EWED data files

Data cover activities at 9,961 individual power plants (>1MW, grid connected) across the United States, including monthly 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. We retrieved electricity generation, greenhouse emission, water consumption, and water withdrawal data for each plant from heterogeneous data sources, including web services and files. We filled remaining data gaps using a coefficient-based approach, and we suggest that users refer to the Related Resources below for more information on methods used to produce these datasets. The data may be useful 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.本数据集涵盖美国境内9961座并网（grid-connected）、单机容量大于1兆瓦（>1MW）的独立电厂的相关运行数据，时间跨度为2003年至2020年，包含月度发电量、温室气体排放量、取水量与耗水量，同时包含直至2050年的预测数据。本数据集的原始信息取自公开数据源，并经过标准化处理，以提供可根据用户多样化需求进行聚合的电厂级粒度数据。研究团队从包含网页服务与文件在内的多源异构数据源中，提取了各电厂的发电量、温室气体排放、耗水量与取水量数据。针对剩余的数据缺口，我们采用基于系数的方法进行填补，并建议用户参阅下文的相关资源，以了解生成本数据集所采用的具体方法细节。本数据集可供研究人员在电厂粒度下，结合排放与用水场景分析发电量，适用于数据分析与机器学习等研究场景。此外，根据不同的分析需求，这些数据可被聚合至不同空间尺度，包括流域、县域、州级乃至国家级层面。除此之外，决策者可在考量排放与用水约束的前提下，利用本数据集开展未来能源与资源配置相关工作。