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Developing high-efficiency hetero-catalysts for transesterification reaction is of great importance in the production of biodiesel from Jatropha curcas L. seed oil (JO). Here, we synthesized a series of sulfated TiO2 by treating with varying H2SO4 concentration (xSO42-/TiO2) and TiO2 catalysts and applied to the transesterification of JO. Furthermore, these heterostructures were characterized by many characterization methods including XRD, FT–IR, N2–adsorption, SEM, TEM, TG, py-IR and NH3-TPD, and their catalytic performance were investigated under various operating conditions. The results reveal that both the Brønsted and Lewis acid sites are presented in the xSO42-/TiO2 catalysts, while only Lewis-type sites are observed in the TiO2 catalyst. And the acid intensity, surface area and mesoporous volume of catalysts are improved obviously after treating with sulfuric acid of TiO2. Then the xSO42-/TiO2 catalysts exhibit much higher catalytic activity than TiO2 catalyst, which is attributed to the larger surface area and mesoporous volume and stronger acidity. Furthermore, the reusability behavior of 1.5SO42-/TiO2 catalyst in transesterification of JO was also studied. Date-Heterogeneous and efficient transesterification of Jatropha curcas L. seed oil

Anaerobic fermentation technology allows the formation of medium chain carboxylates and alcohols via microbial chain elongation. This requires steering the reactor microbiomes to deliver the desired products. Here, CO2 supply is used to control ethanol-based chain elongation and to allow several other bioprocesses to occur simultaneously. Bioreactor performance data presented.

Description: This meta-data on development and management of community managed small-scale irrigation schemes in Ethiopia is presented in a spreadsheet as a table after reviewing 83 published articles. The dataset contains research focus, data collection and analysis method, spatial scale, irrigation typology, irrigation water sources, source of energy for water conveyance from the source, main research results, scheme management systems, identified problems and provided solutions from each research article when available. The spatial scale was categorized as national, regional, district, basin, watershed or scheme, based on the spatial coverage of the research done. The irrigation typology was categorized as large-scale, medium-scale and small-scale based on the Ethiopian classification. Surface water sources such as river, lake, reservoir and flash flood and ground water sources of wells and springs or a combination of more than one source were mentioned as the water sources for irrigation schemes. The sources of energy for water abstraction were categorized as gravity, pump or a combination of both. Year of irrigation scheme commencement, available irrigation scheme infrastructure, number of beneficiaries (households), and stakeholders in scheme management were also extracted when available in the literature. Spatial coverage: Data was collected from community managed small-scale irrigation schemes located in different parts of Ethiopia. Location of some irrigation schemes (in UTM) is indicated in the dataset spreadsheet.

During the July 2021 European floods approximately 8 million pieces of plastic dairy packaging were flushed from a severely damaged dairy processing facility located at the Vesdre river in Belgium. Some of these dairy packaging 'buttertubs' were ultimately flushed into the Meuse river and counted on riverbanks along the Dutch Meuse between July 2021 and July 2023. In addition to recording when and where they were found, some were collected for analysis on their development of mass over the two years between July 2021 - July 2023. The article attached to this dataset is called "Flood-induced buttertub spill reveals riverine plastic transport dynamics" and has the DOI 10.1186/s12302-024-00962-1. Dataset 1 contains the locations where buttertubs were found over the two years, with the location coordinates and sampled area of riverbank. Dataset 2 contains the mass analysis of the collected buttertubs before and after they were cleaned and dried. Dataset 3 contains pictures of the buttertubs analyzed for their mass prior to cleaning.

This Excel file summarises the results of the scenarios that use an OTEC growth rate rOTEC of 28% and 40% per year, respectively.

