Abstract: Identifying priority areas is an essential step in developing management strategies to reduce pesticide loads in surface water. A spatially explicit model-based approach was developed to detect priority areas for diffuse pesticide pollution at catchment scale. The method uses available datasets and considers different pesticide pathways in the environment post-application. The approach was applied in a catchment area in SE Flanders (Belgium) as a case study. Calculated risk areas were obtained using detailed landscape data and combining pesticide emissions and hydrological connectivity. The risk areas obtained were further compared with an alternative observation-based method, developed specifically for this study site that includes long-term field observations and local expert knowledge. Both methods equally classified 50% of the areas. The impact of crop rotation on the calculated risk was analysed. High-risk areas were identified and added to a cumulative map over all five years to evaluate temporal variations. The model-based approach was used for the initial identification of risk areas at the study site. The tool helps to prioritise zones and detect particular fields to target landscape mitigation measures to reduce diffuse pesticide pollution reaching surface water bodies.

Abstract: Polymetallic nodules found in the Clarion Clipperton Fracture Zone in the NE Pacific contain more nickel, manganese and cobalt than all terrestrial reserves combined. Following the 1982 Law of the Sea Convention and its 1994 Implementing Agreement, the resources of the international seabed beyond the limits of national jurisdiction will be developed for the benefit of mankind by attracting investment and technology, whilst demanding that necessary measures be taken to ensure effective protection of the marine environment. To date, no single commercial seabed mining activity has taken place in international waters, and the development of balanced and stimulating exploitation regulation is needed, based on accurate economic analysis. This paper presents the first detailed, vertically integrated, stochastic techno-economic assessment from a contractor's perspective, and contributes to the development of the world's first exploitation regulations. The economic performance measured by the internal rate of return was compared using deterministic and probabilistic commodity price forecasting models. Different levels of a financial payment regime, comprising of a royalty payment and a payment to internalize environmental costs, were considered. When real growth was included, the internal rate of return remains above the hurdle rate when a transitional, total-cost, financial payment regime is below 2 per cent during the initial period and below 4 per cent for the remaining tenure period. Following a 10-year moving average of commodity prices, including real growth, a 77.51 per cent probability was calculated of achieving a hurdle rate of 18 per cent.

Abstract: Natural deep eutectic solvents (NADES) show great promise as media for enzymatic reactions in areas where (bio)compatibility with natural or medicinal products is a must. While in theory they can be tailored to the intended reaction to ensure optimized yields, the knowledge to date is predominantly empirical, with some mechanistic reports providing a fragmented view at best. Therefore, it is not easy to explain experimental observations, let alone make predictions. The aim of this study was to develop a structured, holistic understanding of the effects of NADES media on enzymatic reactions, distinguishing between effects on solubility, solvation, viscosity, inhibition and denaturation. Experimental and computational chemistry methods were combined to separately study the interactions between enzyme, substrate, and NADES as reaction media. The initial enzyme activity and the final conversion of vinyl laurate transesterification by immobilized Candida antarctica lipase were studied experimentally. The direct effect of NADES on the same enzyme was modeled by molecular dynamics simulation. The effect of solubility was studied by both experimental and computational methods. To predict the solubility and viscosity of NADES, data-driven models were developed by combining group contribution and machine learning methods, based on the accumulated experimental knowledge on NADES found in the literature. Finally, the composed relationships and prediction models were applied to the practical example of deacetylation of mannosylerythritol lipids (MELs). The experimental findings show that the chosen NADES system has a significant effect on both the apparent initial activity and the final conversion. However, in the simulations, the enzyme retains its original structure; moreover, NADES has an additional stabilizing effect on the enzyme. In addition, changes in the molar ratio of the compounds in NADES do not show a significant effect on the stability of the enzyme. These results indicate that the main effect of NADES on the reaction is mainly related to the substrate-solvent interactions (solvation energy) and the viscosity of the system. On the other hand, the experimental results only confirmed the significance of solvation, viscosity did not show a clear correlation with the studied reaction parameters. The machine learning models built for solubility and viscosity gave quantitative predictions of these properties. The accumulated knowledge was used to optimize the yield in the deacetylation reaction of MELs. The combination of these methods provides fundamental knowledge about the effect of NADES on biocatalysis, but the results are also applicable to other uses of NADES.

