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Title: Informing energy consumption uncertainty: an analysis of energy data revisions

Abstract

Quality energy consumption data are important for many types of analysis, and global data sets estimate trends of county level energy consumption, derived from country reported data and regional reports. We present a novel basis for informing uncertainty in energy data by quantifying the changes in reported energy consumption as countries update their previously reported data. We use 17 editions of the British Petroleum World Energy Statistics (2001-2017) to evaluate how reported energy consumption is revised over time in aggregate coal, oil, and natural gas consumption data. We find that 70% of non-zero data points are adjusted by an average of 1.3% of a country’s total fossil fuel use in the year after their first publication. Earlier data points are revised less often, but almost half of historical trends contain some revisions in later years. The size and rate of data revisions vary over countries and fuels: coal data points have larger, less frequent revisions while oil data points have smaller more frequent revisions, with natural gas in between. A K-means cluster analysis was performed to group together countries with similar revision patterns. These groups span income, economy classification, OECD membership, and regions. Standard country groupings, therefore, do not predictmore » the extent to which a country's energy data has undergone revisions in the past.« less

Authors:
ORCiD logo;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1497677
Report Number(s):
PNNL-SA-136517
Journal ID: ISSN 1748-9326
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Journal Name:
Environmental Research Letters
Additional Journal Information:
Journal Volume: 13; Journal Issue: 12; Journal ID: ISSN 1748-9326
Publisher:
IOP Publishing
Country of Publication:
United States
Language:
English

Citation Formats

Hoesly, Rachel M., and Smith, Steven J. Informing energy consumption uncertainty: an analysis of energy data revisions. United States: N. p., 2018. Web. doi:10.1088/1748-9326/aaebc3.
Hoesly, Rachel M., & Smith, Steven J. Informing energy consumption uncertainty: an analysis of energy data revisions. United States. doi:10.1088/1748-9326/aaebc3.
Hoesly, Rachel M., and Smith, Steven J. Sat . "Informing energy consumption uncertainty: an analysis of energy data revisions". United States. doi:10.1088/1748-9326/aaebc3.
@article{osti_1497677,
title = {Informing energy consumption uncertainty: an analysis of energy data revisions},
author = {Hoesly, Rachel M. and Smith, Steven J.},
abstractNote = {Quality energy consumption data are important for many types of analysis, and global data sets estimate trends of county level energy consumption, derived from country reported data and regional reports. We present a novel basis for informing uncertainty in energy data by quantifying the changes in reported energy consumption as countries update their previously reported data. We use 17 editions of the British Petroleum World Energy Statistics (2001-2017) to evaluate how reported energy consumption is revised over time in aggregate coal, oil, and natural gas consumption data. We find that 70% of non-zero data points are adjusted by an average of 1.3% of a country’s total fossil fuel use in the year after their first publication. Earlier data points are revised less often, but almost half of historical trends contain some revisions in later years. The size and rate of data revisions vary over countries and fuels: coal data points have larger, less frequent revisions while oil data points have smaller more frequent revisions, with natural gas in between. A K-means cluster analysis was performed to group together countries with similar revision patterns. These groups span income, economy classification, OECD membership, and regions. Standard country groupings, therefore, do not predict the extent to which a country's energy data has undergone revisions in the past.},
doi = {10.1088/1748-9326/aaebc3},
journal = {Environmental Research Letters},
issn = {1748-9326},
number = 12,
volume = 13,
place = {United States},
year = {2018},
month = {12}
}