This dataset contains data associated with Mongird et al. (under review). Files include output from the following three analyses found in the paper: (1) Projected power plant siting intersections with US Disadvantaged Communities (DACs), important farmland, and natural areas; (2) onshore wind and solar photovoltaic capacity factor availability under 27 different siting restriction cases, and (3) output from an analysis that determines how many DACs are projected to see both fossil fuel generation retirement and new renewable power plant development. Each of the files associated with these components are described below. For more detailed information please refer to Mongird et al. (under review), "High-resolution analysis of power plant land requirements for the evolving Western United States power grid indicates coordinated land use policies will be essential" Outputs included in this dataset are associated with two different scenarios. Summaries of each of the two scenarios included are provided below. For additional information, see Ou et al. 2023. Scenario Descriptions business-as-usual: This scenario does not include any long-term federal policies requiring decarbonization. It does include the US Inflation Reduction Act (IRA) incentives. It assumes that CCS technologies are available. high renewables: This scenario includes a clean electricity grid in the U.S. by 2035 and a net-zero economy by 2050. It does include US IRA incentives. It assumes that CCS technologies are available. Data Descriptions 1. Projected power plant siting intersections Description These files identify the intersection of projected power plant locations with three types of land: federall identified disadvantaged communities (DACs), important farmland, and land in close proximity to natural areas. Scenario Files: File Name File Description bau_dac_analysis_2050.csv Results from analysis identifying how many projected power plant sitings through 2050 under the busines-as-usual scenario intersect with federally identified US DACs by technology type and Western US state bau_env_analysis_2050.csv Results from analysis identifying how many projected power plant sitings through 2050 under the busines-as-usual scenario intersect with areas within 1 km, 5 km, and 10km of environmental areas by technology type and Western US state bau_farm_analysis_2050.csv Results from analysis identifying how many projected power plant sitings through 2050 under the busines-as-usual scenario intersect with important farmland by technology type and Western US state hr_dac_analysis_2050.csv Results from analysis identifying how many projected power plant sitings through 2050 under the high renewables scenario intersect with federally identified US DACs by technology type and Western US state hr_env_analysis_2050.csv Results from analysis identifying how many projected power plant sitings through 2050 under the high renewables scenario intersect with areas within 1 km, 5 km, and 10km of environmental areas by technology type and Western US state hr_farm_analysis_2050.csv Results from analysis identifying how many projected power plant sitings through 2050 under the high renewables scenario intersect with important farmland by technology type and Western US state Data Dictionary: Column Description Units state Name of US state N/A technology Power plant technology type inclusive of turbine type, presence of CCS, and cooling type (as applicable) N/A technology_simple Power plant technology type excluding turbine type, presence of CCS, and cooling type (as applicable) N/A layer_name Descriptive name of geospatial raster layer used for intersection analysis N/A layer Name of geospatial raster layer used for intersection analysis N/A total_plants Number of projected power plants of specified technology in specified state under given scenario # intersection Number of projected power plant intersections of specified technology in specified state with given layer under given scenario # fraction ratio of intersection and total_plants fraction Scenario Difference Analysis Files: difference_dac_analysis_2050.csv Results from analysis identifying how many more projected power plant sitings through 2050 under the high renewables scenario intersect with federally identified US DACs by technology type and Western US state compared to projected power plant sitings through 2050 under the business-as-usual scenario. Negative results indicate that the business-as-usual scenario had a greater number of intersections. difference_env_analysis_2050.csv Results from analysis identifying how many more projected power plant sitings through 2050 under the high renewables scenario intersect with areas within 1 km, 5 km, and 10km of environmental areas by technology type and Western US state compared to projected power plant sitings through 2050 under the business-as-usual scenario. Negative results indicate that the business-as-usual scenario had a greater number of intersections. difference_farm_analysis_2050.csv Results from analysis identifying how many more projected power plant sitings through 2050 under the high renewables scenario intersect with important farmland by technology type and Western US state compared to projected power plant sitings through 2050 under the business-as-usual scenario. Negative results indicate that the business-as-usual scenario had a greater number of intersections. Data Dictionary: Column Description Units state Name of US state N/A technology Power plant technology type N/A layer Name of geospatial raster layer used for intersection analysis N/A hr Number of projected power plant intersections with given layer under the high renewables scenario # bau Number of projected power plant intersections with given layer under the business-as-usual scenario # intersection Difference in projected power plant intersections between the high renewables scenario and the business-as-usual scenario # 2. Projected onshore wind and solar photovoltaic capacity factor availability under 27 siting restriction cases Description: This file contains results from an analysis on the capability of reaching high renewables scenario solar and wind generation in 2050 under 27 different siting restriction cases. Relevant File: File Name File Description capacity_factor_analysis_2050.csv Amount of solar PV or onshore wind generation projected to be available in a given state under a specified siting restriction case Data Dictionary: Column Description Units region_name Name of US state N/A technology Power plant technology type (either solar PV or Wind) N/A capacity_density_mw Assumed MW per square-km MW case Name of siting exclusion case N/A total_generation_mwh Projected total generation available given remaining available land after exclusions MWh target_generation_mwh Projected target annual generation in 2050 for technology type under high renewables scenario MWh gcam_trading_region Name of zonal representation of electricity trading regions as defined in the capacity expansion model N/A 3. US DACs that see both fossil fuel generation retirement and new renewable power plant development by 2050 Description: This data contains US census tract GEOIDs that see both new renewable sitings and the retirement of fossil generating resources. Relevant File: File Name File Description dac_fossil_retire_analysis_2050.csv List of US census tracts that see both fossil fuel generation retirement and new renewable generation siting by 2050 Data Dictionary: Column Description census_tract US census tract GEOID state_name Name of US state county_name Name of US county scenario scenario name Funding statement This research was supported by the Grid Operations, Decarbonization, Environmental and Energy Equity Platform (GODEEEP) Investment, under the Laboratory Directed Research and Development (LDRD) Program at Pacific Northwest National Laboratory (PNNL). PNNL is a multi-program national laboratory operated for the U.S. Department of Energy (DOE) by Battelle Memorial Institute under Contract No. DE-AC05-76RL01830. Changelog v1.1 The following updates were made following manuscript revision: "power_density_mw" variable name in `capacity_factor_analysis_2050.csv` file changed to "capacity_density_mw" More estimates are provided in `capacity_factor_analysis_2050.csv` reflecting additional capacity density and turbine hub height assumptions. Scenario naming adjusted to align with manuscript naming