| Citation: |
ZHAO J C, DU Y M, REN S X, DUAN K F, REN R Y. Spatial spillover and threshold effects of rural revitalization on agricultural carbon emissions in the Yellow River Basin[J]. Chinese Journal of Eco-Agriculture, 2024, 32(10): 1766−1779. DOI: 10.12357/cjea.20240060
|
Extreme weather conditions caused by excessive carbon dioxide emissions have attracted the attention of governments worldwide. Agriculture is an important source of carbon emissions, and rural revitalization is an important strategy for promoting comprehensive rural development in China. The Yellow River Basin is an important ecological barrier and economic zone in China. Therefore, clarifying the impact of rural revitalization on agricultural carbon emissions in the region is of great significance for the high-quality development of the Yellow River Basin and the low-carbon development of agriculture. Based on the panel data of 88 prefecture-level cities in the Yellow River Basin from 2001 to 2021, we established evaluation indicators for rural revitalization, measured rural revitalization in the Yellow River Basin using the entropy method, calculated agricultural carbon emissions in the Yellow River Basin using the IPCC carbon emission factor method, adopted a spatial econometric model and threshold regression model to analyze the impact and spatial spillover effect of rural revitalization on agricultural carbon emissions in the Yellow River Basin, and analyzed the nonlinear relationship and regional heterogeneity between them. Results showed that rural revitalization, and agricultural carbon emissions had spatial clustering characteristics of the same type. The spatial econometric model results showed that rural revitalization had a significant promotional effect on agricultural carbon emissions, while exhibiting a significant negative spatial spillover effect. Additionally, industrial structure and urbanization rate had a negative impact on agricultural carbon emissions, while the planting scale, fertilizer application intensity, and agricultural economic development had a positive impact on agricultural carbon emissions. The industrial structure, planting scale, and fertilizer application intensity had a negative spatial spillover effect on agricultural carbon emissions, while urbanization rate and agricultural economic development had a positive spatial spillover effect on agricultural carbon emissions. The threshold model results showed that rural revitalization had a threshold effect on agricultural technological progress in terms of agricultural carbon emissions. When agricultural technological progress exceeded the threshold, the impact of rural revitalization on agricultural carbon emissions changed from positive to negative. From the perspective of heterogeneity, rural revitalization had significant heterogeneity in agricultural carbon emissions; specifically, rural revitalization had an inhibitory effect on agricultural carbon emissions in the major grain-producing areas, whereas it had a promotional effect on agricultural carbon emissions in non-major grain-producing areas. Regarding geographic location, rural revitalization had an inhibitory effect on agricultural carbon emissions in the middle and lower reaches of the Yellow River Basin and a promotional effect in the upper reaches of the Yellow River Basin. This study provides a theoretical reference and policy basis for promoting rural revitalization strategies and low-carbon agricultural development in the Yellow River Basin.
| [1] |
董红敏, 李玉娥, 陶秀萍, 等. 中国农业源温室气体排放与减排技术对策[J]. 农业工程学报, 2008(10): 269−273 doi: 10.3321/j.issn:1002-6819.2008.10.055
