ORIGINAL RESEARCH article
Front. Environ. Sci.
Sec. Environmental Informatics and Remote Sensing
This article is part of the Research TopicAssessing Greenhouse Gas Emissions at City and Regional Levels: Challenges and MethodsView all articles
What Drives Carbon Emissions in the Yellow River Basin: New Insights from Multi-scale Analysis Based on Nighttime Light Data
Provisionally accepted
- North Minzu University, Yinchuan, China
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Developing targeted carbon emissions reduction strategies of the Yellow River Basin (YRB) is essential for achieving sustainable development. At present, nighttime light data provide favorable conditions for studying carbon emissions of large-scale and long-time series. Utilizing nighttime light and statistical data from 2000 to 2022, the spatial-temporal variations of carbon emissions at multi-scale in the YRB are estimated and analyzed. Furthermore, the spatial spillover effects and influencing factors of carbon emissions in the YRB are explored combining Exploratory Spatial Data Analysis (ESDA) and spatial econometric model. The study aims to provide crucial insights for formulating effective carbon emission mitigation strategies in the YRB. Our findings delineate three distinct phases of provincial carbon emissions in the YRB from 2000 to 2022, each marked by unique stages and a converging trend. Urban carbon emissions present distinct spatial distribution characterized by "lower reach > middle reach > upper reach". Spatial correlation test highlights significant spatial clustering characteristics and spillover effects of carbon emissions. Further decomposition of spatial effects reveals that carbon emissions are influenced by the synergistic interactions of various resource elements. Factors such as economic growth, population density, industrial structure, energy consumption structure, technological progress, and foreign direct investment exert complex interactive effects on carbon emissions.
Keywords: carbon emissions, Yellow River Basin, Spatial-temporal variations, Driving factors, Spatial spillover effects, Nighttime light data
Received: 24 Sep 2025; Accepted: 12 Nov 2025.
Copyright: © 2025 Ma, Gao and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Mingjuan Ma, mamingjuan2009@163.com
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