新疆农业碳排放效率时空异质性及其影响因素

doi:10.12118/j.issn.1000-6060.2024.345

Abstract

Abstract:

The promotion of low-carbon agricultural development necessitates in-depth research into the spatiotemporal heterogeneity of agricultural carbon emission efficiency and its influencing factors. This will facilitate the acceleration of Xinjiang’s agricultural economic development while driving the green transformation of agricultural production. This study focused on 14 prefectures and cities in Xinjiang from 2000 to 2020 to assess agricultural carbon emission efficiency. The analysis was conducted using the SBM model of nonexpected output and the Malmquist index. The spatial characteristics of agricultural carbon emission efficiency were further examined using the spatial autocorrelation model, and the Tobit model was applied to explore factors influencing efficiency. The findings suggested the following. (1) From 2000 to 2020, the agricultural carbon emission efficiency in Xinjiang followed a “slow-fast-slow” development pattern, with significant inter-regional disparities. (2) In 2000, the Tacheng Prefecture exhibited a low-high agglomeration pattern in case of agricultural carbon emission efficiency. By 2007, the Changji Hui Autonomous Prefecture transitioned to a high-high agglomeration pattern. Further, by 2014, Turpan City and the Changji Hui Autonomous Prefecture were both exhibited high-high agglomeration. In 2020, the Bayingol Mongolian Autonomous Prefecture, Hami City, and Changji Hui Autonomous Prefecture were situated in a low-high agglomeration. Thus, a general decline in regions exhibiting high-high agglomeration and an increase in those with low-high agglomeration was observed. (3) The extent of arable land scale and the overall advancement of the agricultural economy positively affected the agricultural carbon emission efficiency. Further, the agricultural industry structure, crop cultivation structure, and effective irrigation rate negatively affected the agricultural carbon emission efficiency. Thus, this study highlights the spatial and temporal heterogeneity of agricultural carbon emission efficiency and its influencing factors in Xinjiang. The findings are expected to provide theoretical support and empirical evidence for the sustainable development of agriculture in arid areas.

Key words: agricultural carbon emission efficiency, non-expected output SBM model, spatial correlation, influencing factors, Xinjiang

LIU Haijun, ZHANG Haihong, YAN Junjie, LI Xiang, LI Gaofeng. Spatiotemporal heterogeneity and its influencing factors of agricultural carbon emission efficiency in Xinjiang[J].Arid Land Geography, 2025, 48(5): 866-878.

