Abstract: Photocathodes play a vital role in photoelectrocatalytic water splitting by acting as catalysts for reducing protons to hydrogen gas when exposed to light. Recent advancements in photocathodes have focused on addressing the limitations of noble metal-based materials. These noble metal-based photocathodes rely on expensive and scarce metals such as platinum and gold as cocatalysts or ohmic back contacts, respectively, rendering the final system less sustainable and costly when applied at scale. This mini-review summarizes the important recent progress in the development of non-noble metal-based photocathodes and their performance in the hydrogen evolution reaction during photoelectrochemical (PEC) water splitting. These advancements bring non-noble metal-based photocathodes closer to their noble metal-based counterparts in terms of performance, thereby paving the way forward toward industrial-scale photoelectrolyzers or PEC cells for green hydrogen production.

Abstract: Indoor air pollution affects the global population, especially in developed countries where people spend around 90% of their time indoors. The recent pandemic exacerbated the exposure by relying on indoor spaces and a teleworking lifestyle. VOCs are a group of indoor air pollutants with harmful effects on human health at low concentrations. It is widespread that plants can remove indoor VOCs. To this day, research has combined principles of phytoremediation, biofiltration, and bioremediation into a holistic and sustainable technology called botanical biofiltration. Overall, it is sustained that its main advantage is the capacity to break down and biodegrade pollutants using low energy input. This differs from traditional systems that transfer VOCs to another phase. Furthermore, it offers additional benefits like decreased indoor air health costs, enhanced work productivity, and well-being. However, many disparities exist within the field regarding the role of plants, substrate, and phyllosphere bacteria. Yet their role has been theorized; its stability is poorly known for an engineering approach. Previous research has not addressed the bioaugmentation of the phyllosphere to increase the performance, which could boost the system. Moreover, most experiments have studied passive potted plant systems at a lab scale using small chambers, making it difficult to extrapolate findings into tangible parameters to engineer the technology. Active systems are believed to be more efficient yet require more maintenance and knowledge expertise; besides, the impact of the active flow on the long term is not fully understood. Besides, modeling the system has been oversimplified, limiting the understanding and optimization. This review sheds light on the field’s gains and gaps, like concepts, experiments, and modeling. We believe that embracing a multidisciplinary approach encompassing experiments, multiphysics modeling, microbial community analysis, and coworking with the indoor air sector will enable the optimization of the technology and facilitate its adoption.

Abstract: The number and composition of species in a community can be quantified with alpha-diversity indices, including species richness (R), Simpson's index (D), and the Shannon-Wiener index (HGREEK TONOS). In forest communities, there are large variations in tree size among species and individuals of the same species, which result in differences in ecological processes and ecosystem functions. However, tree size inequality (TSI) has been largely neglected in studies using the available diversity indices. The TSI in the diameter at breast height (DBH) data for each of 999 20 m x 20 m forest census quadrats was quantified using the Gini index (GI), a measure of the inequality of size distribution. The generalized performance equation was used to describe the rotated and right-shifted Lorenz curve of the cumulative proportion of DBH and the cumulative proportion of number of trees per quadrat. We also examined the relationships of alpha-diversity indices with the GI using correlation tests. The generalized performance equation effectively described the rotated and right-shifted Lorenz curve of DBH distributions, with most root-mean-square errors (990 out of 999 quadrats) being < 0.0030. There were significant positive correlations between each of three alpha-diversity indices (i.e., R, D, and H') and the GI. Nevertheless, the total abundance of trees in each quadrat did not significantly influence the GI. This means that the TSI increased with increasing species diversity. Thus, two new indices are proposed that can balance alpha-diversity against the extent of TSI in the community: (1 – GI) x D, and (1 – GI) x H'. These new indices were significantly correlated with the original D and HGREEK TONOS, and did not increase the extent of variation within each group of indices. This study presents a useful tool for quantifying both species diversity and the variation in tree sizes in forest communities, especially in the face of cumulative species loss under global climate change.

