The thesis constitutes an investigation into the production of floating photocatalytic particles (FPP) as a low cost, low carbon footprint and chemical-free wastewater treatment. It is anticipated that this approach would be particularly attractive for developing countries where it could reduce incidences of disease and pollution. The particles were manufactured from cocoa butter (CB), and contained either photocatalytic nanoparticle titanium dioxide TiO2 (P25) or silver-doped TiO2 (0.5% w/w). The photocatalytic activity of the particles was evaluated by means of the decolourisation of the dye indigo carmine (IC). Three arrangements were used; small scale treatment using Petri dishes, an 1800 ml batch-recirculation photoreactor and an 8 litre UV contactor. Membrane emulsification (ME) was the technique used here to generate particles of controlled size. The particles were in effect what are known as Pickering emulsions in which the solid fat core (CB) was stabilised by TiO2 nanoparticles, resulting in composite particles that float easily and can receive incident light to generate highly reactive free radical species. The FPPs were characterised by FEGSEM and EDs mapping analysis, and the images obtained displayed a spherical structure with a rough outer surface, and the EDs showed a good coverage of TiO2 on the surface of at a maximum loading of 10% w/w. Tests were conducted to assess the stability of the particles when used in repeated cycles. Reuse of the particles caused a significant drop of photodegradation activity after four cycles to 42% of that of freshly prepared particles. The correlation of photocatalytic activity with silver dosage was also investigated. The highest photocatalytic activity was achieved at 0.5 wt. % of silver doped TiO2 and was some 10% greater than for un- doped particles. The organic carbon release resulted from TOC analysis for the FPPs that were exposed to UV light for 8.5 hr in water was less than 1 wt. %. First order reaction kinetics were exhibited during decolourisation of IC dye with respect to the initial dye concentration, radiation intensity, percentage coverage of the liquid surface by the FPPs, and the catalytic loading. For a static system (i.e. no forced convection), the most effective surface coverage was identified as being in the range of 60 to 80%. A linear source spherical emission model (LSSE) was adopted to estimate the intensity of the incident radiation on the surface of the FPP layer in the photoreactor and validated. In addition, a preliminary kinetic model to describe of the effect of the photocatalytic active surface concentration of TiO2 as well as the efficient intensity flux in the kinetic model was developed for the FPP layer photoreactor.

The key product from anaerobic digestion (AD) is biogas, which is used to generate heat and/or electricity. Anaerobic digestion involves degradation and stabilisation of the feedstock by microorganisms, leading to the formation of biogas and a digestate residue, which is used as a fertiliser. Contaminants entering the system in the feedstock may limit biogas yield if functioning of the methanogenic archaea is disrupted. Digestate quality may also be compromised. Approximately 40% of the current UK biogas plants are farm-based, using manures and slurry as the main feedstock. Veterinary medicines are excreted in dung of treated animals and if used prophylactically, concentrations in the faeces or urine may be significant. Contaminated animal waste is therefore likely to be used as a feedstock in AD. Since digestates are commonly used as fertilisers, contaminant loading and fate must be understood to prevent transfer into crops, reductions in soil microbial activity, increased antibiotic resistance and detrimental effects to livestock if digestates are applied to fodder crops or pasture. It is unlikely that the use of veterinary pharmaceuticals will be reduced whilst livestock farming is intensifying and the current demand for meat is growing, therefore understanding the operational processes of AD that influence the persistence of commonly used veterinary medicines and subsequent toxicity are crucial to minimising potentially detrimental effects. Research was undertaken using laboratory-scale digestion vessels to quantify the effect of the commonly used veterinary antibiotics, oxytetracycline and tylosin, when added to naïve (organic) cattle dung or to slurry from a conventional dairy farm. Anaerobic digestion units were spiked with either oxytetracycline or tylosin at low (environmentally realistic) and artificially high concentrations, either at start-up (day 0) or once the system was producing gas (day 15). Biogas production was measured and gas collected every 5 days to quantify the temporal effect of the antibiotics on methane production. Oxytetracycline and tylosin significantly reduced both biogas quality and quantity, with the extent of the effect differing with each feedstock. In organic cow dung, the low (4.33 mg L-1) and artificially high (86.63 mg L-1) concentration of oxytetracycline added on day 15 to organic cow dung caused an overall drop in biogas production of 12% and 25% respectively, whilst the same concentrations incorporated at start-up caused a drop of only 4% and 18% respectively. Both the low and artificially high concentrations of tylosin added on day 15 caused a 33% drop in biogas production, whilst the same concentrations incorporated on day 0 caused a drop of 15% and 42% respectively. In conventional dairy slurry, low (4.33 mg L-1) and artificially high (86.63 mg L-1) concentrations of oxytetracycline caused an overall 3% and 10% drop in biogas production respectively, with tylosin amendment causing a decrease in total biogas production of 7% and 22% respectively. Feedstock origin affected biogas production and quality when the system was challenged by antibiotic inputs. These data highlight the complex interactions that can occur between feedstock and exposure to veterinary pharmaceuticals.

