Philip Antwi

Efficiency and bacterial populations related to pollutant removal in an upflow microaerobic sludge reactor treating manure-free piggery wastewater with low COD/TN ratio.

A novel upflow microaerobic sludge reactor (UMSR) had proved excellent in nitrogen removal from manure-free piggery wastewater characterized by high concentration of ammonium (NH4(+)-N) and low chemical oxygen demand (COD) to total nitrogen (TN) ratio, but the biological mechanism in the UMSR was still indeterminate. With a constant nitrogen loading rate of 1.10kg/(m(3)d) at hydraulic retention time 8h, the UMSR was kept performing for 67days in the present research and the average load removal of COD, NH4(+)-N and TN was as high as 0.72, 0.76 and 0.94kg/(m(3)d), respectively. Compared with the inoculated sludge, the acclimated sludge was richer in genera responsible for the biological removal of carbon, nitrogen and phosphorus. Ammonium oxidation bacteria, heterotrophic denitrifiers, autotrophic denitrifiers and phosphate accumulating organisms coexisted perfectly in the microaerobic system, and their synergistic action made the UMSR perform well in COD, NH4(+)-N, TN and phosphate removal.

Nitrogen removal from low COD/TN ratio manure-free piggery wastewater within an upflow microaerobic sludge reactor.

An upflow microaerobic sludge reactor (UMSR) was constructed in treating manure-free piggery wastewater with high ammonium concentration and a COD/TN ratio as low as 0.84. The UMSR offered an outstanding removal of NH4(+)-N and TN at 35°C and hydraulic retention time 8h subsequent to inoculated sludge acclimation. A short NO2(-)-N accumulation phase was observed whenever there was a considerable increase in TN loading rate (NLR), but decreased rapidly along with an evident increase in TN removal. Fed with raw wastewater at a NLR of 1.10 kg/(m(3)d), the average COD, NH4(+)-N and TN removal reached 0.72, 0.76 and 0.94 kg/(m(3)d), respectively. Inference drawn from stoichiometry based on the potential nitrogen removal pathways and the C/N ratio required by denitrification indicated that anammox was the main mechanism for NH4(+)-N and TN removal in the UMSR.

Estimation of Biogas and Methane Yields in an UASB Treating Potato Starch Processing Wastewater with Backpropagation Artificial Neural Network

Three-layered feedforward backpropagation (BP) artificial neural networks (ANN) and multiple nonlinear regression (MnLR) models were developed to estimate biogas and methane yield in an upflow anaerobic sludge blanket (UASB) reactor treating potato starch processing wastewater (PSPW). Anaerobic process parameters were optimized to identify their importance on methanation. pH, total chemical oxygen demand, ammonium, alkalinity, total Kjeldahl nitrogen, total phosphorus, volatile fatty acids and hydraulic retention time selected based on principal component analysis were used as input variables, whiles biogas and methane yield were employed as target variables. Quasi-Newton method and conjugate gradient backpropagation algorithms were best among eleven training algorithms. Coefficient of determination (R2) of the BP-ANN reached 98.72% and 97.93% whiles MnLR model attained 93.9% and 91.08% for biogas and methane yield, respectively. Compared with the MnLR model, BP-ANN model demonstrated significant performance, suggesting possible control of the anaerobic digestion process with the BP-ANN model.

Functional bacterial and archaeal diversity revealed by 16S rRNA gene pyrosequencing during potato starch processing wastewater treatment in an UASB

Microbial community structure of sludge sampled from an UASB treating potato starch processing wastewater (PSPW) was investigated. Operational taxonomic units revealed at 97% sequence identity tolerance was 2922, 2869 and 3919 for bottom, middle and top sections of the reactor, respectively. Overall abundant phylum observed within the UASB was low-G+C-Gram-positive bacteria affiliated to Firmicutes (26.01%) followed by Chloroflexi (16.70%), Proteobacteria (12.71%), Cloacimonetes (10.72%), Bacteroidetes (7.87%), Synergistetes (9.02%) and Euryarchaeota (8.82%). Whiles Firmicutes had dominated the bottom and top section by 34.01% and 28.64%, respectively, middle section was predominantly Euryarchaeota (24.32%) with major dominance in methanogens affiliated to genus Methanosaeta. The results demonstrated substantial stratification of the microbial community structure along the reactor height with various functional bacterial groups which subsequently allowed degradation of organics in PSPW in sequential mode. The findings herein would provide guidance for optimizing the anaerobic process and operation of the UASB.

Efficiency of an upflow anaerobic sludge blanket reactor treating potato starch processing wastewater and related process kinetics, functional microbial community and sludge morphology

Herein, an upflow anaerobic sludge blanket reactor was employed to treat potato starch processing wastewater and the efficacy, kinetics, microbial diversity and morphology of sludge granules were investigated. When organic loading rate (OLR) ranging from 2.70 to 13.27kgCOD/m3.d was implemented with various hydraulic retention times (72h, 48h and 36h), COD removal could reach 92.0-97.7%. Highest COD removal (97.7%) was noticed when OLR was 3.65kgCOD/m3.d, but had declined to 92.0% when OLR was elevated to 13.27kgCOD/m3.d. Methane and biogas production increased from 0.48 to 2.97L/L.d and 0.90 to 4.28L/L.d, respectively. Kinetics and predictions by modified-Gompertz model agreed better with experimental data as opposed to first-order kinetic model. Functional population with highest abundance was Chloroflexi (28.91%) followed by Euryarchaeota (22.13%), Firmicutes (16.7%), Proteobacteria (16.25%) and Bacteroidetes (7.73%). Compared with top sludge, tightly-bound extracellular polymeric substances was high within bottom and middle sludge. Morphology was predominantly Methanosaeta-like cells, Methanosarcina-like cells, rods and cocci colonies.

