Abstract: Biobased chemistry has gained interest and has the potential to tackle some of the sustainability challenges the chemical industry must endure. Sustainability impacts need to be evaluated and monitored to highlight the advantages and pitfalls of different biobased routes over the product life cycle. A better understanding of the potential sustainability of emerging biobased technologies and products is essential to guide additional research and further technology development. This PhD thesis aims to develop a framework for a techno-sustainability assessment (TSA), while accounting for technological as well as economic, environmental, and social aspects in an integrated approach. First, a review of the state-of-the-art sustainability indicators for biobased chemicals was conducted and a gap analysis was performed to identify indicator development needs. Afterwards, a Delphi study was performed to select sustainability indicators specifically for biobased chemical assessment and to reach consensus among experts on a prioritization of these indicators. Next, the selected sustainability indicators were quantified while integrating technological and country-specific data with environmental characterization factors, economic values and social data. Finally, a stochastic, hierarchical multi-criteria decision analysis (MCDA) integrates the independent techno-sustainability indicators expressed in different units, taking into account stochastic and flexible method options. The developed integrated TSA framework was applied to a case for which a production and harvesting plant of microalgae-based food colorants is assessed. The final aim of the integrated TSA is to compare the potential sustainability performance of different scenarios and to make better-informed choices between alternatives by evaluating environmental, economic and social sustainability impacts in one holistic model. Integrated TSA offers a novel framework where decision makers can assess sustainability already in early technology development stages by identifying potential hurdles and opportunities to guide R&D and make sustainable investment decisions.

Abstract: Binary ZrCu nanocomposite amorphous films are synthetized by pulsed laser deposition (PLD) under vac-uum (2 x 10-3 Pa) and 10 Pa He pressure, leading to fully amorphous compact and nanogranular mor-phologies, respectively. Then, post-thermal annealing treatments are carried out to explore thermal stability and crystallization phenomena together with the evolution of mechanical properties. Compact films exhibit larger thermal stability with partial crystallization phenomena starting at 420 degrees C, still to be completed at 550 degrees C, while nanogranular films exhibit early-stage crystallization at 300 degrees C and com-pleted at 485 degrees C. The microstructural differences are related to a distinct evolution of mechanical

Abstract: Between 15 January and 26 February 1987, 51 fine and coarse mode aerosol samples were collected at the Universidad de Santiago de Chile Planetarium using a dichotomous sampler. The samples were analyzed by X-ray fluorescence for up to 17 elements (Mg, Al, Si, P, S, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Br and Pb). Aerosol particles were individually studied by Electron Probe Microanalysis (EPMA) and Laser Microprobe Mass Analysis (LAMMA). The data set consisting of aerosol elemental concentrations and meteorological variables was subjected to Principal Factor Analysis (PFA), allowing the identification of six fine mode particle source classes (soil, industrial, sulfate particles, traffic, residual oil, wood-burnings), and five coarse mode particle source classes (soil, industrial, traffic, residual oil, sulfate particles). Both PFA solutions explained about 81 and 90% of the total variance in the data set, respectively. The regression of elemental mass concentrations on the Absolute Principal Factor Scores allowed the estimation of the contribution of the different source classes to the Santiago aerosol. Within the fine fraction, secondary SO42− particles were responsible for about 49% of the fine mode aerosol mass concentration, while 26, 13, 6.4 and 5.6% were attributed to wood-burning/car exhausts, residual oil combustion, soil dust/metallurgical, and soil dust/wood-burning releases, respectively. The coarse fraction source apportionment was mainly dominated by soil dust, accounting for 74% of the coarse mode aerosol mass concentration. A composite of soil dust and industrial release accounted for 13%; a composite of secondary sulfates contributed with 9%; a composite of soil dust and automotive emissions, and secondary sulfates were responsible for 4 and 0.03% of the coarse aerosol mass concentration, respectively. EPMA results are in satisfactory agreement with those from the bulk analysis and allowed the identification of eight particle types in both fine and coarse mode aerosols, pertaining to different source classes, namely soil, seaspray, secondary SO42−, metallurgical emissions and biomass burning release. EPMA also evidenced that one of the most abundant particle types corresponded to marine aerosol, having an average diameter of 0.7 μm for the fine mode and 2.2 μm for the coarse mode aerosol. LAMMA results indicate that, in fact, seaspray has been transported into the city of Santiago de Chile airshed, suffering several transformations and a sulfur enrichment. This analytical technique also provided evidence of the abundance of carbon-rich particles, which were not detected by either the bulk X-ray analysis or EPMA; they are probably due to fossil-fuel combustion releases.

