Abstract: Elemental composition of aerosols is important to source apportionment studies and to understand atmospheric processes that influence aerosol composition. Energy dispersive X-ray fluorescence spectroscopy was applied for measuring the elemental composition of Amazonian atmospheric aerosols. The instrument used was a spectrometer Epsilon 5, PANalytical B. V., with tridimensional geometry that reduces the background signal with a polarized X-ray detection. The measurement conditions were optimized for low-Z elements, e. g. Mg, Al, Si, that are present at very low concentrations in the Amazon. From Na to K, our detection limits are about 50% to 75% lower than previously published results for similar instrument. Calibration was performed using Micromatter standards, except for P whose standard was produced by nebulization of an aqueous solution of KH2PO4 at our laboratory. The multi-element reference material National Institute of Standards and Technology-2783 (air particulate filter) was used for evaluating the accuracy of the calibration procedure of the 22 elements in our standard analysis routine, and the uncertainty associated with calibration procedures was evaluated. The overall performance of the instrument and validation of our measurements were assessed by comparison with results obtained from parallel analysis using particle-induced X-ray emission and another Epsilon 5 spectrometer. The elemental composition in 660 samples collected at a pristine site in the Amazon Basin and of 1416 samples collected at a site perturbed by land use change was determined. Our measurements show trace elements associated with biogenic aerosols, soil dust, biomass burning, and sea-salt, even for the very low concentrations as observed in Amazonia. Copyright (C) 2014 John Wiley & Sons, Ltd.

Abstract: Energy-autonomous sewage treatment can be achieved if nitrogen (N) removal does not rely on organic carbon (∼chemical oxygen demand, COD), so that a maximum of the COD can be redirected to energy recovery. Shortcut N removal technologies such as partial nitritation/anammox and nitritation/denitritation are therefore essential, enabling carbon- and energy-lean nitrogen removal. In this study, a novel three-reactor pilot design was tested and consisted of a denitrification, an intermittent aeration, and an anammox tank. A vibrating sieve was added for differential sludge retention time (SRT) control. The 13 m3 pilot was operated on pre-treated sewage (A-stage effluent) at 12–24 °C. Selective suppression of unwanted nitrite-oxidizing bacteria over aerobic ammonium-oxidizing bacteria was achieved with strict floccular SRT management combined with innovative aeration control, resulting in a minimal nitrate production ratio of 17 ± 10%. Additionally, anoxic ammonium-oxidizing bacteria (AnAOB) activity could be maintained in the reactor for at least 150 days because of long granular SRT management and the anammox tank. Consequently, the COD/N removal ratio of 2.3 ± 0.7 demonstrated shortcut N removal almost three times lower than the currently applied nitrification/denitrification technology. The effluent total N concentrations of 17 ± 3 mg TN per L (at 21 ± 1 °C) and 17 ± 6 mg TN per L (at 15 ± 1 °C) were however too high for application at the sewage treatment plant Nieuwveer (Breda, The Netherlands). Corresponding N removal efficiencies were 52 ± 12% and 37 ± 21%, respectively. Further development should focus on redirecting more nitrite to AnAOB in the B-stage, exploring effluent-polishing options, or cycling nitrate for increased A-stage denitrification.

Abstract: Energy-dispersive x-ray fluorescence is advantageous for trace analysis of soils present as thin films. A target thickness of about 2 mg cm-2 provides a compromise between optimal sensitivity and minimal absorption effect or optimal accuracy. Sample preparation involves only suspending the finely ground soil in water and drying this suspension on a thin mylar foil glued on a ring that fits into the x.r.f. spectrometer. The effective sample weight present in the exciting beam area is computed from the scatter peaks, a method that cancels out target heterogeneity problems. High accuracy is demonstrated for many elements in reference soil and rock materials; a precision around 5% and a detection limit around 10 ppm can be achieved. As an illustration, results for 16 trace elements and preliminary interpretation are given for a series of pedologically important soil samples from Brasil.

