Article ; Online: Spatio-temporal evolution and gravity center change of carbon emissions in the Guangdong-Hong Kong-Macao greater bay area and the influencing factors
Heliyon. 2023 June, v. 9, no. 6 p.e16596-
2023
Abstract: The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is one of the most densely built and economically vibrant regions in China, it is of vital importance to study the spatio-temporal heterogeneity and influence mechanisms of its carbon emissions against ...
| Abstract | The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is one of the most densely built and economically vibrant regions in China, it is of vital importance to study the spatio-temporal heterogeneity and influence mechanisms of its carbon emissions against the backdrop of peaking carbon dioxide emissions and achieving carbon neutrality. However, systematic research on this area is still lacking. Therefore, this study uses spatial autocorrelation, kernel density estimation, and standard deviation ellipses to construct an exploratory spatial data analysis (ESDA) framework to analyze the spatio-temporal evolutionary characteristics of carbon emissions from GBA and combine it with the geographically and temporally weighted regression (GTWR) model to identify the various influencing factors of carbon emissions in GBA and reveal its implications. The results showed that: (1) Between 2009 and 2019, the total carbon emissions in GBA remained stable and gradually decreased. The gap between the carbon emission intensity of the cities narrowed. (2) The GBA urban agglomeration exhibited spatial autocorrelation, but characteristics of the global spatial pattern had not yet formed a steady state. The kernel density of carbon emissions in GBA showed an obvious "monopolar" phenomenon. (3) The gravity centre of carbon emissions in GBA was located to the southeast of the geometric centre of the whole region, shifting toward the northwest. (4) Population size, level of economic development and energy intensity have a strong positive contribution to carbon emissions, compared to the level of opening up and industrialization level, which has a weaker impact. There is significant spatial heterogeneity in the distribution of regression coefficients for each factor, and GBA should take full account of the characteristics of different types of cities in terms of carbon emissions and implement targeted emission reduction strategies. Our research provides a comprehensive analytical framework for regional carbon emissions, offering theoretical support for low-carbon development in the GBA. |
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| Keywords | autocorrelation ; carbon ; carbon dioxide ; center of gravity ; emissions factor ; energy ; geometry ; gravity ; industrialization ; population size ; spatial data ; spatial variation ; standard deviation ; China ; Guangdong-Hong Kong-Macao Greater bay area ; Carbon emission ; Sustainable development ; Spatiotemporal evolution ; Influencing factors |
| Language | English |
| Dates of publication | 2023-06 |
| Publishing place | Elsevier Ltd |
| Document type | Article ; Online |
| Note | Use and reproduction |
| ZDB-ID | 2835763-2 |
| ISSN | 2405-8440 |
| ISSN | 2405-8440 |
| DOI | 10.1016/j.heliyon.2023.e16596 |
| Database | NAL-Catalogue (AGRICOLA) |
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