Abstract: Urine nitrification is pH-sensitive due to limited alkalinity and high residual ammonium concentrations. This study aimed to investigate how the pH affects nitrogen conversion and the microbial community of urine nitrification with a pH-based feeding strategy. First, kinetic parameters for NH3, HNO2, and NO2– limitation and inhibition were determined for nitrifiers from a urine nitrification reactor. The turning point for ammonia-oxidizing bacteria (AOB), i.e., the substrate concentration at which a further increase would lead to a decrease in activity due to inhibitory effects, was at an NH3 concentration of 12 mg-N L–1, which was reached only at pH values above 7. The total nitrite turning point for nitrite-oxidizing bacteria (NOB) was pH-dependent, e.g., 18 mg-N L–1 at pH 6.3. Second, four years of data from two 120 L reactors were analyzed, showing that stable nitrification with low nitrite was most likely between pH 5.8 and 6.7. And third, six 12 L urine nitrification reactors were operated at total nitrogen concentrations of 1300 and 3600 mg-N L–1 and pH values between 2.5 and 8.5. At pH 6, the AOB Nitrosomonas europaea was found, and the NOB belonged to the genus Nitrobacter. At pH 7, nitrite accumulated, and Nitrosomonas halophila was the dominant AOB. NOB were inhibited by HNO2 accumulation. At pH 8.5, the AOB Nitrosomonas stercoris became dominant, and NH3 inhibited NOB. Without influent, the pH dropped to 2.5 due to the growth of the acid-tolerant AOB “Candidatus Nitrosacidococcus urinae”. In conclusion, pH is a decisive process control parameter for urine nitrification by influencing the selection and kinetics of nitrifiers.

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: Electromagnetic design problems involve optimizing multiple parameters that are nonlinearly related to objective functions. Traditional optimization techniques require significant computational resources that grow exponentially as the problem size increases. Therefore, a method that can produce good results with moderate memory and computational resources is desirable. Bioinspired optimization methods, such as particle swarm optimization (PSO), are known for their computational efficiency and are commonly used in various scientific and technological fields. In this article we explore the potential of advanced PSO-based algorithms to tackle challenging electromagnetic design and analysis problems faced in real-life applications. It provides a detailed comparison between conventional PSO and its quantum-inspired version regarding accuracy and computational costs. Additionally, theoretical insights on convergence issues and sensitivity analysis on parameters influencing the stochastic process are reported. The utilization of a novel quantum PSO-based algorithm in advanced scenarios, such as reconfigurable and shaped lens antenna synthesis, is illustrated. The hybrid modeling approach, based on the unified geometrical description enabled by the Gielis Transformation, is applied in combination with a suitable quantum PSO-based algorithm, along with a geometrical tube tracing and physical optics technique for solving the inverse problem aimed at identifying the geometrical parameters that yield optimal antenna performance.

Abstract: Hydrogen (H2) storage, in the form of clathrate hydrates, has emerged as an attractive alternative to classical storage methods like compression or liquefaction. Nevertheless, the sluggish enclathration kinetics along with low gas storage capacities in bulk systems is currently impeding the progress of this technology. To this end, unstirred systems coupled with porous materials have been shown to tackle the aforementioned drawbacks. In line with this approach, the present study explores the use of hydrophobic periodic organosilica nanoparticles, later denoted as hollow ring-PMO (HRPMO), for H2 storage as clathrate hydrates under mild operating conditions (5.56 mol% THF, 7 MPa, and 265–273 K). The surface of the HRPMO nanoparticles was carefully decorated/functionalized with THF-like moieties, which are well-known promoter agents in clathrate formation when applied in classical, homogeneous systems. The study showed that, while the non-functionalized HRPMO can facilitate the formation of binary H2-THF clathrates, the incorporation of surface-bound promotor structures enhances this process. More intriguingly, tuning the concentration of these surface-bound promotor agents on the HRPMO led to a notable effect on solid-state H2 storage capacities. An increase of 3% in H2 storage capacity, equivalent to 0.26 wt%, along with a substantial increase of up to 28% in clathrate growth kinetics, was observed when an optimal loading of 0.14 mmol g−1 of promoter agent was integrated into the HRPMO framework. Overall, the findings from this study highlight that such tuning effects in the solid-state have the potential to significantly boost hydrate formation/growth kinetics and H2 storage capacities, thereby opening new avenues for the ongoing development of H2 clathrates in industrial applications.

