#### READ ME #### 1. ABOUT THE DATASET -------------------- Title: Dataset associated with "Global energy consumption of the mineral mining industry: exploring the historical perspective and future pathways to 2060" Creator: Emmanuel Aramendia [1], Paul E. Brockway [1], Peter G. Taylor [1], Jonathan Norman [1] Organisation: [1] Sustainability Research Institute, School of Earth and Environment, University of Leeds. Date: 21/09/2023 Description: This file provides information on the data contained in the online repository associated with the paper "Global energy consumption of the mineral mining industry: exploring the historical perspective and future pathways to 2060", published in Global Environmental Change. doi: 10.1016/j.gloenvcha.2023.102745. Cite as: Dataset associated with "Global energy consumption of the mineral mining industry: exploring the historical perspective and future pathways to 2060", 2023. Emmanuel Aramendia, Paul E. Brockway, Peter G. Taylor, Jonathan Norman. doi: 10.5518/1420. Related publication: Global energy consumption of the mineral mining industry: exploring the historical perspective and future pathways to 2060. Emmanuel Aramendia, Paul E. Brockway, Peter G. Taylor, Jonathan Norman. Global Environmental Change, 2023. doi: 10.1016/j.gloenvcha.2023.102745. File types and content: The files of this repository can be classified in terms of: * main scripts (R files starting with a number): relevant code to reproduce the analysis. These start with a number. * helper scripts: scripts used to load/clean the input data, probably not very useful to look into; * input data: the input data matches the input data provided in the SI (.xlsx or .ods file) of the main paper, but in the format that is read by the R code. Scripts used to produce figures are available upon reasonable request. 2. TERMS OF USE --------------- This dataset is licensed under a Creative Commons Attribution 4.0 International Licence: https://creativecommons.org/licenses/by/4.0/.] Note that the input data may however be subject to another license. See Section 4. 3. SCRIPTS IN THE DATASET ------------------------- ## Main scripts: * 1_calc_energy_mining.R: Calculates historical energy consumption of the mining industry. * 2_build_demand_model.R: Builds the linear models linking mineral demand and economic output. * 3_RoE_demand.R: Builds mineral demand projections for the rest of the economy. * 4_RES_demand.R: Builds mineral demand projections for renewable energy systems and other energy transition technologies. * 5_build_production.R: Builds primary production projections. * 6_build_energy.R: Builds final energy consumption projections. * 7_calc_energy_mc.R: Conducts the Monte Carlo simulation on the historical energy consumption of the mining industry. ## Helper scripts: * converting_gdp_func.R: Function to harmonise GDP data from the World Bank and from the Special Report on 1.5C scenarios. * load_iea_data.R: Code to load the IEA WEEB provided the user has these. Such data is only required to build the post-growth scenario in the "degrowth_scenarios.R" script. But the output of that script is saved in the post_growth_data.RData file, so that the IEA's WEEBs are not needed for the user. * degrowth_scenarios.R: Code to build the post-growth scenarios. All code commented out as the output of the script is saved in the post_growth_data.RData file. The reason is that the IEA's World Energy Extended Balances are needed to run this script. * sorting_sr_1_5_data.R: Code to extract data from the IPCC Special Report on 1.5C scenarios. According to the license of the input data (Huppmann et al. 2019), the input data may not be publicly available for download. 4. INPUT DATA FILES, DESCRIPTION AND ASSOCIATED REFERENCES ---------------------------------------------------------- ## MINERAL DEMAND PROJECTIONS FROM LITERATURE FILE File: comparison_demand_projections_v1.csv Description: Demand projections for several minerals from Watari 2020. Associated reference/required citation: Takuma Watari. Review of critical metal dynamics to 2050 for 48 elements. Resources, Conservation and Recycling, page 17, 2020. doi:10.1016/j.resconrec.2019.104669. ## ENERGY COSTS FILE File: Energy_costs_factors_08_07_2022_reviewed.csv Description: Energy requirements data used as input. These data match with data provided in SI. See SI for sources and explanations. ## EMPTY EXTRACTION DATA File: Empty_Global_Extraction_Data.csv Description: Structure of the extraction data used alongside sources provided. Data is proprietary and hence not provided here. Data may be available upon reasonable request. Data from the USGS (Kelly and Matos 2016) can be freely downloaded. Data for uranium available