Spatiotemporal Patterns and Decomposition Analysis of CO<sub>2</sub> Emissions from Transportation in the Pearl River Delta
Controlling and mitigating CO<sub>2</sub> emissions is a challenge for the global environment. Furthermore, transportation is one of the major sources of energy consumption and air pollution emissions. For this reason, this paper estimated CO<sub>2</sub> emissions by the bott...
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MDPI AG
2019-06-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/12/11/2171 |
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| author | Xiaoshu Cao Shishu OuYang Dan Liu Wenyue Yang |
| author_facet | Xiaoshu Cao Shishu OuYang Dan Liu Wenyue Yang |
| author_sort | Xiaoshu Cao |
| collection | DOAJ |
| description | Controlling and mitigating CO<sub>2</sub> emissions is a challenge for the global environment. Furthermore, transportation is one of the major sources of energy consumption and air pollution emissions. For this reason, this paper estimated CO<sub>2</sub> emissions by the bottom-up method, and presented spatiotemporal patterns by spatial autocorrelation methods from transportation during the period 2006 to 2016. It further analyzed the impact factors of CO<sub>2</sub> emissions in the Pearl River Delta by the Logarithmic Mean Divisa Index (LMDI)decomposition method. The results indicated that from 2006 to 2016, total CO<sub>2</sub> emissions increased year by year. Guangzhou and Shenzhen were the major contributors to regional transportation CO<sub>2</sub> emissions. From the perspective of different transport modes, intercity passenger transport and freight transport have always been dominant in the past 11 years. The results indicated that aviation transport was the largest contributor, and that travel by road was the second one. The CO<sub>2</sub> emissions generated by rail and water transport were much lower than those from aviation. Private cars became the main source of urban passenger transport CO<sub>2</sub> emissions, and their advantages kept increasing. The results indicated that the spatial agglomeration trend feature was negatively correlated, and the further the distance, the more similar the attributes. The cumulative contribution values of population, economic development, transport intensity, energy intensity and energy structure were all positive values, while the cumulative contribution values of transport structure and emission factor were negative. The findings of this study offer help for the scientific understanding of those CO<sub>2</sub> emissions from transportation, and for adopting effective measures to reduce CO<sub>2</sub> emissions and for the development of green transportation. |
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| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T11:13:15Z |
| publishDate | 2019-06-01 |
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| series | Energies |
| spelling | doaj.art-cf78252f133e4b19bb29fb14db4ed78c2022-12-22T04:27:19ZengMDPI AGEnergies1996-10732019-06-011211217110.3390/en12112171en12112171Spatiotemporal Patterns and Decomposition Analysis of CO<sub>2</sub> Emissions from Transportation in the Pearl River DeltaXiaoshu Cao0Shishu OuYang1Dan Liu2Wenyue Yang3Shool of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, ChinaShool of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, ChinaShool of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, ChinaCollege of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, ChinaControlling and mitigating CO<sub>2</sub> emissions is a challenge for the global environment. Furthermore, transportation is one of the major sources of energy consumption and air pollution emissions. For this reason, this paper estimated CO<sub>2</sub> emissions by the bottom-up method, and presented spatiotemporal patterns by spatial autocorrelation methods from transportation during the period 2006 to 2016. It further analyzed the impact factors of CO<sub>2</sub> emissions in the Pearl River Delta by the Logarithmic Mean Divisa Index (LMDI)decomposition method. The results indicated that from 2006 to 2016, total CO<sub>2</sub> emissions increased year by year. Guangzhou and Shenzhen were the major contributors to regional transportation CO<sub>2</sub> emissions. From the perspective of different transport modes, intercity passenger transport and freight transport have always been dominant in the past 11 years. The results indicated that aviation transport was the largest contributor, and that travel by road was the second one. The CO<sub>2</sub> emissions generated by rail and water transport were much lower than those from aviation. Private cars became the main source of urban passenger transport CO<sub>2</sub> emissions, and their advantages kept increasing. The results indicated that the spatial agglomeration trend feature was negatively correlated, and the further the distance, the more similar the attributes. The cumulative contribution values of population, economic development, transport intensity, energy intensity and energy structure were all positive values, while the cumulative contribution values of transport structure and emission factor were negative. The findings of this study offer help for the scientific understanding of those CO<sub>2</sub> emissions from transportation, and for adopting effective measures to reduce CO<sub>2</sub> emissions and for the development of green transportation.https://www.mdpi.com/1996-1073/12/11/2171CO<sub>2</sub> emissionstransportationLMDI Methodinfluencing factorsPearl River Delta |
| spellingShingle | Xiaoshu Cao Shishu OuYang Dan Liu Wenyue Yang Spatiotemporal Patterns and Decomposition Analysis of CO<sub>2</sub> Emissions from Transportation in the Pearl River Delta Energies CO<sub>2</sub> emissions transportation LMDI Method influencing factors Pearl River Delta |
| title | Spatiotemporal Patterns and Decomposition Analysis of CO<sub>2</sub> Emissions from Transportation in the Pearl River Delta |
| title_full | Spatiotemporal Patterns and Decomposition Analysis of CO<sub>2</sub> Emissions from Transportation in the Pearl River Delta |
| title_fullStr | Spatiotemporal Patterns and Decomposition Analysis of CO<sub>2</sub> Emissions from Transportation in the Pearl River Delta |
| title_full_unstemmed | Spatiotemporal Patterns and Decomposition Analysis of CO<sub>2</sub> Emissions from Transportation in the Pearl River Delta |
| title_short | Spatiotemporal Patterns and Decomposition Analysis of CO<sub>2</sub> Emissions from Transportation in the Pearl River Delta |
| title_sort | spatiotemporal patterns and decomposition analysis of co sub 2 sub emissions from transportation in the pearl river delta |
| topic | CO<sub>2</sub> emissions transportation LMDI Method influencing factors Pearl River Delta |
| url | https://www.mdpi.com/1996-1073/12/11/2171 |
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