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  • Energy Research
  • 7. Clean energy
  • 12. Responsible consumption
  • Netherlands Research Portal

  • Authors: Wim Hugo;

    * Technical Challenges - Technology is relatively simple and has high conversion efficiency. * Cost Challenges - Despite efficiency, levelised costs are high, due to mainly 2 factors (1) the input cost of raw material is high, and (2) operating costs are high due to feedstock (methanol) and distillation operations. Selling oilcake has a significant effect on final product cost, with a 50% oilcake internal subsidy reducing the costs by R 6,500/ t (0.65 R/kWh). This would bring production cost into line with current range of diesel prices. * Environmental Challenges - Greenhouse gas savings are significant provided land use changes are carbon neutral. Limiting cultivation to subsistence cropland should assist with this goal. * Social and Institutional Challenges - Conversion of subsistence farmers in former homeland areas, with high reliance on cattle and maize, to a cash crop with side products for own consumption and cattle feed will require significant community involvement. Cooperative farming and marketing channels need to be investigated.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Ana Paula Staben Pruchniak (10423459); Graziella dos Santos Portes Silva (10423462); Liliane Schier de Lima (10423465); Sueli Pércio Quináia (4986440);

    Abstract Activated carbon is commonly used as a material for contaminant-adsorption processes in aqueous systems. However, its use is more restricted to charcoal than to coal, for the most part, in view of the fact of the higher cost (~ 40%) if the mineral is a fossil fuel which needs to be extracted from the earth by mining. For this reason, the peach stone that comes from alimentary industrial tailings can be a good choice for the separation of pollutants from aqueous suspensions and other soluble substances. The purpose of this research was the development of a low-cost filter, using stones to remove atrazine from water. Appraisal and characterization studies were performed along with batch experiments to investigate dosing effects of the activated carbon, atrazine concentration, contact time, and adsorption pH on removal procedures. From the results of the experiment, an excellent removal of the analyte in question was observed under conditions that can be considered as close as possible to the environment, such as pH = 6.5, room temperature and 10 minutes of agitation time, always choosing the best alternative with the lowest cost of energy and time. Batch system application has been recommended as versatile for utilization in seasonal problems such as pesticide contamination.

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    figshare
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    figshare
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Smithsonian figshare
    Dataset . 2020
    License: CC BY
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      figshare
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      figshare
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Smithsonian figshare
      Dataset . 2020
      License: CC BY
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Sathre, Roger; Gustavsson, Leif;