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: Based on extensive field information, farmer-led small-scale irrigation systems along the dam-regulated Tekeze River is investigated and the likelihood of future irrigation expansion within the area with modelled potential is discussed, considering facilitating and hampering factors. Due to dam-induced hydrologic alterations, downstream socio-ecological systems have strongly transformed as the irrigated area has quadrupled and the post-dam potential for perennial crop cultivation has attracted numerous migrant investors to the area, inducing inequalities but also providing opportunities. Future dam construction should involve tailored policy interventions to facilitate irrigation expansion, while safeguarding equal and sustainable access to water and land.

Abstract: Background: It has been hypothesized that ambient particulate air pollution is able to modify the autonomic nervous control of the heart, measured as heart rate variability (HRV) . Previously we reported heterogeneous associations between particulate matter with aerodynamic diameter < 2.5 µm (PM2.5) and HRV across three study centers. Objective: We evaluated whether exposure misclassification, effect modification by medication, or differences in particle composition could explain the inconsistencies. Methods: Subjects with coronary heart disease visited clinics biweekly in Amsterdam, the Netherlands ; Erfurt, Germany ; and Helsinki, Finland for 68 months. The standard deviation (SD) of NN intervals on an electrocardiogram (ECG ; SDNN) and high frequency (HF) power of HRV was measured with ambulatory ECG during paced breathing. Outdoor levels of PM2.5 were measured at a central site. In Amsterdam and Helsinki, indoor and personal PM2.5 were measured during the 24 hr preceding the clinic visit. PM2.5 was apportioned between sources using principal component analyses. We analyzed associations of indoor/personal PM2.5, elements of PM2.5, and source-specific PM2.5 with HRV using linear regression. Results: Indoor and personal PM2.5 were not associated with HRV. Increased outdoor PM2.5 was associated with decreased SDNN and HF at lags of 2 and 3 days only among persons not using beta-blocker medication. Traffic-related PM2.5 was associated with decreased SDNN, and long-range transported PM2.5 with decreased SDNN and HF, most strongly among persons not using beta blockers. Indicators for PM2.5 from traffic and long-range transport were also associated with decreased HRV. Conclusions: Our results suggest that differences in the composition of particles, beta-blocker use, and obesity of study subjects may explain some inconsistencies among previous studies on HRV.

Abstract: Background This study explores the repurposing of Auranofin (AF), an anti-rheumatic drug, for treating non-small cell lung cancer (NSCLC) adenocarcinoma and pancreatic ductal adenocarcinoma (PDAC). Drug repurposing in oncology offers a cost-effective and time-efficient approach to developing new cancer therapies. Our research focuses on evaluating AF's selective cytotoxicity against cancer cells, identifying RNAseq-based biomarkers to predict AF response, and finding the most effective co-therapeutic agents for combination with AF. Methods Our investigation employed a comprehensive drug screening of AF in combination with eleven anticancer agents in cancerous PDAC and NSCLC patient-derived organoids (n = 7), and non-cancerous pulmonary organoids (n = 2). Additionally, we conducted RNA sequencing to identify potential biomarkers for AF sensitivity and experimented with various drug combinations to optimize AF's therapeutic efficacy. Results The results revealed that AF demonstrates a preferential cytotoxic effect on NSCLC and PDAC cancer cells at clinically relevant concentrations below 1 µM, sparing normal epithelial cells. We identified Carbonic Anhydrase 12 (CA12) as a significant RNAseq-based biomarker, closely associated with the NF-κB survival signaling pathway, which is crucial in cancer cell response to oxidative stress. Our findings suggest that cancer cells with low CA12 expression are more susceptible to AF treatment. Furthermore, the combination of AF with the AKT inhibitor MK2206 was found to be particularly effective, exhibiting potent and selective cytotoxic synergy, especially in tumor organoid models classified as intermediate responders to AF, without adverse effects on healthy organoids. Conclusion Our research offers valuable insights into the use of AF for treating NSCLC and PDAC. It highlights AF's cancer cell selectivity, establishes CA12 as a predictive biomarker for AF sensitivity, and underscores the enhanced efficacy of AF when combined with MK2206 and other therapeutics. These findings pave the way for further exploration of AF in cancer treatment, particularly in identifying patient populations most likely to benefit from its use and in optimizing combination therapies for improved patient outcomes.

