中国西北生态脆弱区农户清洁能源使用的脆弱性及影响因素

doi:10.12118/j.issn.1000-6060.2025.109

Abstract

Abstract:

Accelerating the transition from traditional solid-fuel energy to clean energy is an inevitable choice for rural areas in ecologically fragile regions to cope with climate change, strengthen environmental governance, and promote interregional sustainable development. However, under passive participation in clean energy reform policies, rural households in ecologically fragile areas of northwest China, which generally have relatively low economic capacity, often exhibit vulnerability phenomena, whereby modern clean energy equipment is “modified but not used” “basically not used” or “used at a low level”. To address this issue, we adopted a reverse energy-transition perspective and conducted field research in 13 counties (districts), covering 2002 rural households across 180 villages in Shaanxi, Gansu, Ningxia and Qinghai regions of China, and established an “exposure-sensitivity-adaptability” model to comprehensively assess the vulnerability of rural households to clean energy use. In addition, a multiple Logit model was used to analyze the influencing factors of vulnerability across three levels: economy, society, and household. The results show that (1) The proportions of rural households in the ecologically fragile areas of northwest China with low, medium, and high vulnerability to clean energy use are 26.12%, 46.55%, and 27.33%, respectively, and there is significant spatial heterogeneity in vulnerability. (2) Factors such as cultivated land area, energy subsidy policies, social networks, age, livelihood type, and household size significantly influence vulnerability. (3) The effects of influencing factors vary across different ecologically fragile regions. Therefore, based on the vulnerability characteristics of clean energy use among rural households in different ecologically fragile areas, the government should implement differentiated, region-specific energy subsidy policies and promotion strategiesaccording to local conditions to consolidate the achievements of clean energy reform policies.

Key words: rural households, sustained use of clean energy, vulnerability, “exposure-sensitivity-adaptability” model, ecologically fragile areas, northwest China

LI Lingyan, WANG Mengmeng, XIA Haoming, DUAN Mimi. Vulnerability and influencing factors of clean energy use of rural households in ecologically fragile areas of northwest China[J].Arid Land Geography, 2026, 49(1): 164-175.

Figures/Tables 11

Fig. 1

Tab. 1

Vulnerability assessment indicator system of clean energy use of rural households"

维度	一级指标层	二级指标层	赋值	方向	权重
暴露度	供暖成本	供暖成本增幅（E₁）	“非常小”至“非常大”依次赋值1~5	+	0.031
	能源易用性	能源获取便捷性（E₂）	“非常便捷”至“非常不便捷”依次赋值1~5	+	0.032
		设备维护易操作性（E₃）	“非常容易”至“非常不容易”依次赋值1~5	+	0.033
		设备操作便捷性（E₄）	“非常便捷”至“非常不便捷”依次赋值1~5	+	0.035
	自然环境	温湿指数（E₅）	60~65=1（很舒适）；56~60或65~70=2；50~56或70~75=3； 45~50或75~80=4；40~45或80~85=5；32~40或85~90=6； <32或>90=7（很不舒适）	+	0.082
	自然环境	植被覆盖率（E₆）	>60%=1；45%~60%=2；30%~45%=3；<30%=4	+	0.068
敏感性	认知水平	受教育程度（S₁）	大专及以上=1；高中或中专技校=2；中学=3；小学及以下=4	+	0.006
	认知水平	生计类型（S₂）	务工或个体经营=1；务农兼务工=2；务农=3；失业=4	+	0.019
	经济水平	家庭年总收入（S₃）	1×10⁵元以上=1；5×10⁴~1×10⁵元=2； 3×10⁴~5×10⁴元=3； 1×10⁴~3×10⁴元=4； 1×10⁴元以下=5	+	0.015
		家庭耕地面积（S₄）	>0.40 hm²=1；0.20~0.40 hm²=2；0.10~0.20 hm²=3； 0.03~0.10 hm²=4；<0.03 hm²=5	+	0.113
		房屋占地面积（S₅）	>240 m²=1；160~240 m²=2；80~160 m²=3；30~80 m²=4；<30 m²=5	+	0.007
	价格感知	设备价格接受度（S₆）	“非常接受”至“非常不接受”依次赋值1~5	+	0.029
	价格感知	设备维护费用接受度（S₇）	“非常接受”至“非常不接受”依次赋值1~5	+	0.042
	心理成本	传统能源改变难度（S₈）	“非常小”至“非常大”依次赋值1~5	+	0.040
		能源转型感知损失度（S₉）	“非常小”至“非常大”依次赋值1~5	+	0.032
		能源设备故障担忧（S₁₀）	“非常小”至“非常大”依次赋值1~5	+	0.039
适应能力	生态价值	转型后室内烟尘量（A₁）	“非常大”至“非常小”依次赋值1~5	-	0.046
		转型后空气质量提升（A₂）	“非常小”至“非常大”依次赋值1~5	-	0.062
		转型后村庄面貌改善（A₃）	“非常小”至“非常大”依次赋值1~5	-	0.063
	个人规范	减少化石能源责任感（A₄）	“非常小”至“非常大”依次赋值1~5	-	0.042
		环保责任感（A₅）	“非常小”至“非常大”依次赋值1~5	-	0.050
		能源升级意识（A₆）	“非常小”至“非常大”依次赋值1~5	-	0.047
	政策满意度	清洁能源推广满意度（A₇）	“非常不满意”至“非常满意”依次赋值1~5	-	0.021
		补贴政策满意度（A₈）	“非常不满意”至“非常满意”依次赋值1~5	-	0.022
		后续服务政策满意度（A₉）	“非常不满意”至“非常满意”依次赋值1~5	-	0.024