    Heavy trucks contribute significantly to climate change, and in 2020 were responsible for 7% of total Swedish GHG emissions and 5% of total global CO2 emissions. Here we study the full lifecycle of cargo trucks powered by different energy pathways, comparing their biomass feedstock use, primary energy use, net biogenic and fossil CO2 emission, and cumulative radiative forcing. We analyse battery electric trucks with bioelectricity from standalone or combined heat and power (CHP) plants, and pathways where bioelectricity is integrated with wind and solar electricity. We analyse trucks operated on fossil diesel fuel and on dimethyl ether (DME). All energy pathways are analysed with and without carbon capture and storage (CCS). Bioelectricity and DME are produced from forest harvest residues. Forest biomass is a limited resource, so in a scenario analysis we allocate a fixed amount of biomass to power Swedish truck transport. Battery lifespan and chemistry, the technology level of energy supply, and the biomass source and transport distance are all varied to understand how sensitive the results are to these parameters. The scenario spans 100 years into the future. We find that pathways using electricity to power battery electric trucks have much lower climate impacts and primary energy use, compared to diesel and DME based pathways. The pathways using bioelectricity with CCS result in negative emissions leading to global cooling of the earth. The pathways using diesel and DME have significant and very similar climate impact, even with CCS. The robust results show that truck electrification and increased renewable electricity production is a much better strategy to reduce the climate impact of cargo transport and much more primary energy efficient than the adoption of DME trucks. This climate impact analysis includes all fossil and net biogenic CO2 emissions as well as the timing of these emissions. Considering only fossil emissions is incomplete and could be misleading. This dataset contains data on 4 metrics (primary energy use, biomass feedstock use, cumulative CO2 emissions, and cumulative radiative forcing) resulting from scenario modeling of cargo truck use in Sweden powered by different energy pathways. The energy pathways include battery electric trucks powered by bioelectricity, solar photovoltaic electricity and wind electricity, and internal combustion trucks powered by fossil diesel and dimethyl ether. The scenario spans 100 years into the future. The Excel sheet "tables" contains input data for the scenario modeling, with sources listed where applicable. The remaining sheets contains the modeled results and generated figures that are also a published in the associated article Sathre & Gustavsson (2023). Refer to the method description and reference list in the included documentation files for details. Tunga lastbilar bidrar kraftigt till klimatförändringarna och stod 2020 för 7% av de totala svenska växthusgasutsläppen och 5% av de totala globala CO2-utsläppen. Här studerar vi hela livscykeln för lastbilar som drivs av olika energivägar, jämför deras användning av biomassaråvaror, primär energianvändning, biogena och fossila CO2-utsläpp netto och kumulativ strålningstvingning. Vi analyserar batterielektriska lastbilar med bioel från fristående eller kraftvärmeverk och vägar där bioel integreras med vind- och solkraft. Vi analyserar lastbilar som drivs med fossilt dieselbränsle och med dimetyleter (DME). Alla energivägar analyseras med och utan avskiljning och lagring av koldioxid (CCS). Bioelektricitet och DME produceras av skogsavverkningsrester. Skogsbiomassa är en begränsad resurs, så i en scenarioanalys avsätter vi en fast mängd biomassa för att driva svenska lastbilstransporter. Batteriets livslängd och kemi, tekniknivån för energiförsörjning och biomassakällan och transportavståndet varierar alla för att förstå hur känsliga resultaten är för dessa parametrar. Scenariot sträcker sig 100 år in i framtiden. Vi finner att vägar som använder el för att driva batterielektriska lastbilar har mycket lägre klimatpåverkan och primär energianvändning, jämfört med diesel- och DME-baserade vägar. De vägar som använder bioelektricitet med CCS resulterar i negativa utsläpp som leder till global kylning av jorden. Vägarna med diesel och DME har betydande och mycket liknande klimatpåverkan, även med CCS. De robusta resultaten visar att elektrifiering av lastbilar och ökad förnybar elproduktion är en mycket bättre strategi för att minska godstransporternas klimatpåverkan än införandet av DME-lastbilar, och mycket mer primärenergieffektiv. Denna klimatkonsekvensanalys omfattar alla fossila och biogena CO2-utsläpp samt tidpunkten för dessa utsläpp. Att bara ta hänsyn till fossila utsläpp är ofullständigt och kan vara missvisande. Detta dataset innehåller data om 4 mätvärden (primär energianvändning, biomassaråvara, kumulativa CO2-utsläpp och kumulativ strålkraftspåverkan) som härrör från scenariomodellering av lastbilsanvändning i Sverige som drivs av olika energivägar. Energivägarna inkluderar batterielektriska lastbilar som drivs av bioelektricitet, solcellselektricitet och vindkraft samt förbränningsbilar som drivs av fossil diesel och dimetyleter. Scenariot sträcker sig 100 år in i framtiden. På arket "tables" i Excelfilen återfinns den indata som använts i modelleringen med angivna källor där detta är tillämpligt. Övriga ark innehåller resultat samt figurer som också publiceras i den samhörande artikeln Sathre & Gustavsson (2023). Se metodbeskrivning samt referenslista i tillhörande dokumentationsfiler för detaljer.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Swedish National Dat...arrow_drop_down
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    Swedish National Data Service
    Dataset . 2023
    Data sources: Datacite
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    Swedish National Data Service
    Dataset . 2023
    Data sources: Datacite
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      Swedish National Data Service
      Dataset . 2023
      Data sources: Datacite
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      Swedish National Data Service
      Dataset . 2023
      Data sources: Datacite
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    Authors: Jiming Hao (1407004); Dijuan Liang (9675638); Xi Lu (288663); Minghao Zhuang (2822963); +3 Authors

    It shows point estimates for national GHG emissions (total emissions and seven agricultural activities) from 1978 to 2016 in China.

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    figshare
    Dataset . 2021
    License: CC 0
    Data sources: Datacite
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    figshare
    Dataset . 2021
    License: CC 0
    Data sources: Datacite
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      figshare
      Dataset . 2021
      License: CC 0
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      figshare
      Dataset . 2021
      License: CC 0
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • Authors: Billy De Lange;

    Data was obtained from a survey conducted by Centre for Renewable and Sustainable Energy Studies at Stellenbosch University on behalf of Eskom.