The presence and impact of steroid estrogens in natural water matrices has driven development and evaluation of wastewater treatment technologies that may reduce the steroid load entering water environments. This work was undertaken to assess and predict the ability of Trametes versicolor laccase to degrade estrone (E1) in water matrices under realistic conditions to wastewater treatment plants (WWTPs) and with consideration of the complex and variable nature of the wastewater matrix. A robust experimental procedure was developed to ensure the efficiency of the enzyme laccase to degrade E1 in water matrices was not overestimated due to errors arising from poor experimental design. These experiments demonstrated that commercially-obtained laccase in concentrations above > 1 mg/ml are inhomogeneous requiring centrifugation prior to use to reduce error and provide more accurate evaluation of laccase capability. Sample filtration, which is necessary for chromatographic analysis, identified regenerated cellulose (RC) membrane filters as the optimum filters for particulates removal from E1 solutions due to their low affinity toward E1 (3.2 ±1.72 %). An optimum enzyme inactivation procedure using hydrochloric acid was also developed to ensure that the enzyme laccase was instantly inactivated without affecting the target steroid E1 itself. Using the established experimental procedure, bench-scale studies evaluating the efficiency of laccase-based treatment in a ‘clean’ water matrix were investigated. Experiments in deionised water provided a proof of concept of laccase ability to degrade E1 in water under realistic ranges of temperature [6˚C - 25˚C] and contact time [0.5 hr – 8 hrs] to the WWTP and evaluate the use of models to fit experimental data and predict within that system. Box Behnken Design (BBD) was applied to determine the number and the conditions of the performed experiments. The experimental data was then utilised to build two different models to predict E1 removal efficiency under any set of conditions and optimise the performance of laccase-based treatment system. The goodness of the fit for each model was tested using statistical indices such as coefficient of determination (R2), mean squared error (MSE) and absolute average deviation (AAD). The artificial neural network (ANN) model showed a better fit to the experimental data than the response surface methodology (RSM) model (RSM and ANN of R2 = 0.9908 and R2 = 0.9992 respectively. In addition, the predictive capabilities of RSM and ANN were tested using a set of statistically designed unseen data that was not previously used in models’ training. Both models showed limited predictive capabilities. The ability of laccase-based treatment to remove E1 in real-world wastewater was studied at bench scale. To account for the complexity and variability of the wastewater matrix, effluent samples during the period December 2014 - June 2015 were characterised for standard water quality parameters, where the temporal variation in wastewater chemical oxygen demand (COD), total suspended solids (TSS) and pH, were observed. A new water quality parameter, “Benchmark” was also developed and applied to quantify the impact of wastewater variability on laccase performance for E1 removal. The average benchmark value in the period between December 2014 and June 2015 was 79.8±3.7%. In addition, the impact of laccase inhibitors, which are likely to be present within the wastewater matrix, such as chloride, copper, iron and zinc, on laccase activity was investigated. The inhibitory effect of chloride ions increased with increasing chloride concentration above 200 mg/l. Copper and zinc ions exhibited negative effects on the enzymatic degradation of E1 at concentrations equal or above 10 mg/l and 200 mg/l. The impact of water matrix temperature, contact time and laccase concentration were studied in wastewater effluent and the experimental data was used to build RSM and ANN models. The predictive capability of the generated RSM model was relatively poor (R2 = 0.863) and even lower than the achieved predictive capability in clean matrix when tested using unseen data, this was partially attributed to the variability of wastewater matrix that could have not been addressed in this type of models. Whilst the improved ANN model showed a better predictive capability than RSM (R2=0.991) An advantage of the ANN model compared to the RSM model and reported for the first time, was the ability to include the impact of matrix complexity and variability on laccase performance, assessed via the benchmark data added as a forth factor in the ANN model. The final ANN model incorporating the matrix variability observed temporally during the sampling period had extremely high predictive capabilities (R2 > 0.99). This model approach holds the potential to help researchers evaluate and optimise laccase-based treatment (as well as other treatment technologies) and predict the removal efficiency of various bioactive chemicals under a wide range of conditions. Performing laccase-based treatment in a continuous reactor, utilising actual wastewater effluent and under realistic conditions to WWTPs, is the next stage that should be investigated in detail.

