Spatiotemporal Differences of Agricultural Carbon Income and Expenditure, and Carbon Compensation Potential of Counties in Hunan Province

Han Chaoyue; Zhao Xianchao; Hu Yijue; Zhang Xiaoxiang

doi:10.13961/j.cnki.stbctb.2023.05.040

您当前的位置：

首页 >

文章列表页 >

Spatiotemporal Differences of Agricultural Carbon Income and Expenditure, and Carbon Compensation Potential of Counties in Hunan Province

- Spatiotemporal Differences of Agricultural Carbon Income and Expenditure, and Carbon Compensation Potential of Counties in Hunan Province
- Bulletin of Soiland Water Conservation Vol. 43, Issue 5, Pages: 343-354(2023)
- 作者机构：
  
  湖南工业大学城市与环境学院,湖南,株洲,412007
- 作者简介：
- 基金信息：
- DOI：10.13961/j.cnki.stbctb.2023.05.040
  CLC： F323
- Published：2023
- 稿件说明：
移动端阅览
Han Chaoyue, Zhao Xianchao, Hu Yijue, et al. Spatiotemporal Differences of Agricultural Carbon Income and Expenditure, and Carbon Compensation Potential of Counties in Hunan Province[J]. Bulletin of Soiland Water Conservation, 2023, 43(5): 343-354.
DOI：

Han Chaoyue, Zhao Xianchao, Hu Yijue, et al. Spatiotemporal Differences of Agricultural Carbon Income and Expenditure, and Carbon Compensation Potential of Counties in Hunan Province[J]. Bulletin of Soiland Water Conservation, 2023, 43(5): 343-354. DOI： 10.13961/j.cnki.stbctb.2023.05.040.

摘要

[目的] 基于碳排放和碳吸收双重视角来探究农业碳收支时空差异和碳补偿潜力，为湖南省农业全面绿色转型和协调发展提供理论参考。[方法] 采用探索性空间数据分析、绝对β收敛、参数对比法和GIS空间分析方法，对湖南省县域农业碳收支时空差异、碳补偿率空间相关性及收敛性特征、农业碳补偿潜力区域差异进行实证分析。[结果] 湖南省县域农业碳排量整体呈“以高值区为中心，向外围逐渐降低”的结构且农田土壤碳排量是其主要来源，县域农业碳排强度呈“西南高，东北低”且逐年显著降低；县域农业碳汇量整体呈“东中北部高，西南部低”的空间格局且其农业碳汇能力渐趋增强。稻谷对农业碳汇量贡献最大，农业碳吸收强度显著提升且其空间格局发生明显转变。县域农业碳补偿率表现为净碳源，存在显著的空间正相关性和收敛性且其空间集聚特征和关联特征均较为明显。县域农业碳补偿潜力在空间上呈现显著不平衡特征，中、高碳补偿县域比例达60.66%，表明湖南省县域农业碳补偿率偏低，仍具有很大碳补偿空间。[结论] 应深入强化区域合作，多方共促绿色转型，充分发挥农业碳补偿率热点区辐射带动效应，维持好农业碳补偿能力较强区域优良低碳农业发展情势，重点关注中、高碳补偿潜力区域绿色农业发展趋势，缩减湖南省各县域低碳农业发展差距。

Abstract

[Objective] The temporal and spatial differences of agricultural carbon budget and carbon compensation potential were analyzed based on the dual perspectives of carbon emission and carbon absorption in order to provide a theoretical reference for the comprehensive green transformation and coordinated development of agriculture in Hunan Province. [Methods] Exploratory spatial data analysis

absolute β convergence

parameter comparison

and GIS spatial analysis were used to empirically analyze the spatial and temporal differences of the agricultural carbon budget

spatial correlation and convergence characteristics of the carbon compensation rate

and regional differences in agricultural carbon compensation potential of counties in Hunan Province. [Results] The overall agricultural carbon emissions of counties in Hunan Province exhibited a structural form of “higher value areas in the center

and gradually decreased outwards”. Farmland soil was the main source of carbon emissions. The agricultural carbon emission intensity of counties exhibited a pattern of “higher in the southwest

