Abstract: Enzyme cost is considered to be one of the most significant factors defining the final product price in lignocellulose hydrolysis and fermentation. Enzyme immobilization and recycling can be a tool to decrease costs. However, high solid loading is a key factor towards high product titers, and recovery of immobilized enzymes from this thick liquid is often overlooked. This paper aims to evaluate the economic feasibility of immobilized enzymes in simultaneous saccharification and fermentation (SSF) of lignocellulose biomass in general, as well as the recuperation of magnetic immobilized enzymes (m-CLEAs) during high solid loading in simultaneous saccharification, detoxification and fermentation processes (SSDF) of lignocellulose biomass. Enzyme prices were obtained from general cost estimations by Klein-Marcuschamer et al. [Klein-Marcuschamer et al. (2012) Biotechnol. Bioeng. 109, 10831087]. During enzyme cost analysis, the influence of inoculum recirculation as well as a shortened fermentation time was explored. Both resulted in 15% decrease of final enzyme product price. Enzyme recuperation was investigated experimentally and 99.5 m/m% of m-CLEAs was recovered from liquid medium in one step, while 88 m/m% could still be recycled from a thick liquid with high solid concentrations (SSF fermentation broth). A mathematical model was constructed to calculate the cost of immobilized and free enzyme utilization and showed that, with current process efficiencies and commercial enzyme prices, the cost reduction obtained by enzyme immobilization can reach around 60% compared to free enzyme utilization, while lower enzyme prices will result in a lower percentage of immobilization related savings, but overall enzyme costs will decrease significantly. These results are applied in a case study, estimating the viability of shifting from sugar to lignocellulose substrate for a 100 t lactic acid fermentation batch. It was concluded that it will only be economically feasible if the enzymes are produced at the most optimistic variable cost and either the activity of the immobilized catalyst or the recovery efficiency is further increased.

Abstract: Complete removal of estrogens such as estrone (E1), estradiol (E2), estriol (E3) and ethinylestradiol (EE2) in wastewater treatment is essential since their release and accumulation in natural water bodies are giving rise to environment and health issues. To improve our understanding towards the estrogen bioremediation process, a mathematical model was proposed for describing estrogen removal by nitrifying activated sludge. Four pathways were involved in the developed model: i) biosorption by activated sludge flocs; ii) cometabolic biodegradation linked to ammonia oxidizing bacteria (AOB) growth; iii) non growth biodegradation by AOB; and iv) biodegradation by heterotrophic bacteria (HB). The degradation kinetics was implemented into activated sludge model (ASM) framework with consideration of interactions between substrate update and microorganism growth as well as endogenous respiration. The model was calibrated and validated by fitting model predictions against two sets of batch experimental data under different conditions. The model could satisfactorily capture all the dynamics of nitrogen, organic matters (COD), and estrogens. Modeling results suggest that for El, E2 and EE2, AOB-linked biodegradation is dominant over biodegradation by HB at all investigated COD dosing levels. However, for E3, the increase of COD dosage triggers a shift of dominant pathway from AOB biodegradation to HB biodegradation. Adsorption becomes the main contributor to estrogen removal at high biomass concentrations. (C) 2018 Elsevier Ltd. All rights reserved.

Abstract: In this study, we applied cluster beam deposition (CBD) as a new approach for fabricating efficient plasmon-based photocatalytic materials. Au nanoclusters (AuNCs) produced in the gas phase were deposited on TiO2 P25-coated silicon wafers with coverage ranging from 2 to 8 atomic monolayer (ML) equivalents. Scanning Electron Microscopy (SEM) images of the AuNCs modified TiO2 P25 films show that the surface is uniformly covered by the AuNCs that remain isolated at low coverage (2 ML, 4 ML) and aggregate at higher coverage (8 ML). A clear relationship between AuNCs coverage and photocatalytic activity towards stearic acid photo-oxidation was measured, both under ultraviolet and green light illumination. TiO2 P25 covered with 4 ML AuNCs showed the best stearic acid photo-oxidation performance under green light illumination (Formal Quantum Efficiency 1.6 x 10-6 over a period of 93 h). These results demonstrate the large potential of gas-phase AuNCs beam deposition technology for the fabrication of visible light active plasmonic photocatalysts.

