Spatio-temporal Variation and Influencing Factors of CO<sub>2</sub> Emission at County Scale in Shaanxi Province Based on Land Use Change

Cao Zhouliang; Zhang Xinrong; Yuan Xuefeng; Chen Jinhong

doi:10.13961/j.cnki.stbctb.2022.05.045

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Spatio-temporal Variation and Influencing Factors of CO₂ Emission at County Scale in Shaanxi Province Based on Land Use Change

- Spatio-temporal Variation and Influencing Factors of CO₂ Emission at County Scale in Shaanxi Province Based on Land Use Change
- Bulletin of Soiland Water Conservation Vol. 42, Issue 5, Pages: 376-385(2022)
- 作者机构：
  
  1. 长安大学, 土地工程学院,陕西,西安,710054
  2. 长安大学地球科学与资源学院,陕西,西安,710054
  3. 陕西省土地整治重点实验室,陕西,西安,710054
  4. 长安大学乡村振兴研究院,陕西,西安,710054
- 作者简介：
- 基金信息：
- DOI：10.13961/j.cnki.stbctb.2022.05.045
  CLC： Q146;F301.2
- Published：2022
- 稿件说明：
移动端阅览
Cao Zhouliang, Zhang Xinrong, Yuan Xuefeng, et al. Spatio-temporal Variation and Influencing Factors of CO₂ Emission at County Scale in Shaanxi Province Based on Land Use Change[J]. Bulletin of Soiland Water Conservation, 2022, 42(5): 376-385.
DOI：

Cao Zhouliang, Zhang Xinrong, Yuan Xuefeng, et al. Spatio-temporal Variation and Influencing Factors of CO₂ Emission at County Scale in Shaanxi Province Based on Land Use Change[J]. Bulletin of Soiland Water Conservation, 2022, 42(5): 376-385. DOI： 10.13961/j.cnki.stbctb.2022.05.045.

摘要

[目的

]

分析2000—2020年陕西省县域碳排放时空变化和影响因素，为陕西省生态文明建设和实现低碳可持续发展提供参考。[方法

]

利用社会经济数据和土地利用数据，构建碳排放估算模型，核算了2000—2020年陕西省县域碳排放总量，分析了陕西省碳排放时空分布格局与演化特征，并通过地理加权回归(GWR)模型探究了碳排放的影响因素。[结果

]

①总量上，2000—2020年陕西省碳排放量总量呈上升趋势，从2000年的3.30×10

t增长至2020年的1.93×10

t，历经“大幅增长—缓慢增长”两个阶段。②空间上，2000—2020年陕西省碳排放量中心逐步向东北方向移动，空间分布范围呈现扩张态势，热点区主要分布在榆林市北部县域、西安市和咸阳市辖区的周边部分县域，冷点区主要分布在佛坪县和石泉县。③影响因素上，人均GDP值、土地利用程度和人均社会零售总额与陕西省各县域碳排放量呈正相关，产业结构与陕西省60.74%县域碳排放量呈负相关，人口密度与陕西省92.52%县域碳排放量呈负相关。[结论

]

建议通过制定差异性区域碳减排方案，优化土地利用结构，控制建设用地增长规模，提高公众低碳环保意识等方式促进陕西省县域低碳发展。

Abstract

[Objective] The spatio-temporal changes and influencing factors of carbon emission at the county scale in Shaanxi Province from 2000 to 2020 were analyzed in order to provide a reference for ecological civilization construction and low-carbon sustainable development in Shaanxi Province. [Methods] Socioeconomic and land use data were used to construct a carbon emission estimation model. The total carbon emission in Shaanxi Province was calculated and the spatiotemporal patterns and changes from 2000 to 2020 were analyzed. Subsequently. The influencing factors of carbon emissions were determined using the geographically weighted regression method. [Results] ① Total carbon emissions increased from 3.30×107 tons in 2000 to 1.93×108 tons in 2020. The evolution of carbon emission can be divided into two stages (substantial growth and slow growth). ② The carbon emission center gradually moved to the northeast from 2000 to 2020

and the spatial distribution range showed an expansion trend. The hot spots were mainly located in the northern counties of Yulin City

and around Xi’an and Xianyang City. The cold spots were mainly located in Foping County and Shiquan County. ③ Per capita GDP

land use degree

and per capita total social retail sales were positively correlated with carbon emissions

while industrial structure and population density were negatively correlated in 60.74% and 92.52% of counties

respectively. [Conclusion] Low-carbon development should be promoted in Shaanxi Province by formulating differentiated regional carbon emission reduction plans

optimizing the land use structure

controlling the expansion of construction land

and by enhancing public awareness of low-carbon environmental protection.

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Spatio-temporal Variation and Influencing Factors of CO2 Emission at County Scale in Shaanxi Province Based on Land Use Change

DOI：10.13961/j.cnki.stbctb.2022.05.045

摘要

Abstract

关键词

Keywords

references

Spatio-temporal Variation and Influencing Factors of CO₂ Emission at County Scale in Shaanxi Province Based on Land Use Change