This work describes the development of mediated amperometric biosensors that are able to monitor the metabolic activity of both single and mixed microbial populations, with applications in toxicity assessment and wastewater treatment plant protection. Biosensor systems have been constructed incorporating either the single-species eubacteria Escherichia coli or Pseudomonas putida, Bioseed®, or a mixture of activated sludge organisms from wastewater treatment plants, as the sensing components immobilised on disposable screen printed electrodes in stirred reaction vials. The biosensor approach is generic allowing for a wide range of microbial cell types to be employed. Appropriate bacterial species can be selected for specific sensor applications in order to confer validity and relevance to the test, hence the biosensor can be tailor-made to assess the toxicity in a particular environment and provide diagnostically valid and relevant results. The biosensors have been used to assess the toxicity of a standard toxicant and toxicant formulations and in blind testing of a range of industrial effluents, in parallel with a number of bioassays including Microtox® and activated sludge respiration inhibition. The biosensor results generally show significant correlation to the appropriate conventional toxicity tests. In this study, an activated sludge based biosensor assay was developed and used to assess the toxicity of industrial process and site effluents with the specific purpose of wastewater treatment plant protection. Data generated compared significantly with those from an activated sludge respiration inhibition test, with added advantages of rapidity, safety and ease of use.

Effective treatment of wastewater is an important process in reducing the environmental impact of industry and human activity. Although conventional water treatment systems can adequately remove the principle components of waste (i.e. substances that can be represented the majority of biological and chemical oxygen demand) several materials are poorly or slowly removed. Tertiary treatment polishing processes are therefore required to remove these contaminants to ensure complete wastewater treatment. This thesis reports investigations made using film reactors that are used to remove recalcitrant materials such as ammonia- nitrogen and endocrine disrupters that although present in low concentrations, if left untreated can have a strong impact on the environment. Film reactors potentially offer several process advantages over conventional activated sludge treatments systems as they allow very long residence time and contact with high concentrations of fixed microbes with the low concentrations of pollutants so enhancing kinetic performance and efficiency of the process. Two reactor configurations, a partial fixed bed (PFBR) and moving bed biofilm reactors (MBBR) were investigated. A thirty liter reactor with a working volume of 16 liters was constructed and contained fixed microbial films on either free suspended or fixed beds plastic packing (K2 AnoxKaldnes). The investigation of ammonia-nitrogen oxidation showed that after a suitable acclimation period (2 weeks) that ammonia was oxidise rapidly reducing the feed concentrations of 35 mg/L to < 2 mg/L in the effluent. To assess the performance for ammonia-nitrogen removal the reactors operated for long periods (up to 3 months) with continuous feed using the reactor in either PFBR or MBBR modes in addition of 17alpha-ethynylestradiol (EE2) and mestranol (MeEE2), the endocrine disrupting compounds commonly found in municipal wastewater. These substances is derived from a synthetic hormones if found in the natural environment can reduced the productivity of the fish as this can cause feminization in aquatic organisms with disastrous consequences on fish populations. The MBBR and PFBR systems were used to investigate the co-metabolism of ammonia-nitrogen, 17alpha-ethynylestradiol (EE2) and mestranol from model waste water feed containing 35 mg/L of ammonia-nitrogen and 100 mug/L of 17alpha-ethynylestradiol (EE2) and mestranol (MeEE2). A kinetic analysis of the systems were made and for the PFBR reactor, the specific growth rate, mumax of 7.092 d-1 with saturation constants, Ks of 1.574 mg/L. The kinetic analysis for the MBBR system was 6.329 d-1 for the mumax with the K.S of 0.652 mg/L. When the PFBR was used removal of EE2 represents 70% MeEE2 was removed. MBBR were shown to be more effective and efficient in removing ammonia-nitrogen reducing the levels under good conditions to > 2 mg/L while the PFBR could also achieve 2 mg/L. The MBBR system was also more competent in the removal of 17alpha-ethynylestradiol (EE2) and mestranol compared to PFBR. This work demonstrates that there are considerable advantages to using thin film reactors as polishing step for the tertiary treatment of waste waters when to compared to other processes in reducing the inorganic pollutants as endocrine disrupting compounds. The significance of these results is discussed in this context.

