基于“自然-社会”视角的陕西省土地利用变化碳核算与演变格局分析

doi:10.16258/j.cnki.1674-5906.2024.08.015

生态环境学报 ›› 2024, Vol. 33 ›› Issue (8): 1306-1317.DOI: 10.16258/j.cnki.1674-5906.2024.08.015

• 研究论文【环境科学】 • 上一篇下一篇

基于“自然-社会”视角的陕西省土地利用变化碳核算与演变格局分析

奥勇¹^,²^,³^,^*(), 张龙¹, 王晓峰¹^,²^,³, 吴彦芸¹, 唐冰倩¹, 张亦恒¹

1.长安大学土地工程学院，陕西西安 710064
2.自然资源部退化及未利用土地整治重点实验室，陕西西安 710064
3.陕西省土地整治重点实验室，陕西西安 710064

收稿日期:2024-03-30 出版日期:2024-08-18 发布日期:2024-09-25
通讯作者: *
作者简介:奥勇（1965年生），男，副教授，博士，主要从事GIS与遥感方面的教学和研究。E-mail: aoyong@chd.edu.cn
基金资助:
国家自然科学基金-联合基金项目(U23A2061);自然资源部退化及未利用土地整治工程重点实验室开放基金项目(SXDJ2019-8);陕西省土地整治重点实验室开放基金项目(2018-JC08)

Carbon Accounting and Evolution Pattern Analysis of Land Use Changes in Shaanxi Province from the “Nature-Society” Perspective

AO Yong¹^,²^,³^,^*(), ZHANG Long¹, WANG Xiaofeng¹^,²^,³, WU Yanyun¹, TANG Bingqian¹, ZHANG Yiheng¹

1. College of Land Engineering, Chang’an University, Xi’an 710064, P. R. China
2. Key Laboratory of Land Consolidation of Shaanxi Province, Xi’an 710064, P. R. China
3. Key Laboratory of Degraded and Unused Land Consolidation Enginerring, Ministry of Natural Resources, Xi’an 710064, P. R. China

Received:2024-03-30 Online:2024-08-18 Published:2024-09-25

摘要/Abstract

摘要：

土地利用变化对碳源-汇有着重要的影响，在全球碳循环中扮演着重要的角色。为揭示土地利用变化对碳平衡的影响，以陕西省为研究区，基于资源清查、土壤调查、能源消费等多源数据，利用簿记模型和GIS软件核算了该省2002-2022年社会间接碳排放和自然直接碳储量，并引入夜间灯光数据反演，揭示了不同地类及地类内部的碳密度差异与时空格局演变。结果表明：1）陕西省土地利用类型空间特征明显，林地和耕地占全省面积71.7%，2022年与2002年相比建设用地、林地、水域面积分别增加2.67×10⁵、1.05×10⁶、7.73×10³ hm²，耕地、草地、未利用地面积分别减少7.76×10⁵、3.75×10⁵、1.73×10⁵ hm²；2）研究期间陕西省土地利用相关碳吸收与碳排放严重失衡，土地利用相关年均碳汇量为4.98×10⁶ t，与林地面积的扩大及固碳能力的提升有关，年均碳排放量为3.10×10⁷ t，增长了7倍，与高排放能源的消耗有关；3）研究期间陕西省碳汇量在2007年后开始由负增长变为正增长，2017年后增长速度变快，碳排放量则一直处于高速增长，但受生态保护和减排政策等影响2017年后排放趋于稳定；4）研究期间陕西省地均碳密度表现为陕南秦巴山地>关中平原地区>陕北黄土高原，增长较为稳定的碳密度>60 t·hm⁻²的地块主要集中在安康与商洛、汉中交界一带，碳排放区域主要集中在关中平原一带和陕西西北部，并在栅格单元空间上呈现扩张趋势。研究还发现，固碳主要依靠林地碳汇，当前陕西省碳排放趋于稳定，如何提升林草地的固碳能力将成为“双碳”目标实现的关键问题。