Figures/Tables 13

Tab. 1

Tab. 2

Tab. 3

Fig. 1

Fig. 2

Tab. 4

Tab. 5

Fig. 3

Fig. 4

Fig. 5

Tab. 6

Tab. 7

Tab. 8

References 28

[1]	张帆, 蔡颖, 邓祥征, 等. 作物-牲畜-生物能源综合系统对中国农业源温室气体的影响评估[J]. 地理学报, 2024, 79(1): 28-44. doi: 10.11821/dlxb202401003
	[Zhang Fan, Cai Ying, Deng Xiangzheng, et al. Assessment of the impact of the integrated crop-livestock-bioenergy system on agricultural greenhouse gases in China[J]. Acta Geographica Sinica, 2024, 79(1): 28-44. ] doi: 10.11821/dlxb202401003
[2]	赵先超, 彭竞霄, 胡艺觉, 等. 基于夜间灯光数据的湖南省县域碳排放时空格局及影响因素研究[J]. 生态科学, 2022, 41(1): 91-99.
	[Zhao Xianchao, Peng Jingxiao, Hu Yijue, et al. Spatial-temporal pattern and influence factors of county carbon emissions in Hunan Province based on nightlight data[J]. Ecological Science, 2022, 41(1): 91-99. ]
[3]	马欣雨, 穆月英. 碳视角下的粮食生产环境技术效率评价——基于超效率SBM-Undesirable模型[J]. 中国农业资源与区划, 2024, 45(3): 26-35.
	[Ma Xinyu, Mu Yueying. Evaluating the environmental efficiency of grain production from the perspective of carbon: Based on super-efficiency SBM-Undesirable model[J]. Chinese Journal of Agricultural Resources and Regional Planning, 2024, 45(3): 26-35. ]
[4]	陈宇斌, 王森, 陆杉. 农产品贸易对农业碳排放的影响——兼议数字乡村发展的门槛效应[J]. 华中农业大学学报(社会科学版), 2022(6): 45-57.
	[Chen Yubin, Wang Sen, Lu Shan. The impact of agricultural products trade on agricultural carbon emissions: The threshold effect of digital rural development[J]. Journal of Huazhong Agricultural University (Social Sciences Edition), 2022(6): 45-57. ]
[5]	李秋萍, 李长建, 肖小勇, 等. 中国农业碳排放的空间效应研究[J]. 干旱区资源与环境, 2015, 29(4): 30-35.
	[Li Qiuping, Li Changjian, Xiao Xiaoyong, et al. The spatial effects of agricultural carbon emissions in China: Based on spatial Durbin model[J]. Journal of Arid Land Resources and Environment, 2015, 29(4): 30-35. ]
[6]	West T O, Marland G. A synthesis of carbon sequestration, carbon emissions, and net carbon flux in agriculture: Comparing tillage practices in the United States[J]. Agriculture, Ecosystems & Environment, 2002, 91(1-3): 217-232.
[7]	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, 24(10): 269-273.
	[Dong Hongmin, Li Yu’e, Tao Xiuping, et al. China greenhouse gas emissions from agricultural activities and its mitigation strategy[J]. Transactions of the Chinese Society of Agricultural Engineering, 2008, 24(10): 269-273. ]
[8]	Lal R. Carbon emission from farm operations[J]. Environment International, 2004, 30(7): 981-990. pmid: 15196846
[9]	张恒硕, 李绍萍, 彭民. 中国农村能源消费碳排放区域非均衡性及驱动因素动态识别[J]. 中国农村经济, 2022(1): 112-134.
	[Zhang Hengshuo, Li Shaoping, Peng Min. Regional imbalance of carbon emissions from China’s rural energy consumption and dynamic identification of driving factors[J]. Chinese Rural Economy, 2022(1): 112-134. ]
[10]	田云, 李波, 张俊飚. 我国农地利用碳排放的阶段特征及因素分解研究[J]. 中国地质大学学报(社会科学版), 2011, 11(1): 59-63.
	[Tian Yun, Li Bo, Zhang Junbiao. Research on stage characteristics and factor decomposition of agricultural land carbon emission in China[J]. Journal of China University of Geosciences (Social Sciences Edition), 2011, 11(1): 59-63. ]
[11]	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.
	[Tian Yun, Lin Zijuan. 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. ]
[12]	Zhang M N, Li L S, Cheng Z H. Research on carbon emission efficiency in the Chinese construction industry based on a three-stage DEA-Tobit model[J]. Environmental Science and Pollution research International, 2021, 28(37): 51120-51136. doi: 10.1007/s11356-021-14298-3 pmid: 33974208
[13]	田云, 张俊飚, 吴贤荣, 等. 碳排放约束下的中国农业生产率增长与分解研究[J]. 干旱区资源与环境, 2015, 29(11): 7-12.
	[Tian Yun, Zhang Junbiao, Wu Xianrong, et al. Growth and sources of agricultural productivity in China under carbon emissions constraint[J]. Journal of Arid Land Resources and Environment, 2015, 29(11): 7-12. ]
[14]	吴昊玥, 黄瀚蛟, 何宇, 等. 中国农业碳排放效率测度、空间溢出与影响因素[J]. 中国生态农业学报, 2021, 29(10): 1762-1773.
	[Wu Haoyue, Huang Hanjiao, He Yu, et al. Measurement, spatial spillover and influencing factors of agricultural carbon emissions efficiency in China[J]. Chinese Journal of Eco-Agriculture, 2021, 29(10): 1762-1773. ]
