Flux-step method for the assessment of operational conditions in a submerged membrane bioreactor.

A flux-step method was used for monitoring the pressure variation in a solids separation membrane at different operating conditions. A submerged membrane bioreactor pilot plant, used during the short-term tests, was used to purify actual restaurant wastewater. The influence of membrane backwash and relaxation on the variation of pressure variation was also evaluated. In order to reduce the deposition of irreversible fouling, the authors modified the literature-supported filtration to backwash cycling with filtration and relaxation cycling. The trials maintained a constant filtration to relaxation ratio that was in line with optimal filtration to backwashing ratios found in the literature. The relaxation cycling between two constant flux-steps effectively counteracted membrane fouling and the excessive decrease in average pressure, and it results in a lower waste of energy and water than a backwashing strategy.

Striking the balance between nutrient removal, greenhouse gas emissions, receiving water quality, and costs.

This Water Environment Research Foundation study considered the relationship between varying nutrient-removal levels at wastewater treatment plants, greenhouse gas emissions, receiving water quality (measured by potential algal production), and costs. The effluent nutrient concentrations required by some U.S. permits are very low, approaching the technology-best-achievable performance. This study evaluated five different treatment levels at a nominal 40 ML/d (10 mgd) flow. Greenhouse gas emissions and costs increase gradually up to the technologies' best-achievable performance, after which they increase exponentially. The gradual increase is attributed to additional biological treatment facilities, increased energy and chemical use, and additional tertiary nitrogen and phosphorus removal processes. Within the limited focus of this study, the evaluation shows that a point of diminishing return is reached as nutrient-removal objectives approach the technology-best-achievable performance, where greenhouse gas emissions and cost of treatment increases rapidly while the potential for algal growth reduce marginally.

Microbial community dynamics in replicate membrane bioreactors--natural reproducible fluctuations.

We operated 4 replicate membrane bioreactors (MBRs) in parallel to test if an acclimated seed inoculum would evolve similarly following even distribution into replicates. A cloning and sequencing library of 16S rRNA genes was obtained from the seed inoculum complemented with terminal restriction fragment length polymorphism (T-RFLP; n=18 per reactor) analysis over the study period (n=113 d) that targeted the 16S rRNA gene. The amoA functional gene was also monitored by T-RFLP. The T-RFLP results were analyzed by means of diversity indices, an adaptation of a moving window of similarity approach within each MBR, and non-metric multi-dimensional scaling (NMS) accompanied with multi-response permutation procedures (MRPP) to assess community interrelationships amongst MBRs. Based on the 16S rRNA microbial communities, the 4 MBRs initially diverged away from one another, followed by a convergence on Day 4. From thereon, the 16S rRNA-based communities evolved similarly throughout (average p-value=0.49 from pair-wise MRPP). In contrast, the nitrifying communities did not undergo any discernable shift over time amongst MBRs according to T-RFLP analysis of amoA and revealed one cluster by NMS (average p-value=0.83 from pair-wise MRPP). The study demonstrates that acclimated microbial communities evolve similarly over time in engineered systems when operational parameters are left unchanged.

Support vector regression model of wastewater bioreactor performance using microbial community diversity indices: effect of stress and bioaugmentation.

The relationship between microbial community structure and function has been examined in detail in natural and engineered environments, but little work has been done on using microbial community information to predict function. We processed microbial community and operational data from controlled experiments with bench-scale bioreactor systems to predict reactor process performance. Four membrane-operated sequencing batch reactors treating synthetic wastewater were operated in two experiments to test the effects of (i) the toxic compound 3-chloroaniline (3-CA) and (ii) bioaugmentation targeting 3-CA degradation, on the sludge microbial community in the reactors. In the first experiment, two reactors were treated with 3-CA and two reactors were operated as controls without 3-CA input. In the second experiment, all four reactors were additionally bioaugmented with a Pseudomonas putida strain carrying a plasmid with a portion of the pathway for 3-CA degradation. Molecular data were generated from terminal restriction fragment length polymorphism (T-RFLP) analysis targeting the 16S rRNA and amoA genes from the sludge community. The electropherograms resulting from these T-RFs were used to calculate diversity indices - community richness, dynamics and evenness - for the domain Bacteria as well as for ammonia-oxidizing bacteria in each reactor over time. These diversity indices were then used to train and test a support vector regression (SVR) model to predict reactor performance based on input microbial community indices and operational data. Considering the diversity indices over time and across replicate reactors as discrete values, it was found that, although bioaugmentation with a bacterial strain harboring a subset of genes involved in the degradation of 3-CA did not bring about 3-CA degradation, it significantly affected the community as measured through all three diversity indices in both the general bacterial community and the ammonia-oxidizer community (α = 0.5). The impact of bioaugmentation was also seen qualitatively in the variation of community richness and evenness over time in each reactor, with overall community richness falling in the case of bioaugmented reactors subjected to 3-CA and community evenness remaining lower and more stable in the bioaugmented reactors as opposed to the unbioaugmented reactors. Using diversity indices, 3-CA input, bioaugmentation and time as input variables, the SVR model successfully predicted reactor performance in terms of the removal of broad-range contaminants like COD, ammonia and nitrate as well as specific contaminants like 3-CA. This work was the first to demonstrate that (i) bioaugmentation, even when unsuccessful, can produce a change in community structure and (ii) microbial community information can be used to reliably predict process performance. However, T-RFLP may not result in the most accurate representation of the microbial community itself, and a much more powerful prediction tool can potentially be developed using more sophisticated molecular methods.

