Analysis of vehicular CO 2 emission in the Central Plains of China and its driving forces
Science of The Total Environment, ISSN: 0048-9697, Vol: 814, Page: 152758
2022
- 22Citations
- 23Captures
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Metrics Details
- Citations22
- Citation Indexes22
- 22
- CrossRef19
- Captures23
- Readers23
- 23
Article Description
The Central Plains of China, represented by Henan province, faces a dramatic rise in vehicular stock and CO 2 emissions. The refined-resolution(1 km × 1 km) vehicular CO 2 emission inventory for Henan province was developed to identify emission patterns. Results show that CO 2 emissions in Henan province reached 77.04 Mt in 2019, and LDGV and HDDT were the major sources that emitted 42.34% and 35.96% of CO 2 emissions, respectively. Based on gridded emission, Moran's Index was used to identify spatial distribution patterns of vehicular CO 2. The higher CO 2 emission intensity areas were concentrated in the central and northern of the province and urban areas in each city, especially in Zhengzhou and its surrounding cities. Moreover, the analysis of the driving forces behind the differences in emissions among cities using the multi-regional (M-R) spatial decomposition model revealed that income and population-scale are significant impacts. In cities such as Zhengzhou, emissions may be dramatically increase owing to high economic growth expectations. ‘Polarization phenomenon’ of CO 2 emission distribution should be vigilant. Findings provided insights for refined policy-making in Henan province to limit CO 2 emission: (1) Take cities as transportation hubs, e.g., Zhengzhou and Shangqiu, and that in the traffic radiation circle, e.g., Jiaozuo and Zhoukou, as the critical areas for CO 2 emission reduction; (2) Promote electric vehicles as replacement for traditional fuel vehicles; especially for cities with large passenger car emissions, such as Zhengzhou, and cities with large truck emissions, such as Shangqiu and Zhoukou; actively guide new consumer groups to choose EVs, especially in cities with high growth expectations such as Zhengzhou; (3) Rely on the advantages of transportation network to promote the ‘road to railway’ of bulk cargo transportation and mainly focus on highways with higher CO 2 density, such as Beijing-Hong Kong&Macao Expressway, Shanghai-Xi'an Expressway, Da Guang Expressway, and Lian Huo Expressway.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0048969721078372; http://dx.doi.org/10.1016/j.scitotenv.2021.152758; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85122278832&origin=inward; http://www.ncbi.nlm.nih.gov/pubmed/34990673; https://linkinghub.elsevier.com/retrieve/pii/S0048969721078372; https://dx.doi.org/10.1016/j.scitotenv.2021.152758
Elsevier BV
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