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The essential to achieving the 2060 carbon neutrality target in China lies in the performance of the construction industry. Decoupling economic development from CO2 emissions is the main strategy for reducing emissions in the construction industry. This paper is based on panel data for China and its 30 provinces during 2009–2019. A Tapio decoupling model is constructed to analyze the decoupling state of economic development and CO2 emissions in the construction industry. The logarithmic mean Divisia index model is constructed to continue the decomposition of the drivers of the decoupling state and CO2 emissions. The results show that (1) the economic development level of most provinces is positively correlated with their CO2 emissions; (2) Beijing and Jiangsu reach the ideal strong decoupling state, and Heilongjiang has the worst decoupling state. The same type of decoupling state shows a certain aggregation phenomenon in space; (3) economic output plays a critical role in promoting CO2 emissions and decoupling of the construction industry in China and the provinces. The main driver of decoupling is indirect carbon intensity; (4) energy intensity has a greater impact on CO2 emissions reduction in regions with more developed economic levels. Understanding the drivers of the decoupling state in China's construction industry provides a valuable basis for energy efficiency and emission reduction efforts in China and other countries. [ABSTRACT FROM AUTHOR]

Emissions trading system (ETS) is a cost-effective way towards achieving the carbon neutrality goal. Based on the gaps in the research on carbon allowance allocation vis-à-vis the carbon neutrality target, this study examines how to allocate carbon allowances equitably and effectively among Chinese provinces. Different from the previous research that mainly considers responsibility, ability, and potential of equity dimensions, this paper proposes a composite indicator allocation approach based on the equity of history, demand, contribution, and guarantee, and it also employs the entropy method and expert survey method to obtain the indicator weight values in different scenarios. Results show that the carbon allowances of some provinces, such as the forest-rich province of Yunnan, vary significantly in five scenarios, but little differences are observed for some provinces, such as the high historical emissions province of Shanxi. More provinces achieve data envelopment analysis efficiency in the preferred scenario. Compared with the objective scenario, the required emission reduction in the preferred gross domestic product (GDP) scenario is 231 million tonnes less, and the emission reduction cost is 190 billion yuan less. It is suggested that the Chinese government should adopt the allocation scheme in preference for the GDP scenario. [ABSTRACT FROM AUTHOR]