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Nearly three billion people in low- and middle-income countries (LMICs) rely on polluting fuels, resulting in millions of avoidable deaths annually. Polluting fuels also emit short-lived climate forcers and greenhouse gases (GHGs). Liquefied petroleum gas (LPG) and grid-based electricity are scalable alternatives to polluting fuels but have raised climate and health concerns. Here, we compare emissions and climate impacts of a business-as-usual household cooking fuel trajectory to four large-scale transitions to gas and/or grid electricity in 77 LMICs. We account for upstream and end-use emissions from gas and electric cooking, assuming electrical grids evolve according to the 2022 World Energy Outlook’s “Stated Policies” Scenario. We input the emissions into a reduced-complexity climate model to estimate radiative forcing and temperature changes associated with each scenario. We find full transitions to LPG and/or electricity decrease emissions from both well-mixed GHG and short-lived climate forcers, resulting in a roughly 5 millikelvin global temperature reduction by 2040. Transitions to LPG and/or electricity also reduce annual emissions of PM2.5 by over 6 Mt (99%) by 2040, which would substantially lower health risks from Household Air Pollution. Primary input data was collected from the following sources: Baseline household fuel choices - WHO household energy database (https://www.nature.com/articles/s41467-021-26036-x) End-use emissions - US EPA lifecycle assessment of household fuels (https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=339679&Lab=NRMRL&simplesearch=0&showcriteria=2&sortby=pubDate&timstype=Published+Report&datebeginpublishedpresented) Upstream emissions - Argonne National Labs GREET Model (https://greet.es.anl.gov/index.php) Current and future population estimates - UNECA (http://data.un.org/Explorer.aspx?d=EDATA) Input data was processed by defining household fuel choice scenarios, estimating national household fuel consumption based on these scenarios, and applying fuel-specific emission factors to create country-specific emission pathways. These emission pathways were input into the FaIR model (https://zenodo.org/record/5513022#.Yt_jfHbMLb0) which generated additional data for each scenario including time series of pollution concentrations, radiative forcing, and temperature changes. All data is provided in CSV format. Nothing proprietary is required. 

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.MOHC.UKESM1-0-LL.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The UKESM1.0-N96ORCA1 climate model, released in 2018, includes the following components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N96; 192 x 144 longitude/latitude; 85 levels; top level 85 km), atmosChem: UKCA-StratTrop, land: JULES-ES-1.0, ocean: NEMO-HadGEM3-GO6.0 (eORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 360 x 330 longitude/latitude; 75 levels; top grid cell 0-1 m), ocnBgchem: MEDUSA2, seaIce: CICE-HadGEM3-GSI8 (eORCA1 tripolar primarily 1 deg; 360 x 330 longitude/latitude). The model was run by the Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, EX1 3PB, UK (MOHC) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.

The datasets present collected data through resident surveys on the perceptions on tourism development and the state of cultural heritage, as part of the Horizon 2020 funded project SmartCulTour (www.smartcultour.eu). The data is collected on individual respondent level for Local Administrative Units (LAUs) for the following municipalities/cities: Spain: Huesca, Graus, Benasque, Barbastro, Ainsa, Jaca, Sariñena the Netherlands: Rotterdam, Dordrecht, Molenlanden, Ridderkerk, Zwijndrecht, Barendrecht, Delft Belgium: Dendermonde, Puurs-Sint-Amands, Bornem, Berlare, Aalst, Denderleeuw, Willebroek Croatia: Split, Trogir, Kaštela, Solin, Sinj, Dugopolje, Klis Finland: Utsjoki Italy: Vicenza, Caldogno, Grumolo, Pojana Maggiore, Lonigo, Montagnana The data is presented as cross-sectional data and available for the following year: 2020. Please consult the metadata on each dataset for an overview of collected indicators and units of measurement.

