Assessing the Spatio-Temporal Dynamics of Land Use Carbon Emissions and Multiple Driving Factors in the Guanzhong Area of Shaanxi Province

Author:

Wang Yali12,Liu Yangyang3,Wang Zijun4,Zhang Yan1,Fang Bo1,Jiang Shengnan5,Yang Yijia6,Wen Zhongming3ORCID,Zhang Wei3,Zhang Zhixin3ORCID,Lin Ziqi3,Han Peidong3,Yang Wenjie1

Affiliation:

1. College of Economics and Management, Northwest A&F University, Yangling 712100, China

2. College of Innovation and Experiment, Northwest A&F University, Yangling 712100, China

3. College of Grassland Agriculture, Northwest A&F University, Yangling 712100, China

4. College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China

5. Wujinglian School of Economics, Changzhou University, Changzhou 213000, China

6. Institute of Management Engineering, Qingdao University of Technology, Qingdao 266525, China

Abstract

Land use change is one of the key elements leading to carbon emission changes, and is of great significance to the process of achieving the goals of carbon peaking and carbon neutrality. In this study, we calculated the land-use carbon emissions (LCE) in the Guanzhong area (GZA) of Shaanxi province from 2000 to 2019 by using an improved LCE measurement model. Meanwhile, the spatial and temporal changes of LCE were analyzed and the driving forces were investigated based on the correlation analysis and multi-scale geographical weighting regression (MGWR). The results showed that the total amount of LCE showed a significant increasing trend from 2000 to 2019. Regions where the LCE significantly increased occupied 71.20% of the total area; these regions were distributed in the central and eastern parts of the study area. The LCE showed a significant positive spatial correlation and had a remarkable aggregation state. The H-H agglomeration area of LCE was distributed in the central urban agglomeration. The L-L agglomeration areas were always distributed in the southwest part of the GZA with low carbon emissions. The average correlation coefficients between LCE and nighttime light (NTL), population density (PD), and gross primary productivity (GPP) were 0.13, 0.21, and −0.05, respectively. The NLT and PD had obvious positive effects on LCE, while GPP has obvious negative effects on carbon emissions, which can be ascribed to the carbon sink effect of forests and grasslands. The results of this study have important reference value regarding the formulation of carbon emission reduction policies and the development of a low-carbon social economy.

Funder

Shaanxi agricultural rural economic and technological system construction project

Startup fund for doctoral research of Northwest A&F University

Special project of science and technology innovation plan of Shaanxi Academy of Forestry Sciences

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

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