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: Enhanced weathering (EW) is an emerging carbon dioxide (CO2) removal technology that can contribute to climate change mitigation. This technology relies on accelerating the natural process of mineral weathering in soils by manipulating the abiotic variables that govern this process, in particular mineral grain size and exposure to acids dissolved in water. EW mainly aims at reducing atmospheric CO2 concentrations by enhancing inorganic carbon sequestration. Until now, knowledge of EW has been mainly gained through experiments that focused on the abiotic variables known for stimulating mineral weathering, thereby neglecting the potential influence of biotic components. While bacteria, fungi, and earthworms are known to increase mineral weathering rates, the use of soil organisms in the context of EW remains underexplored. This protocol describes the design and construction of an experimental setup developed to enhance mineral weathering rates through soil organisms while concurrently controlling abiotic conditions. The setup is designed to maximize weathering rates while maintaining soil organisms' activity. It consists of a large number of columns filled with rock powder and organic material, located in a climate chamber and with water applied via a downflow irrigation system. Columns are placed above a fridge containing jerrycans to collect the leachate. Representative results demonstrate that this setup is suitable to ensure the activity of soil organisms and quantify their effect on inorganic carbon sequestration. Challenges remain in minimizing leachate losses, ensuring homogeneous ventilation through the climate chamber, and avoiding flooding of the columns. With this setup, an innovative and promising approach is proposed to enhance mineral weathering rates through the activity of soil biota and disentangle the effect of biotic and abiotic factors as drivers of EW.

Abstract: Environmental circumstances shaping soil microbial communities have been studied extensively. However, due to disparate study designs, it has been difficult to resolve whether a globally consistent set of predictors exists, or context‐dependency prevails. Here, we used a network of 18 grassland sites (11 of those containing regional plant productivity gradients) to examine (i) if similar abiotic or biotic factors predict both large‐scale (across sites) and regional‐scale (within sites) patterns in bacterial and fungal community composition, and (ii) if microbial community composition differs consistently at two levels of regional plant productivity (low vs. high). Our results revealed that bacteria were associated with particular soil properties (such as base saturation) and both bacteria and fungi were associated with plant community composition across sites and within the majority of sites. Moreover, a discernible microbial community signal emerged, clearly distinguishing high and low‐productivity soils across different grasslands independent of their location in the world. Hence, regional productivity differences may be typified by characteristic soil microbial communities across the grassland biome. These results could encourage future research aiming to predict the general effects of global changes on soil microbial community composition in grasslands and to discriminate fertile from infertile systems using generally applicable microbial indicators.

Abstract: Environmental parameters such as temperature, relative humidity, visible light, UV radiation and pollution influence the deterioration rate of heritage items. To judge on the environmental appropriateness for heritage conservation, it is therefore important to monitor the environment. Often, an incomplete set of environmental parameters is measured, or sporadic or time-averaged measurements are performed. As a result, a wide range of undesirable situations and hazards remain unnoticed. This might lead to an underestimation of environmental dangers (i.e., inaccurate judgement) or to inappropriate mitigation measures (i.e., inaccurate decision making). We present an innovative and user-friendly monitoring device that simultaneously and continuously measures (1) environmental parameters and (2) material behavior. An extended combination of off-the-shelf sensors for temperature, relative humidity, air speed, CO2, NO2, O-3 and particulate matter are connected to a multipurpose datalogger. In-house developed sensors for the shrinkage and expansion behavior of wood, as well as sensors for metal corrosion rates are connected to the same datalogger. Such extended monitoring shows the identification of a wider range of undesirable situations, and it facilitates the search for correlations between such situations and the sources that cause them, i.e., the hazards.

Abstract: Epitaxial heterostructures of two-dimensional (2D) halide perovskites offer a new platform for studying intriguing structural, optical, and electronic properties. However, difficulties with the stability of Pb- and Sn-based heterostructures have repeatedly slowed the progress. Recently, Pb-free halide double perovskites are gaining a lot of attention due to their superior stability and greater chemical diversity, but they have not been successfully incorporated into epitaxial heterostructures for further investigation. Here, we report epitaxial core-shell heterostructures via growing Pb-free double perovskites (involving combinations of Ag(I)-Bi(III), Ag-Sb, Ag-In, Na-Bi, Na-Sb, and Na-In) around Pb perovskite 2D crystals. Distinct from Pb-Pb and Pb-Sn perovskite heterostructures, growths of the Pb-free shell at 45 degrees on the (100) surface of the lead perovskite core are observed in all Pb-free cases. The in-depth structural analysis carried out with electron diffraction unequivocally demonstrates the growth of the Pb-free shell along the [110] direction of the Pb perovskite, which is likely due to the relatively lower surface energy of the (110) surface. Furthermore, an investigation of anionic interdiffusion across heterostructure interfaces under the influence of heat was carried out. Interestingly, halide anion diffusion in the Pb-free 2D perovskites is found to be significantly suppressed as compared to Pb-based 2D perovskites. The great structural tunability and excellent stability of Pb-free perovskite heterostructures may find uses in electronic and optoelectronic devices in the near future.

