ArticleInternational journal of environmental research and public health2023
Spatio-Temporal Variations and Influencing Factors of Country-Level Carbon Emissions for Northeast China Based on VIIRS Nighttime Lighting Data.
Article in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Spatiotemporal dynamics and driving factors of energy-related carbon emissions in the Yangtze River Delta region based on nighttime light data.Scientific reports · 2025Article
- Spatial heterogeneity and scenario simulation of carbon budget on provincial scale in China.Carbon balance and management · 2023Article
- Spatiotemporal Evolution of Carbon Emissions According to Major Function-Oriented Zones: A Case Study of Guangdong Province, China.International journal of environmental research and public health · 2023Article
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5 authors.
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Abstract
This paper constructs a county-level carbon emission inversion model in Northeast China. We first fit the nighttime light data of the Visible Infrared Imaging Radiometer Suite (VIIRS) with local energy consumption statistics and carbon emissions data. We analyze the temporal and spatial characteristics of county-level energy-related carbon emissions in Northeast China from 2012 to 2020. At the same time, we use the geographic detector method to analyze the impact of various socio-economic factors on county carbon emissions under the single effect and interaction. The main results are as follows: (1) The county-level carbon emission model in Northeast China is relatively more accurate. The regression coefficient is 0.1217 and the determination coefficient R
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