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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: Xiao, R (via Mendeley Data);

    Materials:Rice straw, pine sawdust and Phoenix Tree's leaf were selected as the main biomass of this study. Algorithms and methods:Coats-Redfern integral method,Doyle method,Distribution Activation Energy Model (DAEM): The database contains all the original data, intermediate data and final results used in the paper. Fig. 1 was schematic diagram of WRT-3P high temperature TGA and gas flow routes Fig. 2 was influence of particle size on biomass pyrolysis kinetics (a) TG curves of rice straw (b) DTG curves of rice traw (c) TG curves of pine sawdust (d) DTG curves of pine sawdust (e) TG curves of Phoenix Tree's leaf (f) DTG curves of Phoenix Tree's leaf Fig. 3 was influence of heating rate on different biomass (rice straw, pine sawdust and Phoenix Tree's leaf) pyrolysis kinetics (a) TG curves of rice straw (b) DTG curves of rice traw (c) TG curves of pine sawdust (d) DTG curves of pine sawdust (e) TG curves of Phoenix Tree's leaf (f) DTG curves of Phoenix Tree's leaf Fig. 4 was potassium concentration of initial and soaked rice straw Fig. 5 was influence of K+ on rice straw pyrolysis kinetics (a) TG curves (b) DTG curves Fig. 6 was the relationship between and 1/T of three kinds of biomass with a particle size of 0.150 - 0.180 mm at different heating rates. (a) 5℃/min (b) 10℃/min (c) 20℃/min (d) 40℃/min Fig. 7 was the apparent activation energy of biomass pyrolysis obtained by DAEM.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Mendeley Dataarrow_drop_down
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    Mendeley Data
    Dataset . 2021
    License: CC BY NC
    Data sources: Datacite
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Mendeley Data
    Dataset . 2021
    License: CC BY NC
    Data sources: Datacite
    B2FIND
    Dataset . 2021
    Data sources: B2FIND
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Mendeley Dataarrow_drop_down
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Mendeley Data
      Dataset . 2021
      License: CC BY NC
      Data sources: Datacite
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Mendeley Data
      Dataset . 2021
      License: CC BY NC
      Data sources: Datacite
      B2FIND
      Dataset . 2021
      Data sources: B2FIND
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  • Authors: Mekiso Yohannes Sido;

    Cyanobacterial biomass is important for biofuel and biofertilizer, however, biomass production requires expensive chemical growth nutrients. To address this issue, we explored the useof inexpensive growth nutrient media from an integrated manure-seawater system for cyanobacterial biomass production. Salt-tolerant cyanobacterial strain HSaC and salt-sensitive cyanobacterial strain LC were tested to evaluate the potential of integrated manure-seawater media for sustainable cyanobacterial biomass production. As a prerequisite for seawater experiments, strain HSaC was grown at different NaCl concentrations (0 mM, 60 mM, 120 mM, 180 mM, 240 mM and 300 mM) to identify the optimum salt concentration. The highest biomass yield and photosynthetic pigment contents were obtained at 120 mM NaCl concentration. The highest exo-polysaccharide (EPS) content was obtained at 180 mM NaCl concentration. The treatments for the manure-seawater media were cow manure, pig manure, chicken manure and BG11, each with distilled water, diluted seawater and non-diluted seawater. The highest biomass and photosynthetic pigment yield for cyanobacterial strains LC and HSaC were obtained from 0.5 dS/m and 10 dS/m diluted seawater integrated with cow manure, respectively, but pig and chicken manure performed poorly. Overall, the biomass production and photosynthetic pigment results from cow manure-seawater were relatively better than those from the reference media (BG11). Based on the current findings, it is concluded that the growth nutrients from integrated cow manure-seawater can wholly substitute for the BG11 without affecting cyanobacterial growth, thereby reducing the usage of expensive chemical growth media. Thus,The results of study help to enhance the biomass production of both salt-sensitive and salt-tolerant cyanobacteria for sustainable biofuel and biofertilizer production. Cyanobacterial biomass is important for biofuel and biofertilizer, however, biomass production requires expensive chemical growth nutrients. To address this issue, we explored the useof inexpensive growth nutrient media from an integrated manure-seawater system for cyanobacterial biomass production. Salt-tolerant cyanobacterial strain HSaC and salt-sensitive cyanobacterial strain LC were tested to evaluate the potential of integrated manure-seawater media for sustainable cyanobacterial biomass production. As a prerequisite for seawater experiments, strain HSaC was grown at different NaCl concentrations (0 mM, 60 mM, 120 mM, 180 mM, 240 mM and 300 mM) to identify the optimum salt concentration. The highest biomass yield and photosynthetic pigment contents were obtained at 120 mM NaCl concentration. The highest exo-polysaccharide (EPS) content was obtained at 180 mM NaCl concentration. The treatments for the manure-seawater media were cow manure, pig manure, chicken manure and BG11, each with distilled water, diluted seawater and non-diluted seawater. The highest biomass and photosynthetic pigment yield for cyanobacterial strains LC and HSaC were obtained from 0.5 dS/m and 10 dS/m diluted seawater integrated with cow manure, respectively, but pig and chicken manure performed poorly. Overall, the biomass production and photosynthetic pigment results from cow manure-seawater were relatively better than those from the reference media (BG11). Based on the current findings, it is concluded that the growth nutrients from integrated cow manure-seawater can wholly substitute for the BG11 without affecting cyanobacterial growth, thereby reducing the usage of expensive chemical growth media. Thus,The results of study help to enhance the biomass production of both salt-sensitive and salt-tolerant cyanobacteria for sustainable biofuel and biofertilizer production.