Tab. 1

Tab. 2

Tab. 3

Fig. 2

Tab. 4

Fig. 3

Fig. 4

Tab. 5

Tab. 6

Fig. 5

References 37

[1]	韩晓, 魏楚, 吴施美. 中国农村居民生物质能消费估计[J]. 资源科学, 2023, 45(9): 1817-1829. doi: 10.18402/resci.2023.09.09
	[Han Xiao, Wei Chu, Wu Shimei. Estimation of biomass energy consumption in rural China[J]. Resources Science, 2023, 45(9): 1817-1829.] doi: 10.18402/resci.2023.09.09
[2]	张增凯, 彭彬彬, 解伟, 等. 能源转型与管理领域的科学研究问题[J]. 管理科学学报, 2021, 24(8): 147-153.
	[Zhang Zengkai, Peng Binbin, Xie Wei, et al. Scientific research issues in the field of energy transition and management[J]. Journal of Management Science in China, 2021, 24(8): 147-153.]
[3]	沈国锋, 熊瑞, 程和发, 等. 青藏农村生活能源结构及一次PM_2.5排放估算[J]. 科学通报, 2021, 66(15): 1900-1911.
	[Shen Guofeng, Xiong Rui, Cheng Hefa, et al. Rural residential energy carrier structure and primary PM_2.5 emissions from the Qinghai-Tibet Plateau[J]. Chinese Science Bulletin, 2021, 66(15): 1900-1911.]
[4]	畅华仪, 张俊飚, 何可. 村庄吸引力对农村家庭生活能源清洁转型的影响——来自非正式就业的机制解释[J]. 资源科学, 2023, 45(2): 388-402. doi: 10.18402/resci.2023.02.12
	[Chang Huayi, Zhang Junbiao, He Ke. The effect of village attraction on rural household clean energy transition: An explanation from informal off-farm employment[J]. Resources Science, 2023, 45(2): 388-402.] doi: 10.18402/resci.2023.02.12
[5]	EllisonC, Li Y, Yu F, et al. Household transitions to clean energy in a multiprovincial cohort study in China[J]. Nature Sustainability, 2020, 3(1): 42-50. doi: 10.1038/s41893-019-0432-x
[6]	贺克斌, 李雪玉. 中国散煤综合治理研究报告2023[R]. 北京: 北京大学能源研究院, 2023.
	[He Kebin, Li Xueyu. China dispersed coalmanagementreport 2023[R]. Beijing: Institute of Energy, Peking University, 2023.]
[7]	鲍超, 徐牧天. 西北地区投入产出效率的综合测度与时空变化[J]. 干旱区地理, 2021, 44(6): 1772-1783. doi: 10.12118/j.issn.1000–6060.2021.06.25
	[Bao Chao, Xu Mutian. Comprehensive measurement and spatiotemporal variations of input-output efficiency in northwest China[J]. Arid Land Geography, 2021, 44(6): 1772-1783.] doi: 10.12118/j.issn.1000–6060.2021.06.25
[8]	Duan M M, Li L Y, Liu X J, et al. Turning awareness into behavior: Meta-analysis of household residential life energy transition behavior from the dual perspective of internal driving forces and external inducing forces[J]. Energy, 2023, 279: 128072, doi: 10.1016/j.energy.2023.128072.
[9]	Foster V, Trotter P A, Werner S, et al. Development transitions for fossil fuel-producing low and lower-middle income countries in a carbon-constrained world[J]. Nature Energy, 2024, 9(3): 242-250. doi: 10.1038/s41560-023-01440-3
[10]	刘平阔, 卢存禹. 中国能源转型路径选择的影响因素: 理论检验与实证分析[J]. 中国软科学, 2022(6): 51-61.
	[Liu Pingkuo, Lu Cunyu. Influencing factors of the pathway selection for China’s energy transition: Theoretical verification and empirical analysis[J]. China Soft Science, 2022(6): 51-61.]
[11]	庄明浩, 鲁玺, 王艳芬, 等. 青藏高原牧区家庭能源消费对生态环境和人体健康的影响研究现状与展望[J]. 生态学报, 2023, 43(5): 1775-1783.
	[Zhuang Minghao, Lu Xi, Wang Yanfen, et al. Research status and prospect of household energy consumption impact on eco-environment and human health in the pastoral of Qinghai-Xizang Plateau[J]. Acta Ecologica Sinica, 2023, 43(5): 1775-1783.]
[12]	高鸣, 魏佳朔. 促进农民农村共同富裕: 历史方位和实现路径[J]. 中国软科学, 2022(8): 45-57.
	[Gao Ming, Wei Jiashuo. Promoting farmers and rural areas to achieve common prosperity: Historical orientation and realization path[J]. China Soft Science, 2022(8): 45-57.]