Abstract: Various bulk and surface analytical techniques were used to study the chemical deterioration of the 13th-to-15th century limestone cathedral in Mechelen, Belgium. The weathering crust on the walls was found to be rich in sulfate, regardless of the geographic orientation. Nitrate and chloride were only detected in minor amounts in the crust and run-off samples. Attack by gaseous sulfur compounds seems to play a dominant role in the stone deterioration mechanism. Electron microprobe analysis showed predominantly bar-shaped gypsum crystals in the crust, and laser microprobe mass spectrometry showed that carbon seems to be responsible for the blackness of most crust samples. Automated electron microprobe analysis also indicated significant differences in the analytical composition of suspensions in run-off water and in rain-water.

Abstract: A study of wood dust exposure in 20 small- and medium-scale wood-processing enterprises was performed in Ethiopia. Sampling was conducted daily from January to June, 2013 and a total of 360 samples from 113 workers were collected with Institute of Occupational Medicine (IOM) personal samplers. Eight-hour time-weighted average exposure to wood dust ranged from 0.24 to 23.3mg m−3 with a geometric mean (GM) of 6.82mg m−3 and a geometric standard deviation of 1.82. Although Ethiopia did not have any defined standard of Occupational Exposure Limit for wood dust exposure, 71% of the measurements exceeded the limit of 5mg m−3 set by the European Union (EU). Higher than the EU exposure limit was measured while workers perform sanding and sawing activities with a GM of 9.72 and 7.60mg m−3, respectively. In conclusion, wood workers in the small- and medium-scale enterprises are at a higher risk of developing different respiratory health problems with continuous exposure trends.

Abstract: Synchrotron radiation, high-resolution transmission electron microscopy (HRTEM), X-ray powder diffraction, and Raman spectroscopy were used to study the structure and thermal behavior of malayaite, CaSnSiO5. No indications of deviation from A2/a symmetry and no structural transitions were observed between 100 and 870 K. HRTEM revealed that the material is free of domains and antiphase boundaries. However, the lattice constants, cell volume, and Raman-active phonons show a thermal discontinuity near 500 K, which is possibly related to variation of the coordination sphere around the highly anisotropic Ca position.

Abstract: Smart grids (SGs) have a central role in the development of the global power sector. Cost-benefit analyses and environmental impact assessments are used to support policy on the deployment of SG systems and technologies. However, the conflicting and widely varying estimates of costs, benefits, greenhouse gas (GHG) emission reduction, and energy savings in literature leave policy makers struggling with how to advise regarding SG deployment. Identifying the causes for the wide variation of individual estimates in the literature is crucial if evaluations are to be used in decision-making. This paper (i) summarizes and compares the methodologies used for economic and environmental evaluation of SGs (ii) identifies the sources of variation in estimates across studies, and (iii) point to gap in research on economic and environmental analyses of SG systems. Seventeen studies (nine articles and eight reports published between 2000 and 2015) addressing the economic costs versus benefits, energy efficiency, and GHG emissions of SGs were systematically searched, located, selected, and reviewed. Their methods and data were subsequently extracted and analysed. The results show that no standardized method currently exists for assessing the economic and environmental impacts of SG systems. The costs varied between 0.03 and 1143 M/yr, while the benefits ranged from 0.04 to 804 M/yr, suggesting that SG systems do not result in cost savings The primary energy savings ranged from 0.03 to 0.95 MJ/kWh, whereas the GHG emission reduction ranged from 10 to 180 gCO2/kWh, depending on the country grid mix and the system boundary of the SG system considered. The findings demonstrate that although SG systems are energy efficient and reduce GHG emissions, investments in SG systems may not yield any benefits. Standardizing some methodologies and assumptions such as discount rates, time horizon and scrutinizing some key input data will result in more consistent estimates of costs and benefits, GHG emission reduction, and energy savings.

Abstract: Two-dimensional materials have been attracting increasing interests because of their outstanding properties for Lithium-ion battery applications. In particular, a material family called MXenes (Mn+1Cn, where n = 1, 2, 3) have been recently attracted immense interest in this respect due to their incomparable fast-charging properties and high capacity promises. In this article, we review the state-of-the-art computational progress on Li-ion battery applications of MXene materials in accordance with our systematical DFT calculations. Structural, mechanical, dynamical, and electrical properties of 20 distinct MXene (M: Sc, Ti, V, Cr, Nb, Mo, Hf, Ta, W, and Zr) have been discussed. The battery performances of these MXene monolayers are further investigated by Li-ion binding energies, open circuit voltage values, and Li migration energy barriers. The experimental and theoretical progress up to date demonstrates particularly the potential of non-terminated or pristine MXene materials in Li ion-storage applications. Stability analyses show most of the pristine MXenes should be achievable, however susceptible to the development progress on the experimental growth procedures. Among pristine MXenes, Ti2C, V2C, Sc2C, and Zr2C compounds excel with their high charge/discharge rate prospect due to their extremely low Li diffusion energy barriers. Considering also their higher predicted gravimetric capacities, Sc, Ti, V, and Zr containing MXenes are more promising for their utilization in energy storage applications.

