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Brazil is home to the largest tracts of tropical vegetation in the world, harbouring high levels of biodiversity and carbon. Several biomass maps have been produced for Brazil, using different approaches and methods, and for different purposes. These maps have been used to estimate historic, recent, and future carbon emissions from land use change (LUC). It can be difficult to determine which map to use for what purpose. The implications of using an unsuitable map can be significant, since the maps have large differences—both in terms of total carbon storage and its spatial distribution. This dataset of aboveground carbon was created based on data from existing maps and an up-to-date LULC map. The map reflects current LULC, has high accuracy and resolution (50 m), and a national coverage. It can be a useful alternative for scientific studies and policy initiatives concerned with existing LULC and LUC outside of existing forests, especially at local scales when high resolution is necessary, and/or outside the Amazon biome. Map unit: tonnes of aboveground carbon per hectare. This dataset of aboveground carbon was created based on data from existing maps and an up-to-date LULC map. The map reflects current LULC, has high accuracy and resolution (50 m), and a national coverage. It can be a useful alternative for scientific studies and policy initiatives concerned with existing LULC and LUC outside of existing forests, especially at local scales when high resolution is necessary, and/or outside the Amazon biome. Map unit: tonnes of aboveground carbon per hectare. Data är baserade på befintliga kartor och en aktuell LULC-karta (änding av markanvändning) för bildandet av ovanjordiskt kol i Brasilien. Kartan speglar nuvarande LULC, har hög noggrannhet och upplösning (50 m) och en nationell täckning. Mer information på den engelska katalogsidan: https://snd.gu.se/en/catalogue/study/ecds0244 This dataset of aboveground carbon was created based on data from existing maps and an up-to-date LULC map. The map reflects current LULC, has high accuracy and resolution (50 m), and a national coverage. It can be a useful alternative for scientific studies and policy initiatives concerned with existing LULC and LUC outside of existing forests, especially at local scales when high resolution is necessary, and/or outside the Amazon biome. Map unit: tonnes of aboveground carbon per hectare.

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.

Author: Daniel Vázquez Pombo (dvapo@elektro.dtu.dk) ------------------------------------------------------------------------------- This dataset corresponds to the results of the paper titled: "Multi-Horizon Data-Driven Wind Power Forecast: From Nowcast to 2 Days-Ahead" 4th International Conference on Smart Energy Systems and Technologies (SEST) - 2021 -> https://sites.univaasa.fi/sest2021/ Submmited: Dec 2020 Accepted: Feb 2021 Published: Sep 2021 ------------------------------------------------------------------------------- The folder contains all the results presented in the paper, for clarity. Additional resources might be supplied under request. -------------------------------------------------------------------------------

River regulation for hydropower is undertaken worldwide, causing profound alterations to hydrological regimes and running water habitats. Regulated catchments are often subjected to additional stressors, arising inter alia from agriculture, forestry and industry, which are likely to interact with impacts of river regulation on fish and other biota. Such interactions are poorly understood, hindering planning of effective mitigation and restoration. We investigated fish responses to increased discharge (as a restoration measure) in regulated rivers in Sweden. We compiled electrofishing data from river channels downstream of hydropower dams, each of which either has or lacks a mandated minimum discharge corresponding to c. 5% of pre‐regulation discharge. We further analysed interactions between flow restoration and co‐occurring local and regional stressors. River channels without a mandated minimum discharge were characterised by a low diversity of fish species with traits favouring persistence under unpredictable environmental conditions, including omnivory, short life cycles and small size. Additional stressors further reduced diversity, and increased dominance by broad niched, opportunistic species. Both the presence and magnitude of a mandated minimum discharge were positively related to fish diversity and density, and the relative density of three economically and recreationally valuable species. However, the size of these relationships frequently varied with the presence of additional stressors. Increasing levels of hydrological degradation and reduced connectivity at the catchment scale reduced positive flow‐ecology relationships and hindered restoration of fish communities towards reference conditions. However, application of a mandated minimum discharge also assisted in mitigating impacts of some co‐occurring stressors, especially reduced riparian integrity. Synthesis and applications. Additional stressors can strongly influence the outcomes of flow restoration for fish community diversity and composition. Our approach combining fish species and trait data from multiple flow restoration projects with information on additional stressors yielded valuable insights into factors affecting flow restoration success, useful for (i) identifying the systems most likely to benefit from mandated minimum flows, (ii) modelling influences of multiple stressors on flow‐ecology relationships, (iii) prioritising additional measures to manage co‐occurring stressors and enhance outcomes from flow restoration. Fish communities and traits from bypassed river reaches with and without a mandated minimum flowThe file contains data on fish communities sampled as part of Swedish national monitoring from 68 stations situated in bypassed river reaches downstream of hydropower dams in Sweden. The file includes basic information on the reaches, species abundances and diversity, and species trait data scored based on the www.freshwaterecology.info database. For more information, see the README fileGöthe et al for Dryad.xlsx

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.

