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    Evaluating woodchip bioreactors for mitigating drainage nitrate levels from a municipal wastewater land treatment site : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Environmental Sciences at Massey University, Palmerston North, New Zealand
    (Massey University, 2024-09-23) Romero Ramírez, Stefanía Yanina
    Woodchips bioreactors are a well-established end-of-drain treatment technology that has been widely used to reduce nitrate (NO₃-) from agricultural drainage water. However, their application to municipal wastewater land treatment sites remains less explored, despite potential advantages. In New Zealand, land application of pre-treated wastewater is a growing practice to mitigate excessive nutrient discharges to the aquatic environment. Land treatment can prove effective when operated correctly, but challenges arise when large volumes of wastewater, and small areas available for irrigation, necessitate high application rates, which can result in NO₃- enrichment of drainage water. The Levin Wastewater Land Treatment Site (LWLTS) is an example of where relatively high annual volumes of municipal wastewater are irrigated over an under-sized application area, resulting in high application depths (4667 mm/year). Consequently, surface drains and shallow groundwater transfer NO₃- to the Waiwiri Stream continually all year. In order to reduce the impact of the LWLTS on the water quality of the Waiwiri Stream, one of its resource consent requirements involves reducing the NO₃- levels in the Waiwiri Stream, downstream from the site. The objective of this thesis was to evaluate the potential use of woodchip bioreactors for reducing NO₃- concentrations in drainage water from LWLTS, including an assessment of the ability of soluble C dosing to enhance NO₃- removal. Initial experiments used small-scale column woodchips bioreactors, which simulated similar water temperatures and NO₃- concentrations to those at the LWLTS. The effect of different water hydraulic retention times (HRT) and the use of dosing with two soluble C sources, liquid sugar, and ethanol, were assessed. Under warm temperature conditions, the column bioreactors achieved 99% NO₃- removal efficiency with a 10-hour HRT. In contrast, under cool water temperatures at the same HRT, the NO₃- removal efficiency decreased to 31%. Soluble C dosing was an effective strategy for enhancing NO₃- removal, with the choice of C source proving to be crucial. Ethanol demonstrated to be more efficient than liquid sugar. Additionally, it was determined that dosing with ethanol at a C:N dosing rate of 1.5:1 achieved high removal efficiencies of 77% under warm conditions and at a 3.3-hour HRT, and 82% under cool conditions and at a 10-hour HRT. Based on the results of the column bioreactor study, the performance of pilot-scale woodchip bioreactors at reducing NO₃- levels in drainage water were evaluated at the LWLTS under field conditions. These experiments involved quantifying the effects of different HRTs and dosing with ethanol at different C:N ratios. Operating the bioreactors, at a 10-hour HRT achieved average NO₃- removal efficiencies of 43% and 59% during the cool and warm seasons, respectively. While, at a 20-hour HRT, the removal efficiencies were 69% and 85%, respectively. The variations in NO₃- removal efficiency between both seasons demonstrated that during the cool season the bioreactors were on average about one-third less effective. When bioreactors, operating at 6.6-hour HRT in cool conditions, were dosed with ethanol at a C:N ratio of 0.75:1, the NO₃- removal efficiency improved from 24% to 93%. This result demonstrates that under field conditions ethanol dosing proved to be a higher effective strategy for enhancing the performance of woodchip bioreactors, particularly during cool periods. Based on the findings of the pilot-scale bioreactors, two woodchip bioreactor designs were proposed for the LWLTS: a non-dosed woodchip bioreactor of 645 m³ operating at a long HRT (20 hours), and an ethanol-dosed woodchip bioreactor of 197 m³ operating at a short HRT (6.6 hours). The two proposed designs provide contrasting approaches, although both are expected to achieve the same annual NO₃- load removal (1174 kg N/year) and have similar annualised NO₃- removal costs ($6.90 and $6.50/kg N, respectively). In the long term, it is expected that the NO₃- removal of the larger non-dosed bioreactor will decline at a faster rate compared to the ethanol-dosed bioreactor due to relying solely of woodchips as the C source. However, it would be less susceptible to the risk of bioclogging and has greater capacity to increase NO₃- removal. In addition, ethanol dosing could be introduced to the larger non-dosed bioreactor in the future, when a decline in NO₃- removal efficiency is observed. Therefore, the overall flexibility of the larger bioreactor design is an advantage but comes with higher initial set-up cost. The results of this research demonstrate that woodchips bioreactors are effective treatment methods for mitigating drain water NO₃- levels at a municipal wastewater land application site. Additionally, C dosing using ethanol proved to be a promising cost-effective alternative to enhance bioreactor performance, allowing the use of relatively short HRTs, especially during cool conditions. This increases the daily volume of water that can be effectively treated.
