Work

Study on Spatiotemporal Pattern Evolution and Regional Heterogeneity of Carbon Emissions at the County Scale of Major Cities, Inner Mongolia Autonomous Region

Year: 2025

Type: article

Abstract: In-depth exploration of the spatial heterogeneity patterns of urban carbon emissions holds significant scientific importance for regional sustainable development. However, few scholars have examined the spatiotemporal characteristics of county-level carbon emissions in Inner Mongolia. This study focuses on the three major cities of Hohhot, Baotou, and Ordos in Inner Mongolia. By integrating NPP-VIIRS nighttime light data, the CLCD (China Land Cover Dataset) dataset, and statistical yearbooks, it quantifies county-level carbon emissions and establishes a spatiotemporal analysis framework of urban morphology–carbon emissions from 2013 to 2021. Six morphological indicators—Class Area (CA), Landscape Shape Index (LSI), Largest Patch Index (LPI), Patch Cohesion Index (COHESION), Patch Density (PD), and Interspersion Juxtaposition Index (IJI)—are employed to represent urban scale, complexity, centrality, compactness, fragmentation, and adjacency, respectively, and their impacts on regional carbon emissions are examined. Using a geographically and temporally weighted regression (GTWR) model, the results indicate the following: (1) from 2013 to 2021, The high-value areas of carbon emissions in the three cities show a clustered distribution centered on the urban districts. The total carbon emissions increased from 20,670 (104 t/CO2) to 37,788 (104 t/CO2). The overall spatial pattern exhibits a north-to-south increasing gradient, and most areas are projected to experience accelerated carbon emission growth in the future; (2) the global Moran’s I values were all greater than zero and passed the significance tests, indicating that carbon emissions exhibit clustering characteristics; (3) the GTWR analysis revealed significant spatiotemporal heterogeneity in influencing factors, with different cities exhibiting varying directions and strengths of influence at different development stages. The ranking of influencing factors by degree of impact is: CA > LSI > COHESION > LPI > IJI > PD. This study explores urban carbon emissions and their heterogeneity from both temporal and spatial dimensions, providing a novel, more detailed regional perspective for urban carbon emission analysis. The findings enrich research on carbon emissions in Inner Mongolia and offer theoretical support for regional carbon reduction strategies.

Source: Sustainability

DOI: 10.3390/su17209222

Authors: Shibo Wei, Yun Xue, Meijing Zhang

Institution: Inner Mongolia University of Science and Technology

Language: English

Topic: Energy, Environment, Economic Growth

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

SDGs: Sustainable cities and communities, Climate action

Open Access status: gold

Estimated APC paid: $2,896