Abstract: Estimating personal exposure to air pollution is a crucial component in identifying high-risk populations and situations. It will enable policy makers to determine efficient control strategies. Cycling is again becoming a favorite mode of transport both in developing and in developed countries due to increasing traffic congestion and environmental concerns. in Europe, it is also seen as a healthy sports activity. However, due to high levels of hazardous pollutants in the present day road microenvironment the cyclist might be at a higher health risk due to higher breathing rate and proximity to the vehicular exhaust. In this paper we present estimates of the exposure of a cyclist to particles of various size fractions including ultrafine particles (UFP) in the town of Mol (Flanders, Belgium). The results indicate relatively higher UFP concentration exposure during morning office hours and moderate UFP levels during afternoon. The major sources of UFP and PM(10) were identified, which are vehicular emission and construction activities, respectively. We also present a dust mapping technique which can be a useful tool for town planners and local policy makers. (C) 2008 Elsevier B.V. All rights reserved.

Abstract: EU strategies for waste management have long recognized the key role of recycling to move towards sustainable consumption and production. This resulted in a range of regulatory measures, among which the Waste Electrical and Electronic Equipment (WEEE) directive, which sets weight-based targets for recovery, preparation for re-use and recycling. The increasing strategic relevance of the supply of raw materials has, however, spurred a more integrated approach towards resource efficiency. In addition to the prevention of disposal, recycling practices are now also meant to contribute to sustainable materials management by pursuing (i) a higher degree of material cycle closure, (ii) an improved recovery of strategically relevant materials, and (iii) the avoidance of environmental burdens associated with the extraction and refining of primary raw materials. In response to this evolution, this paper reports about the development of an indicator set that allows to quantitatively demonstrate these recycling benefits, hence going further than the weight-based objectives employed in the WEEE directive. The indicators can be calculated for WEEE recycling processes for which information is available on both input and output fractions. It offers a comprehensive framework that aims to support decision making processes on product design, to identify opportunities for the optimization of WEEE End-of-Life scenarios, and to assess the achieved (or expected) results of implemented (or planned) recycling optimization strategies. The paper is illustrated by a case study on the recycling of LCD televisions. (C) 2014 Elsevier Ltd. All rights reserved.

Abstract: Even though nitrification/denitrification is a robust technology to remove nitrogen from sewage, economic incentives drive its future replacement by shortcut nitrogen removal processes. The latter necessitates high potential activity ratios of ammonia oxidizing to nitrite oxidizing bacteria (rAOB/rNOB). The goal of this study was to identify which wastewater and process parameters can govern this in reality. Two sewage treatment plants (STP) were chosen based on their inverse rAOB/rNOB values (at 20 °C): 0.6 for Blue Plains (BP, Washington DC, US) and 1.6 for Nieuwveer (NV, Breda, NL). Disproportional and dissimilar relationships between AOB or NOB relative abundances and respective activities pointed towards differences in community and growth/activity limiting parameters. The AOB communities showed to be particularly different. Temperature had no discriminatory effect on the nitrifiers' activities, with similar Arrhenius temperature dependences (ΘAOB = 1.10, ΘNOB = 1.061.07). To uncouple the temperature effect from potential limitations like inorganic carbon, phosphorus and nitrogen, an add-on mechanistic methodology based on kinetic modelling was developed. Results suggest that BP's AOB activity was limited by the concentration of inorganic carbon (not by residual N and P), while NOB experienced less limitation from this. For NV, the sludge-specific nitrogen loading rate seemed to be the most prevalent factor limiting AOB and NOB activities. Altogether, this study shows that bottom-up mechanistic modelling can identify parameters that influence the nitrification performance. Increasing inorganic carbon in BP could invert its rAOB/rNOB value, facilitating its transition to shortcut nitrogen removal.

