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  • Energy Research
  • 7. Clean energy
  • English

  • 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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    This climate change impact data (future scenarios on temperature-induced GDP losses) and climate change mitigation cost data (REMIND model scenarios) is published under doi: 10.5281/zenodo.3541809 and used in this paper: Ueckerdt F, Frieler K, Lange S, Wenz L, Luderer G, Levermann A (2018) The economically optimal warming limit of the planet. Earth System Dynamics. https://doi.org/10.5194/esd-10-741-2019 Below the individual file contents are explained. For further questions feel free to write to Falko Ueckerdt (ueckerdt@pik-potsdam.de). Climate change impact data File 1: Data_rel-GDPpercapita-changes_withCC_per-country_all-RCP_all-SSP_4GCM.csv Content: Data of relative change in absolute GDP/CAP levels (compared to the baseline path of the respective SSP in the SSP database) for each country, RCP (and a zero-emissions scenario), SSP and 4 GCMs (spanning a broad range of climate sensitivity). Negative (positive) values indicate losses (gains) due to climate change. For figure 1a of the paper, this data was aggregated for all countries. File 2: Data_rel-GDPpercapita-changes_withCC_per-country_all-SSP_4GCM_interpolated-for-REMIND-scenarios.csv Content: Data of relative change in absolute GDP/CAP levels (compared to the baseline path of the respective SSP in the SSP database) for each country, SSP and 4 GCMs (spanning a broad range of climate sensitivity). The RCP (and a zero-emissions scenario) are interpolated to the temperature pathways of the ten REMIND model scenarios used for climate change mitigation costs. Hereby the set of scenarios for climate impacts and climate change mitigation are consistent and can be combined to total costs of climate change (for a broad range of mitigation action). File 3: Data_rel-GDPpercapita-changes_withCC_per-country_SSP2_12GCM_interpolated-for-REMIND-scenarios.csv Content: Same as file 2, but only for the SSP2 (chosen default scenario for the study) and for all 12 GCMs. Data of relative change in absolute GDP/CAP levels (compared to the baseline path of the respective SSP in the SSP database) for each country, SSP-2 and 12 GCMs (spanning a broad range of climate sensitivity). The RCP (and a zero-emissions scenario) are interpolated to the temperature pathways of the ten REMIND model scenarios used for climate change mitigation costs. Hereby the set of scenarios for climate impacts and climate change mitigation are consistent and can be combined to total costs of climate change (for a broad range of mitigation action). In addition, reference GDP and population data (without climate change) for each country until 2100 was downloaded from the SSP database, release Version 1.0 (March 2013, https://tntcat.iiasa.ac.at/SspDb/, last accessed 15Nov 2019). Climate change mitigation cost data The scenario design and runs used in this paper have first been conducted in [1] and later also used in [2]. File 4: REMIND_scenario_results_economic_data.csv File 5: REMIND_scenarios_climate_data.csv Content: A broad range of climate change mitigation scenarios of the REMIND model. File 4 contains the economic data of e.g. GDP and macro-economic consumption for each of the countries and world regions, as well as GHG emissions from various economic sectors. File 5 contains the global climate-related data, e.g. forcing, concentration, temperature. In the scenario description “FFrunxxx” (column 2), the code “xxx” specifies the scenario as follows. See [1] for a detailed discussion of the scenarios. The first dimension specifies the climate policy regime (delayed action, baseline scenarios): 1xx: climate action from 2010 5xx: climate action from 2015 2xx climate action from 2020 (used in this study) 3xx climate action from 2030 4x1 weak policy baseline (before Paris agreement) The second dimension specifies the technology portfolio and assumptions: x1x Full technology portfolio (used in this study) x2x noCCS: unavailability of CCS x3x lowEI: lower energy intensity, with final energy demand per economic output decreasing faster than historically observed x4x NucPO: phase out of investments into nuclear energy x5x Limited SW: penetration of solar and wind power limited x6x Limited Bio: reduced bioenergy potential p.a. (100 EJ compared to 300 EJ in all other cases) x6x noBECCS: unavailability of CCS in combination with bioenergy The third dimension specifies the climate change mitigation ambition level, i.e. the height of a global CO2 tax in 2020 (which increases with 5% p.a.). xx1 0$/tCO2 (baseline) xx2 10$/tCO2 xx3 30$/tCO2 xx4 50$/tCO2 xx5 100$/tCO2 xx6 200$/tCO2 xx7 500$/tCO2 xx8 40$/tCO2 xx9 20$/tCO2 xx0 5$/tCO2 For figure 1b of the paper, this data was aggregated for all countries and regions. Relative changes of GDP are calculated relative to the baseline (4x1 with zero carbon price). [1] Luderer, G., Pietzcker, R. C., Bertram, C., Kriegler, E., Meinshausen, M. and Edenhofer, O.: Economic mitigation challenges: how further delay closes the door for achieving climate targets, Environmental Research Letters, 8(3), 034033, doi:10.1088/1748-9326/8/3/034033, 2013a. [2] Rogelj, J., Luderer, G., Pietzcker, R. C., Kriegler, E., Schaeffer, M., Krey, V. and Riahi, K.: Energy system transformations for limiting end-of-century warming to below 1.5 °C, Nature Climate Change, 5(6), 519–527, doi:10.1038/nclimate2572, 2015.

