• Energy Research

Third generation biofuels, e.g. biofuels production from algal biomass, have gained attention due to increased interest on global renewable energy. However, crop-based biofuels compete with food production and should be avoided. Microalgal cultivation for biofuel production offers an alternative to crops and can become economically viable when combined with the use of used water resources. Besides nutrients and water, harvesting microalgal biomass represents one of the major costs related to biofuel production and thus efficient and cheap solutions are needed. In bacterial-algal systems, there is the potential to produce energy by co-digesting the two types of biomass. We present an innovative approach to recover microalgal biomass via a two-step flocculation using bacterial biomass after the destabilisation of microalgae with conventional cationic polymer. A short solids retention time (SRT) enhanced biological phosphorus removal (EBPR) system was combined with microalgal cultivation. Two different bacterial biomass removal strategies were assessed whereby bacterial biomass was collected from the solid-liquid separation after the anaerobic phase and after the aerobic phase. Microalgal recovery was tested by jar tests where three different chemical coagulants in coagulation-flocculation tests (AlCl3, PDADMAC and Greenfloc 120) were assessed. Furthermore, jar tests were conducted to assess the microalgal biomass recovery by a two-step flocculation method, involving chemical coagulants in the first step and bacterial biomass used in the second step to enhance the flocculation. Up to 97% of the microalgal biomass was recovered using 16 mg polymer/g algae and 0.1 g algae/g bacterial biomass. Moreover, the energy recovery by the short-SRT EBPR system combined with microalgal cultivation was assessed via biomethane potential tests. Up to 560 ± 24 mL CH4/gVS methane yield was obtained by co-digesting bacterial biomass collected after the anaerobic phase and microalgal biomass. The energy recovery in terms of methane production obtained in the short-SRT EBPR system is about 40% of the influent chemical energy.

A sorptive slurry bioscrubber adds powdered activated carbon (PAC) to a conventional suspended-growth bioscrubber. The activated carbon increases pollutant removal from the gas phase due to adsorption on carbon. The carbon is bioregenerated in the oxidation reactor and recycled to the scrubbing column. A three-stage, conventional bioscrubber was tested with and without carbon. The experiments showed that the PAC improved the removal efficiency of the system and that bioregeneration occurred. At an inlet gas-phase acetone concentration of 50 ppmv, the steady-state removal increased from 88 to 95% when activated carbon was added to the biological slurry.

Kinetic characterization of biological processes via batch respirometry requires an accurate estimate of the biomass yield coefficient because it provides the stoichiometric link between biomass synthesis, substrate consumption and oxygen uptake. Expressions for biomass yield coefficients describing autotrophic ammonia and nitrite oxidation were derived from a mechanistically based electron balanced equation. We demonstrate that applying the conventional expression used to calculate the heterotrophic biomass yield results in erroneous estimates for the autotrophic biomass yield. Yield coefficients for autotrophic NH4(+)-N to NO2(-)-N oxidation and NH4(+)-N to NO3(-)-N oxidation were overestimated by 27 to 36%. Due to correlation between the maximum specific growth rate and the biomass yield, the error in yield values propagated in 30 to 40% overestimates of the maximum specific growth rate coefficient for NH4(+)-N oxidation determined from batch respirograms. Therefore, it is essential to employ the correct expression to estimate the autotrophic biomass yield coefficient from batch respirograms due its inadvertent impact on subsequent parameter estimation.

Anaerobic ammonium oxidation (anammox) is a cost-effective process to treat high-strength nitrogenous wastewater. Even without organic carbon input, the effluent contains bioproducts from autotrophic and heterotrophic bacteria. In this work, excitation-emission matrix (EEM) fluorescence spectroscopy was used to characterize the effluent dissolved organic matter (EfOM) from an anammox reactor treating synthetic wastewater. Two dominant EEM components were identified as humic acid-like (component 1) and protein-like (component 2) substances with excitation/emission peaks at <240, 355, 420/464 nm and <240, 280, 330/346 nm, respectively. The presence of both compounds in the effluent was tracked during an activity recovery period (nitrogen load increased from 0.2 to 1.3 kg Nm(-3)d(-1)). The effluent concentration of both components increased during this period, indicating correlation between production and bacterial activity. The dynamics of these bioproducts during both substrate consumption and starvation phases was analyzed in batch experiments. Component 1 was only formed during substrate consumption in a rate proportional to ammonium removal and was considered an up-take associated product characteristic of anammox activity. The results show that the composition of the EfOM was qualitatively and quantitatively influenced by process performance. Monitoring the EfOM could, therefore, offer a useful approach to assess anammox process performance and must be further explored.

