Abstract: Our economy drives on reactive nitrogen (Nr); while Nr emissions to the environment surpass the planetary boundary. Increasingly, it is advocated to recover Nr contained in waste streams and to reuse it ‘directly’ in the agri-food chain. Alternatively, Nr in waste streams may be removed as N2 and refixed via the Haber-Bosch process in an ‘indirect’ reuse loop. As a systematic sustainability analysis of ‘direct’ Nr reuse and its comparison to the ‘indirect’ reuse loop is lacking, this structured review aimed to analyze literature determining the environmental and economic sustainability of Nr recovery technologies. Bibliometric records were queried from 2000 to 2020 using Boolean search strings, and manual text coding. In total, 63 studies were selected for the review. Results suggest that ‘direct’ Nr reuse using Nr recovery technologies is the preferred paradigm as the majority of studies concluded that it is sustainable or that it can be sustainable depending on technological assumptions and other scenario variables. Only 17 studies compared the ‘direct’ with the ‘indirect’ Nr reuse route, therefore a system perspective in Nr recovery sustainability assessments should be more widely adopted. Furthermore, Nr reuse should also be analyzed in the context of a ‘new Nr economy’ that relies on decentralized Nr production from renewable energy. It is also recommended that on-par technology readiness level comparisons should be carried out, making use of technology development and technology learning methodologies. Finally, by-products of Nr recovery are important to be accounted for as they are reducing the environmental burdens through avoided impacts.

Abstract: Being confronted with increasing and expanding urbanisation and the loss of natural green spaces, our living environment is threatened more and more by the effects of global climate change. Green infrastructure is often thought of as the solution to increase climate resilience and reinforce the quality of the lived environment simultaneously. While the benefits, or ecosystem services, that are generated through green infrastructure have been studied intensively, forces that influence green infrastructure decision-making have been far less subjected to thorough research. In this study a discrete choice experiment was conducted with local decision makers in Flemish municipalities to reveal crucial factors in the decision process applied to green infrastructure projects. Flanders is one of the most densely built regions in Europe, stressing the urgency to understand local spatial decision factors to guarantee green space. 568 decision makers active in the local administration of 235 Flemish municipalities participated in the experiment, set in a hypothetical neighbourhood park. Every choice alternative exists of five attributes: investment cost, maintenance cost, deferred investment, recreational value, and climate impact. We find that barriers hampering Flemish munipalities' GI implementation, differ over size of the municipality: smallers municipalities are more affected by knowledge gaps, while larger municipalities are experiencing prioritization issues. Results from hierarchical Bayes choice models indicate that municipal decisions on green infrastructure are highly – almost solely -cost-driven, rarely consider the full range of benefits, and centre around short-term and immediate arguments. Moreover, interaction models reveal that a municipalities' financial result is a key determinant of its willingness to invest in public greening and consider long term benefits, suggesting that GI is a luxury good. The results expose some of the heuristics in GI decision making and can be used to inform higher authorities on ways to overcome barriers towards informed decision-making and to facilitate GI investment.

Abstract: In the present work, the resolution and quantification of mixtures of different opiate compounds in the presence of common cutting agents using an electronic tongue (ET) is evaluated. More specifically, ternary mixtures of heroin, morphine and codeine were resolved in the presence of caffeine and paracetamol. To this aim, an array of three carbon screen-printed electrodes were modified with different ink-like solutions of graphite, cobalt (II) phthalocyanine and palladium, and their responses towards the different drugs were characterized by means of square wave voltammetry (SWV). Developed sensors showed a good performance with good linearity at the mu M level, LODs between 1.8 and 5.3 mu M for the 3 actual drugs, and relative standard deviation (RSD) ca. 2% for over 50 consecutive measurements. Next, a quantitative model that allowed the identification and quantification of the individual substances from the overlapped voltammograms was built using partial least squares regression (PLS) as the modeling tool. With this approach, quantification of the different drugs was achieved at the mu M level, with a total normalized root mean square error (NRMSE) of 0.084 for the test subset.

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: A robust and reproducible methodology to prepare stable inorganic nanoparticles with chiral morphology might hold the key to the practical utilization of these materials. We describe herein an optimized chiral growth method to prepare 4-fold twisted gold nanorods, where the amino acid cysteine is used as a dissymmetry inducer. Four tilted ridges were found to develop on the surface of single-crystal nanorods upon repeated reduction of HAuCl4, in the presence of cysteine as the chiral inducer and ascorbic acid as a reducing agent. From detailed electron microscopy analysis of the crystallographic structures, we propose that dissymmetry results from the development of chiral facets in the form of protrusions (tilted ridges) on the initial nanorods, eventually leading to a twisted shape. The role of cysteine is attributed to assisting enantioselective facet evolution, which is supported by density functional theory simulations of the surface energies, modified upon adsorption of the chiral molecule. The development of R-type and S-type chiral structures (small facets, terraces, or kinks) would thus be non-equal, removing the mirror symmetry of the Au NR and in turn resulting in a markedly chiral morphology with high plasmonic optical activity.

