[粮食换绿工程前后黄河流域生态系统碳储量时空演变及模拟预测]。

Q2 Environmental Science
Xu-Meng Duan, Mei Han, Xiang-Lun Kong, Jin-Xin Sun, Hui-Xin Zhang
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引用次数: 0

摘要

在 "双碳 "背景下,必须探讨 "绿色粮食 "项目的实施对黄河流域生态系统碳储量的影响,为完善新一轮 "绿色粮食 "项目的政策实施、提高黄河流域生态系统的碳汇能力提供重要参考。本研究选取项目实施前的 1990 年作为研究期的起始年,两轮项目实施后的 2020 年作为研究期的结束年。根据1990-2020年的生态系统类型数据,利用InVEST模型计算了1990-2020年黄河流域及项目实施区域生态系统的土壤碳库、地下碳库、地下碳库、死亡有机质碳库和总碳储量。结果表明:①两轮工程实施后,1990-2020 年黄河流域森林生态系统面积扩大了 26610.06 平方公里,耕地面积减少了 46849.06 平方公里。从空间上看,黄河上游以草地等生态系统为主;黄河中游以农田、森林、草地生态系统为主;黄河下游以农田生态系统为主。从 1990 年到 2020 年,项目实施区的碳储量呈波动上升趋势,总碳储量在 2009 年达到峰值(219.47×108 t),随后下降到 218.47×108 t。2009 年达到峰值(219.47×108 t),2020 年降至 218.59×108 t,原因是 2010-2020 年草地生态系统减少。从空间上看,碳储量高值区分布在林草积蓄上游的四川省阿坝藏族羌族自治州和甘肃省南端,中游的陕西省全境和陕西省中南部。陕西省商洛市和内蒙古自治区阿拉善盟是平均碳密度最高和最低的地级市。根据预测,2035 年自然发展情景下的碳储存损失为 0.83×108 t,其他三种情景下的碳储存损失将增加。在中度退耕情景下,黄河流域生态系统固碳能力最强,预测碳储量比 2020 年增加 2.72×108 t,深度退耕情景为综合最优情景。因此,未来黄河流域可参考深耕退耕情景,优化调整 "绿色粮食 "工程实施方案,其碳储量预测值可为实现双碳目标提供一定的数据支撑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
[Spatiotemporal Evolution and Simulation Prediction of Ecosystem Carbon Storage in the Yellow River Basin Before and After the Grain for Green Project].

Under the background of "dual carbon", the impact of the implementation of the Grain for Green project on the carbon storage of the ecosystem in the Yellow River Basin must be explored, which can serve as an important reference for improving the policy implementation of the new round of the Grain for Green project and improving the carbon sink capacity of the ecosystem in the Yellow River Basin. In this study, 1990, before the implementation of the project, was selected as the starting year of the research period, and 2020, after the implementation of the two rounds of the project, was selected as the end year of the research period. Based on the ecosystem type data from 1990 to 2020, the InVEST model was used to calculate the soil carbon pool, underground carbon pool, below carbon pool, dead organic matter carbon pool, and total carbon storage of ecosystems in the Yellow River Basin and the area where the project was implemented from 1990 to 2020. The results showed that: ① From 1990 to 2020, the area of forest ecosystem in the Yellow River Basin expanded by 26 610.06 km2, and the area of farmland decreased by 46 849.06 km2 after the implementation of two rounds of the project. Spatially, the upper reaches of the Yellow River were dominated by grassland and other ecosystems; the middle reaches of the Yellow River were dominated by farmland, forest, and grassland ecosystems; and the lower reaches of the Yellow River were dominated by farmland ecosystems. ② From 1990 to 2020, the carbon storage in the project implementation area showed a fluctuating and increasing trend, and the total carbon storage reached a peak (219.47×108 t) in 2009 and decreased to 218.59×108 t in 2020 due to the decrease of grassland ecosystem from 2010 to 2020. Spatially, the high-value areas of carbon storage were distributed in Aba Tibetan and Qiang Autonomous Prefecture of Sichuan Province and the southern tip of Gansu Province in the upper reaches of the forest and grass accumulation and in the whole of Shanxi Province and the central and southern parts of Shaanxi Province in the middle reaches. Shangluo City in Shaanxi Province and Alxa League in Inner Mongolia Autonomous Region were prefecture-level cities with the highest and lowest average carbon density. ③ In 2035, the carbon storage loss of the natural development scenario was predicted to be 0.83×108 t, and the other three scenarios would increase this loss. Under the moderate farmland return scenario, the Yellow River Basin ecosystem had the strongest carbon sequestration capacity, and the predicted carbon storage would increase by 2.72×108 t compared with that in 2020, and the deep farmland return scenario was the comprehensive optimal scenario. Therefore, in the future, the Yellow River Basin could refer to the deep farmland return scenario to optimize and adjust the implementation plan of the Grain for Green project, and the predicted value of carbon storage can provide some data support for achieving the dual carbon goal.

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来源期刊
Huanjing Kexue/Environmental Science
Huanjing Kexue/Environmental Science Environmental Science-Environmental Science (all)
CiteScore
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