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    ZENODO
    Dataset . 2019
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    ZENODO
    Dataset . 2019
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2019
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      ZENODO
      Dataset . 2019
      License: CC BY
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      Dataset . 2019
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  • Authors: Mooney, Meghan; Waechter, Katy;

    The National Renewable Energy Laboratory's (NREL) PV Rooftop Database for Puerto Rico (PVRDB-PR) is a lidar-derived, geospatially-resolved dataset of suitable roof surfaces and their PV technical potential for virtually all buildings in Puerto Rico. The dataset can be downloaded at the AWS S3 explorer page. The GitHub documentation page provides a description of the dataset with methods and assumptions. The Puerto Rico Solar-For-All dataset provides Census Tract level estimates of residential low-to-moderate income (LMI) PV rooftop technical potential as well as solar electric bill savings potential for LMI communities at the municipality level.

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    Authors: Eslamdoust, Jamshid;

    Plot design and harvesting Twelve sampling plots (16 m × 16 m) in three P. deltoides plantations were established based on systematic random design. To minimize edge effects, surrounding rows were not considered during sampling. The age of the stands was 18-20 years old. In each sampling plot, the DBH (diameter at breast height 1.3 m above the ground) of the individual trees was measured with a caliper in two perpendicular directions and the mean DBH determined. Tree height was measured by Haglöf-Vertex IV hypsometer. Based on the DBH and height measurements, 10 DBH classes from 15 to 42 cm (3 cm intervals) were established. The value of each DBH class represented the central value (i.e., class 15 included all DBH from 12.5 to 17.5 cm). In each DBH class, one representative tree was selected and harvested for a total of 10 P. deltoides trees. Measurements of bark percentagesThe stems of harvested trees were marked and cut into 2 m-segments. The mid-length diameter of each segment was measured outside the bark in two perpendicular directions with a caliper to determine the mean diameter. A 5 cm-thick disc was cut from the middle of each segment. A total of 123 discs were obtained and brought to the laboratory. All the discs were arranged into 2-cm wide diameter classes. The value of each disc class represents the central value (i.e., class 20 included all discs whose diameters ranged from 19.5 to 20.5 cm). Bark was separated from the wood using a peeler knife for each disc. Fresh bark and wood were weighted separately, oven-dried at 80 °C until constant weight, and the oven-dry weight measured. The bark percentage of each disc was considered as bark percentage of a 2 m-segment for fresh and dry weight. Finally, the bark percentage of the whole stem in each DBH class was calculated by adding the 2 m-segments. Bark biomass as an energy source has a high economic value. Bark content variations and production helps recognize the potential of this bioenergy source spatially before harvesting. The percentage of fresh and dry bark in Populus deltoides grown under a monoculture system was examined in the temperate region of northern Iran. Diameter at breast height (DBH) and total height data were analyzed based on an initial inventory. Ten sample trees were felled, separated into 2 m-segments, and weighted in the field. A 5-cm-thick disc from each segment was extracted for determining fresh and dry bark percentages. These were statistically significantly different in disc diameter classes and decreased with increasing disc diameters. Bark percentage of the disc classes ranged from 21.8 to 24.4% in small-sized diameters to 8.1‒9.3% in large-sized diameters. The differences between fresh and dry bark percentages depended on water content variations. Allometric power equations were fitted to data of fresh and dry bark percentages and disc diameters as well as DBH. The values of R2 ranged from 0.89 to 0.90. In addition, allometric power equations provided the best fits for relationships between total stem dry biomass, dry bark biomass, and DBH, R2 = 0.986 and 0.979 for the total stem dry biomass and stem dry bark biomass, respectively. The allometric models can be used to estimate bark percentage and bark production of P. deltoides in segments and for the whole stem for a wide range of segment diameters (8‒44 cm) and DBH (15‒45 cm).