Abstract: Hydrogenotrophic denitrification is a novel and sustainable process for nitrogen removal, which utilizes hydrogen as electron donor, and carbon dioxide as carbon source. Recent studies have shown that nitrous oxide (N2O), a highly undesirable intermediate and potent greenhouse gas, can accumulate during this process. In this work, a new mathematical model is developed to describe nitrogen oxides dynamics, especially N2O, during hydrogenotrophic denitrification for the first time. The model describes electron competition among the four steps of hydrogenotrophic denitrification through decoupling hydrogen oxidation and nitrogen reduction processes using electron carriers, in contrast to the existing models that couple these two processes and also do not consider N2O accumulation. The developed model satisfactorily describes experimental data on nitrogen oxides dynamics obtained from two independent hydrogenotrophic denitrifying cultures under various hydrogen and nitrogen oxides supplying conditions, suggesting the validity and applicability of the model. The results indicated that N2O accumulation would not be intensified under hydrogen limiting conditions, due to the higher electron competition capacity of N2O reduction in comparison to nitrate and nitrite reduction during hydrogenotrophic denitrification. The model is expected to enhance our understanding of the process during hydrogenotrophic denitrification and the ability to predict N2O accumulation.

Abstract: Even though nitrification/denitrification is a robust technology to remove nitrogen from sewage, economic incentives drive its future replacement by shortcut nitrogen removal processes. The latter necessitates high potential activity ratios of ammonia oxidizing to nitrite oxidizing bacteria (rAOB/rNOB). The goal of this study was to identify which wastewater and process parameters can govern this in reality. Two sewage treatment plants (STP) were chosen based on their inverse rAOB/rNOB values (at 20 °C): 0.6 for Blue Plains (BP, Washington DC, US) and 1.6 for Nieuwveer (NV, Breda, NL). Disproportional and dissimilar relationships between AOB or NOB relative abundances and respective activities pointed towards differences in community and growth/activity limiting parameters. The AOB communities showed to be particularly different. Temperature had no discriminatory effect on the nitrifiers' activities, with similar Arrhenius temperature dependences (ΘAOB = 1.10, ΘNOB = 1.061.07). To uncouple the temperature effect from potential limitations like inorganic carbon, phosphorus and nitrogen, an add-on mechanistic methodology based on kinetic modelling was developed. Results suggest that BP's AOB activity was limited by the concentration of inorganic carbon (not by residual N and P), while NOB experienced less limitation from this. For NV, the sludge-specific nitrogen loading rate seemed to be the most prevalent factor limiting AOB and NOB activities. Altogether, this study shows that bottom-up mechanistic modelling can identify parameters that influence the nitrification performance. Increasing inorganic carbon in BP could invert its rAOB/rNOB value, facilitating its transition to shortcut nitrogen removal.

Abstract: Poly aluminum chloride (PAC) is accumulated in waste activated sludge at high levels. However, details of how PAC affects short-chain fatty acids (SCFA) production from anaerobic sludge fermentation has not been documented. This work therefore aims to fill this knowledge gap by analyzing the impact of PAC on the aggregate of sludge flocs, disruption of extracellular polymeric substances (EPS), and the bio-processes of hydrolysis, acid-ogenesis, and methanogenesis. The relationship between SCFA production and different aluminum species (i.e., Ala, Alb, and Alc) was also identified by controlling different OH/Al ratio and pH in different fermentation systems. Experimental results showed that with the increase of PAC addition from 0 to 40 mg Al per gram of total suspended solids, SCFA yield decreased from 212.2 to 138.4 mg COD/g volatile suspended solids. Mechanism exploration revealed that PAC benefited the aggregates of sludge flocs and caused more loosely-and tightly-bound extracellular polymeric substances remained in sludge cells. Besides, it was found that the hydrolysis, acidiogenesis, and methanogenesis processes were all inhibited by PAC. Although three types of Al species, i.e., Ala (Al monomers, dimer, and trimer), Alb (Al-13(AlO4Al12(OH)(24)(H2O) 7+ 12), and Alc (Al polymer molecular weight normally larger than 3000 Da), were co-existed in fermentation systems, their impacts on SCFA production were different. No correlation was found between SCFA and Ala, whereas SCFA production decreased with the contents of Alb and Alc. Compared with Alb, Alc was the major contributor to the decreased SCFA production ( R-2 = 0.5132 vs R-2 = 0.98). This is the first report revealing the underlying mechanism of how PAC affects SCFA production and identifying the contribution of different Al species to SCFA inhibition.