lower in the northeast” and significantly decreased year by year. The overall agricultural carbon sequestration in the counties exhibited a spatial pattern of “higher in the east

central

and north regions

lower in the southwest”. Agricultural carbon sequestration capacity gradually increased across the region. Rice contributed the most to agricultural carbon sequestration

and agricultural carbon absorption intensity significantly increased and its spatial pattern significantly changed. The agricultural carbon compensation rate in the counties was a net carbon source

with significant positive spatial correlation and convergence

and the spatial clustering and correlation characteristics were obvious. The potential of agricultural carbon compensation in the counties showed a significant imbalance in space

with the proportion of medium and higher carbon compensation counties reaching 60.66%

indicating that the agricultural carbon compensation rates of counties in Hunan Province were lower

thous there was still a large potential for increasing carbon compensation. [Conclusion] Regional cooperation should be further strengthened

and green transformation should be jointly promoted by interested parties who should give full attention to the radiation driving effect of agricultural carbon compensation rate hot spots in order to maintain the development of excellent low-carbon agriculture in regions with higher agricultural carbon compensation capacity. The future work should focus on the development of green agriculture in regions with medium and high carbon compensation potential

and on narrowing the development gap of low-carbon agriculture in all Hunan Province.

关键词

Keywords

references

习近平.在第七十五届联合国大会一般性辩论上的讲话[N].人民日报,2020-09-23(3).

Wang Xiuhong. Changes in CO

emissions induced by agricultural inputs in China over 1991—2014[J]. Sustainability, 2016,8(5):414.

李波,张俊飚,李海鹏.中国农业碳排放时空特征及影响因素分解[J].中国人口·资源与环境,2011,21(8):80-86.

尧波,郑艳明,胡丹,等.江西省县域农业碳排放的时空动态及影响因素分析[J].长江流域资源与环境,2014,23(3):311-318.

高鸣,宋洪远.中国农业碳排放绩效的空间收敛与分异: 基于Malmquist-luenberger指数与空间计量的实证分析[J].经济地理,2015,35(4):142-148.

范大莎,杨旭,吴相利,等.东北三省农田生态系统碳排放时空分异特征及驱动因素研究[J].环境科学学报,2017,37(7):2797-2804.

吴贤荣,张俊飚.中国省域农业碳排放: 增长主导效应与减排退耦效应[J].农业技术经济,2017(5):27-36.

Burney J A, Davis S J, Lobell D B. Greenhouse gas mitigation by agricultural intensification [J]. Proceedings of the National Academy of Sciences of the United States of America, 2010,107(26):12052-12057.

李波,杜建国,刘雪琪.湖北省农业碳排放的时空特征及经济关联性[J].中国农业科学,2019,52(23):4309-4319.

陈炜,殷田园,李红兵.1997—2015年中国种植业碳排放时空特征及与农业发展的关系[J].干旱区资源与环境,2019,33(2):37-44.

胡中应.技术进步、技术效率与中国农业碳排放[J].华东经济管理,2018,32(6):100-105.

张大东,张社梅,黄伟.浙江省农业系统碳源、碳汇现状评估分析[J].中国农业资源与区划,2012,33(5):12-19.

曹志宏,秦帅,郝晋珉.河南省农业生产碳汇的演变趋势及其集聚特征分析[J].中国生态农业学报,2018,26(9):1283-1290.

于伟咏,漆雁斌,明辉,等.中国农业系统碳汇和碳源的省域差异及影响因素[J].西部林业科学,2016,45(5):1-7.

Allen M R, Frame D J, Huntingford C, et al. Warming caused by cumulative carbon emissions towards the trillionth tonne [J]. Nature, 2009,458(7242):1163-1166.

夏四友,杨宇.基于主体功能区的京津冀城市群碳收支时空分异与碳补偿分区[J].地理学报,2022,77(3):679-696.

蒋烨林,王让会,彭擎,等.干旱区景观格局演变及碳收支状况研究: 以塔里木盆地为例[J].生态与农村环境学报,2019,35(7):875-884.

李翠华,蔡榕硕,颜秀花.2010—2018年海南东寨港红树林湿地碳收支的变化分析[J].海洋通报,2020,39(4):488-497.