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    ZENODO
    Dataset . 2022
    License: CC 0
    Data sources: ZENODO
    DRYAD
    Dataset . 2022
    License: CC 0
    Data sources: Datacite
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      ZENODO
      Dataset . 2022
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      Dataset . 2022
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  • Authors: HAGLUND STIGNOR, C.; MARTIN SANTANA, S.; LARSSON, O.;

    In this study, a completely new type of air-to-liquid heat exchanger, adapted for obtaining good heat transfer performance even at a laminar flow regime on the liquid side has been evaluated in a display cabinet application. The heat exchanger consists of parallel plates, with liquid in every second passage and air in the other passages. Tests were performed with a traditional open vertical display cabinet, first with a traditional finned-tube coil and thereafter with the new type of heat exchanger placed in the bottom of the display cabinet. The results showed that the same cooling capacity and mean temperature of the “food packages” could be obtained with around 6 K higher inlet temperature of the liquid, -7°C with the traditional coil and -1°C with the new type of heat exchanger, which can lead to considerable energy savings.

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  • Authors: FRANCIS, C.; DAVIES, G.; EVANS, J.; Et Al.;

    Refrigerated road transport (RRT) vehicles are large users of energy, and reportedly have relatively high leakage of hydrofluorocarbon refrigerant gases, both of which contribute to global warming. The experience obtained from widespread research in leak reduction in stationary refrigeration systems can be instructive in combatting leakage in RRT systems, which has received less focus to date. This paper will take an integrated approach to develop and describe a preliminary model for sustainable RRT systems. It will first review lessons learned about refrigerant leakage in stationary systems in an effort to identify problematic/leak prone components common to transport refrigeration systems. This will then be followed by a survey of recent studies conducted in modelling transport refrigeration systems to advance energy efficiency. Initial results from the model illustrate the need to improve the efficiency of the refrigeration system, together with preventative maintenance of the box structure and refrigeration system as a whole.

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  • The HEU MODERATE Building Stock Data provides information regarding the building stock for all EU27 member states at the national level (i.e., NUTS 0) considering 2020 as the reference year. Regarding the Service Sector, the data distinguishes the following subsectors: single-family houses, multifamily houses, and apartment blocks. Regarding the Service Sector, the data distinguishes the following subsectors: offices, trade, education, health, hotels and restaurants, and other non-residential buildings. Moreover, for each subsector, the data distinguishes the following construction periods: before 1945, 1945-1969, 1970-1979, 1980-1989, 1990-1999, 2000-2010, and 2011-2020. For each building stock subsector and construction period, the data provide information regarding total values at the national level for: - Number of buildings - Number of dwellings - Number of dwellings according to ownership (i.e., owner occupied, rented, social housing) - Number of dwellings according to occupation (i.e., occupied, vacant, secondary houses) - Total constructed area - Total heated area - Total cooled area - Total final energy consumption for space heating and domestic hot water - Total final energy consumption for space cooling Moreover, the following average values for single building characteristics are provided: - Number of floors - Volume-to-surface ratio - Vertical area - Ground area - Window surface - U-values for the different building elements (roof, walls, windows, and floors) - Useful energy demand (ued) differentiating between space heating, domestic hot water, and space cooling - Final energy consumption (fed) differentiating between space heating, domestic hot water, and space cooling Finally, the data provide information about the prevalence of: - Building materials and methodology for the different building elements (roof, walls, windows, and floors) - Different systems used for space heating, domestic hot water, and space cooling The data is provided as a `csv` file (long format with all details and data source) and as an excel file (wide format with separate sheets for each country). Data and a complete description of the available fields can be found at https://github.com/MODERATE-Project/building-stock-analysis/tree/main/T3.2-static-analysis The dataset was obtained by combining information from European and national resources and the review of scientific literature. Data gaps were subsequently filled via statistical modeling.