DONG H M, LI Y E, TAO X P, et al. Greenhouse gas emissions from agricultural sources in China and countermeasures for emission reduction technology[J]. Transactions of the Chinese Society of Agricultural Engineering, 2008(10): 269−273 doi: 10.3321/j.issn:1002-6819.2008.10.055
|
| [2] |
朱永彬, 马晓哲, 史雅娟. 县级尺度下河南省农业投入产出效率与减排潜力分析[J]. 中国生态农业学报(中英文), 2022, 30(11): 1852−1861 doi: 10.12357/cjea.20220219
ZHU Y B, MA X Z, SHI Y J. Agricultural input-output efficiency and the potential reduction of emissions in Henan Province at the county scale[J]. Chinese Journal of Eco-Agriculture, 2022, 30(11): 1852−1861 doi: 10.12357/cjea.20220219
|
| [3] |
谢会强, 吴晓迪. 城乡融合对中国农业碳排放效率的影响及其机制[J]. 资源科学, 2023, 45(1): 48−61 doi: 10.18402/resci.2023.01.04
XIE H Q, WU X D. Impact and its mechanism of urban-rural integration on the efficiency of agricultural carbon emissions in China[J]. Resources Science, 2023, 45(1): 48−61 doi: 10.18402/resci.2023.01.04
|
| [4] |
任洪杰, 李辉尚, 冯祎宇. 基于时空视角的广东省农业碳排放动态演化特征及发展趋势研究[J]. 中国生态农业学报(中英文), 2023, 31(8): 1287−1300 doi: 10.12357/cjea.20230168
REN H J, LI H S, FENG Y Y. Dynamic evolution characteristics and development trend of agricultural carbon emissions in Guangdong Province based on spatial and temporal perspective[J]. Chinese Journal of Eco-Agriculture, 2023, 31(8): 1287−1300 doi: 10.12357/cjea.20230168
|
| [5] |
冯誉萱, 薛选登. 考虑水土匹配的黄河流域农业碳排放时空分异研究[J]. 人民黄河, 2023, 45(11): 29−33 doi: 10.3969/j.issn.1000-1379.2023.11.005
FENG Y X, XUE X D. Spatial and temporal variation of agricultural carbon emissions in the Yellow River Basin considering soil and water matching[J]. Yellow River, 2023, 45(11): 29−33 doi: 10.3969/j.issn.1000-1379.2023.11.005
|
| [6] |
高晨曦, 卢秋萍, 欧年青, 等. “双碳” 目标下河南省农业碳排放影响因素及预测研究[J]. 中国生态农业学报(中英文), 2022, 30(11): 1842−1851 doi: 10.12357/cjea.20220267
GAO C X, LU Q P, OU N Q, et al. Research on influencing factors and prediction of agricultural carbon emission in Henan Province under the Carbon Peaking and Carbon Neutrality goal[J]. Chinese Journal of Eco-Agriculture, 2022, 30(11): 1842−1851 doi: 10.12357/cjea.20220267
|
| [7] |
尚杰, 吉雪强, 石锐, 等. 中国农业碳排放效率空间关联网络结构及驱动因素研究[J]. 中国生态农业学报(中英文), 2022, 30(4): 543−557 doi: 10.12357/cjea.20210607
SHANG J, JI X Q, SHI R, et al. Structure and driving factors of spatial correlation network of agricultural carbon emission efficiency in China[J]. Chinese Journal of Eco-Agriculture, 2022, 30(4): 543−557 doi: 10.12357/cjea.20210607
|
| [8] |
田云, 林子娟. 中国省域农业碳排放效率与经济增长的耦合协调[J]. 中国人口·资源与环境, 2022, 32(4): 13−22 doi: 10.12062/cpre.20220107
TIAN Y, LIN Z J. Coupling coordination between agricultural carbon emission efficiency and economic growth at provincial level in China[J]. China Population, Resources and Environment, 2022, 32(4): 13−22 doi: 10.12062/cpre.20220107
|
| [9] |
XIONG C H, CHEN S, XU L T. Driving factors analysis of agricultural carbon emissions based on extended STIRPAT model of Jiangsu Province, China[J]. Growth and Change, 2020, 51: 1401−1416 doi: 10.1111/grow.12384
|
| [10] |
RIDZUAN N H A M, MARWAN N F, KHALID N, et al. Effects of agriculture, renewable energy, and economic growth on carbon dioxide emissions: evidence of the environmental Kuznets curve[J]. Resources, Conservation and Recycling, 2020, 160: 104879
|
| [11] |
颜光耀, 陈卫洪, 钱海慧. 农业技术效率对农业碳排放的影响——基于空间溢出效应与门槛效应分析[J]. 中国生态农业学报(中英文), 2023, 31(2): 226−240 doi: 10.12357/cjea.20220571
YAN G Y, CHEN W H, QIAN H H. Effects of agricultural technical efficiency on agricultural carbon emission: based on spatial spillover effect and threshold effect analysis[J]. Chinese Journal of Eco-Agriculture, 2023, 31(2): 226−240 doi: 10.12357/cjea.20220571
|
| [12] |
DU Y Y, LIU H B, HUANG H, et al. The carbon emission reduction effect of agricultural policy — Evidence from China[J]. Journal of Cleaner Production, 2023, 406: 137005 doi: 10.1016/j.jclepro.2023.137005
|
| [13] |