Twenty soil cores were collected from a field site in Lincolnshire in March 2011, three weeks after planting and Nitrogen fertiliser addition. Soil cores of 150-180 millimetre (mm) depth, containing approximately 1.6 kilogram soil (dry weight) were extracted in Polyvinyl chloride (PVC) pipes (height 215 mm depth 102 mm) and stored at 4 degrees centigrade for 30 days. A four-treatment factorial experiment was designed using soils un-amended or amended with biochar and un-wetted or wetted with deionised water (5 replicates per treatment). Soil in all the cores was mixed to 7 centimetre (cm) depth. To half of the cores, biochar (less than 2 mm) was mixed into the soil at a rate of 3 percent soil dry weight (approximately 22 tons per hectare (t ha-1)). After allowing for any potential Carbon dioxide (CO2) flush from newly-mixed soil to equilibrate for seven days, the cores were placed at 16 degrees centigrade in the dark. Un-wetted soil cores were maintained at 23 percent Gravimetric moisture content (GMC), whilst the GMC of 'wetted' soil cores was increased to 28 percent GMC at the time zero (t0) of four wetting events on day 17, 46, 67 and 116. These water addition rates were based on mean and maximum monthly soil GMC measured in the field between 2009-2010. Data from an investigation of the effects of biochar application to soil on greenhouse gas emissions using soil from a bioenergy crop (Miscanthus X. giganteus). Data include physical (bulk density) and chemical analyses of the soil (total carbon (C) and nitrogen (N), extractable ammonium and nitrate), and greenhouse gas (GHG) emissions (carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O)) during incubations. Data were collected during two incubation experiments investigating the effects of temperature, soil moisture and soil aeration on biochar induced suppression of GHG emissions. Biochar is a carbon rich substances which is being advocated as a climate mitigation tool to increase carbon sequestration and reduce nitrous oxide emissions.

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.AWI.AWI-CM-1-1-MR.ssp370' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The AWI-CM 1.1 MR climate model, released in 2018, includes the following components: atmos: ECHAM6.3.04p1 (T127L95 native atmosphere T127 gaussian grid; 384 x 192 longitude/latitude; 95 levels; top level 80 km), land: JSBACH 3.20, ocean: FESOM 1.4 (unstructured grid in the horizontal with 830305 wet nodes; 46 levels; top grid cell 0-5 m), seaIce: FESOM 1.4. The model was run by the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany (AWI) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 km.

Projections of Sea Level Rise (SLR) under RCP 4.5 and RCP 8.5 (AR5) along the Mekong Coast, Published1 by the Ministry of Natural Resources and Environment (MONRE), Hanoi, Vietnam. Projections of Mekong River discharge during the dry season under RCP 4.5 and RCP 8.5 at Kratie, Cambodia. The data contains the cumulative, minimum and maximum dry season (January-1st to April-30th) discharge from 5 different climate models. PCR-GLOBWB2 was run at 5 arc-min spatial resolution and forced with the data based on output from five ISIMIP CMIP5 global climate models (HadGEM2-ES, GFDL-ESM2, IPSL-CM5A-LR, MIROC-ESM-CHEM, NorESM1-M). 1. Ministry of Natural Resources and Environment (MONRE), V. Climate change and sea level rise scenarios for Vietnam, Ministry of Natural Resources and Environment. (2016). 2. Sutanudjaja, E. H. et al. PCR-GLOBWB 2: a 5 arcmin global hydrological and water resources model. Geosci. Model Dev. 11, 2429–2453 (2018). {"references": ["Sutanudjaja et al. (2018)", "Ministry of Natural Resources and Environment (2016)"]}

This dataset underpins the study "Synergies and conflicts of energy development and water security in Africa". The study provides insights into energy supply and demand, power generation, investments and total system costs, water consumption and withdrawal as well as carbon dioxide emissions for the African continent. We developed a model to evaluate energy supply and water requirements to cover the energy needs of the African continent during the period 2015-2065. The model was developed using the open-source modeling system for long-term energy planning OSeMOSYS. The objective function is to minimise total energy system costs, rather than, for example, co-optimise the energy and water sectors. Other energy resources were also included in the model except for adding the water analysis, and the dataset was updated based on the latest available information. The OSeMOSYS model developed to conduct the study “Energy projections for African countries”, itself extended from the Electricity Model Base for Africa (TEMBA), was further extended, included exports for all fuels, water loss due to evaporation in hydropower plants and more scenarios examined. Furthermore, the latest available data on the energy system of Africa was also updated. The TEMBA model produces aggregate energy, and detailed power system results in each country in the African continent. The power sector results are also reported with power pool aggregation. The OSeMOSYS model and input data used to produce these results can be found at KTH-dESA/jrc_temba: TEMBA 2.1 (Version v2.1) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.4889373 (Authors: Ioannis Pappis, Vignesh Sridharan, Will Usher, & Mark Howells. (2021). The initial study was funded by the Joint Research Centre of the European Commission (contract number C936531 - JRC/PTT/2018/C.7/0038/NC).

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.MOHC.HadGEM3-GC31-MM.amip' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The HadGEM3-GC3.1-N216ORCA025 climate model, released in 2016, includes the following components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N216; 432 x 324 longitude/latitude; 85 levels; top level 85 km), land: JULES-HadGEM3-GL7.1, ocean: NEMO-HadGEM3-GO6.0 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: CICE-HadGEM3-GSI8 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude). The model was run by the Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, EX1 3PB, UK (MOHC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 km.