Partial bioaugmentation to remove 3-chloroaniline slows bacterial species turnover rate in bioreactors.

Bioaugmentation is a potentially powerful tool to direct community structure and metabolic capacities in bioreactors. Yet the outcome of bioaugmentation studies is usually unpredictable and effects on microbial community dynamics are poorly understood. We asked the question whether bioaugmentation could prevent a diversity shift induced by a model toxin, 3-chloroaniline (3-CA), regardless of whether 3-CA was degraded. Four replicate membrane bioreactors (MBRs) operating in parallel were amended with Pseudomonas putida UWC3 (pWDL7::rfp), a strain that carries the upper pathway genes necessary for partial degradation of 3-CA on its plasmid. Two MBRs served as controls and two MBRs were exposed to 3-CA for 71 days. Despite the selective pressure imposed by 3-CA, there was little or no 3-CA removal and neither the 16S rRNA gene of the augmented strain UWC3 nor the plasmid pWDL7::rfp proliferated in any of the reactors. Yet both host strain and plasmid were maintained at reduced levels (~10(4) host strain cells ml(-1)) in all reactors compared to the initial inoculum (~10(7) cells ml(-1); 1% of active cells). Additionally, the microbial community dynamics were evaluated for each MBR via terminal restriction fragment length polymorphism (T-RFLP) analysis (n = 15 per reactor) that targeted a portion of the 16S rRNA gene. Analysis comprised of a suite of multivariate statistics coupled with a theoretical microbial ecological approach, 'Island Biogeography', using a bacterial species time relationship (STR), within each MBR. Control MBRs had a wider range in w values than the treatment MBRs, which is attributed to the lack of a toxin selecting for biota that can withstand its toxic nature. Bioaugmentation alone strongly slowed the bacterial species turnover rate (as revealed by very low w scaling components), compared to non-bioaugmented reactors from a previous study, but did not protect the microbial community from a diversity shift caused by the toxin. Nonmetric multidimensional scaling (NMDS) analysis revealed that treatment MBRs diverged away from the control MBRs after the first 11 days, whereas control MBRs remained clustered. Individual reactors were analyzed by multi-response permutation procedures (MRPP) and a significant difference was found between each control MBR and the treatment MBRs. The study suggests that newly introduced strains can gain a foothold in established microbial communities even at low cell concentrations (about 1% of introduced concentration within the first week) regardless of selective pressure, whereas community dynamics are more affected by the presence of a selector toxin.

Effects of the toxin 3-chloroaniline at low concentrations on microbial community dynamics and membrane bioreactor performance.

The effects of toxins at ambient concentrations on microbial activity and community dynamics are poorly understood. We operated 4 membrane bioreactors (MBRs) in parallel; two reactors were continuously exposed to the toxin 3-chloroaniline (3-CA) at environmentally relevant levels, representing 25% of the total chemical oxygen demand (COD; Total COD = 400 mg l(-1) d(-1)), and two reactors received no 3-CA. During the 70 d exposure to 3-CA the microbial communities never adapted as evidenced by a 48% and 14% reduction in COD and ammonia removal, respectively, compared to over 92% reduction for both measurements in the controls. The bacterial 16S rRNA gene was monitored using terminal restriction fragment length polymorphism (T-RFLP) analysis (n = 15 temporal grab samples per reactor) over the 70 d period. T-RFLP spectra analysis compared the rapid species turnover rate (STR) approach with the more computationally intensive non-metric multi-dimensional scaling (NMS) complemented with multi-response permutation procedure (MRPP). The methods revealed comparable findings and the presence of 3-CA selected for a more convergent community with less bacterial turnover. In contrast, the control MBRs were more divergent as evidenced by greater bacterial turnover variability. The importance of studying replicate reactors is highlighted by the fact that one of the two controls was significantly different from the treatment MBRs (p-value = 0.01, α = 0.05) whereas the other one was not (p-value = 0.24, α = 0.05). The study suggests that analysis of community dynamics with the rapid STR approach and with NMS/MRPP can lead to comparable results when targeting the 16S rRNA gene. The use of replicate bioreactors is essential for meaningful interpretation of microbial community patterns.