Abstract: Exposure to air pollution, such as particulate matter (PM), causes adverse health effects, particularly to the respiratory tract and cardiovascular system. PM is the collective name for all kinds of particles ranging from small particles and liquid droplets, which contain organic compounds, acids and metals, to soil or dust particles. One distinguishes PM10, PM2.5 and PM0.1, which have aerodynamic particle sizes smaller than 10, 2.5 and 0.1 µm, respectively. It is mainly the latter that is the most harmful, as PM0.1 penetrates deep into the respiratory system and carries relatively more toxic substances than the other PM fractions. Over a 15-year period, PM concentrations in European member states have fallen by about 30%. Nevertheless, the World Health Organisation (WHO) air quality guidelines, which became stricter in 2021, are exceeded in most places around the world. Particularly in cities, excessive levels of PM are measured and it is here that PM mitigation should be investigated. For this, the implementation of urban green infrastructure, including trees, shrubs, green roofs and green walls, is being looked at. Plants hinder airflow and remove PM from the air by deposition on their leaves and branches. This process is known as dry deposition. Plants can capture PM very efficiently, due to their complex structure of leaves and branches. Green walls offer significant advantages over other types of urban green infrastructure because they can grow on the huge available wall area and, because they do not hinder air circulation, as we sometimes see with trees. Green walls are believed to have a much greater, untapped potential to reduce PM pollution. However, a literature review showed that we do not know the quantitative impact of green walls and lack the tools and/or general methodology to do so. The objective of this thesis is therefore to develop a method for assessing PM removal by green walls, based on predictive models and based on relevant parameters that are experimentally determined. Computational fluid dynamics (CFD) is a numerical method to simulate airflow in complex environments such as cities. These models can also simulate the vegetation-wind interaction in detail and are interesting tools to assess the effect of green walls on PM concentrations in real environments. It is important to first study the aerodynamic effect of green walls and parameterise it correctly in CFD models. Plants decrease the wind speed and create turbulence through a combination of viscous and form drag, which are determined by the permeability (K) and drag coefficient (Cd), respectively. Wind tunnel experiments were conducted with three commonly found climbers (Hedera helix, Parthenocissus tricuspidata and Parthenocissus quinquefolia) and the variation of leaf area density was investigated for two of them. It was observed that the air resistance depended on plant species, leaf area density and wind speed. The difference between the plant species was assigned to the functional leaf size (FLS), the ratio of the largest circle within the boundaries of the leaf to the total leaf area. FLS is likely associated with other morphological characteristics of plants that, when considered collectively, provide a more comprehensive representation of leaf complexity. The pressure and velocity measurements obtained were used to optimise the permeability and drag coefficient in a CFD model. At wind speeds below 0.6 m s-1, the resistance was mainly determined by viscous drag and a larger leaf size resulted in a higher viscous drag. At wind speeds above 1.5 m s-1, form drag was dominant and the parameterised Cd decreased with increasing wind speed due to the sheltering effect of successive plant elements. The leaf area density had a significant effect on K and Cd and, is therefore an important plant parameters in CFD models. The main conclusion here is that the common practice of using a constant Cd to model the influence of plants on the air flow leads to deviations from reality. Wind tunnels are highly suitable to study the impact of green walls on PM concentration under controlled environmental conditions. For this purpose, a new wind tunnel setup was built and great attention was paid to obtaining a uniform air flow. Thus, based on CFD models, appropriate flow controllers were chosen, consisting of honeycombs and screens with different mesh sizes. New PM generation devices and measuring equipment were installed and set up appropriately. Devices were available for generating and measuring ultrafine dust (<0.1 µm, i.e. PM0.1) and fine dust (<0.3 µm, i.e. PM0.3) consisting of soot particles, and, on the other hand, fine dust with particle sizes smaller than 2.5 (PM2.5) and 10 µm (PM10) consisting of 'Arizona fine test dust'. With the new wind tunnel setup, it was possible to measure the influence of Hedera helix (common ivy), grown in a planter against a climbing aid, on the PM concentration and this was expressed by a collection efficiency, i.e. the difference in concentration in front and behind the plants normalised for the incoming concentration. The collection efficiency of H. helix depended on the particle size of the PM and wind speed. The collection efficiency decreased when the particle size increased from 0.02 to 0.2 µm and increased again for particle sizes above 0.3 µm. The collection efficiency also increased with increasing wind speed, especially for particle sizes > 0.03 µm. On the other hand, relative humidity and the type of PM (soot or dust) did not significantly affect the collection efficiency. The main objective of this study was to obtain an optimised size-resolved deposition model. Dry deposition occurs through several mechanisms, in particular gravity, diffusion, impaction and interception, and the subsequent resuspension of deposited PM back to the environment. The modelling of these mechanisms