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  • Authors: JAVERSCHEK, O.; CRAIG, J.; XIAO, A.;

    This publication highlights important aspects for commercial refrigeration systems, which comprise parallel compression like for example part load conditions and the reverse operation between flash gas bypass and parallel compression. A case study offers and explains possible solutions on basis of a new system design. The system, which comprises novelties with respect to the design, is installed by BITZER at its St. Marys site in Australia. The potential for an improved energy efficiency with parallel compression is shown for a state-of-the-art transcritical CO2 booster system with flash gas bypass, which is installed by BITZER at its Rottenburg site for practical training seminars since autumn 2010.

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    Authors: Gao, Guang; Beardall, John; Jin, Peng; Gao, Lin; +2 Authors

    The atmosphere concentration of CO2 is steadily increasing and causing climate change. To achieve the Paris 1.5 or 2 oC target, negative emissions technologies must be deployed in addition to reducing carbon emissions. The ocean is a large carbon sink but the potential of marine primary producers to contribute to carbon neutrality remains unclear. Here we review the alterations to carbon capture and sequestration of marine primary producers (including traditional ‘blue carbon’ plants, microalgae, and macroalgae) in the Anthropocene, and, for the first time, assess and compare the potential of various marine primary producers to carbon neutrality and climate change mitigation via biogeoengineering approaches. The contributions of marine primary producers to carbon sequestration have been decreasing in the Anthropocene due to the decrease in biomass driven by direct anthropogenic activities and climate change. The potential of blue carbon plants (mangroves, saltmarshes, and seagrasses) is limited by the available areas for their revegetation. Microalgae appear to have a large potential due to their ubiquity but how to enhance their carbon sequestration efficiency is very complex and uncertain. On the other hand, macroalgae can play an essential role in mitigating climate change through extensive offshore cultivation due to higher carbon sequestration capacity and substantial available areas. This approach seems both technically and economically feasible due to the development of offshore aquaculture and a well-established market for macroalgal products. Synthesis and applications: This paper provides new insights and suggests promising directions for utilizing marine primary producers to achieve the Paris temperature target. We propose that macroalgae cultivation can play an essential role in attaining carbon neutrality and climate change mitigation, although its ecological impacts need to be assessed further. To calculate the parameters presented in Table 1, the relevant keywords "mangroves, salt marshes, macroalgae, microalgae, global area, net primary productivity, CO2 sequestration" were searched through the ISI Web of Science and Google Scholar in July 2021. Recent data published after 2010 were collected and used since area and productivity of plants change with decade. For data with limited availability, such as net primary productivity (NPP) of seagrasses and global area and NPP of wild macroalgae, data collection was extended back to 1980. Total NPP and CO2 sequestration for mangroves, salt marshes, seagrasses and wild macroalgae were obtained by the multiplication of area and NPP/CO2 sequestration density and subjected to error propagation analysis. Data were expressed as means ± standard error.

