新疆土地利用强度与碳排放协调发展及多情景模拟

doi:10.13866/j.azr.2025.08.13

Abstract

Abstract:

Exploring the synergistic relationship between land-use intensity and carbon emissions in arid regions with fragile ecological foundations is of practical significance for optimizing the allocation of regional land resources and achieving “dual carbon” goals. Based on land use and energy consumption data from 2000, 2005, 2010, 2015, and 2020, this study employs a land-use carbon emission accounting model, coordination degree model, FLUS model, and Gray Forecast Model to explore the spatiotemporal differentiation and coordinated development level of land-use intensity and carbon emissions in Xinjiang and areas with elevation <1500 m above sea level. Furthermore, the study simulates evolution trends under four scenarios in 2030. The results show that:(1) From 2000 to 2020, the land-use intensity index of Xinjiang increased by 3.2, whereas in areas with elevation <1500 m above sea level, it increased by 4.5, indicating a faster growth rate in these areas. (2) From 2000 to 2020, land-use carbon emissions in Xinjiang increased by 1.70×10⁸t, with more than 95% of the total emissions originating from areas below 1500 m. Moreover, high-emission zones exhibited a significant spillover effect on adjacent low-emission zones. (3) From 2000 to 2020, the coordination coefficient between land-use intensity and carbon emissions in areas with elevation <1500 m above sea level was consistently higher than that of the whole Xinjiang, although this primarily reflected an extensive balance of “high development-high emissions”. (4) Projections for 2030 indicate that under the Ecological Protection Scenario, a better balance between development and reduction in carbon emission could be achieved through the expansion of ecological land. In contrast, the Strategic Development Scenario would yield the largest carbon emission increment, reflecting continued economic reliance on energy consumption. These findings indicate the need for Xinjiang to further integrate economic development with ecological conservation strategies to effectively achieve sustainable development.

Key words: land use, carbon emissions, coordinated development, FLUS model, Xinjiang

GUAN Yiheng, MENG Mei, YANG Songxiao, LI Daqiang. Coordinated development and multi-scenario simulation of land use intensity and carbon emissions in Xinjiang[J].Arid Zone Research, 2025, 42(8): 1501-1513.

Figures/Tables 11

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References 34

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数据类型	数据名称	数据来源	空间分辨率
土地利用数据	2000—2020年土地利用遥感数据	中国科学院资源环境科学数据平台（https://www.resdc.cn/）	30 m×30 m
能源消耗数据	2000—2020年新疆能源消耗量	《中国能源统计年鉴》《新疆统计年鉴》	-
驱动因子数据	高程	地理空间数据云（https://www.gscloud.cn/）基于ArcGIS 10.8对高程数据空间分析得出	30 m×30 m
	坡度
	坡向
	年均气温	国家青藏高原科学数据中心（https://data.tpdc.ac.cn/）	1000 m×1000 m
	年降水量	国家青藏高原科学数据中心（https://data.tpdc.ac.cn/）	1000 m×1000 m
	到国道距离	全国地理信息资源目录服务系统（http://www.webmap.cn/）基于ArcGIS 10.8欧氏距离分析得出	1000 m×1000 m
	到省道距离
	到高速距离
	到铁路距离
	到水系距离
	夜间灯光	中国科学院资源环境科学数据平台（https://www.resdc.cn/）	1000 m×1000 m

能源类型	折标准煤系数	碳排放系数/（t·t^-1）
原煤	0.7143 kgce·t^-1	0.7559
焦炭	0.9714 kgce·t^-1	0.8550
原油	1.4286 kgce·t^-1	0.5857
汽油	1.4714 kgce·^t-1	0.5538
煤油	1.4714 kgce·t^-1	0.5714
柴油	1.4571 kgce·t^-1	0.5921
燃料油	1.4286 kgce·t^-1	0.6185
天然气	1.3300 kgce·m^-3	0.4483
电力	0.1229 kgce·kWh^-1	0.7330

协调度区间	协调度类别	协调度类型	解释说明
0.0~0.5	严重失调	失调衰退区	土地利用强度与碳排放的增长为失调衰退状态
0.5~0.6	轻度失调	失调衰退区	土地利用强度与碳排放的增长为失调衰退状态
0.6~0.7	濒临失调	磨合协调区	土地利用强度与碳排放的增长处于调和状态
0.7~0.8	勉强协调	磨合协调区	土地利用强度与碳排放的增长处于调和状态
0.8~0.9	基本协调	协调发展区	土地利用强度与碳排放协调增长且速度较快
0.9~1.0	良好协调	协调发展区	土地利用强度与碳排放协调增长且速度较快