Abstract: Particulate matter is one of the most persistent global air pollutants that is causing health problems, climate disturbance and building deterioration. A sustainable technique that is able to degrade soot using (sun)light is photocatalysis. Currently, research on photocatalytic soot oxidation focusses on large band gap TiO2-based photocatalysts and thus requires the use of UV light. It would prove useful if visible light, and thus a larger fraction of the (freely available) solar spectrum, could additionally be utilised to drive this process. In this work, a visible light-active photocatalyst, WO3, is benchmarked to TiO2 under both UV and visible light. At the same time, the versatility and drastic improvement of a recently introduced digital image-based soot degradation detection method are demonstrated. An additional step correcting for non-soot related catalyst colour changes is applied, resulting in accurate detection and quantification of soot degradation for all studied photocatalysts, even for materials such as WO3 that are inherently coloured. With this study, we aim to broaden the scope of photocatalytic soot oxidation technology to visible light-active photocatalyst. Along with this study, we provide a versatile soot degradation detection methodology based on digital image analysis that is made widely applicable.

Abstract: It is known that pollutants and their irreparable influence can considerably jeopardize the environment and human health. Such disastrous, growing, hazardous particles urged researchers to find effective ways and diminish their destructive impacts and preserve our planet. This study evaluates the potential of incorporating Titanium Dioxide (TiO2) semiconductor nanoparticles on asphalt pavements to degrade pollutants without compromising bitumen performance. Accordingly, the Response Surface Method (RSM) was employed to develop an experimental matrix based on the central composite design. Image Analysis (IA) was used to determine the rate of soot degradation (as pollutant representative) using MATLAB and ImageJ software. Confocal Laser Scanning Microscopy (CLSM), Fourier Transform Infrared spectroscopy (FTIR), and Dynamic Shear Rheometer (DSR) were finally carried out to estimate the effects of adding different percentages of TiO2 on the micro -structural features and dispersion of the TiO2, chemical fingerprinting, and rheological performance of the bituminous binder. The results showed a promising potential of TiO2 to degrade soot (over 50%) during the conducted experiments. In addition, the RSM outcomes showed that applying a higher amount of TiO2 is more efficient for pollutant degradation. Finally, no negative impact was observed, neither on the rheological behavior nor on the aging susceptibility of the bitumen, even though the homogenous dispersion of the TiO2 was clearly captured via CLSM.

Abstract: Extended producer responsibility (EPR) schemes have effectively increased the plastic waste that is separately collected. However, due to the structure of the recycling industry, EPR cannot increase recycling rates up to the target levels.Additional policy instruments to increase recycling rates such as recycled content targets, green dot fees bonus for recycled content, recycling targets and taxes on non-recycled plastic packaging have been discussed on a political level in the last years. However, very little research has quantitatively studied the effectiveness of these policy interventions.Using a partial equilibrium model, this paper examines the effectiveness of the implementation of the aforementioned policy instruments to increase recycling rates and the impact on different stakeholders of the value chain: plastic producers, consumers, producer responsibility organization and recyclers.Results show that direct interventions (recycled content standards and recycling targets) have the benefit of decoupling the recycling industry from external markets such as the oil market. They can be a good starting point to increase recycling, but in the long term they may be restricting by not presenting incentives to achieve recycling levels beyond the targeted amounts and by limiting technological innovation. On the contrary, eco-nomic interventions such as a green dot fee bonus or a packaging tax create economic incentives for recycling. However, these incentives are diminished by the lower perceived quality of packaging with higher recycled content levels.

Abstract: Wearable electrochemical sensors are driven by the user-friendly capability of on-site detection of key biomarkers for health management. Despite the advances in biomolecule monitoring such as glucose, still, several unmet clinical challenges need to be addressed. For example, patients suffering from phenylketonuria (PKU) should be able to monitor their phenylalanine (PHE) level in a rapid, decentralized, and affordable manner to avoid high levels of PHE in the body which can lead to a profound and irreversible mental disability. Herein, we report a wearable wristband electrochemical sensor for the monitoring of PHE tackling the necessity of controlling PHE levels in PHE hydroxylase deficiency patients. The proposed electrochemical sensor is based on a screen-printed electrode (SPE) modified with a membrane consisting of Nafion, to avoid interferences in biofluids. The membrane also consists of sodium 1,2-naphthoquinone-4-sulphonate for the in situ derivatization of PHE into an electroactive product, allowing its electrochemical oxidation at the surface of the SPE in alkaline conditions. Importantly, the electrochemical sensor is integrated into a wristband configuration to enhance user interaction and engage the patient with PHE self-monitoring. Besides, a paper-based sampling strategy is designed to alkalinize the real sample without the need for sample pretreatment, and thus simplify the analytical process. Finally, the wearable device is tested for the determination of PHE in saliva and blood serum. The proposed wristband-based sensor is expected to impact the PKU self-monitoring, facilitating the daily lives of PKU patients toward optimal therapy and disease management.