[15]	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, 2022, 30(4): 543-557.
	[Shang Jie, Ji Xueqiang, Shi Rui, 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. ]
[16]	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 Xianrong, Zhang Junbiao, Tian Yun, et al. Provincial agricultural carbon emissions in China: Calculation, performance change and influencing factors[J]. Resources Science, 2014, 36(1): 129-138. ]
[17]	杜娅明, 白永平, 梁建设, 等. 黄河流域旅游业碳排放效率综合测度及影响因素研究[J]. 干旱区地理, 2023, 46(12): 2074-2085. doi: 10.12118/j.issn.1000-6060.2023.193
	[Du Yaming, Bai Yongping, Liang Jianshe, et al. Comprehensive measurement and influencing factors of carbon emission efficiency of tourism in the Yellow River Basin[J]. Arid Land Geography, 2023, 46(12): 2074-2085. ] doi: 10.12118/j.issn.1000-6060.2023.193
[18]	解春艳, 黄传峰, 徐浩. 环境规制下中国农业技术效率的区域差异与影响因素——基于农业碳排放与农业面源污染双重约束的视角[J]. 科技管理研究, 2021, 41(15): 184-190.
	[Xie Chunyan, Huang Chuanfeng, Xu Hao. Regional disparity and influencing factors of agricultural technology efficiency in China: Based on dual constraint of agricultural carbon and agricultural non-point source pollution[J]. Science and Technology Management Research, 2021, 41(15): 184-190. ]
[19]	田云, 王梦晨. 湖北省农业碳排放效率时空差异及影响因素[J]. 中国农业科学, 2020, 53(24): 5063-5072. doi: 10.3864/j.issn.0578-1752.2020.24.009
	[Tian Yun, Wang Mengchen. Research on spatial and temporal difference of agricultural carbon emission efficiency and its influencing factors in Hubei Province[J]. Scientia Agricultura Sinica, 2020, 53(24): 5063-5072. ] doi: 10.3864/j.issn.0578-1752.2020.24.009
[20]	朱巧娴, 梅昀, 陈银蓉, 等. 基于碳排放测算的湖北省土地利用结构效率的DEA模型分析与空间分异研究[J]. 经济地理, 2015, 35(12): 176-184.
	[Zhu Qiaoxian, Mei Yun, Chen Yinrong, et al. Regional differentiation characteristics and optimization of the structural efficiency of land use in Hubei Province based on the carbon emissions[J]. Economic Geography, 2015, 35(12): 176-184. ]
[21]	李明, 肖海峰. 畜产品进口对畜牧业碳排放的影响及其空间效应[J]. 中国农业大学学报, 2024, 29(2): 176-191.
	[Li Ming, Xiao Haifeng. Impact of livestock products import on carbon emissions from livestock industry and its spatial effect[J]. Journal of China Agricultural University, 2024, 29(2): 176-191. ]
[22]	段华平, 张悦, 赵建波, 等. 中国农田生态系统的碳足迹分析[J]. 水土保持学报, 2011, 25(5): 203-208.
	[Duan Huaping, Zhang Yue, Zhao Jianbo, et al. Carbon footprint analysis of farmland ecosystem in China[J]. Journal of Soil and Water Conservation, 2011, 25(5): 203-208. ]
[23]	Tone K. A slacks-based measure of efficiency in data envelopment analysis[J]. European Journal of Operational Research, 2001, 130(3): 498-509.
[24]	Feng Y X, He S W, Li G D. Interaction between urbanization and the eco-environment in the Pan-Third Pole region[J]. Science of the Total Environment, 2021, 789: 148011, doi: 10.1016/j.scitotenv.2021.148011.
[25]	Zhang X D, Zhang J, Yang C B. Spatio-temporal evolution of agricultural carbon emissions in China, 2000—2020[J]. Sustainability, 2023, 15(4): 3347, doi: 10.3390/su15043347.
[26]	Chen Y, Su X Y, Zhou Q. Study on the spatiotemporal evolution and influencing factors of urban resilience in the Yellow River Basin[J]. International Journal of Environmental Research and Public Health, 2021, 18(19): 10231, doi: 10.3390/ijerph181910231.
[27]	夏文浩, 王铭扬, 姜磊. 新疆农业碳排放强度时空变化趋势与收敛分析[J]. 干旱区地理, 2023, 46(7): 1145-1154. doi: 10.12118/j.issn.1000-6060.2022.455
	[Xia Wenhao, Wang Mingyang, Jiang Lei. Spatiotemporal variation trends and convergence analysis of agricultural carbon emission intensity in Xinjiang[J]. Arid Land Geography, 2023, 46(7): 1145-1154. ] doi: 10.12118/j.issn.1000-6060.2022.455
[28]	王太祥, 王腾, 吴林海. 西北干旱区农地利用碳排放与农业经济增长的响应关系[J]. 中国农业资源与区划, 2017, 38(4): 170-176.
	[Wang Taixiang, Wang Teng, Wu Linhai. Relationship between agricultural land carbon emission and economic development in the arid region of northwest China[J]. Chinese Journal of Agricultural Resources and Regional Planning, 2017, 38(4): 170-176. ]