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    ZENODO
    Dataset . 2022
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    Data sources: ZENODO
    DRYAD
    Dataset . 2022
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    Data sources: Datacite
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      ZENODO
      Dataset . 2022
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      DRYAD
      Dataset . 2022
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      Data sources: Datacite
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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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      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: 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/

    This climate change impact data (future scenarios on temperature-induced GDP losses) and climate change mitigation cost data (REMIND model scenarios) is published under doi: 10.5281/zenodo.3541809 and used in this paper: Ueckerdt F, Frieler K, Lange S, Wenz L, Luderer G, Levermann A (2018) The economically optimal warming limit of the planet. Earth System Dynamics. https://doi.org/10.5194/esd-10-741-2019 Below the individual file contents are explained. For further questions feel free to write to Falko Ueckerdt (ueckerdt@pik-potsdam.de). Climate change impact data File 1: Data_rel-GDPpercapita-changes_withCC_per-country_all-RCP_all-SSP_4GCM.csv Content: Data of relative change in absolute GDP/CAP levels (compared to the baseline path of the respective SSP in the SSP database) for each country, RCP (and a zero-emissions scenario), SSP and 4 GCMs (spanning a broad range of climate sensitivity). Negative (positive) values indicate losses (gains) due to climate change. For figure 1a of the paper, this data was aggregated for all countries. File 2: Data_rel-GDPpercapita-changes_withCC_per-country_all-SSP_4GCM_interpolated-for-REMIND-scenarios.csv Content: Data of relative change in absolute GDP/CAP levels (compared to the baseline path of the respective SSP in the SSP database) for each country, SSP and 4 GCMs (spanning a broad range of climate sensitivity). The RCP (and a zero-emissions scenario) are interpolated to the temperature pathways of the ten REMIND model scenarios used for climate change mitigation costs. Hereby the set of scenarios for climate impacts and climate change mitigation are consistent and can be combined to total costs of climate change (for a broad range of mitigation action). File 3: Data_rel-GDPpercapita-changes_withCC_per-country_SSP2_12GCM_interpolated-for-REMIND-scenarios.csv Content: Same as file 2, but only for the SSP2 (chosen default scenario for the study) and for all 12 GCMs. Data of relative change in absolute GDP/CAP levels (compared to the baseline path of the respective SSP in the SSP database) for each country, SSP-2 and 12 GCMs (spanning a broad range of climate sensitivity). The RCP (and a zero-emissions scenario) are interpolated to the temperature pathways of the ten REMIND model scenarios used for climate change mitigation costs. Hereby the set of scenarios for climate impacts and climate change mitigation are consistent and can be combined to total costs of climate change (for a broad range of mitigation action). In addition, reference GDP and population data (without climate change) for each country until 2100 was downloaded from the SSP database, release Version 1.0 (March 2013, https://tntcat.iiasa.ac.at/SspDb/, last accessed 15Nov 2019). Climate change mitigation cost data The scenario design and runs used in this paper have first been conducted in [1] and later also used in [2]. File 4: REMIND_scenario_results_economic_data.csv File 5: REMIND_scenarios_climate_data.csv Content: A broad range of climate change mitigation scenarios of the REMIND model. File 4 contains the economic data of e.g. GDP and macro-economic consumption for each of the countries and world regions, as well as GHG emissions from various economic sectors. File 5 contains the global climate-related data, e.g. forcing, concentration, temperature. In the scenario description “FFrunxxx” (column 2), the code “xxx” specifies the scenario as follows. See [1] for a detailed discussion of the scenarios. The first dimension specifies the climate policy regime (delayed action, baseline scenarios): 1xx: climate action from 2010 5xx: climate action from 2015 2xx climate action from 2020 (used in this study) 3xx climate action from 2030 4x1 weak policy baseline (before Paris agreement) The second dimension specifies the technology portfolio and assumptions: x1x Full technology portfolio (used in this study) x2x noCCS: unavailability of CCS x3x lowEI: lower energy intensity, with final energy demand per economic output decreasing faster than historically observed x4x NucPO: phase out of investments into nuclear energy x5x Limited SW: penetration of solar and wind power limited x6x Limited Bio: reduced bioenergy potential p.a. (100 EJ compared to 300 EJ in all other cases) x6x noBECCS: unavailability of CCS in combination with bioenergy The third dimension specifies the climate change mitigation ambition level, i.e. the height of a global CO2 tax in 2020 (which increases with 5% p.a.). xx1 0$/tCO2 (baseline) xx2 10$/tCO2 xx3 30$/tCO2 xx4 50$/tCO2 xx5 100$/tCO2 xx6 200$/tCO2 xx7 500$/tCO2 xx8 40$/tCO2 xx9 20$/tCO2 xx0 5$/tCO2 For figure 1b of the paper, this data was aggregated for all countries and regions. Relative changes of GDP are calculated relative to the baseline (4x1 with zero carbon price). [1] Luderer, G., Pietzcker, R. C., Bertram, C., Kriegler, E., Meinshausen, M. and Edenhofer, O.: Economic mitigation challenges: how further delay closes the door for achieving climate targets, Environmental Research Letters, 8(3), 034033, doi:10.1088/1748-9326/8/3/034033, 2013a. [2] Rogelj, J., Luderer, G., Pietzcker, R. C., Kriegler, E., Schaeffer, M., Krey, V. and Riahi, K.: Energy system transformations for limiting end-of-century warming to below 1.5 °C, Nature Climate Change, 5(6), 519–527, doi:10.1038/nclimate2572, 2015.

