Multi-Scale Analysis of Carbon Emissions in Coastal Cities Based on Multi-Source Data: A Case Study of Qingdao, China DOI Creative Commons
Qingchun Guan, Tianya Meng, Chengyang Guan

et al.

Land, Journal Year: 2024, Volume and Issue: 13(11), P. 1861 - 1861

Published: Nov. 7, 2024

Coastal cities, as centers of economic and industrial activity, accommodate over 40% the national population generate more than 70% GDP. They are critical carbon emissions, making accurate long-term analysis spatiotemporal emission patterns crucial for developing effective regional reduction strategies. However, there is a scarcity studies on continuous emissions in coastal cities. This study focuses Qingdao explores its characteristics at city, county, grid scales. Data from multi-source employed, integrating net primary production (NPP), energy consumption, nighttime light data to construct estimation model. Additionally, Tapio model applied examine decoupling GDP emissions. The results indicate that R2 inversion 0.948. central urban areas Qingdao’s region identified hotspots exhibiting significantly higher compared inland areas. There notable dependence development disparities between have resulted significant geographical differentiation state. Furthermore, optimizing transitioning structure has primarily contributed reduction, while exceptional circumstances, such COVID-19 pandemic, led passive fluctuations provides scientific reference cities formulate targeted policies.

Language: Английский

Multi-Scale Analysis of Carbon Emissions in Coastal Cities Based on Multi-Source Data: A Case Study of Qingdao, China DOI Creative Commons
Qingchun Guan, Tianya Meng, Chengyang Guan

et al.

Land, Journal Year: 2024, Volume and Issue: 13(11), P. 1861 - 1861

Published: Nov. 7, 2024

Coastal cities, as centers of economic and industrial activity, accommodate over 40% the national population generate more than 70% GDP. They are critical carbon emissions, making accurate long-term analysis spatiotemporal emission patterns crucial for developing effective regional reduction strategies. However, there is a scarcity studies on continuous emissions in coastal cities. This study focuses Qingdao explores its characteristics at city, county, grid scales. Data from multi-source employed, integrating net primary production (NPP), energy consumption, nighttime light data to construct estimation model. Additionally, Tapio model applied examine decoupling GDP emissions. The results indicate that R2 inversion 0.948. central urban areas Qingdao’s region identified hotspots exhibiting significantly higher compared inland areas. There notable dependence development disparities between have resulted significant geographical differentiation state. Furthermore, optimizing transitioning structure has primarily contributed reduction, while exceptional circumstances, such COVID-19 pandemic, led passive fluctuations provides scientific reference cities formulate targeted policies.

Language: Английский

Citations

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