关键词: 土地利用变化, 碳核算, 地均碳密度, 时空演变, 陕西省

Abstract:

Land-use change has an important impact on carbon sources and sinks, playing a critical role in the global carbon cycle. To reveal the impact of land use change on carbon balance, this study used Shaanxi Province as the research area and calculated the social indirect carbon emissions and natural direct carbon stocks of the province from 2002 to 2022 using the bookkeeping model and GIS software based on multi-source datasets from resource inventory, soil survey, and energy consumption. Moreover, night light data inversion was applied to illustrate the variations in carbon density and the evolution of spatiotemporal patterns among and within different land classes. The results showed that 1) the distribution of land-use types in Shaanxi Province had obvious features. Forest and cultivated land accounted for 71.7% of the total area of Shaanxi. In 2022, the areas of construction land, forest land, and water area increased by 2.67×10⁵, 1.05×10⁶, and 7.73×10³ hm², whereas the areas of cultivated land, grassland, and unused land decreased by 7.76×10⁵, 3.75×10⁵, and 1.73×10⁵ hm², respectively, compared with those in 2002. 2) During the study period, there was a serious imbalance between land use-related carbon uptake and emissions in the Shaanxi Province. The average annual sink of land use-related carbon was 4.98×10⁶ t, which was related to the expansion of forest area and improvement in carbon sequestration capacity. Nevertheless, the average annual carbon emission was 3.1×10⁷ t and increased by 7 times compared that in 2002, which was related to the energy consumption with high carbon emissions. 3) The carbon sink in the Shaanxi Province decreased from 2002 to 2007, increased after 2007, and exhibited a faster growth rate after 2017. Nevertheless, carbon emissions have been growing at a high speed, but have stabilized after 2017 owing to the impacts of ecological protection and emission reduction policies. 4) The average carbon density of the Shaanxi Province showed a decreasing trend from the Qinling-Daba Mountains in southern Shaanxi to the Guanzhong Plain to the Loess Plateau in northern Shaanxi. Regions with a relatively stable increase in carbon density (>60 t·hm⁻²) were mainly concentrated in the transition zone between Ankang, Shangluo, and Hanzhong. The carbon emission areas were mainly concentrated in the Guanzhong Plain and northwest Shaanxi, and showed an expanding trend in the grid cell space. This study also found that forests dominated the carbon sequestration. At present, carbon emissions in the Shaanxi Province tend to be stable. Improving the carbon sequestration capacity of forests and grasslands is a key issue for the “dual carbon” goal.

Key words: land use change, carbon accounting, carbon density, spatio-temporal evolution, Shaanxi Province

中图分类号:

X144

奥勇, 张龙, 王晓峰, 吴彦芸, 唐冰倩, 张亦恒. 基于“自然-社会”视角的陕西省土地利用变化碳核算与演变格局分析[J]. 生态环境学报, 2024, 33(8): 1306-1317.

AO Yong, ZHANG Long, WANG Xiaofeng, WU Yanyun, TANG Bingqian, ZHANG Yiheng. Carbon Accounting and Evolution Pattern Analysis of Land Use Changes in Shaanxi Province from the “Nature-Society” Perspective[J]. Ecology and Environment, 2024, 33(8): 1306-1317.

图/表 14

图1 陕西省地理示意图

Figure 1 Geographical map of Shaanxi Province

图2 研究框架

Figure 2 Research framework

表1 社会各类能源碳排放因子表

Table 1 Table of carbon emission factors of various energy sources in society

类型	原煤	焦炭	原油	汽油	煤油	柴油	天然气	电力
转换标准煤系数	0.714	0.971	1.43	1.47	1.47	1.46	1.33	1.23
碳含量因子	0.756	0.855	0.585	0.553	0.571	0.592	0.448	0.272
氧化率因子	0.940	0.930	0.980	0.980	0.980	0.980	0.990	1.00

