作者：
Chengwei Zhao;Ruihuan Liu*;Xuanhua Xu;Jishan He
期刊：
Expert Systems with Applications,2025年261:125532 ISSN：0957-4174
通讯作者：
Ruihuan Liu
作者机构：
[Chengwei Zhao] School of Business, Central South University of Forestry and Technology, Changsha, China;[Ruihuan Liu] School of Logistics, Central South University of Forestry and Technology, Changsha, China;[Xuanhua Xu; Jishan He] School of Business, Central South University, Changsha, China
通讯机构：
[Ruihuan Liu] S;School of Logistics, Central South University of Forestry and Technology, Changsha, China
摘要：
为探究中国农业碳排放的时空分布特征及驱动因素,基于2000—2021年中国31个省(自治区、直辖市,不包括香港、澳门和台湾,下同)统计年鉴数据,考察水利用、土地利用和能源消耗的碳排放,利用联合国政府间气候变化专门委员会(IPCC)碳排放因子建立2000—2021年水、土地和能源3个子系统相关变量,计算各省(自治区、直辖市)农业年碳排放总量,结合莫兰指数对农业碳排放时空演变趋势及空间关联特征进行分析,并运用对数均值迪氏分解法(Logarithmic Mean Divisia Index,简称LMDI)探析农业碳排放的主要驱动因素。结果表明:1)从时序变化看,农业碳排放量整体呈倒“V”型变化趋势。2)从农业碳排放来源看,农业源碳排放中源于化肥的碳排放占比最高。3)从农业碳排放空间差异看,碳排放较大的省份(自治区、直辖市)主要集中在黄淮海区域以及中部平原等水土资源条件丰富且优质的地区,西部地区与部分直辖市(北京、上海、天津)农业碳排放量较少,高农业碳排放地区存在向北蔓延的趋势。4)农业碳排放在空间上具有集聚效应,且随着时间推移,集聚效应的显著性有所下降,其中河南、安徽、山东等省份(自治区、直辖市)具有显著的“高-高集聚”效应,北京、天津、青海等省份(自治区、直辖市)具有显著的“低-低集聚”效应。5)农业水资源经济产出因素和农业劳动力密集度因素为正向驱动因素,农业水资源经济产出因素为中国农业碳排放增加的最主要因素;农业生产效率因素、劳动力规模因素和农业水土匹配度因素为碳排放负向驱动因素,其中农业生产效率因素的碳减排贡献率最高,为中国农业碳排放减少的最主要驱动因素。基于以上结果,本文针对中国农业碳减排提出以下建议:政府应加大对低碳农业的投入,支持新型肥料和新能源农机的研发,提高水土资源利用效率。同时,要利用农业碳排放的集聚效应,推动农业集中发展和区域间合作,培养新型农业人才。
摘要：
Excessive fertilizer input and inefficient utilization in agricultural production have caused significant negative environmental impacts. Based on provincial panel data in China from 2005 to 2021, this study adopts the full-cost insurance pilot launched in 2018 and uses the DID method to empirically analyze its impact on fertilizer application intensity and utilization efficiency. The study reveals the following findings: (1) Implementing full-cost insurance can reduce fertilizer application intensity by 21.761% and increase utilization efficiency by 1.915%. (2) Full-cost insurance reduces fertilizer application intensity and improves fertilizer utilization efficiency by expanding the land scale and reducing the agricultural labor force. (3) Full-cost insurance significantly improves fertilizer utilization efficiency in high-risk and low-risk areas. Nevertheless, while the policy significantly reduces fertilizer application intensity in high-risk areas, its effect on low-risk areas is not apparent. (4) Full-cost insurance has an environmental protection effect. It can significantly reduce 11.593% of nitrogen pollution emissions, 2.577% of phosphorus pollution emissions, and 35.400% of equivalent pollution emissions. The implementation of full-cost insurance plays an important role in reducing fertilizer use and improving utilization efficiency. So, we should continue to intensify the promotion of full-cost insurance policy to fully leverage the advantages of agricultural insurance and promote sustainable agricultural development.
摘要：
Ecological security pattern (ESP) represents a sound spatial arrangement of ecosystem occurring in landscape. The research on the optimization of ESP aims to improve and restore the ecosystem functions by rationally allocating and optimizing the ecological elements based on the key ecological issues. Constructing and optimizing ESP can enhance the connectivity of regional habitat patches, which is of great significance for protecting and restoring biodiversity, improving ecosystem stability and resilience, and achieving regional sustainable development. However, it is a challenging task to systematically improve the connectivity and resilience of regional ecological networks under attacks. Little research has been done on enhancing the resilience of ecological networks under edge-based attacks. Based on morphological spatial pattern analysis (MSPA), minimum cumulative resistance (MCR) and greedy algorithm (GA) models, this study presents a new method to construct and optimize ESP. The Dongting Lake Basin in China, which is a typical region with rich biodiversity, complex landscape patterns, and intensive human activities, is taken as an example. The results indicate that the optimization of the ecological network has improved its connectivity by 51.62%, its robustness against random edge-based attacks by 41.13%, and its robustness against targeted edge-based attacks by 43.41%, relative to the initial ecological network. Monte Carlo test verifies the reliability of the optimization solution. The proposed method can be used for finding the network structure with the best robustness for specific edge-based attacks, and it provides valuable decision-making reference for ecological land planning and biodiversity conservation.
摘要：
Introduction The agricultural sector is the second largest emitter of greenhouse gases, accounting for 23% of global anthropogenic carbon emissions. Analysis of the basic state of carbon emissions from China's agriculture is helpful to achieve carbon reduction targets.Methods Agricultural carbon emissions were calculated using the emission factor method, based on data from the China Rural Statistical Yearbook and various provincial statistical yearbooks. To analyze spatial patterns, the standard deviation ellipse method and the center of gravity migration model were employed, uncovering the migration path of agricultural carbon emissions. Regional disparities and the driving factors of agricultural carbon emissions were further examined using the Theil index and the Logarithmic Mean Divisia Index (LMDI) model.Results The analysis indicated that the emissions center has gradually shifted towards the central and western regions, reflecting changes in agricultural production activity areas. Intraregional differences are the primary contributors to the imbalance in agricultural carbon emissions, with pronounced disparities in grain production and consumption balance regions. Key influencing factors include agricultural production efficiency, adjustments in agricultural industrial structure, economic structure and output, and urbanization levels. The economic output effect and urbanization effect are identified as the main drivers of increased carbon emissions, while declining production efficiency has hindered emission reduction efforts.Conclusion The findings provide valuable insights for regional management and policymaking in China's agricultural sector, highlighting the need to enhance production efficiency and optimize agricultural structure to reduce emissions.
