多种发展情景下城市土地利用变化与碳排放的模拟与预测:中国西安案例研究

Land Pub Date : 2024-07-17 DOI:10.3390/land13071079
Rui Bian, Anzhou Zhao, Lidong Zou, Xianfeng Liu, Ruihao Xu, Ziyang Li
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摘要

研究城市土地利用及其对碳排放的影响对于实现中国的双碳目标至关重要。本研究利用第六次国际耦合模式比对项目(CMIP6)中的共享社会经济路径(SSPs)情景126、245和585,以及耦合系统动力学(SD)和斑块生成土地利用模拟(PLUS)模型和碳排放系数方法,模拟和预测了西安市2020-2040年的土地利用碳排放量。结果表明(1)耕地和林地是西安市最主要的土地利用类型,预计到 2040 年,三种 SSP 情景下的耕地和草地面积都将减少。在 SSP585 情景下,建设用地的扩张最为明显,到 2040 年将增加 515.92 平方公里,这主要是以牺牲耕地为代价的。(2)土地利用碳排放量从 2000 年的 414.15×104 t 增加到 2020 年的 2376.10×104 t,其中建设用地是主要的碳排放源,而林地则是主要的碳汇。然而,2020 年的碳汇能力仍然很低,仅为 21.38 × 104 t。(3) 在 2030 年和 2040 年之前,所有情景下的碳排放量预计都将继续增加,但增速将有所下降。SSP126 预测的排放量最低,到 2040 年为 9186.00 × 104 t,而 SSP585 预测的排放量最高,为 14935.00 × 104 t。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simulation and Prediction of Land Use Change and Carbon Emission under Multiple Development Scenarios at the City Level: A Case Study of Xi’an, China
Studying urban land use and its impact on carbon emissions is crucial for achieving China’s dual carbon goals. This research utilized the Shared Socio-economic Pathways (SSPs) scenarios 126, 245, and 585 from the Sixth International Coupled Model Intercomparison Project (CMIP6), along with a coupled System Dynamics (SD) and Patch-generating Land Use Simulation (PLUS) model and a carbon emission coefficient method to simulate and predict Xi’an’s land use carbon emissions from 2020 to 2040. The results indicate the following: (1) Cultivated and forest lands are the predominant land use types in Xi’an, with cultivated and grassland areas projected to decline under all three SSP scenarios by 2040. The most significant expansion of construction land, primarily at the expense of farmland, is projected under the SSP585 scenario, with an increase of 515.92 km2 by 2040. (2) Land use carbon emissions increased from 414.15 × 104 t in 2000 to 2376.10 × 104 t in 2020, with construction land being the primary source of emissions and forest land serving as the main carbon sink. However, the carbon sink capacity remained low at only 21.38 × 104 t in 2020. (3) Carbon emissions are expected to continue increasing under all scenarios through 2030 and 2040, though at a decreasing rate. The SSP126 scenario predicts the lowest emissions, reaching 9186.00 × 104 t by 2040, while SSP585 predicts the highest at 14,935.00 × 104 t. The findings of this study provide theoretical support for future low-carbon and high-quality urban development strategies.
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