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    A mathematical analysis of reaction diffusion systems in chemical and biological reactors with macro and micro structures :|ba thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy at Massey University
    (Massey University, 1992) Parshotam, Aroon A.
    This thesis is concerned with generalised models for biological and chemical reactors such as the tubular, fluidised, fixed, packed, continuously stirred and trickle bed reactors. Suppose n chemical components at concentrations Ci (i = 1,2,..,n) are "diffusing" and reacting in a homogeneous incompressible fluid with a known velocity profile u(z) independent of Ci so that in the reactor region Λ, div u is zero. Immersed in the fluid may be a uniformly distributed population of particles which absorb these chemicals and act as local sites for reaction-diffusion phenomena. The particles are sources and sinks for the chemicals Ci in the fluid and these fluid concentrations govern the boundary conditions for the particle or local behaviour. A system of equations is set up as a general model for these complex interactions. The principle limitations of this model are firstly that u(t, z), the velocity profile in Λ is known and not coupled with the concentrations Ci in any way, and secondly the particles are assumed to be fixed relative to the coordinate system of z in Λ and sufficiently small so that a representative sample of them can be taken to be in a spatially constant concentration environment in Λ. The objectives of this thesis are generalised comparison theorems for these systems which are used to prove uniqueness, existence, stability and other general qualitative features of such models. A number of examples from literature are examined. Models conforming to the system described in this thesis have applications in biological wastewater treatment, biochemical manufacture, urea removal by the compact artificial kidney and industrial fermentation processes. Other potential modelling areas concern fertiliser or pollutants diffusing in soil moisture and reacting with soils, oxidation with product formation in waste deposits and industrial ore reduction processes. There are many other industrial and environmental problems with similar interacting macro and micro structures. These include the catalytic cracking and synthesis processes in chemical industries ranging from the making of synthesis gas from coal to oil refining.
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    Mechanistic, neural network, and intelligent hybrid models for a three-phase fluidised-bed biofilm reactor : a thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Environmental Engineering at Institute of Technology and Engineering, Massey University
    (Massey University, 1998) Hong, Yoon-Seok
    Over the past three decades, considerable amount of research efforts have been undertaken in order to develop a mathematical model for a three-phase fluidised-bed biofilm reactor (TPFBBR). Although biofilm properties such as biofilm thickness and its density are allowed to vary with biofilm growth in the model to simulate the real TPFBBR system, they are assumed to be constant in the majority of models developed for a TPFBBR. The main goal of this thesis is to develop mathematical models incorporating dynamic biofilm growth for a TPFBBR using three different modelling approaches such as a mechanistic model, a neural network model, and an intelligent hybrid model with a neurofuzzy model. This thesis consists of three parts. Firstly, a dynamic biofilm growth model, which reflects the variation of biofilm thickness and its density in time, is developed. This model is derived from a biomass balance equation and is solved by the method of characteristics. The biofilm detachment model is proposed and incorporated within the dynamic biofilm growth model. The dynamic biofilm growth model with detachment is then combined with a reaction-diffusion model and reactor model to form an integrated model of a TPFBBR. Simulation method of integrated model incorporating the dynamic biofilm growth model is developed. It is observed that results predicted are in good agreement with experimental data and the integrated model proposed provides a valuable tool to predict performance of a TPFBBR. Secondly, the sequential neural network model, which is composed of two parts, namely, the neural process estimator and the neural process predictor, is developed to describe the task of process estimation and prediction for a TPFBBR. In order to implement the sequential neural network model, multilayer feedforward neural network (MFNN) with cascaded-correlation (C-C) learning and extended Kalman filtering (EKF) learning, and generalized regression neural network (GRNN) are used. Results shows that the sequential neural network model has the feasibility as intelligent estimators and dynamic predictors and gives considerably good results in process estimation and prediction for a TPFBBR. Finally, this thesis shows how a combination of both mechanistic and empirical modelling approaches, called a hybrid model, can be implemented and utilised for modelling a TPFBBR. The neurofuzzy model as an empirical part of hybrid model is used to estimate the variation of the biofilm thickness and biofilm density, and is combined with mechanistic model-based reaction-diffusion and axial-dispersion models to predict the dynamic behavior and performance of a TPFBBR according to the variation of biofilm density and biofilm thickness. This hybrid modelling approach due to its flexibility shows a unified framework through incorporation of strong points of both mechanistic and empirical models, and provides a new modelling framework with a great potential to be applied to other types of biofilm reactors.