was described by \citet{Zhang2001} and \citet{Petroff2010}. The data obtained from the wind tunnel experiments allowed validating these deposition models. It was for the first time that deposition of real PM on green walls was studied. The different PM deposition mechanisms were found to be strongly dependent on particle size and wind speed. The models of \citet{Zhang2001} and \citet{Petroff2010} each matched PM concentration measurements for only certain particle sizes. Therefore, a combination of the two models was investigated and the root mean square error was lower by on average 3.5% (PM < 0.03 µm) and 46% (PM > 0.03 µm) compared to the original models at wind speeds greater than 1.5 m s-1. For wind speeds less than 1.5 m s-1, the optimised model did not differ from the original models. The optimised model was able to meet the imposed criteria for air quality models, where a correct model exhibits low deviation from measurements ('normalised mean square error' < 1.5), low bias ('fractional bias' between -0.3 and 0.3) and high R2. In comparison, the R$2$ of the optimised model was 0.57, while that of Zhang et al. (2001) and Petroff et al. (2010) was 0.23 and 0.31, respectively. The optimised model was however characterised by a high scatter, with the fraction of modeled results located within a factor of two of the measurements being lower than 50. A model study with a green façade oriented parallel to the incoming airflow showed that deposition by interception and impaction reduced remarkably, but that the orientation had no effect on deposition by Brownian diffusion. A promising green wall form for PM mitigation is the living wall system (LWS). LWS consist of supporting structures with substrate to grow plants in and can be planted with a variety of plant species. This allows to select plant species with optimal characteristics to achieve PM deposition. These characteristics refer to the macro- and microstructure of the leaves, and research has been conducted mainly on these. On the other hand, the influence of the supporting structure and substrate on PM concentrations has rarely been studied. With the new wind tunnel setup, LWS from different manufacturers were tested for their ability to capture PM. The setups were subjected for three hours to an air flow with a low PM concentration (resuspension phase) and then for three hours to an air flow to which additional PM was added (deposition phase). Some setups were able to decrease the PM concentration during both phases, while others just caused the concentration to increase. Some systems were able to reduce particulate matter concentration during both phases, namely LWS consisting of planters (-2% and -4% for PM0.1 and PM2.5, respectively) and textile cloths (-23% and -5% for PM0.1 and PM2.5, respectively). While other systems actually resulted in an increase in concentration especially LWS existing textile fabrics consisting of geotextiles (+11% for both PM fractions) and with moss as substrate (+2% and +5% for PM0.1 and PM2.5, respectively). This highlights the importance of careful selection of suspension systems to reduce particulate matter concentrations. Further research is therefore needed on the materials used in these systems in relation to their particulate content, as well as on plant development in these systems. In addition to air measurements, measurements were taken of the amount of PM deposited on the leaves and suspension system of LWS. This allowed the difference in PM resuspension and deposition between plant species to be investigated. The amount of deposited particulate matter was determined based on 'saturation isothermal remanent magnetisation' (SIRM), a measure of magnetisable particulate matter. This was possible because the added 'Arizona fine test dust' contained iron oxide. However, no significant difference was observed between the SIRM values measured before the wind tunnel experiment, after resuspension and after deposition. This suggested that the iron oxide content in the Arizona fine test dust was too low to measure a significant difference in the SIRM values on leaves after three hours. The plant species did give rise to different SIRM values ranging between 5 and 260 µ A. In particular, SIRM values above 26 µ A were observed for the plant species that were grouped due to their significantly higher accumulation of PM. 'Specific leaf area' (SLA), specifically the ratio of the one-sided 'fresh' leaf area to its dry mass, was the significant leaf characteristic. SLA correlated with leaf complexity. In particular, plant species with elongated leaves were characterized by low SLA, high FLS and high complexity and showed significantly higher SIRM values. Finally, the optimised size-resolved deposition model was also tested in an urban model to get an idea of the impact of a green wall on PM concentrations in a so-called 'street canyon'. These are narrow streets with high buildings on both sides, making air pollution more persistent. To this end, an ideal scenario was tested in which a green wall was introduced along both sides of the street over a length of about 270 m. The model result showed a decrease in PM2.5 and PM10 of 46 ± 12% and 52 ± 14%. This result is of course for a very optimal scenario where the green wall covers the entire building façades. Since this is not feasible in reality, other ways of promoting contact between green walls and polluted air can be explored. The insights obtained illustrate that the use of climbing plants can be a cost-effective and environmentally friendly solution to reduce PM concentrations. Moreover, the findings showed that models can be used to investigate the impact of green walls on PM levels. These findings fit within the broader context of designing healthy and sustainable urban environments and developing innovative solutions based on solid scientific knowledge.

