中国黄河流域碳排放峰值的多情景土地覆被变化与碳排放预测

IF 7 2区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Ecological Indicators Pub Date : 2024-11-01 DOI:10.1016/j.ecolind.2024.112794
Haipeng Niu , Si Chen , Dongyang Xiao
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引用次数: 0

摘要

对未来土地覆被变化和碳排放的研究对于有效管理土地资源和制定可行的碳减排战略至关重要。本研究以黄河流域为研究对象,采用未来土地利用模拟(FLUS)和自回归综合移动平均(ARIMA)模型对未来土地覆被变化和碳排放进行预测。此外,还利用二元空间自相关分析了二者之间的关系。主要结论如下1)从历史上看,黄河流域的建设用地、森林、草地和水域面积不断扩大,而耕地和未利用地则不断减少。其中,建设用地变化最大,而草地变化最小。展望未来,生态保护方案和惯性发展方案在土地类型上都表现出与历史模式一致的趋势。相比之下,经济优先发展情景预测建设用地、耕地和草地会增加,表明与其他情景相比,建设用地、耕地和草地发生了明显变化。然而,事实证明生态保护情景更具可持续性。2) 在没有干预的情况下,全流域建设用地的模拟碳排放量在各种情景下均呈线性增长,各省之间的差异表现为从西南到东北的增长。然而,与其他预测相比,河南和四川的碳排放量减少速度较慢。碳排放与综合指数之间存在明显的正相关关系,表明高排放地区通常经历了巨大的土地和经济发展。3) 2030 年和 2060 年的能源消耗预测表明,要实现中国的碳排放目标,必须降低能源消耗,调整化石燃料与非化石燃料的比例,以减少碳排放。用清洁能源替代煤炭和提高能源效率将更有效地实现低碳排放目标。总之,本研究为中国的生态保护、低碳排放战略和全球碳排放控制工作提供了重要指导。
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Multi-Scenario land cover changes and carbon emissions prediction for peak carbon emissions in the Yellow River Basin, China
Research on future land cover changes and carbon emissions is essential for effective land resource management and developing feasible carbon mitigation strategies. This study focused on the Yellow River Basin and employed the Future Land Use Simulation (FLUS) and Autoregressive Integrated Moving Average (ARIMA) models to project future land cover and carbon emissions. Additionally, bivariate spatial autocorrelation was utilized to analyze the relationship between them. Key findings are as follows: 1) Historically, the Yellow River Basin has experienced an expansion in construction land, forests, grasslands, and water, while cropland and unused land have diminished. Notably, construction land displayed the most significant changes, whereas grasslands showed minimal modification. Looking ahead, both the ecological protection and inertial development scenarios exhibit consistent trends with historical patterns across the land type categories. In contrast, the economic priority development scenario forecasts an increase in construction land, cropland, and grasslands, indicating a distinct shift compared to the other scenarios. However, the ecological protection scenario proves to be more sustainable. 2) In the absence of intervention, the simulated carbon emissions from construction land throughout the basin display a linear increase across various scenarios, with provincial-level variations showing an increase from southwest to northeast. However, Henan and Sichuan are expected to experience slower reductions in carbon emissions, compared to other projections. There is a notable positive correlation between carbon emissions and the comprehensive index, indicating that regions with high emissions typically experience substantial land and economic development. 3) Energy consumption projections for 2030 and 2060 indicate that to align with China’s carbon goals, it is essential to reduce energy consumption and adjust the fossil to non-fossil fuel ratio to reduce carbon emissions. Substituting coal with clean energy and enhancing energy efficiency will be more effective for achieving low-carbon emission targets. In summary, this study provides significant guidance for China’s ecological conservation, low-carbon emission strategies, and global carbon emission control efforts.
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来源期刊
Ecological Indicators
Ecological Indicators 环境科学-环境科学
CiteScore
11.80
自引率
8.70%
发文量
1163
审稿时长
78 days
期刊介绍: The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published. • All aspects of ecological and environmental indicators and indices. • New indicators, and new approaches and methods for indicator development, testing and use. • Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources. • Analysis and research of resource, system- and scale-specific indicators. • Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs. • How research indicators can be transformed into direct application for management purposes. • Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators. • Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.
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