Abstract: Resource-efficient nitrogen management is of high environmental and economic interest, and manure represents the major nutrient flow in livestock-intensive regions. Ammonia stripping/scrubbing (SS) is an appealing nitrogen recovery route from manure, yet its real-life implementation has been limited thus far. In nutrient surplus regions like Flanders, treatment of the liquid fraction (LF) of (co–)digested manure typically consists of nitrification/denitrification (NDN) removing most N as nitrogen gas. Integrating SS before NDN in existing plants would expand treatment capacity and recover N while maintaining low N effluent values, yet cost estimations of this novel approach after process optimisation are not yet available. A programming model was developed and calibrated to minimise the treatment costs of this approach and find the balance between N recovery versus N removal. Four crucial operational parameters (CO2 stripping time, NH3 stripping time, temperature and NaOH addition) were optimised for 18 scenarios which were different in terms of technical set-up, influent characteristics and scrubber acid. The model shows that SS before NDN can decrease the costs by 1 to 56% under optimal conditions compared to treatment with NDN only, with 1 to 8% reduction for the LF of manure (22–29% recovered of N treated), and 11 to 56% reduction for the LF of co-digested manure (42–67% recovered of N treated), primarily dependent on resource pricing. This study shows the power of modelling for minimum-cost design and operation of manure treatment yielding savings while producing useful N recovery products with SS followed by NDN.

Abstract: Energy-lean nitrogen removal technologies, such as partial nitritation/anammox, often encounter effluent issues due to elevated nitrate and ammonium levels. This study proposed a novel autotrophic polishing strategy coupling sulfur-driven denitratation with anammox. To explore the denitratation potential in obtaining stable and sufficient nitrite accumulation, the effects of pH, residual nitrate level, and biomass-specific nitrate loading rate (BSNLR) were investigated in an S0-packed bed reactor at low hydraulic retention time (i.e., 0.2 h). Implementing pH and residual nitrate control strategies would be easier in practice than BSNLR control to polish secondary effluent. Alkaline pH values could realize successful nitrite accumulation without residual nitrate, and further intensify the accumulation under increased residual nitrate levels. The nitrate level was positively correlated with the nitrite accumulation efficiency. At pH 8.5 and nitrate concentration of 1.0 ± 0.8 mg N L−1, sulfur-driven denitratation could successfully maintain nitrite accumulation of 6.4 ± 1.0 mg NO2−-N L−1, ideally for the downstream anammox in case of residual ammonium levels of around 5 mg N L−1. Since Thiobacillus members play a key role in managing nitrite accumulation, their abundance should be guaranteed in the practical application.

Abstract: Nitrification is well-suited for urine stabilization. No base dosage is required if the pH is controlled within an appropriate operating range by urine feeding, producing an ammonium-nitrate fertilizer. However, the process is highly dependent on the selected pH set-points and is susceptible to process failures such as nitrite accumulation or the growth of acid-tolerant ammonia-oxidizing bacteria. To address the need for a robust and reliable process in decentralized applications, two different strategies were tested: operating a two-position pH controller (inflow on/off) with a narrow pH control band at 6.20/6.25 (∆pH = 0.05, narrow-pH) vs. a wider pH control band at 6.00/6.50 (∆pH = 0.50, wide-pH). These variations in pH also cause variations in the chemical speciation of ammonia and nitrite and, as shown, the microbial production of nitrite. It was hypothesized that the higher fluctuations would result in greater microbial diversity and, thus, a more robust process. The diversity of nitrifiers was higher in the wide-pH reactor, while the diversity of the entire microbiome was similar in both systems. However, the wide-pH reactor was more susceptible to tested process disturbances caused by increasing pH or temperature, decreasing dissolved oxygen, or an influent stop. In addition, with an emission factor of 0.47%, the nitrous oxide (N2O) emissions from the wide-pH reactor were twice as high as the N2O emissions from the narrow-pH reactor, most likely due to the nitrite fluctuations. Based on these results, a narrow control band is recommended for pH control in urine nitrification.

