Spatiotemporal evolution and driving factors of carbon emission efficiency of resource-based cities in the Yellow River Basin of China

Song, Malin; Gao, Yunfei; Zhang, Liyan; Dong, Furong; Zhao, Xiaofeng; Wu, Jean

doi:10.1007/s11356-023-29113-4

Cited by 7 publications

(1 citation statement)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Continuous high-resolution nighttime light data can clearly detect human activities. Many scholars have conducted estimation studies on electricity consumption 11 , 12 and carbon emissions based on these data 13 – 15 . Some scholars first constructed a model of nighttime light data and electricity consumption and confirmed their correlation.…”

Section: Introductionmentioning

confidence: 99%

Exploring the dynamics and trends of carbon emission spatiotemporal patterns in the Chengdu–Chongqing Economic Zone, China, from 2000 to 2020

Che,

Guo,

et al. 2024

Sci Rep

View full text Add to dashboard Cite

Analysis of the spatial–temporal pattern and trend of carbon emissions provides an important scientific basis for the development of a low-carbon economy. Based on the corrected NPP-VIIRS and DMSP/OLS nighttime light data, a carbon emission model for the Chengdu–Chongqing Economic Zone (CCEZ) in China is constructed. Furthermore, the article establishes an integrated qualitative and quantitative research system. The qualitative results show that at the city and county scales, the high carbon emission areas and counties are mainly distributed in Chengdu and Chongqing, while the low carbon emission areas are concentrated in the marginal cities of the CCEZ and the counties with low levels of industrialization around the Sichuan Basin. The high-carbon emission zone tended to expand to the north, and the low-carbon emission zone tended to expand to the south. At the grid scale, the carbon emissions of the CCEZ fluctuated and increased from 2000 to 2020, forming a trend connected with those of the central city, with high carbon emissions at the core and radiating outward expansion. Quantitative analysis revealed that carbon emissions at the county and grid scales exhibited a significant positive global spatial correlation, and the overall correlation degree exhibited an increasing trend.

show abstract