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    Authors: Dossou-Yovo, Elliott; Baggie, Idriss; Djagba, Justin Fagnombo; Swart, Sander;

    Inland valleys are becoming increasingly important agricultural production areas for rural households in sub-Saharan Africa due to their relative high and secure water availability and soil fertility. In addition, inland valleys are important as water buffer and biodiversity hot spots and they provide local communities with forest, forage, and fishing resources. As different inland-valley ecosystem functions may conflict with agricultural objectives, indiscriminate development should be avoided. This study aims to analyze the diversity of inland valleys in Sierra Leone and to develop guidelines for their sustainable use. Land use, biophysical and socio-economic data were analyzed on 257 inland valleys using spatial and multivariate techniques. Five cluster groups of inland valleys were identified: (i) semi-permanently flooded with good soil fertility, mostly under natural vegetation; (ii) semi-permanently flooded with very low soil fertility, abandoned by farmers; (iii) seasonally flooded with low soil fertility under low input levels, used for rainfed rice and off-season vegetables for household consumption and market; (iv) well drained with moderate soil fertility under medium input levels, used for rainfed rice and off-season vegetables for household consumption and market; and (v) well drained with moderate soil fertility under low input levels, used for household consumption. Soil fertility, hydrological regime, physical and market accessibility were the major factors affecting agricultural intensification of inland valleys. Opening up the areas in which inland valleys occur through improved roads and markets, and better water control through drainage infrastructures along with an integrated nutrient management would promote the sustainable agricultural use of inland valleys.

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    Dataset . 2018
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      Dataset . 2018
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  • Authors: Balaguer-Benlliure, Victor; Roger, Moya; Johana, Gaitán-Alvarez;

    This data contents information about parental wood and charcoal characteristics of 16 tropical species growing in fast-growth condictions. The data details tha following characterist of parental wood: moisture content (PMC) and wood density (PWD). On the others hand the charcoal characteristics are: Density (CD), moisture content (CMC) and compression strength of charcoal, gross calorific value (GCV), ash and volatile matter and fixed carbon, Carbon (C), nitrogen (N), hydrogen (H), and oxygen (O) contents, C/N ratio, O/Cmol ratio and H/Cmol ratio. Besides it is presented FTIR spectra and the ignition temperature (Ti), the burnout temperature (Tf), the characteristic combustion index (S), the ignition index (Di), the time corresponding to the maximum combustion rate (tp), the ignition time (tig), and the average rate of combustion.

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    Authors: Gerard, Sebastian; Zhao, Yu; Sullivan, Josephine;

    We present a multi-temporal, multi-modal remote-sensing dataset for predicting how active wildfires will spread at a resolution of 24 hours. The dataset consists of 13.607 images across 607 fire events in the United States from January 2018 to October 2021. For each fire event, the dataset contains a full time series of daily observations, containing detected active fires and variables related to fuel, topography and weather conditions. Documentation WildfireSpreadTS_Documentation.pdf includes further details about the dataset, following Gebru et al.'s "Datasheets for Datasets" framework. This documentation is similar to the supplementary material of the associated NeurIPS paper, excluding only information about experimental setup and results. For full details, please refer to the associated paper. Code: Getting started Get started working with the dataset at https://github.com/SebastianGer/WildfireSpreadTS. The code includes a PyTorch Dataset and Lightning DataModule to allow for easy access. We recommend converting the GeoTIFF files provided here to HDF5 files (bigger files, but much faster). The necessary code is also available in the repository. This work is funded by Digital Futures in the project EO-AI4GlobalChange. The computations were enabled by resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS) at C3SE partially funded by the Swedish Research Council through grant agreement no. 2022-06725.

