Notable uncertainties in near real-time CO2 emission estimates in China

Accurate and timely CO2 emission inventories are essential for tracking climate change mitigation progress. This study conducts near real-time CO2 emission estimates for China using different timely-updated activity data sources such as annual bulletins and monthly statistics. Comparing the results with emissions estimated by regular statistics, we find that emission estimates relying solely on either monthly statistics or annual bulletins have uncertainties. Prioritizing annual bulletins where available and supplementing with monthly statistics for the most recent year can balance accuracy and timeliness, yielding a median error of 1.3% across different update intervals. However, near real-time estimates of relative changes in annual CO2 emissions bear large uncertainties regardless of the approach. For the six years investigated, near real-time estimates usually failed to capture the trends in annual emissions, indicating that those near real-time approaches are unreliable for estimating changes in CO2 emissions due to notable differences between timely-updated and regular statistics.

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Publication Details

Journal
npj Climate and Atmospheric Science
Published
2025-03-17
DOI
https://doi.org/10.1038/s41612-025-00991-4
Citations
2
Primary Topic
Air Quality and Health Impacts
Type
article
Field-Weighted Citation Impact
2.40

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Notable uncertainties in near real-time CO2 emission estimates in China

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Notable uncertainties in near real-time CO2 emission estimates in China

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article en
2 citations

Abstract

Accurate and timely CO2 emission inventories are essential for tracking climate change mitigation progress. This study conducts near real-time CO2 emission estimates for China using different timely-updated activity data sources such as annual bulletins and monthly statistics. Comparing the results with emissions estimated by regular statistics, we find that emission estimates relying solely on either monthly statistics or annual bulletins have uncertainties. Prioritizing annual bulletins where available and supplementing with monthly statistics for the most recent year can balance accuracy and timeliness, yielding a median error of 1.3% across different update intervals. However, near real-time estimates of relative changes in annual CO2 emissions bear large uncertainties regardless of the approach. For the six years investigated, near real-time estimates usually failed to capture the trends in annual emissions, indicating that those near real-time approaches are unreliable for estimating changes in CO2 emissions due to notable differences between timely-updated and regular statistics.

npj Climate and Atmospheric ScienceVol. 8(1)
Tsinghua–Berkeley Shenzhen Institute (CN), State Key Joint Laboratory of Environment Simulation and Pollution Control (CN), Tsinghua University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Climate action
Openalex Percentile: Top 14%
Air Quality and Health Impacts
2.40
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