Abstract: In the field of photocatalysis, the fabrication of black titania is a booming topic, as it offers a system with improved solar light harvesting properties and increased overall efficiency. The darkening of white TiO2 powders can be ascribed to surface hydroxylation, oxygen vacancies, Ti3+ centres, or a combination thereof. A handful of studies suggests these defects can be conveniently introduced by acoustic cavitation, generated during sonochemical treatment of pristine TiO2 powders. In reproducing these studies, P25 TiO2 samples were ultrasonicated for various hours with a power density of 8000 W/L, resulting in powders that indeed became gradually darker with increasing sonication time. However, HAADF–STEM revealed that extensive erosion of the sonotrode tip took place and contaminated the samples, which appeared to be the primary reason for the observed colour change. This was confirmed by UV–Vis DRS and DRIFTS, that showed no significant alteration of the catalyst surface after sonication. EPR measurements showed that only an insignificant fraction of Ti3+ centres were produced, far less than in a TiO2 sample that was chemically reduced with NaBH4. No evidence of the presence oxygen vacancies could be found. The enhanced photocatalytic activities of ultrasonicated materials reported in literature can therefore not be ascribed to the synthesis of actual black (defected) TiO2, but rather to specific changes in morphology as a result of acoustic cavitation. Also, this study underlines the importance of considering probe erosion in sonochemical catalyst synthesis, which is an unavoidable side effect that can have an important impact on the catalyst appearance, properties and performance.

Abstract: Measuring the inequality of leaf area distribution per plant (ILAD) can provide a useful tool for quantifying the influences of intra- and interspecific competition, foraging behavior of herbivores, and environmental stress on plants’ above-ground architectural structures and survival strategies. Despite its importance, there has been limited research on this issue. This paper aims to fill this gap by comparing four inequality indices to measure ILAD, using indices for quantifying household income that are commonly used in economics, including the Gini index (which is based on the Lorenz curve), the coefficient of variation, the Theil index, and the mean log deviation index. We measured the area of all leaves for 240 individual plants of the species Shibataea chinensis Nakai, a drought-tolerant landscape plant found in southern China. A three-parameter performance equation was fitted to observations of the cumulative proportion of leaf area vs. the cumulative proportion of leaves per plant to calculate the Gini index for each individual specimen of S. chinensis. The performance equation was demonstrated to be valid in describing the rotated and right shifted Lorenz curve, given that >96% of root-mean-square error values were smaller than 0.004 for 240 individual plants. By examining the correlation between any of the six possible pairs of indices among the Gini index, the coefficient of variation, the Theil index, and the mean log deviation index, the data show that these indices are closely related and can be used interchangeably to quantify ILAD.

Abstract: The goal of this study is to provide a rigorous tool to quantify the inequality of the leaf size distribution of an individual plant, thereby serving as a reference trait for quantifying plant adaptations to local environmental conditions. The tool to be presented and tested employs three components: (1) a performance equation (PE), which can produce flexible asymmetrical and symmetrical bell-shaped curves, (2) the Lorenz curve (i.e., the cumulative proportion of leaf size vs. the cumulative proportion of number of leaves), which is the basis for calculating, and (3) the Gini index, which measures the inequality of leaf size distribution. We sampled 12 individual plants of a dwarf bamboo and measured the area and dry mass of each leaf of each plant. We then developed a generalized performance equation (GPE) of which the PE is a special case and fitted the Lorenz curve to leaf size distribution using the GPE and PE. The GPE performed better than the PE in fitting the Lorenz curve. We compared the Gini index of leaf area distribution with that of leaf dry mass distribution and found that there was a significant difference between the two indices that might emerge from the scaling relationship between leaf dry mass and area. Nevertheless, there was a strong correlation between the two Gini indices (r2 = 0.9846). This study provides a promising tool based on the GPE for quantifying the inequality of leaf size distributions across individual plants and can be used to quantify plant adaptations to local environmental conditions.