	自然发展情景（NDS）						战略发展情景（SDS）						粮食安全情景（FSS）						生态保护情景（EPS）
	A	B	C	D	E	F	A	B	C	D	E	F	A	B	C	D	E	F	A	B	C	D	E	F
A	1	1	1	1	1	0	1	0	0	0	0	0	1	0	0	0	0	0	1	1	1	1	1	1
B	1	1	1	0	1	0	1	1	0	0	1	0	1	1	0	0	0	0	0	1	0	0	0	0
C	1	1	1	0	1	1	1	0	1	0	1	0	1	0	1	0	0	0	0	1	1	0	0	0
D	0	0	1	1	1	1	0	0	0	1	1	0	1	0	0	1	0	0	0	0	0	1	0	0
E	1	1	1	1	1	0	0	0	0	0	1	0	1	0	0	0	1	0	0	0	0	0	1	1
F	1	1	0	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1

时段及情景模拟时段	失调衰退区占比/%	磨合协调区占比/%	协调发展区占比/%	协调系数
2000—2005年	3	57	40	0.700
2005—2010年	8	43	49	0.715
2010—2015年	5	62	33	0.721
2015—2020年	6	79	15	0.732
2000—2020年	6	53	41	0.724
2020—2030年NDS	5	70	25	0.741
2020—2030年SDS	7	73	20	0.748
2020—2030年FSS	5	71	24	0.745
2020—2030年EPS	9	69	22	0.739

Coordinated development and multi-scenario simulation of land use intensity and carbon emissions in Xinjiang

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	自然发展情景（NDS）						战略发展情景（SDS）						粮食安全情景（FSS）						生态保护情景（EPS）
	A	B	C	D	E	F	A	B	C	D	E	F	A	B	C	D	E	F	A	B	C	D	E	F
A	1	1	1	1	1	0	1	0	0	0	0	0	1	0	0	0	0	0	1	1	1	1	1	1
B	1	1	1	0	1	0	1	1	0	0	1	0	1	1	0	0	0	0	0	1	0	0	0	0
C	1	1	1	0	1	1	1	0	1	0	1	0	1	0	1	0	0	0	0	1	1	0	0	0
D	0	0	1	1	1	1	0	0	0	1	1	0	1	0	0	1	0	0	0	0	0	1	0	0
E	1	1	1	1	1	0	0	0	0	0	1	0	1	0	0	0	1	0	0	0	0	0	1	1
F	1	1	0	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1

时期	失调衰退区占比/%	磨合协调区占比/%	协调发展区占比/%	协调系数
2000—2005年	2	64	34	0.720
2005—2010年	3	78%	19	0.727
2010—2015年	3	69	28	0.736
2015—2020年	4	88	8	0.741
2000—2020年	4	66	30	0.725
2020—2030年NDS	3	79	18	0.749
2020—2030年SDS	3	83	14	0.755
2020—2030年FSS	5	81	14	0.752
2020—2030年EPS	9	76	15	0.742