[13]	Pachauri R K, Allen M R, Barros V R, et al. Climate change 2014 synthesis report. Contribution of working groups I, II and III to the fifth assessment report of the intergovernmental panel on climate change[M]. Geneva: IPCC, 2014: 151.
[14]	Polsky C, Neff R, Yarnal B. Building comparable global change vulnerability assessments: The vulnerability scoping diagram[J]. Global Environmental Change, 2007, 17(3-4): 472-485. doi: 10.1016/j.gloenvcha.2007.01.005
[15]	中华人民共和国生态环境部. 全国生态脆弱区保护规划纲要[EB/OL]. [2008-09-27]. https://www.mee.gov.cn/gkml/hbb/bwj/200910/t20091022_174613.htm.
	[Ministry of Ecology and Enviroment National of the People’s Republic of China. Outline of national ecological fragile area protection plan[EB/OL]. [2008-09-27]. https://www.mee.gov.cn/gkml/hbb/bwj/200910/t20091022_174613.htm. ]
[16]	姜璐. 青藏高原农村家庭能源消费与能源贫困研究——以青海省为例[D]. 兰州: 兰州大学, 2019.
	[Jiang Lu. Rural household energy consumption and energy poverty in the Qinghai-Tibet Plateau: Case of Qinghai Province[D]. Lanzhou: Lanzhou University, 2019.]
[17]	Fan S Y, Zha S, Zhao C X, et al. Using energy vulnerability to measure distributive injustice in rural heating energy reform: A case study of natural gas replacing bulk coal for heating in Gaocheng District, Hebei Province, China[J]. Ecological Economics, 2022, 197: 107456, doi: 10.1016/j.ecolecon.2022.107456.
[18]	陶澍, 沈国锋, 沈惠中, 等. 中国生活部门固体燃料消耗的排放贡献和健康风险的区域性差异[R]. 北京: 北京大学, 2024.
	[Tao Shu, Shen Guofeng, Shen Huizhong, et al. Regional differences in emission contributions and health risks from solid fuel consumption in China’s residential sector[R]. Beijing: Peking University, 2024.]
[19]	Xu S Q, Wang R, Gasser T, et al. Delayed use of bioenergy crops might threaten climate and food security[J]. Nature, 2022, 609(7926): 299-306. doi: 10.1038/s41586-022-05055-8
[20]	Sheha M, Mohammadi K, Powell K. Techno-economic analysis of the impact of dynamic electricity prices on solar penetration in a smart grid environment with distributed energy storage[J]. Applied Energy, 2021, 282: 116168, doi: 10.1016/j.apenergy.2020.116168.
[21]	张大永, 姬强, 李佳伽. 中国家庭能源消费: 现状、挑战与未来[M]. 成都: 西南财经大学出版社, 2023: 63-80.
	[Zhang Dayong, Ji Qiang, Li Jiajia. China’s household energy consumption: Current situation, challenges and future[M]. Chengdu: Southwestern University of Finance and Economics Press, 2023: 63-80.]
[22]	滕玉华. 农村居民应用和推广清洁能源意愿影响因素研究——采用江西省695份样本数据的经验分析[J]. 西部论坛, 2018, 28(3): 17-24.
	[Teng Yuhua. Study on influencing factors of the willingness of rural residents to use clean energy: Empirical analysis based on 695 sample data of Jiangxi Province[J]. West Forum, 2018, 28(3): 17-24.]
[23]	Carley S, Evans T P, Graff M, et al. A framework for evaluating geographic disparities in energy transition vulnerability[J]. Nature Energy, 2018, 3(8): 621-627. doi: 10.1038/s41560-018-0142-z
[24]	姜璐, 刘艳娟, 史晓楠, 等. 基于物质流的青海高原城镇社区家庭能源消费研究——以西宁市为例[J]. 干旱区地理, 2023, 46(2): 294-304. doi: 10.12118/j.issn.1000-6060.2022.172
	[Jiang Lu, Liu Yanjuan, Shi Xiaonan, et al. Household energy consumption in urban communities in Qinghai Plateau based on material flow: A case of Xining City[J]. Arid Land Geography, 2023, 46(2): 294-304.] doi: 10.12118/j.issn.1000-6060.2022.172
[25]	吴施美, 郑新业. 收入增长与家庭能源消费阶梯——基于中国农村家庭能源消费调查数据的再检验[J]. 经济学(季刊), 2022, 22(1): 45-66.
