Global carbon emission spatial pattern in 2030 under INDCs: using a gridding approach based on population and urbanization
Purpose – The intended nationally determined contributions (INDCs) is a major outcome of the Paris Agreement on international cooperation to reduce emissions, and is likely to be the future scenario for carbon emissions. This paper aims to obtain the fine spatial pattern of carbon emissions in 2030,...
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| Format: | Article |
| Language: | English |
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Emerald Publishing
2021-12-01
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| Series: | International Journal of Climate Change Strategies and Management |
| Subjects: | |
| Online Access: | https://www.emerald.com/insight/content/doi/10.1108/IJCCSM-04-2021-0038/full/pdf?title=global-carbon-emission-spatial-pattern-in-2030-under-indcs-using-a-gridding-approach-based-on-population-and-urbanization |
| _version_ | 1797995018593501184 |
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| author | Le Tao Yun Su Xiuqi Fang |
| author_facet | Le Tao Yun Su Xiuqi Fang |
| author_sort | Le Tao |
| collection | DOAJ |
| description | Purpose – The intended nationally determined contributions (INDCs) is a major outcome of the Paris Agreement on international cooperation to reduce emissions, and is likely to be the future scenario for carbon emissions. This paper aims to obtain the fine spatial pattern of carbon emissions in 2030, identify hot spots and analyze changes of carbon emissions with a spatial grid method. Design/methodology/approach – Based on the integrated quantified INDCs of each economy in 2030, the authors predict the population density pattern in 2030 by using the statistics of current population density, natural growth rates and differences in population growth resulting from urbanization within countries. Then the authors regard population density as a comprehensive socioeconomic indicator for the top-bottom allocation of the INDC data to a 0.1° × 0.1° grid. Then, the grid spatial pattern of carbon emissions in 2030 is compared with that in 2016. Findings – Under the unconditional and conditional scenarios, the global carbon emission grid values in 2030 will be within [0, 59,200.911] ktCO2 and [0, 51,800.942] ktCO2, respectively; eastern China, northern India, Western Europe and North America will continue to be the major emitters; grid carbon emissions will increase in most parts of the world compared to 2016, especially in densely populated areas. Originality/value – While many studies have explored the overall global carbon emissions or warming under the INDC scenario, attention to spatial details is also required to help us make better emissions attributions and policy decisions from the perspective of the grid unit rather than the administrative unit. |
| first_indexed | 2024-04-11T09:54:50Z |
| format | Article |
| id | doaj.art-4484fe80b5f84bdeb35afe4b0d9be7e7 |
| institution | Directory Open Access Journal |
| issn | 1756-8692 1756-8706 |
| language | English |
| last_indexed | 2024-04-11T09:54:50Z |
| publishDate | 2021-12-01 |
| publisher | Emerald Publishing |
| record_format | Article |
| series | International Journal of Climate Change Strategies and Management |
| spelling | doaj.art-4484fe80b5f84bdeb35afe4b0d9be7e72022-12-22T04:30:40ZengEmerald PublishingInternational Journal of Climate Change Strategies and Management1756-86921756-87062021-12-01141789910.1108/IJCCSM-04-2021-0038676168Global carbon emission spatial pattern in 2030 under INDCs: using a gridding approach based on population and urbanizationLe Tao0Yun Su1Xiuqi Fang2Faculty of Geographic Science, Beijing Normal University, Beijing, ChinaFaculty of Geographic Science, Beijing Normal University, Beijing, China and Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing, ChinaFaculty of Geographic Science, Beijing Normal University, Beijing, China and Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing, ChinaPurpose – The intended nationally determined contributions (INDCs) is a major outcome of the Paris Agreement on international cooperation to reduce emissions, and is likely to be the future scenario for carbon emissions. This paper aims to obtain the fine spatial pattern of carbon emissions in 2030, identify hot spots and analyze changes of carbon emissions with a spatial grid method. Design/methodology/approach – Based on the integrated quantified INDCs of each economy in 2030, the authors predict the population density pattern in 2030 by using the statistics of current population density, natural growth rates and differences in population growth resulting from urbanization within countries. Then the authors regard population density as a comprehensive socioeconomic indicator for the top-bottom allocation of the INDC data to a 0.1° × 0.1° grid. Then, the grid spatial pattern of carbon emissions in 2030 is compared with that in 2016. Findings – Under the unconditional and conditional scenarios, the global carbon emission grid values in 2030 will be within [0, 59,200.911] ktCO2 and [0, 51,800.942] ktCO2, respectively; eastern China, northern India, Western Europe and North America will continue to be the major emitters; grid carbon emissions will increase in most parts of the world compared to 2016, especially in densely populated areas. Originality/value – While many studies have explored the overall global carbon emissions or warming under the INDC scenario, attention to spatial details is also required to help us make better emissions attributions and policy decisions from the perspective of the grid unit rather than the administrative unit.https://www.emerald.com/insight/content/doi/10.1108/IJCCSM-04-2021-0038/full/pdf?title=global-carbon-emission-spatial-pattern-in-2030-under-indcs-using-a-gridding-approach-based-on-population-and-urbanizationcarbon emissionclimate changeurbanizationgridpopulation growth rateintended nationally determined contributions (indcs) |
| spellingShingle | Le Tao Yun Su Xiuqi Fang Global carbon emission spatial pattern in 2030 under INDCs: using a gridding approach based on population and urbanization International Journal of Climate Change Strategies and Management carbon emission climate change urbanization grid population growth rate intended nationally determined contributions (indcs) |
| title | Global carbon emission spatial pattern in 2030 under INDCs: using a gridding approach based on population and urbanization |
| title_full | Global carbon emission spatial pattern in 2030 under INDCs: using a gridding approach based on population and urbanization |
| title_fullStr | Global carbon emission spatial pattern in 2030 under INDCs: using a gridding approach based on population and urbanization |
| title_full_unstemmed | Global carbon emission spatial pattern in 2030 under INDCs: using a gridding approach based on population and urbanization |
| title_short | Global carbon emission spatial pattern in 2030 under INDCs: using a gridding approach based on population and urbanization |
| title_sort | global carbon emission spatial pattern in 2030 under indcs using a gridding approach based on population and urbanization |
| topic | carbon emission climate change urbanization grid population growth rate intended nationally determined contributions (indcs) |
| url | https://www.emerald.com/insight/content/doi/10.1108/IJCCSM-04-2021-0038/full/pdf?title=global-carbon-emission-spatial-pattern-in-2030-under-indcs-using-a-gridding-approach-based-on-population-and-urbanization |
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