Examining spatiotemporal dynamics of CO2 emission at multiscale based on nighttime light data
Carbon emissions have increasingly been the focus of all governments as countries throughout the world choose carbon neutrality as a national development strategy. The analysis of the spatiotemporal dynamics of CO2 emission has emerged as a significant research topic considering the dual-carbon goal...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-01-01
|
| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844025001860 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832573155170844672 |
|---|---|
| author | Binbin Zhang Zongzheng Liang Wenru Guo Zhanyou Cui Deguang Li |
| author_facet | Binbin Zhang Zongzheng Liang Wenru Guo Zhanyou Cui Deguang Li |
| author_sort | Binbin Zhang |
| collection | DOAJ |
| description | Carbon emissions have increasingly been the focus of all governments as countries throughout the world choose carbon neutrality as a national development strategy. The analysis of the spatiotemporal dynamics of CO2 emission has emerged as a significant research topic considering the dual-carbon goal. In this research, we explore the spatiotemporal changes of CO2 emission at different scales based on nighttime light data. The Chinese Academy of Science's Earth Luminous Dataset, CO2 emission data from Carbon Emission Accounts and Datasets, and basic national geographical data are used for analysis. A linear regression model between nighttime light data and CO2 emission is constructed. Thereafter, the global Moran's I index of exploratory spatial data analysis is used to verify the spatial parameters of all provinces. The trend value method is utilized to analyze the changing trend of CO2 emission at multiscale levels, covering the Chinese mainland, three major economic regions, and six largest agglomerations from 2012 to 2019. Experimental results show a significant positive correlation between the CO2 emission and nighttime light data from 2012 to 2019. The nighttime light data could be used to effectively estimate the total CO2 emission at the provincial and municipal levels in China. The growth rate of CO2 emissions in China is stable and has decreased in 2015. Furthermore, the spatiotemporal dynamics of CO2 emission in different agglomerations vary. Our work provides a scientific basis for the different provinces and cities to develop feasible emission reduction policies. |
| format | Article |
| id | doaj-art-7b977720c8b642f1b518c1472fec7210 |
| institution | Kabale University |
| issn | 2405-8440 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj-art-7b977720c8b642f1b518c1472fec72102025-02-02T05:28:15ZengElsevierHeliyon2405-84402025-01-01112e41806Examining spatiotemporal dynamics of CO2 emission at multiscale based on nighttime light dataBinbin Zhang0Zongzheng Liang1Wenru Guo2Zhanyou Cui3Deguang Li4College of Sciences, Shihezi University, Shihezi, 832003, China; Corresponding author.Academy of Regional and Global Governance, Beijing Foreign Studies University, Beijing 100089, ChinaSchool of Information Technology, Luoyang Normal University, Luoyang 471934, ChinaFaculty of Engineering, Huanghe S&T University, Zhengzhou 450000, ChinaSchool of Information Technology, Luoyang Normal University, Luoyang 471934, ChinaCarbon emissions have increasingly been the focus of all governments as countries throughout the world choose carbon neutrality as a national development strategy. The analysis of the spatiotemporal dynamics of CO2 emission has emerged as a significant research topic considering the dual-carbon goal. In this research, we explore the spatiotemporal changes of CO2 emission at different scales based on nighttime light data. The Chinese Academy of Science's Earth Luminous Dataset, CO2 emission data from Carbon Emission Accounts and Datasets, and basic national geographical data are used for analysis. A linear regression model between nighttime light data and CO2 emission is constructed. Thereafter, the global Moran's I index of exploratory spatial data analysis is used to verify the spatial parameters of all provinces. The trend value method is utilized to analyze the changing trend of CO2 emission at multiscale levels, covering the Chinese mainland, three major economic regions, and six largest agglomerations from 2012 to 2019. Experimental results show a significant positive correlation between the CO2 emission and nighttime light data from 2012 to 2019. The nighttime light data could be used to effectively estimate the total CO2 emission at the provincial and municipal levels in China. The growth rate of CO2 emissions in China is stable and has decreased in 2015. Furthermore, the spatiotemporal dynamics of CO2 emission in different agglomerations vary. Our work provides a scientific basis for the different provinces and cities to develop feasible emission reduction policies.http://www.sciencedirect.com/science/article/pii/S2405844025001860CO2 emissionSpatiotemporal dynamicsNighttime light dataDMSP-OLSLinear regression model |
| spellingShingle | Binbin Zhang Zongzheng Liang Wenru Guo Zhanyou Cui Deguang Li Examining spatiotemporal dynamics of CO2 emission at multiscale based on nighttime light data Heliyon CO2 emission Spatiotemporal dynamics Nighttime light data DMSP-OLS Linear regression model |
| title | Examining spatiotemporal dynamics of CO2 emission at multiscale based on nighttime light data |
| title_full | Examining spatiotemporal dynamics of CO2 emission at multiscale based on nighttime light data |
| title_fullStr | Examining spatiotemporal dynamics of CO2 emission at multiscale based on nighttime light data |
| title_full_unstemmed | Examining spatiotemporal dynamics of CO2 emission at multiscale based on nighttime light data |
| title_short | Examining spatiotemporal dynamics of CO2 emission at multiscale based on nighttime light data |
| title_sort | examining spatiotemporal dynamics of co2 emission at multiscale based on nighttime light data |
| topic | CO2 emission Spatiotemporal dynamics Nighttime light data DMSP-OLS Linear regression model |
| url | http://www.sciencedirect.com/science/article/pii/S2405844025001860 |
| work_keys_str_mv | AT binbinzhang examiningspatiotemporaldynamicsofco2emissionatmultiscalebasedonnighttimelightdata AT zongzhengliang examiningspatiotemporaldynamicsofco2emissionatmultiscalebasedonnighttimelightdata AT wenruguo examiningspatiotemporaldynamicsofco2emissionatmultiscalebasedonnighttimelightdata AT zhanyoucui examiningspatiotemporaldynamicsofco2emissionatmultiscalebasedonnighttimelightdata AT deguangli examiningspatiotemporaldynamicsofco2emissionatmultiscalebasedonnighttimelightdata |