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    ZENODO
    Dataset . 2023
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    ZENODO
    Dataset . 2023
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    ZENODO
    Dataset . 2023
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    ZENODO
    Dataset . 2023
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      ZENODO
      Dataset . 2023
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      ZENODO
      Dataset . 2023
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      Dataset . 2023
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  • Authors: Wim Hugo;

    * Technical Challenges - Technology is relatively simple and has high conversion efficiency. * Cost Challenges - Despite efficiency, levelised costs are high, due to mainly 2 factors (1) the input cost of raw material is high, and (2) operating costs are high due to feedstock (methanol) and distillation operations. Selling oilcake has a significant effect on final product cost, with a 50% oilcake internal subsidy reducing the costs by R 6,500/ t (0.65 R/kWh). This would bring production cost into line with current range of diesel prices. * Environmental Challenges - Greenhouse gas savings are significant provided land use changes are carbon neutral. Limiting cultivation to subsistence cropland should assist with this goal. * Social and Institutional Challenges - Conversion of subsistence farmers in former homeland areas, with high reliance on cattle and maize, to a cash crop with side products for own consumption and cattle feed will require significant community involvement. Cooperative farming and marketing channels need to be investigated.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Ana Paula Staben Pruchniak (10423459); Graziella dos Santos Portes Silva (10423462); Liliane Schier de Lima (10423465); Sueli Pércio Quináia (4986440);

    Abstract Activated carbon is commonly used as a material for contaminant-adsorption processes in aqueous systems. However, its use is more restricted to charcoal than to coal, for the most part, in view of the fact of the higher cost (~ 40%) if the mineral is a fossil fuel which needs to be extracted from the earth by mining. For this reason, the peach stone that comes from alimentary industrial tailings can be a good choice for the separation of pollutants from aqueous suspensions and other soluble substances. The purpose of this research was the development of a low-cost filter, using stones to remove atrazine from water. Appraisal and characterization studies were performed along with batch experiments to investigate dosing effects of the activated carbon, atrazine concentration, contact time, and adsorption pH on removal procedures. From the results of the experiment, an excellent removal of the analyte in question was observed under conditions that can be considered as close as possible to the environment, such as pH = 6.5, room temperature and 10 minutes of agitation time, always choosing the best alternative with the lowest cost of energy and time. Batch system application has been recommended as versatile for utilization in seasonal problems such as pesticide contamination.

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    Dataset . 2021
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    Dataset . 2021
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    Smithsonian figshare
    Dataset . 2020
    License: CC BY
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      Smithsonian figshare
      Dataset . 2020
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    Authors: Sathre, Roger; Gustavsson, Leif;