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    ZENODO
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2019
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2019
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2019
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2019
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  • Authors: Mooney, Meghan; Waechter, Katy;

    The National Renewable Energy Laboratory's (NREL) PV Rooftop Database for Puerto Rico (PVRDB-PR) is a lidar-derived, geospatially-resolved dataset of suitable roof surfaces and their PV technical potential for virtually all buildings in Puerto Rico. The dataset can be downloaded at the AWS S3 explorer page. The GitHub documentation page provides a description of the dataset with methods and assumptions. The Puerto Rico Solar-For-All dataset provides Census Tract level estimates of residential low-to-moderate income (LMI) PV rooftop technical potential as well as solar electric bill savings potential for LMI communities at the municipality level.

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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: Eslamdoust, Jamshid;

    Plot design and harvesting Twelve sampling plots (16 m × 16 m) in three P. deltoides plantations were established based on systematic random design. To minimize edge effects, surrounding rows were not considered during sampling. The age of the stands was 18-20 years old. In each sampling plot, the DBH (diameter at breast height 1.3 m above the ground) of the individual trees was measured with a caliper in two perpendicular directions and the mean DBH determined. Tree height was measured by Haglöf-Vertex IV hypsometer. Based on the DBH and height measurements, 10 DBH classes from 15 to 42 cm (3 cm intervals) were established. The value of each DBH class represented the central value (i.e., class 15 included all DBH from 12.5 to 17.5 cm). In each DBH class, one representative tree was selected and harvested for a total of 10 P. deltoides trees. Measurements of bark percentagesThe stems of harvested trees were marked and cut into 2 m-segments. The mid-length diameter of each segment was measured outside the bark in two perpendicular directions with a caliper to determine the mean diameter. A 5 cm-thick disc was cut from the middle of each segment. A total of 123 discs were obtained and brought to the laboratory. All the discs were arranged into 2-cm wide diameter classes. The value of each disc class represents the central value (i.e., class 20 included all discs whose diameters ranged from 19.5 to 20.5 cm). Bark was separated from the wood using a peeler knife for each disc. Fresh bark and wood were weighted separately, oven-dried at 80 °C until constant weight, and the oven-dry weight measured. The bark percentage of each disc was considered as bark percentage of a 2 m-segment for fresh and dry weight. Finally, the bark percentage of the whole stem in each DBH class was calculated by adding the 2 m-segments. Bark biomass as an energy source has a high economic value. Bark content variations and production helps recognize the potential of this bioenergy source spatially before harvesting. The percentage of fresh and dry bark in Populus deltoides grown under a monoculture system was examined in the temperate region of northern Iran. Diameter at breast height (DBH) and total height data were analyzed based on an initial inventory. Ten sample trees were felled, separated into 2 m-segments, and weighted in the field. A 5-cm-thick disc from each segment was extracted for determining fresh and dry bark percentages. These were statistically significantly different in disc diameter classes and decreased with increasing disc diameters. Bark percentage of the disc classes ranged from 21.8 to 24.4% in small-sized diameters to 8.1‒9.3% in large-sized diameters. The differences between fresh and dry bark percentages depended on water content variations. Allometric power equations were fitted to data of fresh and dry bark percentages and disc diameters as well as DBH. The values of R2 ranged from 0.89 to 0.90. In addition, allometric power equations provided the best fits for relationships between total stem dry biomass, dry bark biomass, and DBH, R2 = 0.986 and 0.979 for the total stem dry biomass and stem dry bark biomass, respectively. The allometric models can be used to estimate bark percentage and bark production of P. deltoides in segments and for the whole stem for a wide range of segment diameters (8‒44 cm) and DBH (15‒45 cm).

