Scholarlink

<p>As a traditional old industrial base in Liaoning Province, structural industrial rigidities, inefficient land allocation, and pronounced population shrinkage pose significant challenges to achieving China’s carbon neutrality goals. Clarifying how county-level land use change affects carbon neutrality is therefore critical for promoting low-carbon transformation and regional sustainable development in resource-dependent regions. This study calculated the carbon neutrality index for Liaoning Province using county-level population and land use data. A geographically and temporally weighted regression (GTWR) model was employed to identify the spatiotemporal heterogeneity of factors influencing the carbon neutrality index. The Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model is applied to simulate multi-scenario carbon emission trajectories. The results show continuous population decline, expansion of unused and construction land, and a significant reduction in grassland area. Although land use intensity and diversity increased, overall land use dynamics weakened. Carbon emissions grew rapidly while carbon sequestration stagnated, resulting in a persistent decline in the carbon neutrality index. Land use intensity, land use diversity, urbanization, and population aging exerted negative but gradually weakening effects on carbon neutrality.Under the STIRPAT framework, population, GDP per capita, and energy intensity all significantly increased carbon emissions, with population exerting the strongest effect. These findings highlight the necessity of optimizing land use structure and advancing population and energy transition policies, providing theoretical foundations and policy references for the sustainable development of old industrial zones.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

The impact mechanisms of land use change to carbon neutrality under population shrinkage in Liaoning Province, China

  • 期刊论文

  • 发表日期：

    2026年4月13日

查看全文
  • Anqi Zeng,
  • Mei Gai,
  • Xiaodong Liu

摘要

As a traditional old industrial base in Liaoning Province, structural industrial rigidities, inefficient land allocation, and pronounced population shrinkage pose significant challenges to achieving China’s carbon neutrality goals. Clarifying how county-level land use change affects carbon neutrality is therefore critical for promoting low-carbon transformation and regional sustainable development in resource-dependent regions. This study calculated the carbon neutrality index for Liaoning Province using county-level population and land use data. A geographically and temporally weighted regression (GTWR) model was employed to identify the spatiotemporal heterogeneity of factors influencing the carbon neutrality index. The Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model is applied to simulate multi-scenario carbon emission trajectories. The results show continuous population decline, expansion of unused and construction land, and a significant reduction in grassland area. Although land use intensity and diversity increased, overall land use dynamics weakened. Carbon emissions grew rapidly while carbon sequestration stagnated, resulting in a persistent decline in the carbon neutrality index. Land use intensity, land use diversity, urbanization, and population aging exerted negative but gradually weakening effects on carbon neutrality.Under the STIRPAT framework, population, GDP per capita, and energy intensity all significantly increased carbon emissions, with population exerting the strongest effect. These findings highlight the necessity of optimizing land use structure and advancing population and energy transition policies, providing theoretical foundations and policy references for the sustainable development of old industrial zones.