Inter-provincial sectoral embodied CO2 net-transfer analysis in China based on hypothetical extraction method and complex network analysis.
Sci Total Environ
; 786: 147211, 2021 Sep 10.
Article
em En
| MEDLINE
| ID: mdl-33965825
ABSTRACT
To address the CO2 emissions issue, China promised to increase its nationally determined contributions, trying to reach a CO2 emissions peak by 2030. For optimizing emission reduction policies, it is important to clarify the CO2 linkage structure and transfer characteristics. Previous research mainly focused on the calculation and comparison of CO2 linkage at the national level or the regional level and lacked inter-provincial sector-sector transfer analysis. This study uses hypothetical extraction method (HEM) to calculate the inter-provincial sectoral linkages of embodied CO2 in 2012 and 2015, providing a new perspective for sectoral CO2 linkage studies in China. We use net transfer to reveal the impact of provincial trade on the embodied CO2 emissions, and identify key CO2 emitter sectors. Combined with complex networks, we describe the clustering feature visualized and identify the transfer media sectors. The results are as follows (1) the key sectors with large linkage are mainly the heavy industries located in North China. The electricity industry has the largest net CO2 outflow as the energy supplier, whereas the construction industry has the largest net inflow as the driving sector. (2) The CO2 transfer networks present closely connected and spatial clustering features, reflecting the embodied CO2 linkage between geographically adjacent sectors closer. (3) The important media sectors are mostly located in northwest China with small industrial scale and linkage degrees, such as the transport equipment industry in Shanxi. Emission reduction policies should be overall planned and tailored to local conditions. Consequently, possible policy implications of the results are discussed, which could provide additional insights for CO2 mitigation.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Sci Total Environ
Ano de publicação:
2021
Tipo de documento:
Article