Spatiotemporal Evolution and Driving Factors of the Relationship Between Land Use Carbon Emissions and Ecosystem Service Value in Beijing-Tianjin-Hebei

Anjia Li, Xu Yin and Hui Wei ()
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Anjia Li: School of Public Management, Hebei University of Economics and Business, Shijiazhuang 050061, China
Xu Yin: School of Geographic Science, Hebei Normal University, Shijiazhuang 050024, China
Hui Wei: School of Public Management, Hebei University of Economics and Business, Shijiazhuang 050061, China

Land, 2025, vol. 14, issue 8, 1-24

Abstract: Land use change significantly affects regional carbon emissions and ecosystem service value (ESV). Under China’s Dual Carbon Goals, this study takes Beijing-Tianjin-Hebei, experiencing rapid land use change, as the study area and counties as the study unit. This study employs a combination of methods, including carbon emission coefficients, equivalent-factor methods, bivariate spatial autocorrelation, and a multinomial logit model. These were used to explore the spatial relationship between land use carbon emissions and ESV, and to identify their key driving factors. These insights are essential for promoting sustainable regional development. Results indicate the following: (1) Total land use carbon emissions increased from 2000 to 2015, then declined until 2020; emissions were high in municipal centers; carbon sinks were in northwestern ecological zones. Construction land was the primary contributor. (2) ESV declined from 2000 to 2010 but increased from 2010 to 2020, driven by forest land and water bodies. High-ESV clusters appeared in northwestern and eastern coastal zones. (3) A significant negative spatial correlation was found between carbon emissions and ESV, with dominant Low-High clustering in the north and Low-Low clustering in central and southern regions. Over time, clustering dispersed, suggesting improved spatial balance. (4) Population density and cultivated land reclamation rate were core drivers of carbon–ESV clustering patterns, while average precipitation, average temperature, NDVI, and per capita GDP showed varied effects. To promote low-carbon and ecological development, this study puts forward several policy recommendations. These include implementing differentiated land use governance and enhancing regional compensation mechanisms. In addition, optimizing demographic and industrial structures is essential to reduce emissions and improve ESV across the study area.

Keywords: land use carbon emissions; ecosystem service value; spatiotemporal evolution; driving factors; county scale; the Beijing-Tianjin-Hebei region (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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