PUGH T A M, ARNETH A, OLIN S, et al. Simulated carbon emissions from land-use change are substantially enhanced by accounting for agricultural management[J]. Environmental Research Letters, 2015, 10(12): 124008 doi: 10.1088/1748-9326/10/12/124008
|
| [14] |
覃朝晖, 潘昱辰, 丁志国. 极端气温对长江经济带农业碳排放的影响研究: 抑制还是促进?[J]. 华中农业大学学报(社会科学版), 2023(6): 70−82
QIN Z H, PAN Y C, DING Z G. The impact of extreme temperature on agricultural carbon emissions in the Yangtze River economic belt: promoting or inhibiting?[J]. Journal of Huazhong Agricultural University (Social Sciences Edition), 2023(6): 70−82
|
| [15] |
CHEN X W. The core of China’s rural revitalization: exerting the functions of rural area[J]. China Agricultural Economic Review, 2019, 12(1): 1−13
|
| [16] |
ZHOU Y, LI Y M, XU C. Land consolidation and rural revitalization in China: mechanisms and paths[J]. Land Use Policy, 2020, 91: 104379
|
| [17] |
李周. 乡村振兴战略的主要含义、实施策略和预期变化[J]. 求索, 2018(2): 44−50
LI Z. The main meaning, implementation strategy and expected changes of rural revitalization strategy[J]. Seeker, 2018(2): 44−50
|
| [18] |
张海鹏, 郜亮亮, 闫坤. 乡村振兴战略思想的理论渊源、主要创新和实现路径[J]. 中国农村经济, 2018(11): 2−16
ZHANG H P, GAO L L, YAN K. Strategic thinking on rural revitalization strategy: theoretical origin, main innovation and realization path[J]. Chinese Rural Economy, 2018(11): 2−16
|
| [19] |
黄祖辉. 准确把握中国乡村振兴战略[J]. 中国农村经济, 2018(4): 2−12
HUANG Z H. On the strategy of rural revitalization in China[J]. Chinese Rural Economy, 2018(4): 2−12
|
| [20] |
刘冀. 乡村振兴视域下农村治理能力提升研究[J]. 农业经济, 2023(8): 43−44 doi: 10.3969/j.issn.1001-6139.2023.08.015
LIU J. Research on the improvement of rural governance ability from the perspective of rural revitalization[J]. Agricultural Economy, 2023(8): 43−44 doi: 10.3969/j.issn.1001-6139.2023.08.015
|
| [21] |
AGYEKUMHENE C, DE VRIES J D, PAASSEN A, et al. Making smallholder value chain partnerships inclusive: exploring digital farm monitoring through farmer friendly smartphone platforms[J]. Sustainability, 2020, 12(11): 4580 doi: 10.3390/su12114580
|
| [22] |
李松睿, 曹迎. “乡村振兴” 视角下生态宜居评价及其对农村经济转型发展的启发−以川西林盘四川都江堰精华灌区为例[J]. 农村经济, 2019(6): 66−74
LI S R, CAO Y. Eco-livability evaluation from the perspective of “rural revitalization” and its enlightenment to rural economic transformation and development: A case study of Dujiangyan elite irrigation area in Linpan, Western Sichuan[J]. Rural Economy, 2019(6): 66−74
|
| [23] |
任世鑫, 李二玲, 赵金彩, 等. 黄河流域耕地利用碳排放时空特征及影响因素研究[J]. 中国土地科学, 2023, 37(10): 102−113
REN S X, LI E L, ZHAO J C, et al. Spatial-temporal characteristics of carbon emissions from cultivated land use in the Yellow River Basin and the influencing factors[J]. China Land Science, 2023, 37(10): 102−113
|
| [24] |
贺青, 张虎, 张俊飚. 农业产业聚集对农业碳排放的非线性影响[J]. 统计与决策, 2021, 37(9): 75−78
HE Q, ZHANG H, ZHANG J B. Nonlinear effects of agricultural industrial agglomeration on agricultural carbon emissions[J]. Statistics & Decision, 2021, 37(9): 75−78
|
| [25] |
李宽, 史磊. 农村产业融合对农业碳排放的影响: 机制路径及空间溢出效应分析[J]. 中国农业资源与区划, 2023, 45(4): 1–14
LI K, SHI L. Effects of rural industrial convergence on agricultural carbon emissions: mechanism path and spatial spillover effect analysis[J]. Chinese Journal of Agricultural Resources and Regional Planning, 2023, 45(4): 1–14
|
| [26] |
杨钧. 农业技术进步对农业碳排放的影响−中国省级数据的检验[J]. 软科学, 2013, 27(10): 116−120 doi: 10.3969/j.issn.1001-8409.2013.10.025
YANG J. The effects of technological advances on agricultural carbon emission — Evidence from Chinese provincial data[J]. Soft Science, 2013, 27(10): 116−120 doi: 10.3969/j.issn.1001-8409.2013.10.025
|
| [27] |
周勇, 林源源. 技术进步对能源消费回报效应的估算[J]. 经济学家, 2007(2): 45−52 doi: 10.3969/j.issn.1003-5656.2007.02.007
ZHOU Y, LIN Y Y. The estimation of technological progress on the energy consumption returns effects[J]. Economist, 2007(2): 45−52 doi: 10.3969/j.issn.1003-5656.2007.02.007
