatment systems inherit a high complexity with interconnected web of biochemical reactions and complex hydraulic processes. As such, its simulation requires a large and integrated model, which has been a challenge for pond engineers. In this study, we develop an all-encompassing model to gain a quantitative and comprehensive understanding of the hydraulic, physicochemical and microbiological conversion processes in the most common pond, a facultative pond. Moreover, to deal with an evitable issue of large mechanistic models as overparameterization leading to poor identifiability, a systematic parameter estimation was implemented. The application of sensitivity analysis reveals the most influential parameters on pond performance. Particularly, physical parameters, such as vertical eddy diffusivity, water temperature, and maximum growth rate of heterotrophs induce the most changes of organic matters while microbial assimilation and ammonia volatilization appear to be main processes for nutrient removal. In contrast, the efficiency of phosphate precipitation and nutrient biological removal via polyphosphate accumulating organisms and denitrifying bacteria is limited. Identifiability problems are addressed mainly by the characterization of light dependence of algal growth, interaction between water temperature and its coefficient, and the growth of autotrophic bacteria while based on the determinant measures, the most important parameter subsets affecting model outputs are related to physical processes and algal activity. After the establishment of the influential and identifiable parameter subset, an automatic calibration with the data collected from Ucubamba pond system (Ecuador) demonstrates the effect of high-altitude climatic conditions on pond behaviors. An aerobic prevailing condition is observed as a result of high light intensity causing accelerated algal activities, hence, leading to the limitation of hydrolysis, anaerobic processes, and the growth of anoxic heterotrophs for denitrification. Furthermore, the output of uncertainty analysis indicates that a large avoidable uncertainty as a result of vast complexity of the applied model can be reduced greatly via a systematic approach for parameter estimation.

Exploring the influence of meteorological conditions on the performance of a waste stabilization pond at high altitude with structural equation modeling.

Algal photosynthesis plays a key role in the removal mechanisms of waste stabilization ponds (WSPs), which is indicated in the variations of three parameters, dissolved oxygen, pH, and chlorophyll a. These variations can be considerably affected by extreme climatic conditions at high altitude. To investigate these effects, three sampling campaigns were conducted in a high-altitude WSP in Cuenca (Ecuador). From the collected data, the first application of structure equation modeling (SEM) on a pond system was fitted to analyze the influence of high-altitude characteristics on pond performance, especially on the three indicators. Noticeably, air temperature appeared as the highest influencing factors as low temperature at high altitude can greatly decrease the growth rate of microorganisms. Strong wind and large diurnal variations of temperature, 7-20 °C, enhanced flow efficiency by improving mixing inside the ponds. Intense solar radiation brought both advantages and disadvantages as it boosted oxygen level during the day but promoted algal overgrowth causing oxygen depletion during the night. From these findings, the authors proposed insightful recommendations for future design, monitoring, and operation of high-altitude WSPs. Moreover, we also recommended SEM to pond engineers as an effective tool for better simulation of such complex systems like WSPs.

Integration of methane removal in aerobic anammox-based granular sludge reactors.

Combined partial nitritation-anaerobic ammonium oxidation (anammox) processes have been widely applied for nitrogen removal from anaerobic digestion reject water. However, such streams also contain dissolved methane that can escape to the atmosphere, hence contributing to global warming. This study investigates the possibility of integrating methane removal in aerobic anammox-based granular sludge reactors, through modelling and simulation. Methane removal could be established through aerobic methane-oxidizing bacteria (MOB), denitrifying anaerobic methane-oxidizing bacteria (damoB, NO2- + CH4 → N2 + CO2), and/or archaea (damoA, NO3- + CH4 → NO2- + CO2). The simulation results demonstrated that the combined removal of nitrogen and methane was feasible at low dissolved oxygen conditions. Aerobic MOB were the main responsible microorganisms for removing methane. A sensitivity analysis of key kinetic parameters showed a shift in the methanotrophic populations depending on the most favourable parameters for each microbial group, while keeping high nitrogen and methane removal efficiencies. Possible methane stripping during aeration could be limited by increasing the depth within the reactor column at which aeration was supplied. Overall, the integration of methane removal in aerobic anammox-based granular sludge reactors seems to be a promising process option to reduce the carbon footprint from wastewater treatment.

Design of waste stabilization pond systems: A review.

A better design instruction for waste stabilization ponds is needed due to their growing application for wastewater purification, increasingly strict environmental regulations, and the fact that most of previous design manuals are outdated. To critically review model-based designs of typical pond treatment systems, this paper analyzed more than 150 articles, books, and reports from 1956 to 2016. The models developed in these publications ranged from simple rules and equations to more complex first-order and mechanistic models. From a case study on all four approaches, it appeared that rules of thumb is no longer a proper tool for pond designs due to its low design specification and very high output variability and uncertainty. On the other hand, at the beginning phase of design process or in case of low pressure over land and moderate water quality required, regression equations can be useful to form an idea for pond dimensions. More importantly, mechanistic models proved their capacity of generating more precise and comprehensive designs but still need to overcome their lack of calibration and validation, and overparameterization. In another case study, an essential but often overlooked role of uncertainty analysis in pond designs was investigated via a comparison between deterministic and uncertainty-based approaches. Unlike applying a safety factor representing all uncertainty sources, probabilistic designs quantify the uncertainty of model outputs by including prior uncertainty of inputs and parameters, which generates more scientifically reliable outcomes for decision makers. Based on these findings, we advise engineers and designers to shift from the conventional approaches to more innovative and economic tools which are suitable for dealing with large variations of natural biological systems.