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• 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]

• A dynamic fleet-based life cycle assessment framework combined the vehicle lightweight design model is established. • The fleet-scale and long-term greenhouse gas mitigation potential attributable to the vehicle lightweighting along with the electrification trend is estimated. • Along with the electrification trend, the mitigation potential shrinks due to the decline of fuel saving with powertrain efficiency improvement. Lightweighting is believed to be a silver bullet to reduce greenhouse gas (GHG) emissions related to the road transportation. However, the fleet-scale and long-term GHG emissions estimation on the light-duty passenger vehicle (LDPV) fleet in China is still underexplored. A dynamic fleet-based life cycle assessment (LCA) model is developed to predict the annual GHG emissions attributable to the lightweight LDPV fleet in China at provincial level. With the most aggressive implementation of lightweighting, the cumulative mitigation potential of lightweight LDPV fleet from 2021 to 2050 is 0.72 Gt CO 2 eq and 0.55 Gt CO 2 eq using high-strength steel (AHSS) and aluminium (Al), respectively. Sooner implementation brings a higher cumulative reduction in GHG emissions. Delaying the implementation by five years would sacrifice 0.16 Gt CO 2 eq ∼0.2 Gt CO 2 eq cumulative reduction, and the loss would increase to 0.31 Gt CO 2 eq ∼0.41 Gt CO 2 eq when postpone the lightweighting by ten years. [Display omitted] [ABSTRACT FROM AUTHOR]

The article presents a study on the consequences of North American Free Trade Agreement in allocating national responsibility for carbon-dioxide emissions to the environment. Trade data used in the study came from the U.S. Census Bureau and coded by the North American Industry Classification System. Estimation are made on carbon dioxide embodied in manufactured products and exported to another nation. The study used the economic input-output life-cycle assessment (EIO-LCA) software developed by Green Design Initiative and is based on the U.S. economic input and output data on 1997. EIO-LCA is used to trace economic transactions, resource requirements and environmental emissions of a certain product manufactured in the U.S.