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    ZENODO
    Dataset . 2022
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    DRYAD
    Dataset . 2022
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      ZENODO
      Dataset . 2022
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  • Authors: HAGLUND STIGNOR, C.; MARTIN SANTANA, S.; LARSSON, O.;

    In this study, a completely new type of air-to-liquid heat exchanger, adapted for obtaining good heat transfer performance even at a laminar flow regime on the liquid side has been evaluated in a display cabinet application. The heat exchanger consists of parallel plates, with liquid in every second passage and air in the other passages. Tests were performed with a traditional open vertical display cabinet, first with a traditional finned-tube coil and thereafter with the new type of heat exchanger placed in the bottom of the display cabinet. The results showed that the same cooling capacity and mean temperature of the “food packages” could be obtained with around 6 K higher inlet temperature of the liquid, -7°C with the traditional coil and -1°C with the new type of heat exchanger, which can lead to considerable energy savings.

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  • Authors: FRANCIS, C.; DAVIES, G.; EVANS, J.; Et Al.;

    Refrigerated road transport (RRT) vehicles are large users of energy, and reportedly have relatively high leakage of hydrofluorocarbon refrigerant gases, both of which contribute to global warming. The experience obtained from widespread research in leak reduction in stationary refrigeration systems can be instructive in combatting leakage in RRT systems, which has received less focus to date. This paper will take an integrated approach to develop and describe a preliminary model for sustainable RRT systems. It will first review lessons learned about refrigerant leakage in stationary systems in an effort to identify problematic/leak prone components common to transport refrigeration systems. This will then be followed by a survey of recent studies conducted in modelling transport refrigeration systems to advance energy efficiency. Initial results from the model illustrate the need to improve the efficiency of the refrigeration system, together with preventative maintenance of the box structure and refrigeration system as a whole.

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  • The HEU MODERATE Building Stock Data provides information regarding the building stock for all EU27 member states at the national level (i.e., NUTS 0) considering 2020 as the reference year. Regarding the Service Sector, the data distinguishes the following subsectors: single-family houses, multifamily houses, and apartment blocks. Regarding the Service Sector, the data distinguishes the following subsectors: offices, trade, education, health, hotels and restaurants, and other non-residential buildings. Moreover, for each subsector, the data distinguishes the following construction periods: before 1945, 1945-1969, 1970-1979, 1980-1989, 1990-1999, 2000-2010, and 2011-2020. For each building stock subsector and construction period, the data provide information regarding total values at the national level for: - Number of buildings - Number of dwellings - Number of dwellings according to ownership (i.e., owner occupied, rented, social housing) - Number of dwellings according to occupation (i.e., occupied, vacant, secondary houses) - Total constructed area - Total heated area - Total cooled area - Total final energy consumption for space heating and domestic hot water - Total final energy consumption for space cooling Moreover, the following average values for single building characteristics are provided: - Number of floors - Volume-to-surface ratio - Vertical area - Ground area - Window surface - U-values for the different building elements (roof, walls, windows, and floors) - Useful energy demand (ued) differentiating between space heating, domestic hot water, and space cooling - Final energy consumption (fed) differentiating between space heating, domestic hot water, and space cooling Finally, the data provide information about the prevalence of: - Building materials and methodology for the different building elements (roof, walls, windows, and floors) - Different systems used for space heating, domestic hot water, and space cooling The data is provided as a `csv` file (long format with all details and data source) and as an excel file (wide format with separate sheets for each country). Data and a complete description of the available fields can be found at https://github.com/MODERATE-Project/building-stock-analysis/tree/main/T3.2-static-analysis The dataset was obtained by combining information from European and national resources and the review of scientific literature. Data gaps were subsequently filled via statistical modeling.