|
| [28] |
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 doi: 10.3969/j.issn.1002-2104.2011.08.013
LI B, ZHANG J B, LI H P. Research on spatial-temporal characteristics and affecting factors decomposition of agricultural carbon emission in China[J]. China Population, Resources and Environment, 2011, 21(8): 80−86 doi: 10.3969/j.issn.1002-2104.2011.08.013
|
| [29] |
赵荣钦, 刘英, 丁明磊, 等. 河南省农田生态系统碳源/汇研究[J]. 河南农业科学, 2010, 39(7): 40−44 doi: 10.3969/j.issn.1004-3268.2010.07.011
ZHAO R Q, LIU Y, DING M L, et al. Research on carbon source and sink of farmland ecosystem in Henan Province[J]. Journal of Henan Agricultural Sciences, 2010, 39(7): 40−44 doi: 10.3969/j.issn.1004-3268.2010.07.011
|
| [30] |
徐雪, 王永瑜. 中国乡村振兴水平测度、区域差异分解及动态演进[J]. 数量经济技术经济研究, 2022, 39(5): 64−83
XU X, WANG Y Y. Measurement, regional difference and dynamic evolution of rural revitalization level in China[J]. The Journal of Quantitative & Technical Economics, 2022, 39(5): 64−83
|
| [31] |
魏金义, 祁春节. 农业技术进步与要素禀赋的耦合协调度测算[J]. 中国人口·资源与环境, 2015, 25(1): 90−96 doi: 10.3969/j.issn.1002-2104.2015.01.013
WEI J Y, QI C J. Coupling coordination degree analysis of the agricultural technology progress and factor endowment in China[J]. China Population, Resources and Environment, 2015, 25(1): 90−96 doi: 10.3969/j.issn.1002-2104.2015.01.013
|
| [32] |
吕德胜, 王珏, 程振. 黄河流域数字经济、生态保护与高质量发展时空耦合及其驱动因素[J]. 经济问题探索, 2022(8): 135−148
LV D S, WANG J, CHENG Z. Spatio-temporal coupling and driving factors of digital economy, ecological protection and high-quality development in the Yellow River Basin[J]. Inquiry into Economic Issues, 2022(8): 135−148
|
| [33] |
LESAGE J P, PACE R K. Introduction to Spatial Econometrics[M]. Boca Raton: CRC Press, 2009
|
| [34] |
王惠, 卞艺杰. 农业生产效率、农业碳排放的动态演进与门槛特征[J]. 农业技术经济, 2015(6): 36−47
WANG H, BIAN Y J. Dynamic evolution and threshold characteristics of agricultural production efficiency and agricultural carbon emission[J]. Journal of Agrotechnical Economics, 2015(6): 36−47
|
| [35] |
黎孔清, 马豆豆, 李义猛. 基于STIRPAT模型的南京市农业碳排放驱动因素分析及趋势预测[J]. 科技管理研究, 2018, 38(8): 238−245 doi: 10.3969/j.issn.1000-7695.2018.08.034
LI K Q, MA D D, LI Y M. Driving factors and trends prediction of urban agricultural carbon emissions in Nanjing based on STIRPAT[J]. Science and Technology Management Research, 2018, 38(8): 238−245 doi: 10.3969/j.issn.1000-7695.2018.08.034
|
| [36] |
李绵德, 周冬梅, 朱小燕, 等. 河西走廊2000—2020年农业碳排放时空特征及其影响因素[J]. 农业资源与环境学报, 2023, 40(4): 940−952, 989
LI M D, ZHOU D M, ZHU X Y, et al. Spatial-temporal characteristics of agricultural carbon emissions and influencing factors in the Hexi Corridor from 2000 to 2020[J]. Journal of Agricultural Resources and Environment, 2023, 40(4): 940−952, 989
|
| [37] |
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 doi: 10.11870/cjlyzyyhj201403001
YAO B, ZHENG Y M, HU D, et al. Spatial and temporal variations of county based agricultural carbon emissions and associated effect factors in Jiangxi Province[J]. Resources and Environment in the Yangtze Basin, 2014, 23(3): 311−318 doi: 10.11870/cjlyzyyhj201403001
|
| [38] |
吴贤荣, 张俊飚, 田云, 等. 中国省域农业碳排放: 测算、效率变动及影响因素研究−基于DEA-Malmquist指数分解方法与Tobit模型运用[J]. 资源科学, 2014, 36(1): 129−138
WU X R, ZHANG J B, TIAN Y, et al. Provincial agricultural carbon emissions in China: calculation, performance change and influencing factors[J]. Resources Science, 2014, 36(1): 129−138
|
| 1. |
吴宜静，赵天祎，王露，张一鸣，蔡明，李运远，刘燕，张启翔. 基于蜂类视觉的北京公园常用园林植物花色分析. 北京林业大学学报. 2022(11): 100-110 .
| |
| 2. |
段美春，覃如霞，张宏斌，陈宝雄，金彬，张松泊，任少鹏，金树权，朱升海，华家宁，刘云慧，宇振荣. 农田节肢动物不同取样方法的综合比较. 生物多样性. 2021(04): 477-487 .
| |
| 3. |
李敏婷，刘小玲，罗杰，孙传谆，李景刚，杜继丰，吴顺辉. 农用地利用集约度与昆虫传粉服务之间的关系研究. 广东农业科学. 2019(10): 140-146 .
|
Supported by: Beijing Renhe Information Technology Co., Ltd. 
DownLoad: