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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.

This is the dataset used to analyse biomass of fauna collected in farmed and wild kelp at the West coast of Norway (Søre Sunnmøre) in April 2019. Coordinates are given in the fil. 

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.

Society faces the double challenge of increasing biomass production to meet the future demands for food, materials and bioenergy, while addressing negative impacts of current (and future) land use. In the discourse, land use change (LUC) has often been considered as negative, referring to impacts of deforestation and expansion of biomass plantations. However, strategic establishment of suitable perennial production systems in agricultural landscapes can mitigate environmental impacts of current crop production, while providing biomass for the bioeconomy. Here, we explore the potential for such “beneficial LUC” in EU28. First, we map and quantify the degree of accumulated soil organic carbon losses, soil loss by wind and water erosion, nitrogen emissions to water, and recurring floods, in ∼81.000 individual landscapes in EU28. We then estimate the effectiveness in mitigating these impacts through establishment of perennial plants, in each landscape. The results indicate that there is a substantial potential for effective impact mitigation. Depending on criteria selection, 10–46% of the land used for annual crop production in EU28 is located in landscapes that could be considered priority areas for beneficial LUC. These areas are scattered all over Europe, but there are notable “hot-spots” where priority areas are concentrated, e.g., large parts of Denmark, western UK, The Po valley in Italy, and the Danube basin. While some policy developments support beneficial LUC, implementation could benefit from attempts to realize synergies between different Sustainable Development Goals, e.g., “Zero hunger”, “Clean water and sanitation”, “Affordable and Clean Energy”, “Climate Action”, and “Life on Land”. I studien har vi utforskat potentialen för fördelaktig markanvändningsförändring genom strategisk perennialisering i Europa. Miljöproblematiken i fler än 81,000 individuella landskap har kvantifierats och potentialen att lindra miljöproblematik med hjälp av strategisk etablering av perenna grödor har uppskattats i varje enskilt landskap. För mer information, se engelsk beskrivning.

The world’s demand for energy has steadily increased in recent years, driven by economic and population growth, coupled with the need to reduce greenhouse gas emissions. However, using fossil fuels to meet the energy demand has led to various environmental and social problems, including air pollution, climate change, and geopolitical conflicts. As a result, there has been a growing interest in shifting from fossil energy to green energy sources, which offer a cleaner, and often more cost-effective alternative. This essay will explore the opportunities and challenges of transitioning from fossil energy to renewable energy, with a focus on the economic, environmental, and social implications of this shift, throughout the current state of renewable energy technologies and their potential for widespread adoption, as well as the political and regulatory frameworks that facilitate or hinder this transition. The essay also provides an empirical literature overview of the costs and benefits of transitioning from fossil fuels to renewable energy, including the impact on the environment and employment. I argue that while the transition to renewable energy will not be easy, it is necessary to ensure a sustainable future for our planet and future generations

The data report weekly measurements of soil nitrous oxide (N2O) emission and methane (CH4) uptake in the growing seasons 2015 and 2016 in a maize field experiment performed on the Hawassa University campus, Central Rift Valley, Ethiopia. The experiment was designed to test the effect of intercropping the forage legumes lablab (L. purpureus) and Crotalaria (C. juncea) into nitrogen (N) and phosphorous (P) fertilized maize 3 and 6 weeks after sowing of maize. The forage legumes were harvested at flowering and half of the biomass was returned to the same plots as mulch in the first season. In the second season, N fertilization was halved in mulched plots. Intercropping effects are evaluated against fully and non-fertilized maize treatments. The results are published in Raji SG and Dörsch P, Biogesciences, https://doi.org/10.5194/bg-2019-303

The scenarios are developed based on projected climate and socio-economic changes, following the representative concentration pathways (RCPs) and the shared socioeconomic pathways (SSPs) for the region. The Norrström-Baltic SD model analyzes possible future shifts in the annual average conditions of sectoral and natural water system interactions. Such shifts are evaluated based on recent annual averages reflecting the condition of system components. Parameters taken into account are, amongst others, sectoral water availability, water fluxes between sectors and the corresponding nutrient (nitrogen and phosphorus) exchanges, coastal runoff and nitrogen and phosphorous loads ending up in the Baltic Sea. An overview of the model input variables and the parameters that are identified as system external uncertainties that may affect the behavior of the model: - Precipitation: climate change - Agricultural land: Development policies and market forces, food security and trade regulations, population growth and corresponding food demand/diet changes - Built-up land: Development policies and market forces, population growth, regional urbanization level, tourism expansion level - Forest land: Mitigation policies on climate change (i.e. afforestation and/or reforestation to maintain/enhance carbon capture and storage capacity), socio-economic developments leading to sectoral land competition (i.e. deforestation) - Open lands and wetlands: Policies and market forces supporting social and economic development in the region A total of 5 scenarios were developed for the Norrström/Baltic Sea case. One of them represents the ‘Base case’ conditions, while the rest are rooted in the combination of a certain SSP with a climate scenario linked to a certain RCP. The following overview shows the combinations used during the scenario building process: - Scenario 1: SSP1 + RCP 4.5 - Scenario 2: SSP2 + RCP 4.5 - Scenario 3: SSP4 + RCP 4.5 - Scenario 4: SSP5 + RCP 4.5 - Base Case scenario: Continuation into the future of the past-recent long-term average conditions in relation to hydro-climate and land use variables in the SD model. All the scenarios developed for the Norrström-Baltic region are linked to a climate scenario corresponding with RCP4.5, because projected patterns and changes for climate variables under this climate scenario were found to be more consistent with the observed changes in the region than other RCPs. The period 2010-2100 is compared with the normal mean for the period 1961-1990. Each year is compared separately with the long-term annual average precipitation. The xsls file is organized as follows. It comprises three sheets: Precipitation RCP with annual data of changes in annual precipitation (in percentage), precipitation (in million of m3/year and in mm/year); Land cover RCPs and SSPs with scenario data on land cover, annual change in land cover (in percentage), annual land cover areas for the Norrström water management district area, land dover area average for teh Norrström water management district area and average change in land cover compared to the long-term average (in percentage); Input data model with the four input variables (precipitation change rate in hydro-climate scenarios, urban growth rate in socioeconomic scenarios, forest land change rate in socioeconomic scenarios and agricultural land change rate in socioeconomic scenarios) and their change for each scenario (expressed in percentage).

Three scenarios of large-scale deployment for riparian buffers and windbreaks, across over 81,000 landscapes in Europe, with quantified corresponding areas, biomass output, and environmental benefits. Abstract: Within the scope of the new Common Agricultural Policy of the European Union, in coherence with other EU policies, new incentives are developed for farmers to deploy practices that are beneficial for climate, water, soil, air, and biodiversity. Such practices include establishment of multifunctional biomass production systems, designed to reduce environmental impacts while providing biomass for food, feed, bioenergy, and other biobased products. Here, we model three scenarios of large-scale deployment for two such systems, riparian buffers and windbreaks, across over 81,000 landscapes in Europe, and quantify the corresponding areas, biomass output, and environmental benefits. The results show that these systems can effectively reduce nitrogen emissions to water and soil loss by wind erosion, while simultaneously providing substantial environmental co-benefits, having limited negative effects on current agricultural production. This kind of beneficial land-use change using strategic perennialization is important for meeting environmental objectives while advancing towards a sustainable bioeconomy. Tre scenarier för storskalig etablering av buffertzoner och lähägn, över fler än 81,000 landskap i Europa, med kvantifierad areal, biomassaproduktion, och miljönytta. Se engelsk beskrivning för information om studien.