The onset of the Water Framework Directive (WFD) will challenge water utilities to further reduce their wastewater phosphorus discharges to < 0.5 mg.L- 1. Whilst conventional treatments, such as chemical dosing, are able to meet these new discharge consents, the strategies are representative of a linear economy model where resources are unrecovered and disposed. An alternative solution which can contribute to the aspiration of a circular economy is microalgae. Microalgae are ubiquitous in wastewater environments and assimilate phosphorus during their growth, to residual concentrations complementary of the WFD. Furthermore, microalgal biomass can be anaerobically digested to produce biomethane offering the potential for an energy neutral approach. However, uptake of microalgal systems are lacking in the UK through limited knowledge of operation; and the belief that such solutions are synonymous to large, shallow open ponds with extensive treatment times. The development of alternative microalgal reactors are increasingly investigated to overcome these implementation challenges. Of these, immobilised microalgae has shown great potential; and whilst within its infancy demonstrates the greatest opportunity for development and optimisation. This thesis determines the critical operational parameters that influence the remediation efficacy of immobilised microalgae for tertiary nutrient removal; including species selection, biomass concentration, treatment period and lighting; with recommendations for optimal performance. These recommendations are then applied to the design and operation of an immobilised bioreactor (IBR) to understand the key design and operating components that influence the overall economic viability. In doing so, the potential for an IBR to be economically viable, within the next decade, in comparison to traditional approaches are discussed.

This thesis focuses on soft sensor development based on fuzzy logic used for real time online monitoring of anaerobic digestion to improve methane output and for robust fermentation. Important process parameter indicators such as pH, biogas production, daily difference in pH and daily difference in biogas production were used to infer alkalinity, a reliable indicator of process stability. Additionally, a fuzzy logic and a rule-based controller were developed and tested with single stage anaerobic digesters operating with cow slurry and cellulose. Alkalinity predictions from the fuzzy logic algorithm were used by both controllers to regulate the organic loading rate that aimed to optimise the biogas process. The predictive performance of a software sensor determining alkalinity that was designed using fuzzy logic and subtractive clustering and was validated against multiple linear regression models that were developed (Partner N° 2, Rothamsted Research 2010) for the same purpose. More accurate alkalinity predictions were achieved by utilizing a fuzzy software sensor designed with less amount of data compared to a multiple linear regression model whose design was based on a larger database. Those models were utilised to control the organic loading rate of a twostage, semi-continuously fed stirred reactor system. Three 5l reactors without support media and three 5l reactors with different support media (burst cell reticulated polyurethane foam coarse, burst cell reticulated polyurethane foam medium and sponge) were operated with cow slurry for a period of seven weeks and twenty weeks respectively. Reactors with support media were proven to be more stable than the reactors without support media but did not exhibit higher gas productivity. Biomass support media were found to influence digester recovery positively by reducing the recovery period. Optimum process parameter ranges were identified for reactors with and without support media. Increased biogas production was found to occur when the loading rates were 3-3.5g VS/l/d and 4-5g VS/l/d respectively. Optimum pH ranges were identified between 7.1-7.3 and 6.9-7.2 for reactors with and without support media respectively, whereas all reactors became unstable at ph<6.9. Alkalinity levels for system stability appeared to be above 3500 mg/l of HCO3 - for reactors without media and 3480 mg/l of HCO3 - for reactors with support media. Biogas production was maximized