Abstract: Economic and technological assessments have identified difficulties with the commercialization of bulk products from microalgae, like biofuels. To overcome these problems, a multi-product algal-based biorefinery has been proposed. This paper performs a techno-economic assessment of such a biorefinery. Four production pathways, ranging from a base case with commercial technologies to an improved case with innovative technologies, are analyzed. All region-specific parameters were adapted to Belgian conditions. Three scenarios result in techno-economically viable production plants. The most profitable scenario is the scenario which uses a specialized membrane for medium recycling and an open pond algae cultivation. Although the inclusion of a photobioreactor decreases the culture medium costs, the higher investment costs result in lower economic profits. The carotenoid content and price are identified as critical parameters. Furthermore, the economies of scale assumption for the photobioreactor is critical for the feasibility of this cultivation technology. The techno-economic assessment is an important methodology to guide and evaluate further improvements in research and shorten the time-to-market for innovative technologies in this field.

Abstract: Novel emerging biorefinery technologies have gained interest and have the potential to tackle several sustainability challenges in our society. A lignin-first biorefinery process – reductive catalytic fractionation (RCF) – is currently under development with the aim to process wood into high-value end-products that replace highly polluting fossil oil-based products. However, such emerging technologies are not matured yet, holding a certain degree of technological, economic, and environmental uncertainty. Hence, an appropriate assessment method is required to assess techno-economic feasibility and environmental impacts of emerging uncertain technologies (e.g lignin-first RCF process). This dissertation aims to develop an integrated techno-environmental economic assessment framework to assess emerging technologies dynamically and prospectively from economic and environmental points of view. First, a techno-economic assessment (TEA) is performed to assess the economic feasibility and the most influential economic and technological parameters of the lignin-first RCF biorefinery taking the whole wood value chain into account. By making the relations across the wood value chain, the scale of the biorefinery, wood species, and output prices highly determine the economic feasibility. The economic feasibility can be reached by a sufficient capacity level which depends on wood species-specific conditions. Also, waste wood proves to be the most profitable feedstock in comparison to virgin wood. Second, an analytical real options analysis (ROA) is performed taking two correlated market uncertainties and the value of flexibility into account to identify the optimal investment decision in an RCF biorefinery. Two different investment options, separated and united investments in harvesting equipment and RCF biorefinery, are analyzed. In both scenarios, market uncertainty postpones the investment. When both investment decisions are united, the probability of investment increases in comparison to separated investments. The study reveals that RCF has the potential to stimulate investments within the wood value chain. Third, a consequential life cycle assessment (LCA) is performed to assess the carbon emissions and the environmental consequences of the lignin-first RCF process and its products. The study reveals that at the current stage RCF products have higher carbon emissions than their alternative counterparts. Several options to improve the environmental performance are discussed such as different RCF technology configurations, targeting different RCF products with the ability to replace higher polluting alternative counterparts on the markets. Other discussion points such as transportation type and the distance, (in-)direct land-use change, the use stage and disposal stages implications, and a more comprehensive environmental view of the RCF products, show the potential to improve the environmental performance of the RCF technology. Overall, the study shows that the RCF process can be environmentally desirable if the appropriate RCF configuration and products are chosen. Finally, the above-mentioned methods – techno-economic assessment, analytical real options analysis, and consequential life cycle assessment – are uniquely integrated within the newly developed integrated assessment framework. The framework has the aim to complement the shortcomings and combine the advantages of all three methods. The framework assesses emerging technologies to give predictive insights about the time-specific economic and environmental performance under the newly developed three threshold conditions: technological readiness, economic feasibility, and environmental desirability. The developed integrated assessment framework assesses dynamically and prospectively the RCF biorefinery implementation under Belgian conditions. It reveals that the economic feasibility increases and carbon emissions decrease over time. The RCF biorefinery fulfills all three threshold conditions – technological readiness, economic feasibility, and environmental desirability – consecutively. The newly developed integrated assessment framework offers decision support to several stakeholders of emerging technologies starting from low technology readiness level (TRL). Practitioners such as the technology developers, researchers, and policymakers can use the framework to evaluate emerging technologies that deal with high levels of technological, economic, and environmental uncertainties. The framework assesses emerging technologies on a detailed level to give decision-makers in-depth insights into the intertwined nature of the technological, economic, and environmental dimensions. It offers insights into the expected time-specific economic and environmental performances, potential, and challenges of the emerging technology to further improve the technology and direct R&Ds along the right path.