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  • Authors: JAVERSCHEK, O.; CRAIG, J.; XIAO, A.;

    This publication highlights important aspects for commercial refrigeration systems, which comprise parallel compression like for example part load conditions and the reverse operation between flash gas bypass and parallel compression. A case study offers and explains possible solutions on basis of a new system design. The system, which comprises novelties with respect to the design, is installed by BITZER at its St. Marys site in Australia. The potential for an improved energy efficiency with parallel compression is shown for a state-of-the-art transcritical CO2 booster system with flash gas bypass, which is installed by BITZER at its Rottenburg site for practical training seminars since autumn 2010.

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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: Gao, Guang; Beardall, John; Jin, Peng; Gao, Lin; +2 Authors

    The atmosphere concentration of CO2 is steadily increasing and causing climate change. To achieve the Paris 1.5 or 2 oC target, negative emissions technologies must be deployed in addition to reducing carbon emissions. The ocean is a large carbon sink but the potential of marine primary producers to contribute to carbon neutrality remains unclear. Here we review the alterations to carbon capture and sequestration of marine primary producers (including traditional ‘blue carbon’ plants, microalgae, and macroalgae) in the Anthropocene, and, for the first time, assess and compare the potential of various marine primary producers to carbon neutrality and climate change mitigation via biogeoengineering approaches. The contributions of marine primary producers to carbon sequestration have been decreasing in the Anthropocene due to the decrease in biomass driven by direct anthropogenic activities and climate change. The potential of blue carbon plants (mangroves, saltmarshes, and seagrasses) is limited by the available areas for their revegetation. Microalgae appear to have a large potential due to their ubiquity but how to enhance their carbon sequestration efficiency is very complex and uncertain. On the other hand, macroalgae can play an essential role in mitigating climate change through extensive offshore cultivation due to higher carbon sequestration capacity and substantial available areas. This approach seems both technically and economically feasible due to the development of offshore aquaculture and a well-established market for macroalgal products. Synthesis and applications: This paper provides new insights and suggests promising directions for utilizing marine primary producers to achieve the Paris temperature target. We propose that macroalgae cultivation can play an essential role in attaining carbon neutrality and climate change mitigation, although its ecological impacts need to be assessed further. To calculate the parameters presented in Table 1, the relevant keywords "mangroves, salt marshes, macroalgae, microalgae, global area, net primary productivity, CO2 sequestration" were searched through the ISI Web of Science and Google Scholar in July 2021. Recent data published after 2010 were collected and used since area and productivity of plants change with decade. For data with limited availability, such as net primary productivity (NPP) of seagrasses and global area and NPP of wild macroalgae, data collection was extended back to 1980. Total NPP and CO2 sequestration for mangroves, salt marshes, seagrasses and wild macroalgae were obtained by the multiplication of area and NPP/CO2 sequestration density and subjected to error propagation analysis. Data were expressed as means ± standard error.

    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 . 2022
    License: CC 0
    Data sources: ZENODO
    DRYAD
    Dataset . 2022
    License: CC 0
    Data sources: Datacite
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      ZENODO
      Dataset . 2022
      License: CC 0
      Data sources: ZENODO
      DRYAD
      Dataset . 2022
      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/
    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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      Dataset . 2023
      Data sources: Datacite
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      Swedish National Data Service
      Dataset . 2023
      Data sources: Datacite
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