图3 碳排放与夜间灯光总值拟合关系

Figure 3 Fitting relationship between carbon emission and total value of night light

表2 碳排放与夜间灯光总值拟合精度

Table 2 The fitting precision of carbon emission and total night light value

年份	绝对误差/10⁶ t	相对误差/%
2002	1.18	4.21
2007	2.10	3.19
2012	4.34	3.55
2017	13.3	6.93
2022	16.9	8.79

图4 2002-2022年陕西省土地利用类型空间分布

Figure 4 Spatial distribution of land use types in Shaanxi Province from 2002 to 2022

表3 2002-2022年陕西省土地利用类型面积变化

Table 3 Land use type area change in Shaanxi Province from 2002 to 2022

土地利用类型	2002年面积/ 10⁵hm²	2002-2012年变化率/ %	2012年面积/ 10⁵ hm²	2012-2022年变化率/ %	2022年面积/ 10⁵hm²	2002-2022年变化率/ %
耕地	59.9	−9.60	54.2	−3.69	52.2	−12.9
林地	84.6	6.57	90.2	5.47	95.1	12.4
草地	55.7	0.494	55.9	−7.20	51.9	−6.74
水域	0.570	11.3	0.634	2.07	0.647	13.6
建设用地	2.79	47.9	4.13	32.5	5.46	95.9
未利用地	1.94	−75.7	0.472	−54.7	0.214	−89.0

表4 2002-2022年陕西省土地利用转移矩阵

Table 4 Land use transfer matrix of Shaanxi Province from 2002 to 2022 104 hm2

2002年	2022年
2002年	耕地	林地	草地	水域	建设用地	未利用地	期间减少
耕地	439	68.3	6.66	1.26	24.1	0.060	160
林地	14.3	830	1.62	0.007	0.100	0.001	16.1
草地	66.1	52.6	434	0.286	2.72	0.969	123
水域	0.930	0.013	0.087	3.99	0.618	0.056	1.71
建设用地	0.245	0.001	0.011	0.873	26.8	0.001	1.13
未利用地	1.15	0.001	16.9	0.050	0.298	1.05	18.4
期间增加	82.8	121	85.2	2.48	27.9	1.09	2055

图5 2002-2022年陕西省土地利用转移示意图

Figure 5 Map of land use transfer in Shaanxi Province from 2002 to 2022

表5 2002-2022年陕西省不同土地类型碳储量

Table 5 Carbon sink quantity of different land types in Shaanxi Province from 2002 to 2022 108 t

年份	耕地	林地	草地	建设用地	未利用地	碳汇量
2002	4.48	6.83	3.36	−0.281	0.035	‒
2007	4.27	7.04	3.32	−0.660	0.029	−0.050
2012	4.05	7.43	3.38	−1.22	0.009	0.215
2017	3.82	7.96	3.38	−1.93	0.004	0.293
2022	3.90	8.59	3.14	−1.92	0.004	0.470

图6 2002-2022年陕西省土地利用地均碳密度空间分布

Figure 6 Spatial distribution of carbon density of land use in Shaanxi Province from 2002 to 2022

图7 2002-2022年陕西省土地利用和碳汇演变图

Figure 7 Characteristics of land use and carbon convergence in Shaanxi Province from 2002 to 2022

表6 2002-2022年陕西省全局Moran’s I统计表

Table 6 Statistical table of global Moran's I in Shaanxi Province from 2002 to 2022

年份	2002	2007	2012	2017	2022
Moran’s I	0.520	0.563	0.546	0.562	0.557
p值	0.000	0.000	0.000	0.000	0.000
z值	333	352	360	359	357

图8 2002-2022年陕西省碳储量空间聚集分布

Figure 8 Spatial clustering distribution of carbon in Shaanxi Province from 2002 to 2022

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基于“自然-社会”视角的陕西省土地利用变化碳核算与演变格局分析

Carbon Accounting and Evolution Pattern Analysis of Land Use Changes in Shaanxi Province from the “Nature-Society” Perspective

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