Abstract
This article describes datasets that were produced in connection with the research article: “Visualizing the United States electricity-water-climate nexus” published in Environmental Modeling and Software (https://doi.org/10.1016/j.envsoft.2021.105128). Data cover 9,961 individual power plants across the United States, including monthly values for electricity generation, greenhouse gas emissions, water withdrawal, and water consumption between 2003 and 2020, as well as projections out to 2050. Data were retrieved from publicly available sources and processed for the purpose of providing plant-level information that can be aggregated according to various user needs. Power plant information was retrieved from the US EPA Facility Registry Service (FRS) web service through the filter of “EIA860.” For these plants, we retrieved electricity generation, greenhouse emission, water consumption, and water withdrawal of each plant from heterogeneous data sources, including web services and files, clean and process them, and save them in our database tables. We filled remaining data gaps using a coefficient-based approach. This data article describes metadata and methods for producing the historical and projected datasets in the format of CSV files. The datasets are beneficial for researchers to view electricity generation in the context of emissions and water usage at the granularity of power plants, such as for data analysis and machine learning. These data also can be aggregated to different spatial scales, such as watershed, county, state, and national level, according to different analytical needs. In addition, decision makers can use these data for future energy and resource allocations with the awareness of emission and water constraints.