	[Wu Shimei, Zheng Xinye. Revisit of household energy ladder: Empirical evidence from a household survey in rural China[J]. China Economic Quarterly, 2022, 22(1): 45-66.]
[26]	Ajzen I. The theory of planned behavior[J]. Organizational Behavior and Human Decision Processes, 1991, 50(2): 179-211. doi: 10.1016/0749-5978(91)90020-T
[27]	王火根, 梁弋雯. 基于扎根理论农村清洁能源推广影响因素研究[J]. 科技管理研究, 2018, 38(11): 234-239.
	[Wang Huogen, Liang Yiwen. Analysis on factors affecting promotion of clean energy in the countryside based on the grounded theory[J]. Science and Technology Management Research, 2018, 38(11): 234-239.]
[28]	Zhu H G, Fang S Y, Zhang S P, et al. Effects of social capital on energy poverty: Evidence from the national key ecological function zones in northeast China[J]. Energy, 2024, 304: 131956, doi: 10.1016/j.energy.2024.131956.
[29]	畅华仪, 何可, 张俊飚. 挣扎与妥协: 农村家庭缘何陷入能源贫困“陷阱”[J]. 中国人口·资源与环境, 2020, 30(2): 11-20.
	[Chang Huayi, He Ke, Zhang Junbiao. Energy poverty in rural China: A psychological explanations base on households[J]. China Population, Resources and Environment, 2020, 30(2): 11-20.]
[30]	Geng J C, Long R Y, Chen H, et al. Exploring the motivation-behavior gap in urban residents’ green travel behavior: A theoretical and empirical study[J]. Resources, Conservation and Recycling, 2017, 125: 282-292. doi: 10.1016/j.resconrec.2017.06.025
[31]	韩振, 彭超, 刘合光. 政府保障、社会监督与农村居民生活垃圾集中处理行为——基于183村1365份农户调查数据的分析[J]. 农村经济, 2023(10): 73-82.
	[Han Zhen, Peng Chao, Liu Heguang. Government guarantee, social supervision and rural residents’ domestic waste concentrated disposal behavior: Based on the survey data of 1365 households in 183 villages[J]. Rural Economy, 2023(10): 73-82.]
[32]	Neves C, Oliveira T. Drivers of consumers’ change to an energy-efficient heating appliance (EEHA) in households: Evidence from five European countries[J]. Applied Energy, 2021, 298: 117165,doi: 10.1016/j.apenergy.2021.117165.
[33]	秦格霞, 孟治元, 李妮. 黄土高原水分利用效率动态及其对干旱和地表温度的响应[J]. 干旱区地理, 2024, 47(11): 1887-1898. doi: 10.12118/j.issn.1000-6060.2023.719
	[Qin Gexia, Meng Zhiyuan, Li Ni. Dynamics of water use efficiency and its response to drought and land surface temperature on the Loess Plateau[J]. Arid Land Geography, 2024, 47(11): 1887-1898.] doi: 10.12118/j.issn.1000-6060.2023.719
[34]	马明德, 李俊杰, 薛晨皓. 宁夏区域发展对环境胁迫的时空演变及驱动机制分析[J]. 干旱区地理, 2024, 47(6): 1061-1072. doi: 10.12118/j.issn.1000-6060.2023.318
	[Ma Mingde, Li Junjie, Xue Chenhao. Spatiotemporal evolution and driving mechanism of environmental stress of regional development in Ningxia Hui Autonomous Region[J]. Arid Land Geography, 2024, 47(6): 1061-1072.] doi: 10.12118/j.issn.1000-6060.2023.318
[35]	Cao Z, Meng Q, Gao B Z. The consumption patterns and determining factors of rural household energy: A case study of Henan Province in China[J]. Renewable and Sustainable Energy Reviews, 2021, 146: 111142, doi: 10.1016/j.rser.2021.111142.
[36]	Yang Y, Xia S Y, Huang P, et al. Energy transition: Connotations, mechanisms and effects[J]. Energy Strategy Reviews, 2024, 52: 101320, doi: 10.1016/j.esr.2024.101320.
[37]	滕玉华, 刘长进, 陈燕, 等. 基于结构方程模型的农户清洁能源应用行为决策研究[J]. 中国人口·资源与环境, 2017, 27(9): 186-195.
	[Teng Yuhua, Liu Changjin, Chen Yan, et al. Decision research on rural residents’ clean energy applied behavior based on a SEM model[J]. China Population, Resources and Environment, 2017, 27(9): 186-195.]

