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本文引用的文献

1
Water Use in the United States Energy System: A National Assessment and Unit Process Inventory of Water Consumption and Withdrawals.美国能源系统中的用水量:全国用水量和取水量评估及单元过程清单。
Environ Sci Technol. 2018 Jun 5;52(11):6695-6703. doi: 10.1021/acs.est.8b00139. Epub 2018 May 16.

美国电力-水-气候关系的历史和预测数据集。

Historical and projected datasets of the United States electricity-water-climate nexus.

作者信息

Fulton Julian, Jin Ying

机构信息

Department of Environmental Studies, California State University Sacramento, USA.

Department of Computer Science, California State University Sacramento, USA.

出版信息

Data Brief. 2021 Sep 20;38:107399. doi: 10.1016/j.dib.2021.107399. eCollection 2021 Oct.

DOI:10.1016/j.dib.2021.107399
PMID:34611537
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8477143/
Abstract

This article describes datasets that were produced in connection with the research article: "Visualizing the United States electricity-water-climate nexus" published in (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.

摘要

本文描述了与研究论文《可视化美国电力 - 水 - 气候关系》(发表于https://doi.org/10.1016/j.envsoft.2021.105128)相关生成的数据集。数据涵盖美国9961个独立发电厂,包括2003年至2020年期间的月度发电量、温室气体排放、取水量和用水量,以及到2050年的预测数据。数据从公开可用来源获取,并经过处理以提供可根据各种用户需求进行汇总的电厂级信息。通过“EIA860”过滤器从美国环境保护局设施注册服务(FRS)网络服务中检索电厂信息。对于这些电厂,我们从包括网络服务和文件在内的异构数据源中检索每个电厂的发电量、温室气体排放、用水量和取水量,进行清理和处理,然后保存在我们的数据库表中。我们使用基于系数的方法填补了其余的数据空白。本文描述了以CSV文件格式生成历史和预测数据集的元数据及方法。这些数据集有助于研究人员在电厂粒度层面,结合排放和用水情况查看发电量,例如用于数据分析和机器学习。这些数据还可根据不同分析需求汇总到不同空间尺度,如流域、县、州和国家层面。此外,决策者可以在考虑排放和用水限制的情况下,利用这些数据进行未来的能源和资源分配。