Abstract: Background Patient-derived organoids are invaluable for fundamental and translational cancer research and holds great promise for personalized medicine. However, the shortage of available analysis methods, which are often single-time point, severely impede the potential and routine use of organoids for basic research, clinical practise, and pharmaceutical and industrial applications. Methods Here, we developed a high-throughput compatible and automated live-cell image analysis software that allows for kinetic monitoring of organoids, named Organoid Brightfield Identification-based Therapy Screening (OrBITS), by combining computer vision with a convolutional network machine learning approach. The OrBITS deep learning analysis approach was validated against current standard assays for kinetic imaging and automated analysis of organoids. A drug screen of standard-of-care lung and pancreatic cancer treatments was also performed with the OrBITS platform and compared to the gold standard, CellTiter-Glo 3D assay. Finally, the optimal parameters and drug response metrics were identified to improve patient stratification. Results OrBITS allowed for the detection and tracking of organoids in routine extracellular matrix domes, advanced Gri3D (R)-96 well plates, and high-throughput 384-well microplates, solely based on brightfield imaging. The obtained organoid Count, Mean Area, and Total Area had a strong correlation with the nuclear staining, Hoechst, following pairwise comparison over a broad range of sizes. By incorporating a fluorescent cell death marker, infra-well normalization for organoid death could be achieved, which was tested with a 10-point titration of cisplatin and validated against the current gold standard ATP-assay, CellTiter-Glo 3D. Using this approach with OrBITS, screening of chemotherapeutics and targeted therapies revealed further insight into the mechanistic action of the drugs, a feature not achievable with the CellTiter-Glo 3D assay. Finally, we advise the use of the growth rate-based normalised drug response metric to improve accuracy and consistency of organoid drug response quantification. Conclusion Our findings validate that OrBITS, as a scalable, automated live-cell image analysis software, would facilitate the use of patient-derived organoids for drug development and therapy screening. The developed wet-lab workflow and software also has broad application potential, from providing a launching point for further brightfield-based assay development to be used for fundamental research, to guiding clinical decisions for personalized medicine.

Abstract: Background Breast cancer (BC) is the most common cancer in women in the developed world. In order to find developing cancers in an early stage, BC screening is commonly used. In Flanders, screening is performed in and outside an organized breast cancer screening program (BCSP). However, the determinants of BC screening coverage for both screening strategies are yet unknown. Objective To assess the determinants of BC screening coverage in Flanders. Methods Reimbursement data were used to attribute a screening status to each woman in the target population for the years 2008-2016. Yearly coverage data were categorized as screening inside or outside BCSP or no screening. Data were clustered by municipality level. A generalized linear equation model was used to assess the determinants of screening type. Results Over all years and municipalities, the median screening coverage rate inside and outside BCSP was 48.40% (IQR: 41.50-54.40%) and 14.10% (IQR: 9.80-19.80%) respectively. A higher coverage rate outside BSCP was statistically significantly (P < 0.001) associated with more crowded households (OR: 3.797, 95% CI: 3.199-4.508), younger age, higher population densities (OR: 2.528, 95% CI: 2.455-2.606), a lower proportion of unemployed job seekers (OR: 0.641, 95% CI: 0.624-0.658) and lower use of dental care (OR: 0.969, 95% CI: 0.967-0.972). Conclusion Coverage rate of BC screening is not optimal in Flanders. Women with low SES that are characterized by younger age, living in a high population density area, living in crowded households, or having low dental care are less likely to be screened for BC in Flanders. If screened, they are more likely to be screened outside the BCSP.