when alkalinity was 3 between 3500-4500 mg/l of HCO3 - for reactors without support media and 3480- 4300 mg/l of HCO3 - for reactors with support media. Two fuzzy logic models predicting alkalinity based on the operation of the three 5l reactors with support media were developed (FIS I, FIS II). The FIS II design was based on a larger database than FIS I. FIS II performance when applied to the reactor where sponge was used as the support media was characterized by quite good MAE and bias values of 466.53 mg/l of HCO3- and an acceptable value for R2= 0.498. The NMSE was close to 0 with a value of 0.03 and a slightly higher FB= 0.154 than desired. The fuzzy system robustness was tested by adding NaHCO3 to the reactor with the burst cell reticulated polyurethane foam medium and by diluting the reactor where sponge was used as the support media with water. FIS I and FIS II were able to follow the system output closely in the first case, but not in the second. FIS II functionality as an alkalinity predictor was tested through the application on a 28l cylindrical reactor with sponge as the biomass support media treating cow manure. If data that was recorded when severe temperature fluctuations occurred (that highly impact digester performance), are excluded, FIS II performance can be characterized as good by having R2= 0.54 and MAE=Bias= 587 mg/l of HCO3-. Predicted alkalinity values followed observed alkalinity values closely during the days that followed NaHCO3 addition and water dilution. In a second experiment a rulebased and a Mamdani fuzzy logic controller were developed to regulate the organic loading rate based on alkalinity predictions from FIS II. They were tested through the operation of five 6.5l reactors with biomass support media treating cellulose. The performance indices of MAE=763.57 mg/l of HCO3-, Bias= 398.39 mg/l of HCO3-, R2= 0.38 and IA= 0.73 indicate a pretty good correlation between predicted and observed values. However, although both controllers managed to keep alkalinity within the desired levels suggested for stability (>3480 mg/l of HCO3-), the reactors did not reach a stable state suggesting that different loading rates should be applied for biogas systems treating cellulose.

Sewage epidemiology is increasingly becoming an alternative method of estimating drug usage and consumption patterns for a given population. With the constant emergence of new psychoactive substances such as cathinones and piperazines, versatile, reliable, specific and sensitive analytical methods are needed for their detection in complex matrices such as waste water. This thesis reports the development of an analytical method based on solid phase extraction, derivatization with pentafluoropropionic anhydride and analysis by gas chromatography-mass spectrometry for the simultaneous analysis of 29 illicit and therapeutic drugs of abuse. All 29 drugs could be reliably identified in spiked waste water samples using selected ion monitoring and splitless injection. Recoveries for the majority of the drugs were above 70 %. Linearity varied based on the analyte but was assessed in the range 2.0 x 10-4 to 1.4 μg/mL. Intra-assay and intermediate precision of the instrument was determined at 0.005, 0.1 and 1.0 μg/mL, with the majority of relative standard deviations less than 10 %. Limits of detection and quantification for drugs such as amphetamine and methamphetamine were better than reported values for liquid chromatography-tandem mass spectrometry, a more commonly used technique. Untreated 72 h composite waste water samples from Cambridge, UK, were analysed using a six-point standard addition curve. Eleven drugs of abuse were detected, including amphetamine, methamphetamine, butylone and 4-fluoromethamphetamine. The latter two having been detected for the very first time in waste water. Using the validated method, the consumption of heroin, ketamine, cocaine, methamphetamine and amphetamine, in Cambridge, UK, was estimated to be 399.4 ± 90.8, 2463.5 ± 182.5, 195.5 ± 95.4, 84.3 ± 59.1 and 38.9 ± 24.8 mg/day per 1000 inhabitants. This is the first reported validated method for the detection of both classic drugs of abuse and new psychoactive substances in waste water using gas chromatography-mass spectrometry and derivatization with pentafluoropropionic anhydride.