维度	变量		赋值	样本均值
因变量	农户清洁能源使用的脆弱性（y）		低脆弱性=1；中脆弱性=2；高脆弱性=3	2.00
自变量	经济层面	家庭收入（x₁）	1×10⁴元以下=1；1×10⁴~3×10⁴元=2；3×10⁴~5×10⁴元=3；5×10⁴~1×10⁵元=4；1×10⁵元以上=5	2.60
	经济层面	耕地面积（x₂）	<0.03 hm²=1；0.03~0.10 hm²=2；0.10~0.20 hm²=3；0.20~0.40 hm²=4；>0.40 hm²=5	4.14
	社会层面	能源补贴政策（x₃）	“非常不满意”至“非常满意”依次赋值1~5	3.00
	社会层面	社会网络（x₄）	受邻居影响：“非常小”至“非常大”依次赋值1~5	3.97
	家庭层面	性别（x₅）	女=0；男=1	0.59
		年龄（x₆）	20岁以下=1；20岁~29岁=2；30~39岁=3；40~49岁=4；50~59岁=5；60岁以上=6	4.56
		生计类型（x₇）	务农或失业=1；务农兼打工=2；务工（包括个体经营）=3；企事业单位人员（包括村干部）=4；其他=5	1.74
		受教育程度（x₈）	小学及以下=1；初中毕业=2；高中/中专/职专毕业=3；大专及以上=4	1.39
		党员数量（x₉）	没有=0；有=1	0.13
		家庭规模（x₁₀）	家庭常住人口数量/人	3.60