Abstract: Autotrophic denitrification with sulfur is an underexplored alternative to heterotrophic denitrification to remove nitrate from wastewater poor in organics. The application on ion exchange regeneration water (19.432.1 mS cm−1) is novel. Three fixed bed reactors were tested at 15 °C for >4 months, inoculated with activated sludge from sewage treatment. All were fast in start-up (<10 days) with high performance (94 ± 2% removal efficiency). pH control with NaOH rendered higher nitrate removal rates than limestone addition to the bed (211 ± 13 vs. 102 ± 13 mg N L−1 d−1), related to higher pH (6.64 vs. 6.24) and sulfur surface area. Bacterial communities were strongly enriched in Sulfurimonas (6367%) and Thiobacillus (2426%). In an economic comparison, sulfur-based denitrification (5.3 kg−1 N) was 15% cheaper than methanol-based denitrification (6.22 kg−1 N) and both treatments were opex dominated (85.9 vs. 86.5%). Overall, the technological and economic feasibility should boost further implementation of sulfurotrophic denitrification.

Abstract: Atmospheric pressure plasmas have shifted in recent years from being a burgeoning research field in the academic setting to an actively investigated technology in the chemical, oil, and environmental industries. This is largely driven by the climate change mitigation efforts, as well as the evident pathways of value creation by converting greenhouse gases (such as CO2) into useful chemical feedstock. Currently, most high technology readiness level (TRL) plasma-based technologies are based on volumetric and power-based scaling of thermal plasma systems, which results in large capital investment and regular maintenance costs. This work investigates bringing a quasi-thermal (so-called “warm”) plasma setup, namely, a gliding arc plasmatron, from a lab-scale to a pilot-scale capacity with an increase in throughput capacity by a factor of 10. The method of scaling is the parallelization of plasmatron reactors within a single housing, with the aim of maintaining a warm plasma regime while simultaneously improving build cost and efficiency (compared to separate reactors operating in parallel). Special attention is also given to the safety and control features implemented in the setup, a key component required for integration into industrial systems. The performance of the multi-reactor gliding arc plasmatron (MRGAP) reactor is investigated, focusing on the influence of flow rate and the number of active reactors. The location of active reactors was deemed to have a negligible effect on the monitored metrics of conversion, energy efficiency, and energy cost. The optimum operating conditions were found to be with the most active reactors (five) at the highest investigated flow rate (80 L/min). Analysis of results suggests that an optimum conversion (9%) and plug power-based energy efficiency (19%) can be maintained at a specific energy input (SEI) around 5.3 kJ/L (or 1 eV/molecule). The concept of parallelization of plasmatron reactors within a singular housing was demonstrated to be a viable method for scaling up from a lab-scale to a prototype-scale device, with performance analysis suggesting that increasing the power (through adding more reactor channels) and total flow rate, while maintaining an SEI around 5.3 or 4.2 kJ/L, i.e., 1.3 or 1 eV/molecule (based on plug power and plasma-deposited power, respectively), can result in increased conversion rate without sacrificing absolute conversion or energy efficiency.

Abstract: Atmospheric aerosols were collected during the winter in Bethlehem, South Africa. The particulate mass concentrations, ambient carbon mass concentrations, and chemical composition of various particulate fractions showed that the area is highly polluted. The fine particle mass concentrations peaked at 1000 µg/m3 for PM2.5. Ambient carbon mass concentrations ranged from 20 to 40 µg/m3. Single particle analysis confirmed that the fine particle fraction was dominated by organic particles. The topographical conditions, causing a low inversion, together with the high amounts of emissions from biomass burning, result in unacceptable levels of air pollution and pose a considerable health threat to the population.

