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The effectiveness of climate policies will determine CO 2 emissions and goal achievement. However, the coupled integration among driving factors on emissions is not given enough attention and analysis in most quantitative modeling. To clarify the effectiveness of de-carbonization pathways, here we identify coupled factors documented across a range of studies and connect them in a coupled system framework. The empirical analysis reveals the de-carbonization significance and potential of coupled variables in the GBA. These potentials can be decisive for determining policies and emission outcomes. After in-depth spatial and time-fixed analysis, spatial spillover effects of driving factors are identified. And the driving effect of the independent variable is further decomposed into direct effect and indirect effect to show a complex coupled correlation. The novelty of this study is that it explores the coupled correlation among driving factors and quantitatively verified these relationships. Research findings have important reference value for policymakers in assisting de-carbonization strategies design. • Proposed a Coupled system framework to connect driving factors. • Identified driving factors for implementing de-carbonization goals in the GBA. • Used an integrated STIRPAT-SDM model to empirical analysis. • Extended transportation factor to clarify its direct and indirect de-carbonization potential. [ABSTRACT FROM AUTHOR]

The Chinese government is increasingly concerned about the impacts of climate change mitigation policies on social equity. Carbon pricing is an effective measure for reducing carbon emissions, but its distributional effects may exacerbate inequity among different rural and urban households. As a leading carbon pricing pilot area in China, Guangdong Province is the subject area of this paper. By using the environmentally extended input-output model and calculating the Suits index, this study aims to compare the carbon price payments of ten income-level households in Guangdong Province in 2012 and 2017. The results indicate that higher-income households need to pay more for carbon emissions. Total carbon pricing in Guangdong is slightly progressive, and the progressivity increased from 2012 to 2017. Thus, the implementation of carbon pricing may not intensify the inequality between urban and rural areas and between different income groups. Only carbon pricing on residential energy consumption is regressive, which could be compensated by revenue recycling policies. The findings of this study contribute by offering a positive theoretical basis for China's future policies on carbon pricing such as carbon taxes. • Urban households and higher-income households would bear a greater burden of carbon payment in Guangdong. • Carbon pricing will not exacerbate the original income inequality of different households in Guangdong. • Households in urban areas have higher-carbon lifestyles than rural households. • From 2012 to 2017, the progressivity of carbon pricing increased slightly. • Carbon pricing for direct energy consumption is regressive, so revenue recycling schemes are needed. [ABSTRACT FROM AUTHOR]