Modeling the dynamic volatile fatty acids profiles with pH and hydraulic retention time in an anaerobic baffled reactor during the startup period.

To predict the dynamic profiles in volatile fatty acids (VFAs) with pH and hydraulic retention time (HRT) during the startup of a 4-compartment ABR, a mathematical model was constructed by introducing pH and thermodynamic inhibition functions into the biochemical processes derived from the ADM1. The calibration of inhibition parameter for propionate uptake effectively improved the prediction accuracy of VFAs. The developed model could simulate the VFAs profiles very well no matter the observable change of pH or/and HRT. The simulation results indicated that both H2-producing acetogenesis and methanogenesis in the ABR would be inhibited with a pH less than 4.61, and the propionate oxidation could be thermodynamically restricted even with a neutral pH. A decreased HRT would enhanced the acidogenesis and H2-producing acetogenesis in the first 3 compartments, but no observable increase in effluent VFAs could be found due to the synchronously enhanced methanogenesis in the last compartment.

Modeling the performance of an anaerobic baffled reactor with the variation of hydraulic retention time

Anaerobic baffled reactors (ABRs) have been widely used in engineering but very few models have been developed to simulate its performance. Based on the integration of biomass retention and liquid-gas mass transfer of biogas into the biochemical process derived in the International Water Association (IWA) Anaerobic Digestion Model No.1 (ADM1), a mathematical model was developed to predict volatile fatty acids (VFAs), chemical oxygen demand (CODCr) and biogas in a 4-compartment ABR operated with variable hydraulic retention time (HRT). The model was calibrated and validated with the experimental data obtained from the reactor when the HRT decreased from 2.0 to 1.0d by stages. It was found that the predicted VFAs, CODCr and biogas agreed well with the experimental data. Consequently, the developed model was a reliable tool to enhance the understanding among the mechanisms of the anaerobic digestion in ABRs, as well as to reactors designing and operation.

Enhanced nitrogen removal from piggery wastewater with high NH 4 + and low COD/TN ratio in a novel upflow microaerobic biofilm reactor

To enhance nutrient removal more cost-efficiently in microaerobic process treating piggery wastewater characterized by high ammonium (NH4+-N) and low chemical oxygen demand (COD) to total nitrogen (TN) ratio, a novel upflow microaerobic biofilm reactor (UMBR) was constructed and the efficiency in nutrient removal was evaluated with various influent COD/TN ratios and reflux ratios. The results showed that the biofilm on the carriers had increased the biomass in the UMBR and enhanced the enrichment of slow-growth-rate bacteria such as nitrifiers, denitrifiers and anammox bacteria. The packed bed allowed the microaerobic biofilm process perform well at a low reflux ratio of 35 with a NH4+-N and TN removal as high as 93.1% and 89.9%, respectively. Compared with the previously developed upflow microaerobic sludge reactor, the UMBR had not changed the dominant anammox approach to nitrogen removal, but was more cost-efficiently in treating organic wastewater with high NH4+-N and low COD/TN ratio.

The role of COD/N ratio on the start-up performance and microbial mechanism of an upflow microaerobic reactor treating piggery wastewater

This study investigated the role of COD/N ratio on the start-up and performance of an upflow microaerobic sludge reactor (UMSR) treating piggery wastewater at 0.5 mgO2/L. At high COD/N ratio (6.24 and 4.52), results showed that the competition for oxygen between ammonia-oxidizing bacteria, nitrite-oxidizing bacteria and heterotrophic bacteria limited the removal of nitrogen. Nitrogen removal efficiency was below 40% in both scenarios. Decreasing the influent COD/N ratio to 0.88 allowed achieving high removal efficiencies for COD (∼75%) and nitrogen (∼85%) due to the lower oxygen consumption for COD mineralization. Molecular biology techniques showed that nitrogen conversion at a COD/N ratio 0.88 was dominated by the anammox pathway and that Candidatus Brocadia sp. was the most important anammox bacteria in the reactor with a relative abundance of 58.5% among the anammox bacteria. Molecular techniques also showed that Nitrosomonas spp. was the major ammonia-oxidiser bacteria (relative abundance of 86.3%) and that denitrification via NO3- and NO2- also contributed to remove nitrogen from the system.

Feedforward neural network model estimating pollutant removal process within mesophilic upflow anaerobic sludge blanket bioreactor treating industrial starch processing wastewater.

In this a, three-layered feedforward-backpropagation artificial neural network (BPANN) model was developed and employed to evaluate COD removal an upflow anaerobic sludge blanket (UASB) reactor treating industrial starch processing wastewater. At the end of UASB operation, microbial community characterization revealed satisfactory composition of microbes whereas morphology depicted rod-shaped archaea. pH, COD, NH4+, VFA, OLR and biogas yield were selected by principal component analysis and used as input variables. Whilst tangent sigmoid function (tansig) and linear function (purelin) were assigned as activation functions at the hidden-layer and output-layer, respectively, optimum BPANN architecture was achieved with Levenberg-Marquardt algorithm (trainlm) after eleven training algorithms had been tested. Based on performance indicators such the mean squared errors, fractional variance, index of agreement and coefficient of determination (R2), the BPANN model demonstrated significant performance with R2 reaching 87%. The study revealed that, control and optimization of an anaerobic digestion process with BPANN model was feasible.