Metrics

Viewed

Full text

155

HTML			PDF

Just accepted	Online first	Issue	Just accepted	Online first	Issue
0	0	18	0	0	137

From	Others	local

Times	117	38
Rate	75%	25%

Abstract

137

Just accepted	Online first	Issue

0	0	137

From	Others	local

Times	106	31
Rate	77%	23%

Cited

Web of Science	Crossref	ScienceDirect	Search for Citations in Google Scholar >>


This page requires you have already subscribed to WoS.

Shared

指标	变量	变量说明
投入指标	化肥投入	化肥施用折纯量/10⁴ t
	灌溉	有效灌溉面积/10³ hm²
	机械投入	农用机械总动力/kW
	牲畜投入	牛、羊数量采用各年末存栏量/10⁴头
期望产出指标	农业总产值	农林牧渔总产值/10⁴元
非期望产出指标	农业碳排放量	化肥、灌溉、动物养殖等的排放总量/10⁴ t

类别	碳排放源	碳排放系数	数据来源
农业物资	化肥施用折纯量	0.896 kg C·kg^-1	美国橡树岭国家实验室
	农用机械总动力	0.180 kg C·kW^-1	朱巧娴等^[20]
	有效灌溉面积	266.480 kg C·hm^-2	段华平等^[22]
牲畜养殖	牛	415.910 kg C·头^-1·a^-1	联合国政府间气候变化专门委员会
	羊	35.182 kg C·头^-1·a^-1	联合国政府间气候变化专门委员会

地州市	农业碳排放量/10⁷t
地州市	2000年	2007年	2014年	2020年	2000—2020年平均值
乌鲁木齐市	7.35	11.24	0.80	2.36	5.44
克拉玛依市	0.96	2.57	5.24	4.73	3.38
昌吉州	71.33	80.49	92.08	116.06	89.99
伊犁州直	158.05	184.12	63.81	73.96	119.99
塔城地区	69.50	87.03	110.48	124.99	98.00
阿勒泰地区	26.64	32.45	47.54	59.58	41.55
博州	19.05	20.77	26.51	37.33	25.92
吐鲁番市	8.54	8.12	14.07	19.27	12.50
哈密市	11.76	11.74	18.26	16.10	14.47
巴州	35.54	52.48	81.30	79.78	62.28
阿克苏地区	89.59	92.56	64.35	116.24	90.69
克州	10.16	8.11	3.75	7.64	7.42
喀什地区	103.31	135.71	43.60	84.82	91.86
和田地区	42.87	43.98	34.66	47.86	42.34
平均值	46.76	55.10	43.32	56.48	50.42
总量	654.65	771.37	606.45	790.72	705.83