于贵瑞,王秋凤,朱先进.区域尺度陆地生态系统碳收支评估方法及其不确定性[J].地理科学进展,2011,30(1):103-113.

王兴,薛建福,王钰乔,等.我国西部地区种植业碳收支分析[J].中国农业科技导报,2016,18(3):104-111.

康霞.甘肃省农田生态系统碳收支动态[J].中国沙漠,2018,38(6):1237-1242.

伍国勇,陈莹,孙小钧.中国种植业碳补偿率区域差异、动态演进及收敛性分析[J].中国生态农业学报(中英文),2021,29(10):1774-1785.

吴昊玥,何艳秋,陈文宽,等.中国农业碳补偿率空间效应及影响因素研究: 基于空间Durbin模型[J].农业技术经济,2020(3):110-123.

Denstadli J M, Veisten K. The flight is valuable regardless of the carbon tax scheme: a case study of Norwegian leisure air travelers [J]. Tourism Management, 2020,81:104150.

李璐,董捷,徐磊,等.功能区土地利用碳收支空间分异及碳补偿分区: 以武汉城市圈为例[J].自然资源学报,2019,34(5):1003-1015.

夏四友,赵媛,许昕,等.近20年来中国农业碳排放强度区域差异、时空格局及动态演化[J].长江流域资源与环境,2020,29(3):596-608.

闵继胜,胡浩.中国农业生产温室气体排放量的测算[J].中国人口·资源与环境,2012,22(7):21-27.

田云,张俊飚,李波.中国农业碳排放研究: 测算、时空比较及脱钩效应[J].资源科学,2012,34(11):2097-2105.

伍国勇,孙小钧,于福波,等.中国种植业碳生产率空间关联格局及影响因素分析[J].中国人口·资源与环境,2020,30(5):46-57.

Cao M. Methane emissions from China's paddyland [J]. Agriculture, Ecosystems & Environment, 1995,55(2):129-137.

王明星,李晶,郑循华.稻田甲烷排放及产生、转化、输送机理[J].大气科学,1998,22(4):600-612.

庞军柱,王效科,牟玉静,等.黄土高原冬小麦地N

O排放[J].生态学报,2011,31(7):1896-1903.

邱炜红,刘金山,胡承孝,等.种植蔬菜地与裸地氧化亚氮排放差异比较研究[J].生态环境学报,2010,19(12):2982-2985.

罗怀良.中国农田作物植被碳储量研究进展[J].生态环境学报,2014,23(4):692-697.

韩召迎,孟亚利,徐娇,等.区域农田生态系统碳足迹时空差异分析: 以江苏省为案例[J].农业环境科学学报,2012,31(5):1034-1041.

王腊芳,段文静,赖明勇,等.中国制造业节能潜力的区域及行业差异[J].地理研究,2015,34(1):109-121.

吴昊玥,何宇,黄瀚蛟,等.中国种植业碳补偿率测算及空间收敛性[J].中国人口·资源与环境,2021,31(6):113-123.

Views

620

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Evaluation on Eco-security of Agricultural Sustainable Development——A Case Study in Hu'nan Province

Prediction of Demands on Arable Land in Hu.nan Province Based on Multi-objectives

Comprehensive Evaluation of Water Resources Carrying Capacity in Hu'nan Province During 2009-2018 Based on TOPSIS and Coupling Coordination Development

Spatial and Temporal Distribution Characteristics of Service Function Importance of Soil and Water Conservation in Hunan Province Based on GIS

Regional characteristics of soil moisture and nutrients under artificial forests in typical loess regions

Related Author

XU Lian-fang

WANG Ke-lin

LI Xiao-qing

LIU Xin-ping

LIU Ming

QIN Shi-ya

YIN Hui-bin

Yang Bincheng

Related Institution

Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, Hu’nan Province

Graduate School of the Chinese Academy of Sciences

College of Resources and Environment Science, Hunan Normal University, Changsha 410081, Hu’nan Province

School of Resources and Safety Engineering, Central South University,, Hu’nan

School of Civil Engineering and Architecture, Changsha University of Science & Technology,, Hu’nan

⁰