聚类结果	脆弱性分布		脆弱性指数
聚类结果	农户数量/户	农户占比/%	取值范围	均值
低度脆弱性	522	26.12	-0.068~0.121	0.083
中度脆弱性	933	46.55	0.121~0.200	0.158
高度脆弱性	547	27.33	0.200~0.392	0.243

生态脆弱区	暴露度指数		敏感性指数		适应能力指数		脆弱性指数
生态脆弱区	指数	排序	指数	排序	指数	排序	指数	排序
黄土高原	0.142	1	0.133	2	0.125	1	0.149	3
沙漠	0.140	2	0.129	3	0.098	3	0.171	2
青藏高原	0.134	3	0.148	1	0.100	2	0.181	1

变量	总样本		黄土高原生态脆弱区		沙漠生态脆弱区		青藏高原生态脆弱区
变量	B	Exp(B)	B	Exp(B)	B	Exp(B)	B	Exp(B)
x₁	-0.074	0.929	-0.032	0.969	-0.188	0.829	-0.359^***	0.698
x₂	-0.822^***	0.440	-1.000^***	0.368	-0.841^***	0.431	-0.608^***	0.544
x₃	-0.359^***	0.698	-0.445^***	0.641	-0.003	0.997	-0.396^***	0.673
x₄	0.538^***	1.713	0.608^***	1.837	0.508^***	1.662	0.453^***	1.573
x₅	-0.074	0.929	-0.004	0.996	-0.176	0.839	-0.178	0.837
x₆	0.308^***	1.361	0.338^***	1.402	0.534^***	1.706	0.142^*	1.153
x₇	-0.179^***	0.836	-0.354^***	0.702	-0.206	0.814	-0.226^*	0.798
x₈	-0.119	0.888	-0.121	0.886	-0.333^*	0.717	-0.091	0.913
x₉	-0.115	0.891	-0.030	0.970	-0.187	0.829	-0.578	0.561
x₁₀	0.063^**	1.065	0.042	1.043	0.003	1.003	0.162^**	1.176

变量	更换自变量回归		缩小研究样本回归
变量	B	Exp(B)	B	Exp(B)
x₁	-0.163^***	0.850	-0.054	0.947
x₂	0.099	1.104	-0.673^***	0.510
x₃	-0.367^***	0.693	-0.276^***	0.759
x₄	0.515^***	1.674	0.421^***	1.523
x₅	-0.166^*	0.847	-0.065	0.937
x₆	0.261^***	1.298	0.267^***	1.306
x₇	-0.207^***	0.813	-0.187^**	0.829
x₈	-0.151^**	0.860	-0.084	0.919
x₉	-0.139	0.870	-0.025	0.975
x₁₀	0.050^*	1.051	0.110^*	1.116

Vulnerability and influencing factors of clean energy use of rural households in ecologically fragile areas of northwest China