地区	地州市	农业碳排放效率
地区	地州市	2000年	2007年	2014年	2020年	2000—2020年平均值	区平均值
北疆	乌鲁木齐市	0.124	0.270	1.000	1.000	0.599	0.370
	克拉玛依市	0.226	0.610	0.758	1.000	0.649
	昌吉州	0.127	0.244	0.553	0.404	0.332
	伊犁州直	0.114	0.154	0.386	0.475	0.282
	塔城地区	0.096	0.139	0.323	0.349	0.227
	阿勒泰地区	0.110	0.170	0.232	0.355	0.217
	博州	0.101	0.194	0.476	0.371	0.286
南疆	巴州	0.123	0.243	0.591	0.509	0.367	0.319
	阿克苏地区	0.099	0.156	0.461	0.502	0.305
	克州	0.084	0.135	0.235	0.283	0.184
	喀什地区	0.102	0.194	0.508	0.739	0.386
	和田地区	0.124	0.188	0.403	0.700	0.354
东疆	吐鲁番市	0.179	0.335	0.824	1.000	0.585	0.445
	哈密市	0.105	0.203	0.409	0.507	0.306	0.445
平均值		0.122	0.231	0.511	0.585	0.363
总量		1.714	3.235	7.159	8.194	5.079

地区	地州市	技术效率	技术进步	纯技术效率	规模效率	全要素生产率
北疆	乌鲁木齐市	1.284	1.116	1.255	1.022	1.433
	克拉玛依市	1.000	1.054	1.000	1.000	1.054
	昌吉州	1.134	0.997	1.000	1.134	1.131
	伊犁州直	1.162	1.024	1.000	1.162	1.189
	塔城地区	1.116	0.999	1.042	1.071	1.115
	阿勒泰地区	1.166	1.006	1.029	1.133	1.174
	博州	1.181	0.994	1.074	1.099	1.174
南疆	巴州	0.974	1.102	1.000	0.974	1.074
	阿克苏地区	1.156	1.041	1.156	1.001	1.204
	克州	0.936	1.139	0.875	1.070	1.067
	喀什地区	1.160	1.094	1.000	1.160	1.268
	和田地区	1.206	0.978	1.032	1.169	1.179
东疆	吐鲁番市	1.000	1.047	1.000	1.000	1.047
	哈密市	1.087	0.980	0.797	1.364	1.065

Spatiotemporal heterogeneity and its influencing factors of agricultural carbon emission efficiency in Xinjiang

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 13

References 28

Related Articles 15

Metrics

Comments

Recommended 0

变量名称	指标解释
农业产业结构（X₁）	农业生产总值与农林牧渔总产值之比
作物种植结构（X₂）	粮食种植面积与作物播种面积之比
耕地规模化程度（X₃）	耕地面积与农业从业人员之比
有效灌溉率（X₄）	有效灌溉面积与耕地面积之比
农业经济发展水平（X₅）	农林牧渔总产值与农村人口之比

变量	Y	X₁	X₂	X₃	X₄	X₅
Y	1.000	-0.126	-0.381	0.170	-0.097	0.466
X₁	-0.126	1.000	-0.003	-0.086	0.059	-0.411
X₂	-0.381	-0.003	1.000	-0.083	-0.030	-0.371
X₃	0.170	-0.086	-0.083	1.000	-0.020	0.332
X₄	-0.097	0.059	-0.030	-0.020	1.000	-0.055
X₅	0.466	-0.411	-0.371	0.332	-0.055	1.000

变量	系数	标准误差	Z值	P值	95%置信区间
X₁	-0.346	0.188	-1.840	0.066	[-0.714, 0.022]
X₂	-0.245	0.081	-3.030	0.002	[-0.403, -0.087]
X₃	0.013	0.020	0.670	0.504	[-0.025, 0.051]
X₄	-0.008	0.004	-1.900	0.058	[-0.016, 0.000]
X₅	0.011	0.002	6.040	0.000	[0.008, 0.015]
常数项	0.601	0.125	4.810	0.000	[0.356, 0.845]