Plant responses to biotic and abiotic legacies left in soil by preceding plants is known as plant–soil feedback (PSF). PSF is an important mechanism to explain plant community dynamics and plant performance in natural and agricultural systems. However, most PSF studies are short-term and small-scale due to practical constraints for field-scale quantification of PSF effects, yet field experiments are warranted to assess actual PSF effects under less controlled conditions. Here we used unmanned aerial vehicle (UAV)-based optical sensors to test whether PSF effects on plant traits can be quantified remotely. We established a randomized agro-ecological field experiment in which six different cover crop species and species combinations from three different plant families (Poaceae, Fabaceae, Brassicaceae) were grown. The feedback effects on plant traits were tested in oat (Avena sativa) by quantifying the cover crop legacy effects on key plant traits: height, fresh biomass, nitrogen content, and leaf chlorophyll content. Prior to destructive sampling, hyperspectral data were acquired and used for calibration and independent validation of regression models to retrieve plant traits from optical data. Subsequently, for each trait the model with highest precision and accuracy was selected. We used the hyperspectral analyses to predict the directly measured plant height (RMSE = 5.12 cm, R2 = 0.79), chlorophyll content (RMSE = 0.11 g m−2, R2 = 0.80), N-content (RMSE = 1.94 g m−2, R2 = 0.68), and fresh biomass (RMSE = 0.72 kg m−2, R2 = 0.56). Overall the PSF effects of the different cover crop treatments based on the remote sensing data matched the results based on in situ measurements. The average oat canopy was tallest and its leaf chlorophyll content highest in response to legacy of Vicia sativa monocultures (100 cm, 0.95 g m−2, respectively) and in mixture with Raphanus sativus (100 cm, 1.09 g m−2, respectively), while the lowest values (76 cm, 0.41 g m−2, respectively) were found in response to legacy of Lolium perenne monoculture, and intermediate responses to the legacy of the other treatments. We show that PSF effects in the field occur and alter several important plant traits that can be sensed remotely and quantified in a non-destructive way using UAV-based optical sensors; these can be repeated over the growing season to increase temporal resolution. Remote sensing thereby offers great potential for studying PSF effects at field scale and relevant spatial-temporal resolutions which will facilitate the elucidation of the underlying mechanisms. van der Meij et al_Biogeosciences2017_dataThe experimental set-up, treatments, data collection and data analyses are thoroughly described in the Biogeoscience manuscript ‘Remote sensing of plant trait responses to field-based plant-soil feedback using UAV-based optical sensors’ doi:10.5194/bg-2016-452. Therefore we refer to the manuscript for detailed information an here we provide a brief summary to enable readers to follow what the data entail. The data were collected from a 2-year field experiment with plant rotations in a full factorial design. The plant treatments we focused on are legacy effects of the plant treatments (listed below) to the following oat crop. In this oat crop we quantified several plant traits both in situ and via remote sensing by use of UAV and hyperspectral and EGB sensors. The experiment was set-up in five randomized field blocks. We used part of the in situ collected data to parameterize the hyperspectral data based models and we validated these models with the other half of the field plots. Plant treatments Fa= fallow Lp= Lolium perenne Rs= Raphanus sativus Tr= Trifolium repens Vs= Vicia sativa Lp+Tr= 50:50 species mixture (relative to the monoculture seed densities) of the species Lp and Tr Rs+Vs= 50:50 species mixture (relative to the monoculture seed densities) of the species Rs and Vs

The Flameless Combustion (FC) regime has been pointed out as a promising combustion technique to lower the emissions of nitrogen oxides (NOx) while maintaining low CO and soot emissions, as well as high efficiencies. However, its accurate modeling remains a challenge. The prediction of pollutant species, especially NOx, is affected by the usually low total values that require higher precision from computational tools, as well as the incorporation of relevant formation pathways within the overall reaction mechanism that are usually neglected. The present work explores a multiple step modeling approach to tackle these issues. Initially, a CFD solution with simplified chemistry is generated [both the Eddy Dissipation Model (EDM) as well as the Flamelet Generated Manifolds (FGM) approach are employed]. Subsequently, its computational cells are clustered to form ideal reactors by user-defined criteria, and the resulting Chemical Reactor Network (CRN) is subsequently solved with a detailed chemical reaction mechanism. The capabilities of the clustering and CRN solving computational tool (AGNES—Automatic Generation of Networks for Emission Simulation) are explored with a test case related to FC. The test case is non-premixed burner based on jet mixing and fueled with CH4 tested for various equivalence ratios. Results show that the prediction of CO emissions was improved significantly with respect to the CFD solution and are in good agreement with the experimental data. As for the NOx emissions, the CRN results were capable of reproducing the non-monotonic behavior with equivalence ratio, which the CFD simulations could not capture. However, the agreement between experimental values and those predicted by CRN for NOx is not fully satisfactory. The clustering criteria employed to generate the CRNs from the CFD solutions were shown to affect the results to a great extent, pointing to future opportunities in improving the multi-step procedure and its application.