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

IF 8.5 1区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

npj Climate and Atmospheric Science Pub Date : 2025-03-17 DOI:10.1038/s41612-025-00991-4

Hanwen Hu, Guannan Geng, Ruochong Xu, Yang Liu, Qinren Shi, Qingyang Xiao, Xiaodong Liu, Bo Zheng, Qiang Zhang, Kebin He

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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.

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来源期刊

npj Climate and Atmospheric Science Earth and Planetary Sciences-Atmospheric Science

CiteScore

8.80

自引率

3.30%

发文量

审稿时长

21 weeks

期刊介绍： npj Climate and Atmospheric Science is an open-access journal encompassing the relevant physical, chemical, and biological aspects of atmospheric and climate science. The journal places particular emphasis on regional studies that unveil new insights into specific localities, including examinations of local atmospheric composition, such as aerosols. The range of topics covered by the journal includes climate dynamics, climate variability, weather and climate prediction, climate change, ocean dynamics, weather extremes, air pollution, atmospheric chemistry (including aerosols), the hydrological cycle, and atmosphere–ocean and atmosphere–land interactions. The journal welcomes studies employing a diverse array of methods, including numerical and statistical modeling, the development and application of in situ observational techniques, remote sensing, and the development or evaluation of new reanalyses.