Abstract: Dry deposition is an important process determining pollutant concentrations, especially when studying the influence of urban green infrastructure on particulate matter (PM) levels in cities. Computational fluid dynamics (CFD) models of PM capture by vegetation are useful tools to increase their applicability. The meso-scale models of Zhang et al. (Atmos Environ 35:549-560, 2001) and Petroff and Zhang (Geosci Model Dev 3(2):753-769, 2010) have often been adopted in CFD models, however a comparison of these models with measurements including all PM particle sizes detrimental to health has been rarely reported and certainly not for green wall species. This study presents dry deposition experiments on real grown Hedera helix in a wind tunnel setup with wind speeds from 1 to 4 m s(-1) and PM consisting of a mixture of soot (0.02 – 0.2 mu mu m) and dust particles (0.3 – 10 mu mu m). Significant factors determining the collection efficiency (%) were particle diameter and wind speed, but relative air humidity and the type of PM (soot or dust) did not have a significant influence. Zhang's model outperformed Petroff's model for particles < 0.3 mu mu m, however the inclusion of turbulent impaction in Petroff's model resulted in better agreement with the measurements for particles > 2 – 3 mu mu m. The optimised model had an overall root-mean-square-error of similar to 4% for collection efficiency (CE) and 0.4 cm s-1 for deposition velocity (nu d), which was shown to be highly competitive against previously described models. It can thus be used to model PM deposition on other plant species, provided the correct parameterisation of the drag by this species. A detailed description of the spatial distribution of the vegetation could solve the underestimation for particle sizes of 0.3 – 2 mu mu m.

Abstract: It is a generally accepted idea that the particle size distribution strongly affects the optical spectra of colloidal plasmonic nanoparticles. It is often quoted as one of the main reasons while explaining the mismatch between the theoretical and experimental optical spectra of such nanoparticles. In this work, these aspects are critically analyzed by means of a bottom up statistical approach that considers variables such as mean, standard deviation and skewness of the nanoparticle size distribution independently from one another. By assuming normal and log-normal distributions of the particle size, the effect of the statistical parameters on the Mie analytical optical spectra of colloidal nanoparticles was studied. The effect of morphology was also studied numerically in order to understand to what extent it can play a role. It is our finding that the particle polydispersity, skewness and surface morphology in fact only weakly impact the optical spectra. While, the selection of suitable optical constants with regard to the crystallinity of the nanoparticles is a far more influential factor for correctly predicting both the plasmon band position and the plasmon bandwidth in theoretical simulations of the optical spectra. It is shown that the mean particle size can be correctly estimated directly from the plasmon band position, as it is the mean that determines the resonance wavelength. The standard deviation can on the other hand be estimated from the intensity distribution data obtained from dynamic light scattering experiments. The results reported herein clear the ambiguity around particle size distribution and optical response of colloidal plasmonic nanoparticles.

Abstract: Organic fertilizers and especially microbial biomass, also known as microbial fertilizer, can enable a paradigm shift to the conventional fertilizer-to-food chain, particularly when produced on secondary resources. Microbial fertilizers are already common practice (e.g. Bloom® and Synagro); yet microbial fertilizer blends to align the nutrient release profile to the plant’s needs are, thus far, unexplored. Moreover, most research only focuses on direct fertilization effects without considering added value properties, such as disease prevention. This study has explored three promising types of microbial fertilizers, namely dried biomass from a consortium of aerobic heterotrophic bacteria, a microalga (Arthrospira platensis) and a purple non-sulfur bacterium (Rhodobacter sphaeroides). Mineralization and nitrification experiments showed that the nitrogen mineralization profile can be tuned to the plant’s needs by blending microbial fertilizers, without having toxic ammonium peaks. In a pot trial with perennial ryegrass (Lolium perenne L.), the performance of microbial fertilizers was similar to the reference organic fertilizer, with cumulative dry matter yields of 5.6–6.7 g per pot. This was confirmed in a pot trial with tomato (Solanum lycopersicum L.), showing an average total plant length of 90–99 cm after a growing period of 62 days for the reference organic fertilizer and the microbial fertilizers. Moreover, tomato plants artificially infected with powdery mildew (Oidium neolycopersici), a devastating disease for the horticultural industry, showed reduced disease symptoms when A. platensis was present in the growing medium. These findings strengthen the application potential of this novel class of organic fertilizers in the bioeconomy, with a promising match between nutrient mineralization and plant requirements as well as added value in crop protection.