    Heavy trucks contribute significantly to climate change, and in 2020 were responsible for 7% of total Swedish GHG emissions and 5% of total global CO2 emissions. Here we study the full lifecycle of cargo trucks powered by different energy pathways, comparing their biomass feedstock use, primary energy use, net biogenic and fossil CO2 emission, and cumulative radiative forcing. We analyse battery electric trucks with bioelectricity from standalone or combined heat and power (CHP) plants, and pathways where bioelectricity is integrated with wind and solar electricity. We analyse trucks operated on fossil diesel fuel and on dimethyl ether (DME). All energy pathways are analysed with and without carbon capture and storage (CCS). Bioelectricity and DME are produced from forest harvest residues. Forest biomass is a limited resource, so in a scenario analysis we allocate a fixed amount of biomass to power Swedish truck transport. Battery lifespan and chemistry, the technology level of energy supply, and the biomass source and transport distance are all varied to understand how sensitive the results are to these parameters. The scenario spans 100 years into the future. We find that pathways using electricity to power battery electric trucks have much lower climate impacts and primary energy use, compared to diesel and DME based pathways. The pathways using bioelectricity with CCS result in negative emissions leading to global cooling of the earth. The pathways using diesel and DME have significant and very similar climate impact, even with CCS. The robust results show that truck electrification and increased renewable electricity production is a much better strategy to reduce the climate impact of cargo transport and much more primary energy efficient than the adoption of DME trucks. This climate impact analysis includes all fossil and net biogenic CO2 emissions as well as the timing of these emissions. Considering only fossil emissions is incomplete and could be misleading. This dataset contains data on 4 metrics (primary energy use, biomass feedstock use, cumulative CO2 emissions, and cumulative radiative forcing) resulting from scenario modeling of cargo truck use in Sweden powered by different energy pathways. The energy pathways include battery electric trucks powered by bioelectricity, solar photovoltaic electricity and wind electricity, and internal combustion trucks powered by fossil diesel and dimethyl ether. The scenario spans 100 years into the future. The Excel sheet "tables" contains input data for the scenario modeling, with sources listed where applicable. The remaining sheets contains the modeled results and generated figures that are also a published in the associated article Sathre & Gustavsson (2023). Refer to the method description and reference list in the included documentation files for details. Tunga lastbilar bidrar kraftigt till klimatförändringarna och stod 2020 för 7% av de totala svenska växthusgasutsläppen och 5% av de totala globala CO2-utsläppen. Här studerar vi hela livscykeln för lastbilar som drivs av olika energivägar, jämför deras användning av biomassaråvaror, primär energianvändning, biogena och fossila CO2-utsläpp netto och kumulativ strålningstvingning. Vi analyserar batterielektriska lastbilar med bioel från fristående eller kraftvärmeverk och vägar där bioel integreras med vind- och solkraft. Vi analyserar lastbilar som drivs med fossilt dieselbränsle och med dimetyleter (DME). Alla energivägar analyseras med och utan avskiljning och lagring av koldioxid (CCS). Bioelektricitet och DME produceras av skogsavverkningsrester. Skogsbiomassa är en begränsad resurs, så i en scenarioanalys avsätter vi en fast mängd biomassa för att driva svenska lastbilstransporter. Batteriets livslängd och kemi, tekniknivån för energiförsörjning och biomassakällan och transportavståndet varierar alla för att förstå hur känsliga resultaten är för dessa parametrar. Scenariot sträcker sig 100 år in i framtiden. Vi finner att vägar som använder el för att driva batterielektriska lastbilar har mycket lägre klimatpåverkan och primär energianvändning, jämfört med diesel- och DME-baserade vägar. De vägar som använder bioelektricitet med CCS resulterar i negativa utsläpp som leder till global kylning av jorden. Vägarna med diesel och DME har betydande och mycket liknande klimatpåverkan, även med CCS. De robusta resultaten visar att elektrifiering av lastbilar och ökad förnybar elproduktion är en mycket bättre strategi för att minska godstransporternas klimatpåverkan än införandet av DME-lastbilar, och mycket mer primärenergieffektiv. Denna klimatkonsekvensanalys omfattar alla fossila och biogena CO2-utsläpp samt tidpunkten för dessa utsläpp. Att bara ta hänsyn till fossila utsläpp är ofullständigt och kan vara missvisande. Detta dataset innehåller data om 4 mätvärden (primär energianvändning, biomassaråvara, kumulativa CO2-utsläpp och kumulativ strålkraftspåverkan) som härrör från scenariomodellering av lastbilsanvändning i Sverige som drivs av olika energivägar. Energivägarna inkluderar batterielektriska lastbilar som drivs av bioelektricitet, solcellselektricitet och vindkraft samt förbränningsbilar som drivs av fossil diesel och dimetyleter. Scenariot sträcker sig 100 år in i framtiden. På arket "tables" i Excelfilen återfinns den indata som använts i modelleringen med angivna källor där detta är tillämpligt. Övriga ark innehåller resultat samt figurer som också publiceras i den samhörande artikeln Sathre & Gustavsson (2023). Se metodbeskrivning samt referenslista i tillhörande dokumentationsfiler för detaljer.

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    Swedish National Data Service
    Dataset . 2023
    Data sources: Datacite
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    Swedish National Data Service
    Dataset . 2023
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Swedish National Dat...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Swedish National Data Service
      Dataset . 2023
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Swedish National Data Service
      Dataset . 2023
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Jiming Hao (1407004); Dijuan Liang (9675638); Xi Lu (288663); Minghao Zhuang (2822963); +3 Authors

    It shows point estimates for national GHG emissions (total emissions and seven agricultural activities) from 1978 to 2016 in China.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ figsharearrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    figshare
    Dataset . 2021
    License: CC 0
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    figshare
    Dataset . 2021
    License: CC 0
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ figsharearrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      figshare
      Dataset . 2021
      License: CC 0
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      figshare
      Dataset . 2021
      License: CC 0
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • Authors: Billy De Lange;

    Data was obtained from a survey conducted by Centre for Renewable and Sustainable Energy Studies at Stellenbosch University on behalf of Eskom.