Abstract: Silver nanoparticles are widely used in the field of plasmonics because of their unique optical properties. The wavelength-dependent surface plasmon resonance gives rise to a strongly enhanced electromagnetic field, especially at so-called hot spots located in the nanogap in-between metal nanoparticle assemblies. Therefore, the interparticle distance is a decisive factor in plasmonic applications, such as surface-enhanced Raman spectroscopy (SERS). In this study, the aim is to engineer this interparticle distance for silver nanospheres using a convenient wet-chemical approach and to predict and quantify the corresponding enhancement factor using both theoretical and experimental tools. This was done by building a tunable ultrathin polymer shell around the nanoparticles using the layer-by-layer method, in which the polymer shell acts as the separating interparticle spacer layer. Comparison of different theoretical approaches and corroborating the results with SERS analytical experiments using silver and silver−polymer core−shell nanoparticle clusters as SERS substrates was also done. Herewith, an approach is provided to estimate the extent of plasmonic near-field enhancement both theoretically as well as experimentally.

Abstract: The implementation of nitritation/denitritation (Nit/DNit) as alternative to nitrification/denitrification (N/DN) is driven by operational cost savings, e.g. 1.0-1.8 EUR/ton slurry treated. However, as for any biological nitrogen removal process, Nit/DNit can emit the potent greenhouse gas nitrous oxide (N2O). Challenges remain in understanding formation mechanisms and in mitigating the emissions, particularly at a low ratio of organic carbon consumption to nitrogen removal (CODrem/N-rem). In this study, the centrate (centrifuge supernatant) from anaerobic co-digestion of pig slurry was treated in a sequencing batch reactor. The process removed approximately 100% of ammonium a satisfactory nitrogen loading rate (0.4 g N/L/d), with minimum nitrite and nitrate in the effluent. Substantial N2O emission (around 17% of the ammonium nitrogen loading) was observed at the baseline operational condition (dissolved oxygen, DO, levels averaged at 0.85 mg O-2/L; CODrem/N-rem of 2.8) with similar to 68% of the total emission contributed by nitritation. Emissions increased with higher nitrite accumulation and lower organic carbon to nitrogen ratio. Yet, higher DO levels (similar to 2.2 mg O-2/L) lowered the aerobic N2O emission and weakened the dependency on nitrite concentration, suggesting a shift in N2O production pathway. The most effective N2O mitigation strategy combined intermittent patterns of aeration, anoxic feeding and anoxic carbon dosage, decreasing emission by over 99% (down to similar to 0.12% of the ammonium nitrogen loading). Without anaerobic digestion, mitigated Nit/DNit decreases the operational carbon footprint with about 80% compared to N/DN. With anaerobic digestion included, about 4 times more carbon is sequestered. In conclusion, the low CODrem/N-rem feature of Nit/DNit no longer offsets its environmental sustainability provided the process is smartly operated. (c) 2017 Elsevier Ltd. All rights reserved.

Abstract: The mobilization of arsenic (As) in aquatic environment (groundwater) can cause severe environmental and healthy issues. To develop remediation strategies, we proposed a comprehensive mathematical model to describe the As removal in a arsenite (As (III)) oxidizing and ferrous iron (Fe (II)) oxidizing denitrifying granular biofilm system. In the model framework, the growth-linked microbial oxidation of As (III) and Fe (II) was coupled to chemolithotrophic denitrification of one-step reduction of nitrate to nitrogen gas. Meanwhile, the precipitation of ferric iron (Fe (III)) and adsorption of arsenate (As (V)) onto the biogenic Fe (III) (hydr)oxides were also considered. The model was calibrated by comparing the model predictions against experimental data from batch experiments. The validity of the model was further demonstrated through testing against long-term experimental results from five independent bioreactors with different reactor configurations and operational conditions. Modeling results revealed that the granule size would exert a limited impact on arsenic and iron removal. Nevertheless, their removal efficiencies increased rapidly with the increase of hydraulic retention time (HRT) from 1 h to 12 h, but became independent of HRT as it further increased. The established model framework enables interpretation of a range of experimental observations on As and Fe removal and helps to identify the optimal conditions for enhanced arsenic remediation. (C) 2017 Elsevier Ltd. All rights reserved.