Energy demand, greenhouse gas emissions, and operational costs are continuing to rise year on year in the wastewater treatment sector, with traditional treatment options unable to provide sustainable solutions to increasing volumes and tightening quality standards. Current processes produce inherent fugitive greenhouse gas (GHG) emissions, whilst also generating large quantities of sludge for disposal. Anaerobic ponds (APs) are natural wastewater treatment processes that have traditionally been confined to a pre-treatment stage of larger stabilisation pond systems. Consequently, current standard guidelines are not suited for low temperature, weak strength wastewaters, or for the emerging usage of APs for energy recovery and enhanced organic breakdown. To establish effective guidelines for adapting AP design for this purpose, this thesis explores the fundamental mechanisms with APs, in order to provide design alterations to enhance AP performance for full flow domestic wastewater treatment with a focus on the UK water sector. Initially, a literature review of current AP design guidelines was conducted to determine the current state of the art and understand the fundamental design processes currently adopted. The review found that most APs are currently underloaded, largely to avoid malodour emissions, but this leads to unnecessarily large footprints and inhibits the digestion process through restricting biomass/substrate contact. It was concluded that the current design guidelines are not suitable for recent AP developments and application, such as covering to prevent odour escape, and the use of baffling to improve mixing and enhance organic degradation. A pilot scale study was conducted on UK domestic wastewater to gain insight into the limitations of current AP design for this application and identify areas for optimisation. The pilot trial demonstrated the efficacy of AP usage for low temperature, weak strength wastewaters, even with unoptimised design. Decoupling hydraulic and solids retention time lead to biomass retention and subsequent acclimatisation, and was able to compensate for the low temperatures and weak wastewater. It was concluded that APs can provide an attractive alternative to current primary treatment options, through reducing GHG emissions and providing less frequent desludging requirements. To optimise AP design, the effect of baffle configuration on AP hydrodynamics and the subsequent impact on treatment efficiency was investigated, in order to develop structural designs specifically targeting enhanced anaerobic degradation. Advantages found in baffling APs included improving mixing patterns between baffles, enhancing biomass/substrate contact, and creating an overall plug flow effect through the entire pond enabling the retention of biomass. Furthermore, the removal mechanism with the pond can be manipulated with use of baffles, with different orientations generating different flow patterns and therefore creating conditions preferential for greater solids settlement and capture, or mixing and contact. Following trials on single stage alternate baffling configurations, the development of a novel two stage AP design was trialled, applying knowledge gained from trials of differing baffle orientations to target separate stages of organic breakdown. Further trials were conducted on the staged AP to establish optimal loading rates to be applied to APs in order to maximise performance and reduce physical footprint. These trials led to recommended design improvements including shorter hydraulic retention times (HRTs) to enhance mixing and decrease physical footprint, and improvements to the staged AP design to greater separate the stages of anaerobic digestion and provide optimal conditions for the stages at different points in the AP. Finally, the knowledge gained from experimental work was used to present evidence for the inclusion of APs into decentralised WWT through flowsheet modelling of a proposed AP treatment works compared to a current base case. Advantages were found in decreasing sludge management requirements whilst providing suitable primary treatment, with additional potential benefits in renewable energy generation, which could increase both with improved biogas yields and the option of combining with other renewable technologies. In some circumstances, it may be possible for an AP flowsheet to operate entirely off-grid, eliminating the need for costly infrastructure such as permanent access roads and national electrical grid connection.

Economic utilisation of biogas arising from sewage sludge is hampered by the need to remove siloxanes, which damage gas engines upon combustion. This thesis applies on-line Fourier transform infrared spectroscopy to measure siloxanes in biogas upstream and downstream of the activated carbon vessels designed to adsorb siloxanes. On-line analysis provides accurate measurement of siloxane concentrations with a detection limit below the siloxane limits set by engine manufacturers, high data intensity and timely identification of breakthrough. Cost savings of up to £0.007 kWh- 1 may be realised compared to existing grab sampling. Using on-line analysis, the performance of full-scale and bench-scale carbon vessels were measured. Full-scale carbon contactors are typically operated at Reynold’s numbers close to the boundary between the laminar and transitional regimes (Re = 40 - 55). This thesis demonstrates, at full- and bench-scale, that increasing the Reynold’s number to site the adsorption process in the transitional regime increases media capacity, by 36% in dry gas and by 400% at 80% humidity. It is postulated that the change in gas velocity profile which occurs as Reynold’s number increases reduces the resistance to siloxane transport caused by gas and water films around the carbon particles, and therefore increases the rate of the overall adsorption process. In the laminar regime (Re = 31) increasing humidity from zero to 80% led to the classical stepwise reduction in adsorption capacity observed by other researchers, caused by the increasing thickness of the water film, but in the transitional regime (Re = 73) increasing humidity had no effect as no significant water film develops. It is therefore recommended that siloxane adsorption vessels should be designed to operate at Reynold’s numbers above 55. By choosing a high aspect ratio (tall and thin) both Reynold’s number and contact time can be optimised.