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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: Xiao, R (via Mendeley Data);

    Materials:Rice straw, pine sawdust and Phoenix Tree's leaf were selected as the main biomass of this study. Algorithms and methods:Coats-Redfern integral method,Doyle method,Distribution Activation Energy Model (DAEM): The database contains all the original data, intermediate data and final results used in the paper. Fig. 1 was schematic diagram of WRT-3P high temperature TGA and gas flow routes Fig. 2 was influence of particle size on biomass pyrolysis kinetics (a) TG curves of rice straw (b) DTG curves of rice traw (c) TG curves of pine sawdust (d) DTG curves of pine sawdust (e) TG curves of Phoenix Tree's leaf (f) DTG curves of Phoenix Tree's leaf Fig. 3 was influence of heating rate on different biomass (rice straw, pine sawdust and Phoenix Tree's leaf) pyrolysis kinetics (a) TG curves of rice straw (b) DTG curves of rice traw (c) TG curves of pine sawdust (d) DTG curves of pine sawdust (e) TG curves of Phoenix Tree's leaf (f) DTG curves of Phoenix Tree's leaf Fig. 4 was potassium concentration of initial and soaked rice straw Fig. 5 was influence of K+ on rice straw pyrolysis kinetics (a) TG curves (b) DTG curves Fig. 6 was the relationship between and 1/T of three kinds of biomass with a particle size of 0.150 - 0.180 mm at different heating rates. (a) 5℃/min (b) 10℃/min (c) 20℃/min (d) 40℃/min Fig. 7 was the apparent activation energy of biomass pyrolysis obtained by DAEM.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Mendeley Dataarrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Mendeley Data
    Dataset . 2021
    License: CC BY NC
    Data sources: Datacite
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Mendeley Data
    Dataset . 2021
    License: CC BY NC
    Data sources: Datacite
    B2FIND
    Dataset . 2021
    Data sources: B2FIND
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Mendeley Dataarrow_drop_down
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Mendeley Data
      Dataset . 2021
      License: CC BY NC
      Data sources: Datacite
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Mendeley Data
      Dataset . 2021
      License: CC BY NC
      Data sources: Datacite
      B2FIND
      Dataset . 2021
      Data sources: B2FIND
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  • Authors: Mekiso Yohannes Sido;

    Cyanobacterial biomass is important for biofuel and biofertilizer, however, biomass production requires expensive chemical growth nutrients. To address this issue, we explored the useof inexpensive growth nutrient media from an integrated manure-seawater system for cyanobacterial biomass production. Salt-tolerant cyanobacterial strain HSaC and salt-sensitive cyanobacterial strain LC were tested to evaluate the potential of integrated manure-seawater media for sustainable cyanobacterial biomass production. As a prerequisite for seawater experiments, strain HSaC was grown at different NaCl concentrations (0 mM, 60 mM, 120 mM, 180 mM, 240 mM and 300 mM) to identify the optimum salt concentration. The highest biomass yield and photosynthetic pigment contents were obtained at 120 mM NaCl concentration. The highest exo-polysaccharide (EPS) content was obtained at 180 mM NaCl concentration. The treatments for the manure-seawater media were cow manure, pig manure, chicken manure and BG11, each with distilled water, diluted seawater and non-diluted seawater. The highest biomass and photosynthetic pigment yield for cyanobacterial strains LC and HSaC were obtained from 0.5 dS/m and 10 dS/m diluted seawater integrated with cow manure, respectively, but pig and chicken manure performed poorly. Overall, the biomass production and photosynthetic pigment results from cow manure-seawater were relatively better than those from the reference media (BG11). Based on the current findings, it is concluded that the growth nutrients from integrated cow manure-seawater can wholly substitute for the BG11 without affecting cyanobacterial growth, thereby reducing the usage of expensive chemical growth media. Thus,The results of study help to enhance the biomass production of both salt-sensitive and salt-tolerant cyanobacteria for sustainable biofuel and biofertilizer production. Cyanobacterial biomass is important for biofuel and biofertilizer, however, biomass production requires expensive chemical growth nutrients. To address this issue, we explored the useof inexpensive growth nutrient media from an integrated manure-seawater system for cyanobacterial biomass production. Salt-tolerant cyanobacterial strain HSaC and salt-sensitive cyanobacterial strain LC were tested to evaluate the potential of integrated manure-seawater media for sustainable cyanobacterial biomass production. As a prerequisite for seawater experiments, strain HSaC was grown at different NaCl concentrations (0 mM, 60 mM, 120 mM, 180 mM, 240 mM and 300 mM) to identify the optimum salt concentration. The highest biomass yield and photosynthetic pigment contents were obtained at 120 mM NaCl concentration. The highest exo-polysaccharide (EPS) content was obtained at 180 mM NaCl concentration. The treatments for the manure-seawater media were cow manure, pig manure, chicken manure and BG11, each with distilled water, diluted seawater and non-diluted seawater. The highest biomass and photosynthetic pigment yield for cyanobacterial strains LC and HSaC were obtained from 0.5 dS/m and 10 dS/m diluted seawater integrated with cow manure, respectively, but pig and chicken manure performed poorly. Overall, the biomass production and photosynthetic pigment results from cow manure-seawater were relatively better than those from the reference media (BG11). Based on the current findings, it is concluded that the growth nutrients from integrated cow manure-seawater can wholly substitute for the BG11 without affecting cyanobacterial growth, thereby reducing the usage of expensive chemical growth media. Thus,The results of study help to enhance the biomass production of both salt-sensitive and salt-tolerant cyanobacteria for sustainable biofuel and biofertilizer production.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Dossou-Yovo, Elliott; Baggie, Idriss; Djagba, Justin Fagnombo; Swart, Sander;