Abstract: To properly estimate and manage pesticide occurrence in urban rivers, it is essential, but often highly challenging, to identify the key pesticide transport pathways in association to the main sources. This study examined the concentration-discharge hysteresis behaviour (hysteresis analysis) for three pesticides and the parent-metabolite concentration dynamics for two metabolites at sites with different levels of urban influence in a mixed land use catchment (25 km(2)) within the Swiss Greifensee area, aiming to identify the dominant pesticide transport pathways. Combining an adapted hysteresis classification framework with prior knowledge of the field conditions and pesticide usage, we demonstrated the possibility of using hysteresis analysis to qualitatively infer the dominant pesticide transport pathway in mixed land-use catchments. The analysis showed that hysteresis types, and therefore the dominant transport pathway, vary among pesticides, sites and rainfall events. Hysteresis loops mostly correspond to dominant transport by flow components with intermediate response time, although pesticide sources indicate that fast transport pathways are responsible in most cases (e.g. urban runoff and combined sewer overflows). The discrepancy suggests the fast transport pathways can be slowed down due to catchment storages, such as topographic depressions in agricultural areas, a wastewater treatment plant (WWTP) and other artificial storage units (e.g. retention basins) in urban areas. Moreover, the WWTP was identified as an important factor modifying the parent-metabolite concentration dynamics during rainfall events. To properly predict and manage pesticide occurrence in catchments of mixed land uses, the hydrological delaying effect and chemical processes within the artificial structures need to be accounted for, in addition to the catchment hydrology and the diversity of pesticide sources. This study demonstrates that in catchments with diverse pesticide sources and complex transport mechanisms, the adapted hysteresis analysis can help to improve our understanding on pesticide transport behaviours and provide a basis for effective management strategies.(C) 2017 Elsevier Ltd. All rights reserved.

Abstract: Nitrate contamination of groundwater has been recognized as a significant environmental problem world widely. Sulfur-driven mixotrophic denitrification has been demonstrated as a promising groundwater treatment process, which though plays an important role in nitrous oxide (N2O) emissions, significantly contributing to the overall carbon footprint of the system. However, the current process optimizations only focus on nitrate removal and excess sulfate control, with the N2O emission being ignored. In this work, an integrated mathematical model was proposed to evaluate the N2O emission as well as the excess sulfate production and carbon source utilization in sulfur-driven mixotrophic denitrification process. In this model, autotrophic and heterotrophic denitrifiers use their corresponding electron donors (sulfur and organic matter, respectively) to reduce nitrate to nitrogen gas, with each modeled as three-step denitrification (NO3 to N-2 via NO2 and N2O) driven by sulfur or organic matter to describe all potential N2O accumulation steps. The developed model, employing model parameters previously reported in literature, was successfully validated using N2O and sulfate data from two mixotrophic denitrification systems with different initial conditions. Modeling results revealed substantial N2O accumulation due to the relatively low autotrophic N2O reduction activity as compared to heterotrophic N2O reduction activity, explaining the observation that higher carbon source addition resulted in lower N2O accumulation in sulfur-driven mixotrophic denitrifying system. Based on the validated model, optimizations of the overall system performance were carried out. Application of the model to simulate long-term operations of sulfur-driven mixotrophic denitrification process indicates that longer sludge retention time reduces N2O emission due to better retention of active biomass. High-level total nitrogen removal with significant N2O emission mitigation, appropriate excess sulfate control and maximized COD utilization can be achieved simultaneously through controlling the influent nitrate and COD concentrations. (C) 2017 Elsevier Ltd. All rights reserved.

Abstract: This study investigates the impact of lower temperature on short term and long term (down to 10 degrees C) on a completely anoxic anammox granular sludge process. This is the first time granular sludge Anammox is operated in pure anoxic condition in SBR and at low temperature. Conversion performance, kinetic parameters, sludge characteristics and microbial community were analyzed.