Scholarlink

<p>Accurate and timely CO<sub>2</sub> emission inventories are essential for tracking climate change mitigation progress. This study conducts near real-time CO<sub>2</sub> 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 CO<sub>2</sub> 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 CO<sub>2</sub> emissions due to notable differences between timely-updated and regular statistics.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年3月17日

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

摘要

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.