    Inland valleys are becoming increasingly important agricultural production areas for rural households in sub-Saharan Africa due to their relative high and secure water availability and soil fertility. In addition, inland valleys are important as water buffer and biodiversity hot spots and they provide local communities with forest, forage, and fishing resources. As different inland-valley ecosystem functions may conflict with agricultural objectives, indiscriminate development should be avoided. This study aims to analyze the diversity of inland valleys in Sierra Leone and to develop guidelines for their sustainable use. Land use, biophysical and socio-economic data were analyzed on 257 inland valleys using spatial and multivariate techniques. Five cluster groups of inland valleys were identified: (i) semi-permanently flooded with good soil fertility, mostly under natural vegetation; (ii) semi-permanently flooded with very low soil fertility, abandoned by farmers; (iii) seasonally flooded with low soil fertility under low input levels, used for rainfed rice and off-season vegetables for household consumption and market; (iv) well drained with moderate soil fertility under medium input levels, used for rainfed rice and off-season vegetables for household consumption and market; and (v) well drained with moderate soil fertility under low input levels, used for household consumption. Soil fertility, hydrological regime, physical and market accessibility were the major factors affecting agricultural intensification of inland valleys. Opening up the areas in which inland valleys occur through improved roads and markets, and better water control through drainage infrastructures along with an integrated nutrient management would promote the sustainable agricultural use of inland valleys.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Harvard Dataversearrow_drop_down
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    Harvard Dataverse
    Dataset . 2018
    License: CC 0
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Harvard Dataversearrow_drop_down
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      Harvard Dataverse
      Dataset . 2018
      License: CC 0
      Data sources: Datacite
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  • Authors: Balaguer-Benlliure, Victor; Roger, Moya; Johana, Gaitán-Alvarez;

    This data contents information about parental wood and charcoal characteristics of 16 tropical species growing in fast-growth condictions. The data details tha following characterist of parental wood: moisture content (PMC) and wood density (PWD). On the others hand the charcoal characteristics are: Density (CD), moisture content (CMC) and compression strength of charcoal, gross calorific value (GCV), ash and volatile matter and fixed carbon, Carbon (C), nitrogen (N), hydrogen (H), and oxygen (O) contents, C/N ratio, O/Cmol ratio and H/Cmol ratio. Besides it is presented FTIR spectra and the ignition temperature (Ti), the burnout temperature (Tf), the characteristic combustion index (S), the ignition index (Di), the time corresponding to the maximum combustion rate (tp), the ignition time (tig), and the average rate of combustion.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Gerard, Sebastian; Zhao, Yu; Sullivan, Josephine;

    We present a multi-temporal, multi-modal remote-sensing dataset for predicting how active wildfires will spread at a resolution of 24 hours. The dataset consists of 13.607 images across 607 fire events in the United States from January 2018 to October 2021. For each fire event, the dataset contains a full time series of daily observations, containing detected active fires and variables related to fuel, topography and weather conditions. Documentation WildfireSpreadTS_Documentation.pdf includes further details about the dataset, following Gebru et al.'s "Datasheets for Datasets" framework. This documentation is similar to the supplementary material of the associated NeurIPS paper, excluding only information about experimental setup and results. For full details, please refer to the associated paper. Code: Getting started Get started working with the dataset at https://github.com/SebastianGer/WildfireSpreadTS. The code includes a PyTorch Dataset and Lightning DataModule to allow for easy access. We recommend converting the GeoTIFF files provided here to HDF5 files (bigger files, but much faster). The necessary code is also available in the repository. This work is funded by Digital Futures in the project EO-AI4GlobalChange. The computations were enabled by resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS) at C3SE partially funded by the Swedish Research Council through grant agreement no. 2022-06725.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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