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Towards customized mitigation strategy in the transportation sector: An integrated analysis framework combining LMDI and hierarchical clustering method.
- Source :
- Sustainable Cities & Society; Jul2024, Vol. 107, pN.PAG-N.PAG, 1p
- Publication Year :
- 2024
-
Abstract
- • Applied entropy weight & LMDI to trace CO 2 disparity sources. • Used hierarchical clustering on 30 provinces' emission data. • Found 3 growth-transport decarbonization patterns in china. • Detected 27 provinces with growth-emission misalignment. As the world's largest CO 2 emitter, China's decarbonization in the transportation sector is vital for achieving global sustainable goals. This study develops an in-depth framework to elucidate and tailor decarbonization strategies across regions effectively. Through the application of the Logarithmic Mean Divisia Index (LMDI) approach, this analysis spans transportation, energy, economic, and demographic factors influencing CO 2 emissions in China's 30 provinces over the decade 2010–2019. The Entropy Weight Method (EWM), applied innovatively, pinpoints regional disparities in emission drivers. A dual-dimensional hierarchical clustering analysis evaluates the emission characteristics at provincial-level, laying the groundwork for customized mitigation strategies. The study delineates three principal discoveries: (1) robust economic development has spurred transportation demand over the past decade, escalating emissions. While initiatives like the "Beautiful China" campaign and decarbonization policies have fostered weak decoupling between economic growth and emissions, economic activity remains a dominant driver of emissions at the provincial level. (2) The energy intensity, freight intensity, and industrial structure are the primary sources of regional disparities in the driving mechanism of CO 2 emissions in the transportation sector. In economically developed areas, freight intensity is a considerable emissions accelerator, marking a departure from its national-level emissions reduction role. Given the starkly distinct regional disparity, a "one-size-fits-all" approach for China would be imprudent. (3) The novel application of hierarchical clustering reveals three synergistic relationships between regional development and transportation decarbonization, highlighting the misalignment between emissions reduction potential and driving forces in 27 provinces. This misalignment underscores the inefficiency of current management practices, necessitating the development of precise tailored strategies. By pioneering in the methodological analysis of emissions dynamics and stressing the imperative of customized mitigation strategies, this research significantly enriches the discourse on sustainable transportation and regional policy innovation. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 22106707
- Volume :
- 107
- Database :
- Supplemental Index
- Journal :
- Sustainable Cities & Society
- Publication Type :
- Academic Journal
- Accession number :
- 177107149
- Full Text :
- https://doi.org/10.1016/j.scs.2024.105340