| 2000~2021中国土地利用碳排放时空特征演变及碳排放预测 |
| 摘要点击 986 全文点击 34 投稿时间：2025-01-13 修订日期：2025-10-10 |
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| 中文关键词 土地利用 碳排放 时空特征 脱钩效应 高斯过程回归（GPR） |
| 英文关键词 land use carbon emissions spatiotemporal characteristics decoupling effect Gaussian process regression （GPR） |
| DOI 10.13227/j.hjkx.202501138 |
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| 中文摘要 |
| 碳排放的时空演变及其未来趋势预测，作为应对全球气候变化的重要科学问题，已成为气候学、环境科学与政策研究的关键领域. 中国作为全球最大碳排放国，其土地利用变化对碳排放的动态变化产生了深远影响. 利用武汉大学年度土地利用数据集、《中国统计年鉴》（2001~2022年）的社会经济数据以及MODIS的全球净初级生产力（NPP）数据，考察不同区域建筑用地、耕地和林地等类型的碳排放和碳吸收，系统分析2000~2021年间中国土地利用变化对碳排放的具体影响，并通过高斯过程回归（GPR）模型进行碳排放预测，同时结合基尼系数和TAPIO脱钩模型分析碳排放的空间分布与经济发展的关系. 结果表明：①2000~2021年，建筑用地扩张67.28%（2000~2021年），年均增速超4%，东部耕地转化显著. 林地、水体面积增2.12%和10.38%，西部生态修复成效突出. 草地、耕地和未利用地减少1.86%~3.28%，集约利用特征明显. ②2000~2021年，建筑用地碳排放占比处于主导地位，总量增长235%（年均6.07%），空间扩散至中西部. 林地碳汇量增至17.49×108 t（年均增长0.77%），草地碳吸收微降，东西部碳功能分化加剧. ③ 碳排放基尼系数从2000年的0.592 2下降到2021年的0.540 7，表明碳排放分布更加均匀. 前10%网格的碳排放量从1.089×108 t增加到3.304×108 t，显示出高排放区域仍在推动碳排放的增长，西部内部差异最大（基尼系数为0.847 3）. ④从2000~2013年，我国处于“弱脱钩”状态，经济增长的同时碳排放量有所增加. 2014~2016年则进入“强脱钩”阶段，GDP增长而碳排放减少. 自2017年起，碳排放再次上升，恢复到“弱脱钩”状态. ⑤ GPR模型预测中国将在2028年碳达峰，2060年前碳中和；西部已成碳汇，东中部2027年前后碳达峰. 云、藏、蒙具碳中和潜力，鲁、辽等重工业省域压力突出，需负碳技术与生态补偿协同. |
| 英文摘要 |
| The spatiotemporal evolution of carbon emissions and its future trend prediction， as an important scientific issue in response to global climate change， has become a key area of research in climate science， environmental science， and policy studies. As the world's largest emitter of carbon， China's land use changes have had a profound impact on the dynamic changes in carbon emissions. This study utilizes the annual land use dataset from Wuhan University， socioeconomic data from the China Statistical Yearbook， and MODIS global net primary productivity （NPP） data to examine the carbon emissions and carbon sequestration from various 3land types such as urban areas， arable land， and forest land in different regions. It systematically analyzes the specific impact of land use changes in China on carbon emissions from 2000 to 2021. Additionally， the study employs a Gaussian Process Regression （GPR） model for carbon emission forecasting and analyzes the spatial distribution of carbon emissions in relation to economic development using the Gini coefficient and the TAPIO decoupling model. The results indicate that： ① From 2000 to 2021， construction land expanded by 67.28% （2000-2021）， with an average annual growth rate exceeding 4%. Significant conversion of arable land occurred in the eastern region. Forest land/water body areas increased by 2.12% and 10.38%， respectively， with notable ecological restoration in the western region. Grassland， arable land， and unused land decreased by 1.86%-3.28%， showing clear characteristics of intensive land use. ② From 2000 to 2021， carbon emissions from construction land dominated in proportion， with total emissions increasing by 235% （an annual growth rate of 6.07%） and spatial diffusion extending to the central and western regions. Forest carbon sequestration increased by 16.6% （an annual growth rate of 0.77%）， while carbon absorption by grasslands slightly declined， and the carbon function differentiation between the eastern and western regions intensified. ③ The carbon emission Gini coefficient decreased from 0.592 2 in 2000 to 0.540 7 in 2021， indicating a more even distribution of carbon emissions. The carbon emissions of the top 10% grids increased from 108.9 million tons to 330.4 million tons， showing that high-emission areas were still driving the growth of carbon emissions. The internal differences in the western region were the largest （Gini coefficient of 0.847 3）. ④ From 2000 to 2013， China was in a “weak decoupling” state， with economic growth accompanied by an increase in carbon emissions. From 2014 to 2016， China entered a “strong decoupling” phase， where GDP growth occurred alongside a reduction in carbon emissions. From 2017 onwards， carbon emissions began to rise again， returning to a “weak decoupling” state. ⑤ The GPR model predicted that China's carbon emissions will peak in 2028， and carbon neutrality will be achieved before 2060. The western region has already become a carbon sink， while the central and eastern regions will reach their peak around 2027. The potential for carbon neutrality in regions like Tibet， Qinghai， and Inner Mongolia is significant， while heavy industrial provinces such as Shandong， Liaoning， and others face notable pressure， requiring collaborative solutions of carbon-negative technologies and ecological compensation. |
