CMIP6とSSP-RCPシナリオ組み合わせに基づく中国カーボンニュートラルデータセット
China Carbon Neutrality Dataset Based on CMIP6 and SSP-RCP Scenario Combination (原題)
Ge Rong, Zhang Mengyu, Zhiyao Xu, Xu Qian, He Honglin
🤖 gxceed AI 要約
日本語
本データセットは、CMIP6の10の地球システムモデルとSSP-RCPシナリオ（SSP126-585）を組み合わせ、中国および各省の1980-2060年の純生態系生産性（NEP）とCO2排出量を0.5°解像度で提供する。歴史期間と将来予測を統合し、カーボンニュートラル研究の基盤となる。
English
This dataset integrates CMIP6 Earth system models with SSP-RCP scenarios (SSP126-585) to provide annual NEP and CO2 emissions for China and provinces at 0.5° resolution from 1980-2060. It supports carbon neutrality research by combining historical and projected data.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
中国のカーボンニュートラル目標（2060年）の達成に向けた地域別の炭素吸収・排出データは、日本の企業が中国市場でのサプライチェーン排出量算定や気候リスク評価に活用できる。また、SSBJ対応のScope 3算定にも間接的に有用。
In the global GX context
This dataset provides high-resolution carbon sink and emission data for China, valuable for global climate disclosure and transition risk assessment. It complements TCFD/ISSB reporting needs for companies with Chinese operations, offering empirical basis for scenario analysis.
👥 読者別の含意
🔬研究者:Provides a standardized dataset for China's carbon neutrality research, enabling multi-model scenario analysis.
🏢実務担当者:Useful for assessing climate risks and opportunities in Chinese operations, supporting disclosure and strategy.
🏛政策担当者:Informs regional carbon neutrality planning and policy evaluation with consistent data.
📄 Abstract（原文）
This dataset combines scenarios of shared socio-economic pathways (SSPs) and representative concentration pathways (RCPs), selecting four typical pathways: SSP1-2.6 (SSP126), SSP2-4.5 (SSP245), SSP3-7.0 (SSP370), and SSP5-8.5 (SSP585), covering the complete radiative forcing range from low to high emissions, to evaluate future global change and its impact on carbon neutrality under different combinations of socio-economic and climate policies. The carbon sink data in this dataset is selected from 10 representative Earth System Models (ESM) in CMIP6, including ACCESS-ESM1-5、BCC-CSM2-MR、CanESM5、CESM2-WACCM、CMCC-CM2-SR5、CMCC-ESM2、IPSL-CM6A-LR、MPI-ESM1-2-LR、NorESM2-LM And TaiESM1. The Net Ecosystem Productivity (NEP) simulated by the land surface process modules of the ESMs models above characterizes the carbon absorption dynamics during historical periods (1980-2014) and predicted scenarios (2015-2060). Convert all model raw data（ https://esgf-node.llnl.gov/search/cmip6/ ）Download and uniformly process it as an annual scale mean, then refer to existing research in China to uniformly resample it to a resolution of 0.5 °× 0.5 °, and finally perform spatial pruning based on the administrative boundaries of China to calculate the multimodal ensemble average. The dataset provides annual NEP data for China and various provinces. This dataset includes both historical (1980-2014) and predicted (2015-2060) CO2 emission data, and the raw data can be obtained from the CMIP6 driven data platform - Earth System Grid Federation (ESGF)（ https://esgf-node.llnl.gov/search/input4mips/ ）Publicly available, covering emission sources from multiple sectors, including agriculture, energy, industry, transportation, construction, solvent production and application, waste treatment, shipping, and negative emission technologies. After downloading the original NetCDF file from the ESGF node, the Chinese regional dataset underwent resolution, unit conversion, and time aggregation processing. All historical and scenario data were resampled to a resolution of 0.5 °× 0.5 °, and the original annual or monthly emission data was converted into annual emission fluxes. The dataset provides annual carbon emission data for the China region.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.57760/sciencedb.j00100.00075first seen 2026-08-23 04:44:49
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