Batch autotrophic ammonia oxidation tracked through oxygen uptake measurements displays a preliminary acceleration phase. Failure to recognize the acceleration phase and fitting batch ammonia oxidation profiles with standard Monod‐type mathematical models can result in meaningless kinetic parameter estimates. The objectives of this study were to examine the factors controlling the acceleration phase and to derive and test empirical and metabolic models for its description. Because of possible sustained reducing power limitation during batch ammonia oxidation, the extent of the acceleration phase (1) increased with increasing initial ammonia concentration, (2) did not systematically vary with initial biomass concentrations, and (3) increased in response to starvation. Concurrent hydroxylamine oxidation significantly reduced the acceleration phase potentially by relieving reducing power limitation. A nonlinear empirical model described the acceleration phase more accurately than a linear empirical model. The metabolic model also captured experimental trends exceedingly well, but required determination of additional parameters and variables.

AbstractAddition of hydroxylamine (NH2OH) to autotrophic biomass in nitrifying bioreactors affected the activity, physical structure, and microbial ecology of nitrifying aggregates. When NH2OH is added to nitrifying cultures in 6‐h batch experiments, the initial NH3‐N uptake rates were physiologically accelerated by a factor of 1.4–13. NH2OH addition caused a 20–40% decrease in the median aggregate size, broadened the shape of the aggregate size distribution by up to 230%, and caused some of the microcolonies to appear slightly more dispersed. Longer term NH2OH addition in fed batch bioreactors decreased the median aggregate size, broadened the aggregate size distribution, and decreased NH3‐N removal from >90% to values ranging between 75% and 17%. This altered performance is explained by quantitative fluorescence in situ hybridization (FISH) results that show inhibition of nitrifying populations, and by qPCR results showing that the copy numbers of amoA and nxrA genes gradually decreased by up to an order‐of‐magnitude. Longer term NH2OH addition damaged the active biomass. This research clarifies the effect of NH2OH on nitrification and demonstrates the need to incorporate NH2OH‐related dynamics of the nitrifying biomass into mathematical models, accounting for both ecophysiological and structural responses. Biotechnol. Bioeng. 2009; 102: 714–724. © 2008 Wiley Periodicals, Inc.

The NDHA model comprehensively describes nitrous oxide (N2O) producing pathways by both autotrophic ammonium oxidizing and heterotrophic bacteria. The model was calibrated via a set of targeted extant respirometric assays using enriched nitrifying biomass from a lab-scale reactor. Biomass response to ammonium, hydroxylamine, nitrite and N2O additions under aerobic and anaerobic conditions were tracked with continuous measurement of dissolved oxygen (DO) and N2O. The sequential addition of substrate pulses allowed the isolation of oxygen-consuming processes. The parameters to be estimated were determined by the information content of the datasets using identifiability analysis. Dynamic DO profiles were used to calibrate five parameters corresponding to endogenous, nitrite oxidation and ammonium oxidation processes. The subsequent N2O calibration was not significantly affected by the uncertainty propagated from the DO calibration because of the high accuracy of the estimates. Five parameters describing the individual contribution of three biological N2O pathways were estimated accurately (variance/mean < 10% for all estimated parameters). The NDHA model response was evaluated with statistical metrics (F-test, autocorrelation function). The 95% confidence intervals of DO and N2O predictions based on the uncertainty obtained during calibration are studied for the first time. The measured data fall within the 95% confidence interval of the predictions, indicating a good model description. Overall, accurate parameter estimation and identifiability analysis of ammonium removal significantly decreases the uncertainty propagated to N2O production, which is expected to benefit N2O model discrimination studies and reliable full scale applications.

A comprehensive and global sensitivity analysis was conducted under a range of operating conditions. The relative importance of mass transfer resistance versus kinetic parameters was studied and found to depend on the operating regime as follows: Operating under the optimal loading ratio of 1.90(gO(2)/m(3)/d)/(gN/m(3)/d), the system was influenced by mass transfer (10% impact on nitrogen removal) and performance was limited by AOB activity (75% impact on nitrogen removal), while operating above, AnAOB activity was limiting (68% impact on nitrogen removal). The negative effect of oxygen mass transfer had an impact of 15% on nitrogen removal. Summarizing such quantitative analyses led to formulation of an optimal operation window, which serves a valuable tool for diagnosis of performance problems and identification of optimal solutions in nitritation/anammox applications.