[1]	LU Han, ZENG Yongnian, WANG Pancheng. Spatiotemporal variation of actual evapotranspiration and its influencing factors in the northeast Qinghai-Xizang Plateau [J]. Arid Land Geography, 2025, 48(5): 753-764.
[2]	LI Mengran, XU Xiaoren, WANG Liang, DUAN Jian, SHI Shuqi, REN Dandan. Spatial-temporal characteristics and influencing factors of agricultural carbon emissions in the Yellow River Basin [J]. Arid Land Geography, 2025, 48(5): 854-865.
[3]	WANG Liqi, LI Guozhu. Spatial-temporal characteristics and influencing factors of urban ecological resilience in China [J]. Arid Land Geography, 2025, 48(5): 893-904.
[4]	PANG Jiapeng, LI Mengyuan. Spatial differences and causes of tourism and leisure blocks in China [J]. Arid Land Geography, 2025, 48(5): 905-915.
[5]	LI Weilu, ZHANG Mingdou. Coordinated study of urban population agglomeration and land ecological resilience in the Yellow River Basin [J]. Arid Land Geography, 2025, 48(4): 728-738.
[6]	LI Songrui, LIN Qiuping, YANG Shangguang. Multi-scale evolution characteristics and influencing factors of spatial layout of logistics enterprises in Xinjiang [J]. Arid Land Geography, 2025, 48(4): 739-752.
[7]	YANG Xiaoya, YU Kunxia, LI Zhanbin, LI Peng, LIU Yonggang, MO Shuhong, YANG Jianhong. Regional differences and threshold of ecological base flow in the Qinling Mountains-Loess Plateau region [J]. Arid Land Geography, 2025, 48(3): 380-390.
[8]	WANG Fuhong, XIA Yong. Spatio-temporal pattern evolution and influencing factors of main crops production in arid region: A case of Xinjiang [J]. Arid Land Geography, 2025, 48(3): 444-454.
[9]	ZHANG Jie, QU Jianjun, CHEN Hai, SHI Jinxin, MA Yuhe, LIU Di. Spatial and temporal evolution and influencing factors of ecological security pattern based on circuit theory: A case of Loess Plateau in northern Shaanxi [J]. Arid Land Geography, 2025, 48(3): 494-505.
[10]	FU Xiao, HUANG Yingmin. Spatial pattern and influencing factors of high-quality development in China’s old revolutionary areas from the perspective of main functions [J]. Arid Land Geography, 2025, 48(3): 517-527.
[11]	LI Mengyuan, PANG Jiapeng, LI Huan. Coordinated development of comprehensive accessibility of provincial typical tourism distribution centers and their spatial relationship: A case of Xinjiang [J]. Arid Land Geography, 2025, 48(3): 539-548.
[12]	ZHU Yiting, ZHAO Chen, CAO Kaijun, LIANG Guixian, YAO Hao. Influencing factors of recreation satisfaction in national mining park [J]. Arid Land Geography, 2025, 48(3): 549-558.
[13]	Jianiya YERKEN, HOU Jiannan, LIU Sibo. Spatio-temporal characterization of tourism climate comfort in Xinjiang prefectures and cities in the last 30 years [J]. Arid Land Geography, 2025, 48(2): 212-222.
[14]	TANG Yandong, ZANG Cuiping, YU Yunpeng, YU Qinglin. Developmental characteristics and influencing factors of gullies based on fractal theory in eastern Gansu Province [J]. Arid Land Geography, 2025, 48(2): 223-233.
[15]	GUO Jiali, DU Hongru. Network pattern of oasis cities in Xinjiang from the perspective of multiple flows [J]. Arid Land Geography, 2025, 48(2): 323-332.