Abstract: Acid-tolerant ammonia-oxidizing bacteria (AOB) can open the door to new applications, such as partial nitritation at low pH. However, they can also be problematic because chemical nitrite oxidation occurs at low pH, leading to the release of harmful nitrogen oxide gases. In this publication, the role of acid-tolerant AOB in urine treatment was explored. On the one hand, the technical feasibility of ammonia oxidation under acidic conditions for source-separated urine with total nitrogen concentrations up to 3.5 g-N L−1 was investigated. On the other hand, the abundance and growth of acid-tolerant AOB at more neutral pH was explored. Under acidic conditions (pH of 5), ammonia oxidation rates of 500 mg-N L−1 d−1 and 10 g-N g-VSS-1 d-1 were observed, despite high concentrations of 15 mg-N L−1 of the AOB-inhibiting compound nitrous acid and low concentration of 0.04 mg-N L−1 of the substrate ammonia. However, ammonia oxidation under acidic conditions was very sensitive to process disturbances. Even short periods of less than 12 h without oxygen or without influent resulted in a complete cessation of ammonia oxidation with a recovery time of up to two months, which is a problem for low maintenance applications such as decentralized treatment. Furthermore, undesirable nitrogen losses of about 10% were observed. Under acidic conditions, a novel AOB strain was enriched with a relative abundance of up to 80%, for which the name “Candidatus (Ca.) Nitrosacidococcus urinae” is proposed. While Nitrosacidococcus members were present only to a small extent (0.004%) in urine nitrification reactors operated at pH values between 5.8 and 7, acid-tolerant AOB were always enriched during long periods without influent, resulting in an uncontrolled drop in pH to as low as 2.5. Long-term experiments at different pH values showed that the activity of “Ca. Nitrosacidococcus urinae” decreased strongly at a pH of 7, where they were also outcompeted by the acid-sensitive AOB Nitrosomonas halophila. The experiment results showed that the decreased activity of “Ca. Nitrosacidococcus urinae” correlated with the limited availability of dissolved iron at neutral pH.

Abstract: Many natural objects exhibit radial or axial symmetry in a single plane. However, a universal tool for simulating and fitting the shapes of such objects is lacking. Herein, we present an R package called 'biogeom' that simulates and fits many shapes found in nature. The package incorporates novel universal parametric equations that generate the profiles of bird eggs, flowers, linear and lanceolate leaves, seeds, starfish, and tree-rings, and three growth-rate equations that generate the profiles of ovate leaves and the ontogenetic growth curves of animals and plants. 'biogeom' includes several empirical datasets comprising the boundary coordinates of bird eggs, fruits, lanceolate and ovate leaves, tree rings, seeds, and sea stars. The package can also be applied to other kinds of natural shapes similar to those in the datasets. In addition, the package includes sigmoid curves derived from the three growth-rate equations, which can be used to model animal and plant growth trajectories and predict the times associated with maximum growth rate. 'biogeom' can quantify the intra- or interspecific similarity of natural outlines, and it provides quantitative information of shape and ontogenetic modification of shape with important ecological and evolutionary implications for the growth and form of the living world.

Abstract: The co-gasification of biomass and coal is a promising approach for efficiently integrating the unique advantages of different gasification feedstock with syngas production. Additionally, syngas from the co-gasification of locally available biomass and coal could supplement the natural gas used in household and industrial burners. The top-lit updraft gasifier features a moving ignition front that starts at the top and propagates downward through the solids bed, while air enters from the bottom and the gas product flows upwards. This study assesses the co-gasification performance of palm kernel shell and high-volatile bituminous coal in a top-lit updraft fixed bed gasifier using 70, 85, and 100 vol% biomass and equivalence ratios ranging from 0.26 to 0.34. The results indicate that the ignition front propagates faster and is more uniform as the biomass volume increases. Micro GC analysis revealed that the H2/CO ratio remained in the range of 0.57–0.59, 0.49–0.51, and 0.42–0.46 for experiments with 70, 85, and 100 vol% biomass, respectively. A gas interchangeability analysis showed that syngas-natural gas blends with up to 15 vol% of syngas could combust in atmospheric natural gas burners without modifications. Thus, the top-lit updraft gasifier shows excellent potential for the co-gasification of coal and biomass. Further research on this technology should explore steam as a gasification agent to enhance the syngas energy content and continuous solids feeding.

Abstract: Recently, a universal equation by Narushin, Romanov, and Griffin (hereafter, the NRGE) was proposed to describe the shape of avian eggs. While NRGE can simulate the shape of spherical, ellipsoidal, ovoidal, and pyriform eggs, its predictions were not tested against actual data. Here, we tested the validity of the NRGE by fitting actual data of egg shapes and compared this with the predictions of our simpler model for egg shape (hereafter, the SGE). The eggs of nine bird species were sampled for this purpose. NRGE was found to fit the empirical data of egg shape well, but it did not define the egg length axis (i.e., the rotational symmetric axis), which significantly affected the prediction accuracy. The egg length axis under the NRGE is defined as the maximum distance between two points on the scanned perimeter of the egg's shape. In contrast, the SGE fitted the empirical data better, and had a smaller root-mean-square error than the NRGE for each of the nine eggs. Based on its mathematical simplicity and goodness-of-fit, the SGE appears to be a reliable and useful model for describing egg shape.