Abstract: Expressions are presented for calculating the matrix effect and the pure particle size effect in the XRF analysis of particulate samples with a discrete particle size. The equations are based on the absorption-weighted radiometric diameter concept. Two excitationdetection geometries are considered, with the angles between the sample plane and both the incident and emerging radiation being either 90° (π geometry) or 45° (π/2 geometry). Calculations were made for different sample loadings and exciting radiation energies. The influence of these parameters on the matrix and pure particle size effects is shown. From the results, it is possible to predict the performances of alternative experimental correction procedures for the particle size effect, involving dual measurements at different excitation energies or in different excitationdetection geometries.

Abstract: Extension professionals are expected to help disseminate agricultural technologies, information, knowledge and skills to farmers. In order to develop valuable and long-lasting extension services, it is essential to understand the methods of extension that farmers find most beneficial. This understanding helps adopt improved practices, overcome barriers, provide targeted interventions and continuously improve agricultural extension programs. Thus, assessing factors affecting farmers' choice of agricultural extension methods is essential for developing extension methods that comply with farmers' needs and socio-economic conditions. Therefore, we analyzed the factors affecting farmers' preferences in extension methods, using cross-sectional data collected from 300 households in two sample districts and 16 Kebelles in Ethiopia between September 2019 and March 2020. Four extension methods, including training, demonstration, office visits and phone calls were considered as outcome variables. We fitted a multivariate probit model to estimate the factors that influence farmers' choice of extension methods. The results of the study showed that the number of dependents in the household head, formal education and membership of Idir (an informal insurance program a community or group runs to meet emergencies) were negatively associated with farmers' choices to participate in different extension methods compared to no extension. On the other hand, the sex of the household head, farm experience, participation in non-farm activities, monetary loan access, owning a mobile phone, radio access and membership of cooperatives were found to have a statistically significant positive impact on farmers' choices of extension methods. Based on these findings, the government and the concerned stakeholders should take farmers' socio-economic and institutional traits into account when selecting and commissioning agricultural extension methods. This could help to develop contextually relevant extension strategies that are more likely to be chosen and appreciated by farmers. Furthermore, such strategies can aid policymakers in designing extension programs that cater to farmers' needs and concerns. In conclusion, farmers' socio-economic and institutional affiliation should be taken into consideration when selecting agricultural extension methods.

Abstract: External fields are a powerful tool to probe optical excitations in a material. The linear energy shift of an excitation in a magnetic field is quantified by its effective g factor. Here we show how exciton g factors and their sign can be determined by converged first-principles calculations. We apply the method to monolayer excitons in semiconducting transition metal dichalcogenides and to interlayer excitons in MoSe2/WSe2 heterobilayers and obtain good agreement with recent experimental data. The precision of our method allows us to assign measured g factors of optical peaks to specific transitions in the band structure and also to specific regions of the samples. This revealed the nature of various, previously measured interlayer exciton peaks. We further show that, due to specific optical selection rules, g factors in van der Waals heterostructures are strongly spin and stacking-dependent. The calculation of orbital angular momenta requires the summation over hundreds of bands, indicating that for the considered two-dimensional materials the basis set size is a critical numerical issue. The presented approach can potentially be applied to a wide variety of semiconductors.