[1]	ZUO Ximei, ZHAO Wenting. Assessment of the spatio-temporal dynamics and emission reduction potential of China's industrial carbon footprint from 2000 to 2021 [J]. Arid Zone Research, 2025, 42(9): 1703-1714.
[2]	ZHANG Kun, WU Xinping, LIU Yongqiang, ZHANG Lifang, QIN Yan, YANG Yulu, GAN Hui. Spatiotemporal evolution and prediction of carbon storage in Xinjiang using the PLUS-InVEST model [J]. Arid Zone Research, 2025, 42(9): 1715-1725.
[3]	LIN Qi, ZHANG Yanlong, CAO Liangming, WANG Xiaoyi, Rouzi TUREPU, GAO Guizhen. Agrilus viduus Kerremans: An emerging pest in Xinjiang wild fruit forest and assessment of associated damage [J]. Arid Zone Research, 2025, 42(7): 1348-1356.
[4]	DU Jun, LI Guang, DU Mengyin, YAO Yao, MA Weiwei, YUAN Jianyu. Effects of different land use types on soil N₂O fluxes on the Loess Plateau [J]. Arid Zone Research, 2025, 42(6): 1043-1054.
[5]	LIU Xiaoming, ZHENG Shiyan, QIAO Zhanming. Dynamic simulation of land use change and habitat quality in the Three River Source Region based on the PLUS-InVEST models [J]. Arid Zone Research, 2025, 42(6): 1080-1092.
[6]	GUO Jianmao, WU Dengguo, HAN Jinlong, ZHANG Rushui, WANG Yong. Precipitation retrieval for Xinjiang region based on radar and remote sensing satellites [J]. Arid Zone Research, 2025, 42(6): 957-969.
[7]	CHEN Ying, LIU Jing, SHAO Weiling, Jiazila BAISHAN, TIAN Shuting. Multi-time scale circulation characteristics of extreme low-temperature events in Xinjiang during winter from 1981 to 2020 [J]. Arid Zone Research, 2025, 42(5): 775-787.
[8]	CHEN Zhen, CAI Zhaozhao, MA Nan, DAI Shuo, WANG Zhenlu. Spatial-temporal pattern and driving force analysis of NDVI in Xinjiang from 2001 to 2023 [J]. Arid Zone Research, 2025, 42(5): 922-932.
[9]	LIU Jing, ZHENG Yulin, LIU Yan, LI Hanwei. Interdecadal variations and influencing factors in the leading modes of summer precipitation in Xinjiang [J]. Arid Zone Research, 2025, 42(4): 577-588.
[10]	LI Xiaopeng, LI Kang, LEI Shuang, JIA Fugui, XU Jing. Spatiotemporal variations in drought conditions in Xinjiang based on TVDI [J]. Arid Zone Research, 2025, 42(4): 589-599.
[11]	ZHANG Yan, YANG Weixin, LYU Tao. Driving factors analysis and multi-scenario simulation of land use change based on GeoDetector-Mixed-cell Cellular Automata: A case of the Gansu section in the Yellow River Basin [J]. Arid Zone Research, 2025, 42(4): 668-681.
[12]	WANG Liyuan, ZHANG Yong. Evolution of spatiotemporal patterns and multiscenario simulation of land use transition in Gansu Province [J]. Arid Zone Research, 2025, 42(4): 695-707.
[13]	LUO Lei, LI Xiguang, LI Xiaoting, WANG Lei, WANG Lei. Potential distribution pattern of Hippophae rhamnoides in Xinjiang under climate change predicted using the MaxEnt model [J]. Arid Zone Research, 2025, 42(3): 511-522.
[14]	WANG Wei, YANG Shuting, HAI Yunrui. The spatiotemporal evolution and influencing factors of carbon emissions from land use in Ningxia [J]. Arid Zone Research, 2025, 42(3): 545-555.
[15]	ZHAO Shikang, MU Zhenxia, LI Gang, YANG Rongqin, HUANG Mianting. Spatial and temporal evolution characteristics of atmospheric precipitable water vapor in Xinjiang and its relationship with precipitation conversion [J]. Arid Zone Research, 2025, 42(2): 191-201.

	自然发展情景（NDS）						战略发展情景（SDS）						粮食安全情景（FSS）						生态保护情景（EPS）
	A	B	C	D	E	F	A	B	C	D	E	F	A	B	C	D	E	F	A	B	C	D	E	F
A	1	1	1	1	1	0	1	0	0	0	0	0	1	0	0	0	0	0	1	1	1	1	1	1
B	1	1	1	0	1	0	1	1	0	0	1	0	1	1	0	0	0	0	0	1	0	0	0	0
C	1	1	1	0	1	1	1	0	1	0	1	0	1	0	1	0	0	0	0	1	1	0	0	0
D	0	0	1	1	1	1	0	0	0	1	1	0	1	0	0	1	0	0	0	0	0	1	0	0
E	1	1	1	1	1	0	0	0	0	0	1	0	1	0	0	0	1	0	0	0	0	0	1	1
F	1	1	0	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1

	自然发展情景（NDS）						战略发展情景（SDS）						粮食安全情景（FSS）						生态保护情景（EPS）
	A	B	C	D	E	F	A	B	C	D	E	F	A	B	C	D	E	F	A	B	C	D	E	F
A	1	1	1	1	1	0	1	0	0	0	0	0	1	0	0	0	0	0	1	1	1	1	1	1
B	1	1	1	0	1	0	1	1	0	0	1	0	1	1	0	0	0	0	0	1	0	0	0	0
C	1	1	1	0	1	1	1	0	1	0	1	0	1	0	1	0	0	0	0	1	1	0	0	0
D	0	0	1	1	1	1	0	0	0	1	1	0	1	0	0	1	0	0	0	0	0	1	0	0
E	1	1	1	1	1	0	0	0	0	0	1	0	1	0	0	0	1	0	0	0	0	0	1	1
F	1	1	0	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1