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 11

References 37

Related Articles 15

Metrics

Comments

Recommended 0

[1]	ZHENG Menglin, ZHAO Yong, YANG Xia. Interdecadal changes and associated circulations in the dominant modes of summer rainfall anomaly in the arid region of northwest China [J]. Arid Land Geography, 2025, 48(9): 1511-1520.
[2]	YU Han, MENG Zhihua, WANG Jing’ai. Comprehensive assessment and regionalization of social vulnerability for natural disasters in Gansu Province [J]. Arid Land Geography, 2025, 48(8): 1421-1431.
[3]	HAN Yuchen, SUN Qinke, ZHOU Liang, LI Yu’ang. Spatial synergistic evolution of oasis and oasis cities in arid zones in the process of urbanization and analysis of their patterns [J]. Arid Land Geography, 2025, 48(8): 1469-1479.
[4]	LI Zhi, SU Yang, SHU Qin. Static-dynamic matching of ecosystem service supply and demand and ecological management zoning in northwest China [J]. Arid Land Geography, 2025, 48(6): 1115-1126.
[5]	SONG Xiaolong, LI Longtang, REN Jie, WU Yue, WANG Peng, MI Wenbao, MA Mingde. Spatio-temporal variation characteristics and driving factors of NDVI in the arid and semi-arid region of northwest China [J]. Arid Land Geography, 2025, 48(6): 951-962.
[6]	YANG Xuemei, WANG Ranghui, LIU Chunwei. Assessment and prediction of water resource vulnerability in Kekeya area under the future multi-scenario model [J]. Arid Land Geography, 2025, 48(4): 640-648.
[7]	ZHENG Menglin, ZHAO Yong, YANG Xia. Variation characteristics of summer precipitation in the arid region of northwest China from 1961 to 2022 [J]. Arid Land Geography, 2025, 48(3): 367-379.
[8]	LI Kangning, LIN Yilin, ZHAO Junsan, WANG Jian, GE Feng. Driving mechanisms of vegetation change and ecological vulnerability in the Three-River Headwater Region [J]. Arid Land Geography, 2025, 48(2): 283-295.
[9]	DENG Wenbin, SONG Sen, YI Hongmei. Spatiotemporal dynamics of ecological quality in the Zhundong region based on an arid modified remote sensing ecological index model [J]. Arid Land Geography, 2025, 48(12): 2073-2086.
[10]	LIN Mofei, GUAN Yawen, LIAN Yifei. Ecological vulnerability assessment of Tarim Populus euphratica Forest Park based on SRP model [J]. Arid Land Geography, 2025, 48(11): 2019-2030.
[11]	TIAN Jinhua, HUANG Xiao, GAO Yayu, HAO Jianbin, WU Guanheng, HE Wenbo. Ecological benefits of inter-basin water transfer in arid ecological migration regions of northwest China: A case of Huanghuatan ecological immigrant area [J]. Arid Land Geography, 2025, 48(11): 1926-1938.
[12]	ZHU Aiai, YIN Songkui, LIU Qionghui. Spatial and temporal differentiation and influencing factors of agricultural ecological efficiency in northwest China [J]. Arid Land Geography, 2024, 47(7): 1210-1219.
[13]	HUANG Manjie, LI Yanzhong, WANG Yuangang, YU Zhiguo, ZHUANG Jiacheng, XING Yincong. Evaluation of meteorological drought performance of multisource remote-sensing precipitation products in arid northwest China [J]. Arid Land Geography, 2024, 47(4): 549-560.
[14]	BAI Yang, TAN Li’na, LIU Xiaoyan, LU Wen. Integration path and influence effect of tourism economy in northwest China [J]. Arid Land Geography, 2024, 47(12): 2124-2134.
[15]	BAO Wei, HUANG Xiaojun, JI Wangdi. Evaluation of heat vulnerability and its spatial-temporal variation in the Guanzhong area [J]. Arid Land Geography, 2024, 47(11): 1863-1875.