from Grancea and Hanly 2018. Data from Krausmann et al. 2018 proprietary. Associated references: T.D. Kelly and G.R. Matos. Historical statistics for mineral and material commodities in the United States (2016 version). Series 140. Technical report, U.S. Geological Survey, 2016. URL https://www.usgs.gov/centers/nmic/historical-statistics-mineral-and-material-commodities-united-states. Last accessed: 12/07/2022. Fridolin Krausmann, Christian Lauk, Willi Haas, and Dominik Wiedenhofer. From resource extraction to outflows of wastes and emissions: The socioeconomic metabolism of the global economy, 1900-2015. Global Environmental Change, 52:131–140, 2018. ISSN 0959-3780. doi:10.1016/j.gloenvcha.2018.07.003. Luminita Grancea and Adrienne Hanly. Uranium 2018: Resources, Production and Demand. Technical report, Organisation for Economic Co-Operation and Development, 2018. URL https://www.oecd-nea.org/jcms/pl_15080/ uranium-2018-resources-production-and-demand?details=true. Last accessed: 12/07/2022. ## MEDEAS DATA FILES File: medeas_data.RData Description: Corresponds to output data from the MEDEAS Integrated Assessment Model that we use to complement the data from Watari 2020 on the material requirements of the energy transition. Csv data available upon request. Property rights: Data propriety of the Group of Energy, Economics and System Dynamics at the University of Valladolid (Spain). Shared with permission. Associated reference/required citation: Iñigo Capellán-Pérez, Carlos de Castro, and Luis Javier Miguel González. Dynamic Energy Return on Energy Investment (EROI) and material requirements in scenarios of global transition to renewable energies. Energy Strategy Reviews, 26: 100399, 2019. ISSN 2211467X. doi:10.1016/j.esr.2019.100399. Iñigo Capellán-Pérez, Ignacio de Blas, Jaime Nieto, Carlos de Castro, Luis Javier Miguel, Óscar Carpintero, Margarita Mediavilla, Luis Fernando Lobejón, Noelia Ferreras-Alonso, Paula Rodrigo, Fernando Frechoso, and David Álvarez-Antelo. MEDEAS: A new modeling framework integrating global biophysical and socioeconomic constraints. Energy & Environmental Science, 13(3):986–1017, 2020. ISSN 1754-5692, 1754-5706. doi:10.1039/C9EE02627D. ## POST-GROWTH DATA FILES File: post_growth_data.RData Description: Output from the "degrowth_scenarios.R" script saved. The reason why this intermediate result is saved is that the IEA's World Energy Extended Balances are needed to run the "degrowth_scenarios.R" script. Users with such data can produce the "post_growth_data.RData" file themselves using by running the "degrowth_scenarios.R" script. ## SPECIAL REPORT ON 1.5C SCENARIOS Description: Some input data is required from the IPCC Special Report on 1.5 degree. These data are freely available for download, but may not be made available for download elsewhere. We only provide the code with which we process the input data. The data are available upon reasonable request. License: https://data.ene.iiasa.ac.at/iamc-1.5c-explorer/#/license Associated reference/required citation: Daniel Huppmann, Elmar Kriegler, Volker Krey, Keywan Riahi, Joeri Rogelj, Steven K. Rose, John Weyant, Nico Bauer, Christoph Bertram, Valentina Bosetti, Katherine Calvin, Jonathan Doelman, Laurent Drouet, Johannes Emmerling, Stefan Frank, Shinichiro Fujimori, David Gernaat, Arnulf Grubler, Celine Guivarch, Martin Haigh, Christian Holz, Gokul Iyer, Etsushi Kato, Kimon Keramidas, Alban Kitous, Florian Leblanc, Jing-Yu Liu, Konstantin Löffler, Gunnar Luderer, Adriana Marcucci, David McCollum, Silvana Mima, Alexander Popp, Ronald D. Sands, Fuminori Sano, Jessica Strefler, Junichi Tsutsui, Detlef Van Vuuren, Zoi Vrontisi, Marshall Wise, and Runsen Zhang. IAMC 1.5◦ C Scenario Explorer and Data hosted by IIASA. Integrated Assessment Modeling Consortium and International Institute for Applied Systems Analysis, 2019. URL https://data.ene.iiasa.ac.at/iamc-1.5c-explorer/#/login?redirect=%2Fworkspaces. Version 2.0. Last accessed: 12/07/2022. ## wb_gdp_constant_2010_US_dols.csv Description: GDP input data from the World Bank (constant 2010 US$; NY.GDP.MKTP.KD). Note that this version does not match anymore the publicly available version. License: CC-BY 4.0 Associated reference/required citation: https://data.worldbank.org/indicator/NY.GDP.MKTP.KD 5. FUNDING INFORMATION ---------------------------------- We acknowledge support for P.E.B. under EPSRC Fellowship award EP/R024251/1, and for E.A., funded by the School of Earth of Environment of the University of Leeds, UK, in support for P.E.B.’s fellowship award. The contributions of P.G.T. and J.N. were supported by the Centre for Research into Energy Demand Solutions funded by UK Research and Innovation (grant number EP/R035288/1).