Spatio-temporal heterogeneity of transportation carbon emissions and its driving factors in China’s main urban agglomerations
The transportation sector in China has the characteristics of large total carbon emissions, high level, and unbalanced spatial distribution. For carbon emissions reduction, it is of great significance to study the carbon emissions of transportation in China in different regions. Focusing on China’s...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2023-01-01
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| Series: | E3S Web of Conferences |
| Subjects: | |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/31/e3sconf_rees2023_01027.pdf |
| _version_ | 1827929808224387072 |
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| author | Wei Shicheng |
| author_facet | Wei Shicheng |
| author_sort | Wei Shicheng |
| collection | DOAJ |
| description | The transportation sector in China has the characteristics of large total carbon emissions, high level, and unbalanced spatial distribution. For carbon emissions reduction, it is of great significance to study the carbon emissions of transportation in China in different regions. Focusing on China’s three urban agglomerations: Beijing-Tianjin-Hebei Region, Yangtze River Delta Region and Pearl River Delta Region, this paper explores and compares the spatio-temporal heterogeneity of China’s traffic carbon emissions from 2000 to 2019 by using methods such as GWR and ESDA. The results show that: 1) As for carbon emissions, the total carbon emissions and per capita carbon emissions of the three urban agglomerations have shown a significant growth trend. The high-value aggregation in Beijing-Tianjin-Hebei Region has weakened, the high-value and low-value aggregation in the Yangtze River Delta Region has increased, and the change in the Pearl River Delta Region is not obvious. 2) As for influencing factors, motor vehicle ownership has the greatest impact on regional carbon emissions, but the impact intensity of motor vehicle ownership on carbon emissions of the three urban agglomerations is different. 3) As for spatio-temporal heterogeneity, after 2010, the spatial correlation of carbon emissions of the three urban agglomerations was lower than that of the surrounding areas, and all of them were weakened. |
| first_indexed | 2024-03-13T06:26:41Z |
| format | Article |
| id | doaj.art-45fdff56373949549b1af84aca00a3ed |
| institution | Directory Open Access Journal |
| issn | 2267-1242 |
| language | English |
| last_indexed | 2024-03-13T06:26:41Z |
| publishDate | 2023-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj.art-45fdff56373949549b1af84aca00a3ed2023-06-09T09:14:32ZengEDP SciencesE3S Web of Conferences2267-12422023-01-013940102710.1051/e3sconf/202339401027e3sconf_rees2023_01027Spatio-temporal heterogeneity of transportation carbon emissions and its driving factors in China’s main urban agglomerationsWei Shicheng0School of Life and Environmental Sciences, Minzu University of ChinaThe transportation sector in China has the characteristics of large total carbon emissions, high level, and unbalanced spatial distribution. For carbon emissions reduction, it is of great significance to study the carbon emissions of transportation in China in different regions. Focusing on China’s three urban agglomerations: Beijing-Tianjin-Hebei Region, Yangtze River Delta Region and Pearl River Delta Region, this paper explores and compares the spatio-temporal heterogeneity of China’s traffic carbon emissions from 2000 to 2019 by using methods such as GWR and ESDA. The results show that: 1) As for carbon emissions, the total carbon emissions and per capita carbon emissions of the three urban agglomerations have shown a significant growth trend. The high-value aggregation in Beijing-Tianjin-Hebei Region has weakened, the high-value and low-value aggregation in the Yangtze River Delta Region has increased, and the change in the Pearl River Delta Region is not obvious. 2) As for influencing factors, motor vehicle ownership has the greatest impact on regional carbon emissions, but the impact intensity of motor vehicle ownership on carbon emissions of the three urban agglomerations is different. 3) As for spatio-temporal heterogeneity, after 2010, the spatial correlation of carbon emissions of the three urban agglomerations was lower than that of the surrounding areas, and all of them were weakened.https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/31/e3sconf_rees2023_01027.pdfcarbon emissions from transportationurban agglomerationsdriving factorsspatio-temporal heterogeneity |
| spellingShingle | Wei Shicheng Spatio-temporal heterogeneity of transportation carbon emissions and its driving factors in China’s main urban agglomerations E3S Web of Conferences carbon emissions from transportation urban agglomerations driving factors spatio-temporal heterogeneity |
| title | Spatio-temporal heterogeneity of transportation carbon emissions and its driving factors in China’s main urban agglomerations |
| title_full | Spatio-temporal heterogeneity of transportation carbon emissions and its driving factors in China’s main urban agglomerations |
| title_fullStr | Spatio-temporal heterogeneity of transportation carbon emissions and its driving factors in China’s main urban agglomerations |
| title_full_unstemmed | Spatio-temporal heterogeneity of transportation carbon emissions and its driving factors in China’s main urban agglomerations |
| title_short | Spatio-temporal heterogeneity of transportation carbon emissions and its driving factors in China’s main urban agglomerations |
| title_sort | spatio temporal heterogeneity of transportation carbon emissions and its driving factors in china s main urban agglomerations |
| topic | carbon emissions from transportation urban agglomerations driving factors spatio-temporal heterogeneity |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/31/e3sconf_rees2023_01027.pdf |
| work_keys_str_mv | AT weishicheng spatiotemporalheterogeneityoftransportationcarbonemissionsanditsdrivingfactorsinchinasmainurbanagglomerations |