Abstract: The shape of leaf laminae exhibits considerable diversity and complexity that reflects adaptations to environmental factors such as ambient light and precipitation as well as phyletic legacy. Many leaves appear to be elliptical which may represent a ‘default’ developmental condition. However, whether their geometry truly conforms to the ellipse equation (EE), i.e., (x/a)2 + (y/b)2 = 1, remains conjectural. One alternative is described by the superellipse equation (SE), a generalized version of EE, i.e., |x/a|n +|y/b|n = 1. To test the efficacy of EE versus SE to describe leaf geometry, the leaf shapes of two Michelia species (i.e., M. cavaleriei var. platypetala, and M. maudiae), were investigated using 60 leaves from each species. Analysis shows that the majority of leaves (118 out of 120) had adjusted root-mean-square errors of < 0.05 for the nonlinear fitting of SE to leaf geometry, i.e., the mean absolute deviation from the polar point to leaf marginal points was smaller than 5% of the radius of a hypothesized circle with its area equaling leaf area. The estimates of n for the two species were ˂ 2, indicating that all sampled leaves conformed to SE and not to EE. This study confirms the existence of SE in leaves, linking this to its potential functional advantages, particularly the possible influence of leaf shape on hydraulic conductance.

Abstract: High-rate activated sludge (HRAS) relies on good bioflocculation and subsequent solid-liquid separation to maximize the capture of organics. However, full-scale applications often suffer from poor and unpredictable effluent suspended solids (ESS). While the biological aspects of bioflocculation are thoroughly investigated, the effects of fines (settling velocity < 0.6 m3/m2/h), shear and surface overflow rate (SOR) are unclear. This work tackled the impact of fines, shear, and SOR on the ESS in absence of settleable influent solids. This was assessed on a full-scale HRAS step-feed (SF) and pilot-scale HRAS contact-stabilization (CS) configuration using batch settling tests, controlled clarifier experiments, and continuous operation of reactors. Fines contributed up to 25% of the ESS in the full-scale SF configuration. ESS decreased up to 30 mg TSS/L when bioflocculation was enhanced with the CS configuration. The feast-famine regime applied in CS promoted the production of high-quality extracellular polymeric substances (EPS). However, this resulted in a narrow and unfavorable settling velocity distribution, with 50% ± 5% of the sludge mass settling between 0.6 and 1.5 m3/m2/h, thus increasing sensitivity towards SOR changes. A low shear environment (20 s−1) before the clarifier for at least one min was enough to ensure the best possible settling velocity distribution, regardless of prior shear conditions. Overall, this paper provides a more complete view on the drivers of ESS in HRAS systems, creating the foundation for the design of effective HRAS clarifiers. Tangible recommendations are given on how to manage fines and establish the optimal settling velocity of the sludge.

Abstract: During the conversion of lignocellulose, phenolic wastewaters are generated. Therefore, researchers have investigated wastewater valorization processes in which these pollutants are converted to chemicals, i.e., lipids. However, wastewaters are lean feedstocks, so these valorization processes in research typically require the addition of large quantities of sugars and sterilization, which increase costs. This paper investigates a repeated batch fermentation strategy with Rhodotorula kratochvilovae EXF7516 and Cutaneotrichosporon oleaginosum ATCC 20509, without these requirements. The pollutant removal and its conversion to microbial oil were evaluated. Because of the presence of non-monomeric substrates, the ligninolytic enzyme activity was also investigated. The repeated batch fermentation strategy was successful, as more lipids accumulated every cycle, up to a total of 5.4 g/L (23% cell dry weight). In addition, the yeasts consumed up to 87% of monomeric substrates, i.e., sugars, aromatics, and organics acids, and up to 23% of non-monomeric substrates, i.e., partially degraded xylan, lignin, cellulose. Interestingly, lipid production was only observed during the harvest phase of each cycle, as the cells experienced stress, possibly due to oxygen limitation. This work presents the first results on the feasibility of valorizing non-sterilized lignocellulosic wastewater with R. kratochvilovae and C. oleaginosum using a cost-effective repeated batch strategy.