Production of biodiesel from yellow grease (waste cooking oil and waste animal fats) is fast emerging as a promising alternative to address the twin challenges before the biodiesel industry today-fluctuation in prices of vegetable oil and the food versus fuel debate. Yellow grease has a high percentage of free fatty acids (FFA) and proves to be an unsuitable feedstock for biodiesel production from commercially viable alkali-catalyzed production systems due to saponification problems.“Green” methodologies based on heterogeneous solid acid catalyzed reactions have the potential to simultaneously promote esterification and transesterification reactions of yellow grease to produce biodiesel without soap formation and offer easy catalyst separation without generation of toxic streams. This paper presents kinetic studies for the conversion of model yellow grease feeds to biodiesel using a heteropolyacid supported on alumina (HSiW/Al2O3) using a batch autoclave. Three model yellow grease feeds were prepared using canola oil with added FFA such as palmitic, oleic and linoleic acid. A pseudo homogeneous kinetic model for the parallel esterification and transesterification was developed. The rate constants and activation parameters for esterification and transesterification reactions for the model yellow grease feeds were determined. The rate constants for esterification are higher than the transesterification rate constants. The kinetic model was validated using the experimental biodiesel data obtained from processing a commercial yellow grease feed. The kinetic model could be used to design novel processes to convert various low-value waste oils, fats and non-food grade oils to sustainable biodiesel. Keywords: Yellow grease, Canola oil, Free fatty acids, Heteropolyacid, Kinetics for esterification and transesterification

Understanding N budgets of tundra ecosystems is crucial for projecting future changes in plant community composition, greenhouse gas balances and soil N stocks. Winter warming can lead to higher tundra winter nitrogen (N) mineralization rates, while summer warming may increase both growing season N mineralization and plant N demand. The undulating tundra landscape is inter-connected through water and solute movement on top of and within near-surface soil, but the importance of lateral N fluxes for tundra N budgets is not well known. We studied the size of lateral N fluxes and the fate of lateral N input in the snowmelt period with a shallow thaw layer, and in the late growing season with a deeper thaw layer. We used 15N to trace inorganic lateral N movement in a Low-arctic mesic tundra heath slope in West Greenland and to quantify the fate of N in the receiving area. We found that half of the early-season lateral N input was retained by the receiving ecosystem, whereas half was transported downslope. Plants appear as poor utilizers of early-season N, indicating that higher winter N mineralization may influence plant growth and carbon (C) sequestration less than expected. Still, evergreen plants were better at utilizing early-season N, highlighting how changes in N availability may impact plant community composition. In contrast, later growing season lateral N input was deeper and offered an advantage to deeper-rooted deciduous plants. The measurements suggest that N input driven by future warming at the study site will have no significant impact on the overall N2O emissions. Our work underlines how tundra ecosystem N allocation, C budgets and plant community composition vary in their response to lateral N inputs, which may help us understand future responses in a warmer Arctic. (Less)

The aim of this paper is to contribute to the establishment of a robust framework for the assessment of Sustainable Development Goals (SDGs) in businesses, using the construction industry as an example and with the primary focus on combating climate change (SDG 13). We provide a critical analysis of a selection of relatively widely used SDG impact assessment tools, combined with a case study from the construction industry to explore how a meaningful SDG assessment can be framed with linkages between SDG 13 and other related SDGs. Our analysis points towards the importance of framing SDG assessments in a way that discourages "Greenwashing". Any SDG assessment that relates to climate targets in line with the Paris Agreement should identify the processes and activities that can be expected to be particularly challenging in terms of their abatement. In our road construction work case, we identify four such hard-to-abate activities: 1) introducing biomass for renewable transportation fuels for use in construction equipment and heavy transport; 2) electrification of transport and industrial processes; 3) substitution as part of transitioning from fossil fuel use; and 4) applying carbon capture and storage technologies in the production of basic materials, such as cement and steel. The approach applied will avoid that businesses only focus on SDGs in situations where they are already performing well or can apply low-cost measures or that they only relate to the part of the supply chain that pertains to their own business (Scope 1 emissions). For an SDG assessment to provide basis for informed decisions regarding real change towards more sustainable and equitable corporate practices it should: (i) identify and include concrete measures to align with the terms of the Paris Agreement; (ii) include relevant value chains; and (iii) consider both the short-term and long-term effects of strategic choices.