Abstract: At or below the surface of painted works of art, valuable information is present that provides insights into an object’s past, such as the artist’s technique and the creative process that was followed or its conservation history, but also on its current state of preservation. Typically, a (very) limited set of small paint samples is taken which provide direct access to the individual paint layers. The chemical build-up of these layers can then be investigated in great detail using various microscopic analytical methods. However, in recent years a new trend towards both elemental and chemical imaging techniques has been set which are capable of visualizing the (often) heterogeneous composition of painted objects on a macroscopic scale. In this dissertation, various forms of specificity attainable with X‑ray powder diffraction (XRPD) imaging are explored: at the chemical, material and spatial level. This high specificity is illustrated throughout several applications stemming from the field of cultural heritage, both at the macroscopic (MA) and microscopic (µ) scale. As a first step, XRPD imaging was transformed to a transportable instrument that can be employed for the in situ investigation of artworks, e.g., inside museums and conservation workshops. With this unique instrument large‑scale maps (cm2 – dm2) reflecting the distribution of crystalline phases on/below the surface of flat painted artefacts can be visualized in a noninvasive manner. In this way compound-specific information was attained which can be related to original pigments or materials that have been added in a later stage and even degradation/secondary products that have formed spontaneously inside the paint layers. Additionally, with MA‑XRPD imaging it was possible to link quantitative information of pigment compositions and preferred orientation effects to the 2D compound‑specific distribution images, allowing for a further distinction between very similar artists’ materials. Furthermore, promising results for the limited depth-selectivity of this technique, obtained by exploiting the small shift in the position of the diffraction signals originating from the layered sequence of the pigments, are shown. Finally, a minute paint sample from Wheat stack under a cloudy sky by Van Gogh was investigated at a synchrotron radiation facility with tomographic µ‑XRPD imaging at the microscopic scale. The high chemical and spatial specificity of this imaging method was exploited to further elucidate the degradation pathway of the red lead pigment.

Abstract: Assay and electrochemical behaviour of betahistine hydrochloride in BrittonRobinsons (BR) buffer of pH range 2.512.0 at a glassy carbon electrode have been investigated. Addition of anionic surfactant (sodium lauryl sulphate) to the betahistine hydrochloride solution containing electrolyte enhanced the reduction current signal while neutral surfactant (Tween-20) and cationic surfactant cetyl trimethylammonium bromide (CTAB) showed an opposite effect. Voltammograms of betahistine hydrochloride exhibited a single wave. Based on reduction behaviour of betahistine hydrochloride, a direct square-wave voltammetric method has been developed for the assay of betahistine hydrochloride in pharmaceutical formulation. The proposed method has been validated as per ICH guideline. System and method precision in terms of RSD were 1.88% and 1.60% respectively, whereas the method accuracy was indicated by the recovery of 97.6101.9%. Reduction peak current was linear over the target concentration with correlation coefficient 0.998. The proposed method was successfully applied to the determination of betahistine hydrochloride in pharmaceutical formulation. The results were compared with those obtained by the reference high performance liquid chromatographic method. No significant differences were found between results of proposed and reference methods.

Abstract: Aside from potential environmental benefits, the implementation of circular economy principles in businesses can have merits for the labour market. The current unemployment in several regions of Europe and the qualitative mismatch between supply and demand could be countered by reskilling the labour force to adjust supply and demand to one another for increased reuse, repair, or recycling, among others. This study uses interviews to increase the focus of the research question and uses survey data to perform an ordered probit regression analysis to sketch the current and future landscape of startups’ skills in Flanders (Belgium), and to analyse the relationship between circular strategies and different types of skills. The results show that design to lower material use increases the need for transport and logistics skills, digitalisation increases the need for R&D and IT skills, and the recuperation of waste requires technical knowledge. Furthermore, gender, age, and experience of the entrepreneur influence the needed skills. The paper probed for policy recommendations for the uptake of circular strategies and recommendations for future research. The most asked policy measures by the respondents are innovation and collaboration support (subsidies), fiscal measures that support circular goods and services, and public procurement for circular goods and services. This research is of relevance for several stakeholders, such as startup ecosystems, sector organisations, policy makers in innovation policy and labour market policy, and educational institutions.