Abstract: Purple non-sulfur bacteria (PNSB) form an interesting group of microbes for resource recovery from wastewater. Solid/liquid separation is key for biomass and value-added products recovery, yet insights into PNSB aggregation are thus far limited. This study explored the effects of organic loading rate (OLR), hydraulic retention time (HRT) and water composition on the aggregation of Rhodobacter capsulatus in an anaerobic upflow photobioreactor. Between 2.0 and 14.6 gCOD/(L.d), the optimal OLR for aggregation was 6.1 gCOD/(L.d), resulting in a sedimentation flux of 5.9 kgTSS/(m2.h). With HRT tested between 0.04 and 1.00 d, disaggregation occurred at the relatively long HRT (1 d), possibly due to accumulation of thus far unidentified heat-labile metabolites. Chemical oxygen demand (COD) to nitrogen ratios (6–35 gCOD/gN) and the nitrogen source (ammonium vs. glutamate) also impacted aggregation, highlighting the importance of the type of wastewater and its pre-treatment. These novel insights to improve purple biomass separation pave the way for cost-efficient PNSB applications.

Abstract: In the last few years, governments all around the world have agreed upon migrating towards carbon-neutral economies as a strategy for restraining the effects of climate change. A major obstacle limiting this achievement is greenhouse gases emissions, for which the aviation sector is a key contributor because of its dependence on fossil fuels. As an alternative, biofuels with similar characteristics to current fossil-fuels and fully compatible with the existing petroleum infrastructure (i.e., drop-in biofuels) are being developed. In this regard, microalgae are a promising feedstock thanks to, among other aspects, their potential for lipid accumulation. This review outlines the development status, opportunities, and challenges of different technologies that are capable of or applicable to transform microalgae into aviation fuels. To this effect, a baseline of the existing jet fuels and the requirements for potential aviation biofuels is initially presented. Then, microalgae production and valorization techniques are discussed with an emphasis on the thermochemical pathways. Finally, an assessment of the present techno-economic feasibility of microalgae-derived aviation fuels is discussed, along with the authors’ point of view on the suitability of these techniques. Further developments are needed to reduce the costs of cultivation and harvesting of microalgae, and a biorefinery approach might improve the economics of the overall process. In addition, while each of the conversion routes described has its advantages and drawbacks, they converge upon the need of optimizing the deoxygenation techniques and the proportion of the suitable type of hydrocarbons that match fuel requirements.

Abstract: Plasma catalysis is gaining increasing interest for various applications, but the underlying mechanisms are still far from understood. Hence, more fundamental research is needed to understand these mechanisms. This can be obtained by both modelling and experiments. This foundations paper describes the fundamental insights in plasma catalysis, as well as efforts to gain more insights by modelling and experiments. Furthermore, it discusses the state-of-the-art of the major plasma catalysis applications, as well as successes and challenges of technology transfer of these applications.

Abstract: The Quantemol database (QDB) provides cross sections and rates of processes important for plasma models; heavy particle collisions (chemical reactions) and electron collision processes are considered. The current version of QDB has data on 28 917 processes between 2485 distinct species plus data for surface processes. These data are available via a web interface or can be delivered directly to plasma models using an application program interface; data are available in formats suitable for direct input into a variety of popular plasma modeling codes including HPEM, COMSOL, ChemKIN, CFD-ACE+, and VisGlow. QDB provides ready assembled plasma chemistries plus the ability to build bespoke chemistries. The database also provides a Boltzmann solver for electron dynamics and a zero-dimensional model. Thesedevelopments, use cases involving O₂, Ar/NF₃, Ar/NF₃/O₂, and He/H₂O/O₂chemistries, and plans for the future are presented.

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: Doping two single transition-metal (TM) atoms on a substrate host opens numerous possibilities for catalyst design. However, what if the substrate contains more than one vacancy site? Then, the combination of two TMs along with their distribution patterns becomes a design parameter potentially complementary to the substrate itself and the bimetal composition. In this study, we investigate ammonia synthesis under mild electrocatalytic conditions on a transition-metal-doped porous C24N24 catalyst using density functional theory (DFT). The TMs studied include Ti, Mn, and Cu in a 2:4 dopant ratio (Ti2Mn4@C24N24 and Ti2Cu4@N-24(24)). Our computations show that a single Ti atom in both catalysts exhibits the highest selectivity for N-2 fixation at ambient conditions. This work is a good theoretical model to establish the structure-activity relationship, and the knowledge earned from the metal-N-4 moieties may help studies of related nanomaterials, especially those with curved structures.