Identification of key carbon emitters from the perspective of network analysis
Climate risks are sharpened and adaptation actions are urgent. However, the economic system is a whole composed of numerous interrelated and interactive economic elements and poses a challenge for carbon mitigation. To explore the carbon emission effects of producers in complex economic systems and...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-06-01
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| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X23004260 |
| _version_ | 1827958060909330432 |
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| author | Lijuan Xia Yongli Li Xiaochen Ma |
| author_facet | Lijuan Xia Yongli Li Xiaochen Ma |
| author_sort | Lijuan Xia |
| collection | DOAJ |
| description | Climate risks are sharpened and adaptation actions are urgent. However, the economic system is a whole composed of numerous interrelated and interactive economic elements and poses a challenge for carbon mitigation. To explore the carbon emission effects of producers in complex economic systems and formulate targeted carbon mitigation policies, this study constructs three indicators to assess the carbon emission effect embodied in the economy through network analysis. More specifically, the total emission effect of each producer is measured by the push-type effect and pull-type effect and tested by comparing with the hypothetical extraction method. Taking China as an example, the results show that the effect of different sectors on carbon emissions varies greatly. The production and distribution of electric power and heat power is a key sector dominated by the push-type effect. This is, its carbon emissions are mainly triggered by the demands of its downstream sectors. The total emission effects of Construction and Smelting and processing of metals are also strong, but their pull-type effect is dominant. According to the dominant effect in the total emission effect, we can draft targeted emission reduction strategies. |
| first_indexed | 2024-04-09T15:29:41Z |
| format | Article |
| id | doaj.art-0622d0fe8fd94350a2fa7a3c80587c64 |
| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-04-09T15:29:41Z |
| publishDate | 2023-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj.art-0622d0fe8fd94350a2fa7a3c80587c642023-04-28T08:55:02ZengElsevierEcological Indicators1470-160X2023-06-01150110284Identification of key carbon emitters from the perspective of network analysisLijuan Xia0Yongli Li1Xiaochen Ma2School of Economics and Management, Harbin Institute of Technology, Harbin 150001, ChinaCorresponding author.; School of Economics and Management, Harbin Institute of Technology, Harbin 150001, ChinaSchool of Economics and Management, Harbin Institute of Technology, Harbin 150001, ChinaClimate risks are sharpened and adaptation actions are urgent. However, the economic system is a whole composed of numerous interrelated and interactive economic elements and poses a challenge for carbon mitigation. To explore the carbon emission effects of producers in complex economic systems and formulate targeted carbon mitigation policies, this study constructs three indicators to assess the carbon emission effect embodied in the economy through network analysis. More specifically, the total emission effect of each producer is measured by the push-type effect and pull-type effect and tested by comparing with the hypothetical extraction method. Taking China as an example, the results show that the effect of different sectors on carbon emissions varies greatly. The production and distribution of electric power and heat power is a key sector dominated by the push-type effect. This is, its carbon emissions are mainly triggered by the demands of its downstream sectors. The total emission effects of Construction and Smelting and processing of metals are also strong, but their pull-type effect is dominant. According to the dominant effect in the total emission effect, we can draft targeted emission reduction strategies.http://www.sciencedirect.com/science/article/pii/S1470160X23004260Carbon emissionsNetwork analysisEmbodied CO2 flowsEnvironmental input–output analysis |
| spellingShingle | Lijuan Xia Yongli Li Xiaochen Ma Identification of key carbon emitters from the perspective of network analysis Ecological Indicators Carbon emissions Network analysis Embodied CO2 flows Environmental input–output analysis |
| title | Identification of key carbon emitters from the perspective of network analysis |
| title_full | Identification of key carbon emitters from the perspective of network analysis |
| title_fullStr | Identification of key carbon emitters from the perspective of network analysis |
| title_full_unstemmed | Identification of key carbon emitters from the perspective of network analysis |
| title_short | Identification of key carbon emitters from the perspective of network analysis |
| title_sort | identification of key carbon emitters from the perspective of network analysis |
| topic | Carbon emissions Network analysis Embodied CO2 flows Environmental input–output analysis |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X23004260 |
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