Abstract: Clathrate hydrates gained significant attention as a viable option for large-scale storage of natural gas, primarily methane (CH4). Unlike employing the nanoconfinement for enhancing the nucleation sites and hydrate growth as in the porous materials, whose synthesis is often associated with high costs and poor batch reproducibility, a new approach for promoting CH4 hydrates using pure water (H2O) in an unstirred reactor packed with stainless steel beads (SSB) was proposed in this fundamental work, where the interstitial space between the beads was exploited for enhanced hydrate growth. SSB of two diameters, 5 mm and 2 mm, were used as. a packed bed to investigate their effects on CH4 hydrate formation at 273.65 K, 275.65 K, and 277.65 K with an initial pressure of 6 MPa. The thermal conductivity of SSB packing potentially aided hydrate growth by expelling the hydration heat, while, the results also revealed that driving force has a substantial impact on the rate of CH4 hydrate formation and gas uptake. The experiments conducted in both 5 mm and 2 mm SSB packed bed reactors showed a maximum gas uptake of 0.147 mol CH4/mol H2O at 273.65 K with water to hydrate conversion of 84.42% with no significant variation. The results established the promotion effect on the kinetics of CH4 hydrate formation in the unstirred reactor packed with 2 mm SSB due to the availability of more interstitial space offering multiple nucleation sites for CH4 hydrate by providing a larger specific surface area for H2O-CH4 reaction. Experiments with varying H2O content were also performed and the results showed that the water to hydrate conversion and rate of hydrate formation could be enhanced at a lower H2O content in a packed bed reactor. This study demonstrates that the use of costly or intricate porous materials can be made redundant, by exploiting the interstitial voids in packing of cheap and widely available SSB as a promising alternative material for enhancing the kinetics of artificial CH4 hydrate synthesis.

Abstract: Supershapes are used in Parametric Design to model, literally, thou-sands of natural and man-made shapes with a single 6 parameter formula. However, users are left to probe such a rich yet dense collection of supershapes using a set of independent 1-D sliders. Some of the formula’s parameters are non-linear in nature, making them particularly difficult to grasp with conventional 1-D sliders alone. VR appears as a promising setting for Parametric Design with supershapes since it empowers users with more natural visual inspection and shape browsing techniques, with multiple solutions being displayed at once and the possibility to design more interesting forms of slider interaction. In this work, we propose VR shape widgets that allow users to probe and select supershapes from a multitude of solutions. Our designs take leverage on thumbnails, mini-maps, haptic feedback and spatial interaction, while supporting 1-D, 2-D and 3-D supershape parameter spaces. We conducted a user study (N = 18) and found that VR shape widgets are effective, more efficient, and natural than conventional VR 1-D sliders while also usable for users without prior knowledge on supershapes. We also found that the proposed VR widgets provide a quick overview of the main supershapes, and users can easily reach the desired solution without having to perform fine-grain handle manipulations.

Abstract: The interaction of diatoms with sunlight is fundamental in order to deeply understand their role in terrestrial ecology and biogeochemistry, essentially due to their massive contribution to global primary production through photosynthesis and its e↵ect on carbon, oxygen and silicon cycles. Following the journey of light through natural waters, its propagation through the intricate frustule micro- and nano-structure and, finally, its fate inside the photosynthetic machinery of the living cell requires several mathematical and computational models in order to accurately describe all the involved phenomena taking place at di↵erent space scales and physical regimes. In this chapter, we review the main analytical models describing the underwater optical field, the essential numerical algorithms for the study of photonic properties of the diatom frustule seen as a natural metamaterial, as well as the principal models describing photon harvesting in diatom plastids and methods for complex EM propagation problems and wave propagation in dispersive materials with multiple relaxation times. These mathematical methods will be integrated in a unifying geometric perspective.

Abstract: The gas-solid vortex reactor (GSVR) has enormous process intensification potential. However the huge gas consumption can be a serious disadvantage for the GSVR in some applications such as fast pyrolysis. In this work, we demonstrate a recent novel design, where a stator-rotor vortex chamber (STARVOC) is driven by the fluid's kinetic energy, to decouple the solids bed rotation and gas. Gas-solid fluidization by using air and monosized aluminum balls was performed to investigate the hydrodynamics. A constructed fluidization flow regime map for a fixed solids loading of 100 g shows that the bed can only be fluidized for a rotation speed between 200 and 400 RPM. Below 200 RPM, particles settle down on the bottom plate and cannot form a stable bed due to inertia and friction. Above 400 RPM, the bed cannot be fluidized with superficial velocities up to 1.8 m/s (air flow rate of 90 Nm(3)/h). The bed thickness shows some non-uniformities, being smaller at the top of the bed than at the bottom counterpart. However by increasing the air flow rate or rotation speed the axial nonuniformity can be resolved. The bed pressure drop first increases with increasing gas flow rate and then levels off, showing similar characteristics as conventional fluidized beds. Theoretical pressure drops calculated from mathematical models such as Kao et al. model agree well with experimental measurements. Particle velocity discrepancies between the top and bottom particles reveal that the impact of gravity cannot be completely neglected. Design guidelines and possible applications for further development of STARVOC concept are proposed based on fundamental data provided in this work.