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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]

• City-level agricultural production efficiency is mapped by Super-Efficiency Data Envelopment Analysis model. • The agricultural production efficiency is featured as spatial agglomerations. • The OLS and GWR models are used to explore the spatial heterogeneity and driving mechanisms of agricultural production efficiency. • Series of policy recommendations are provided. The level of agricultural production efficiency (APE) affects farmers' livelihood decisions and the transformation and reconstruction of the rural territorial system. This paper constructs an evaluation index system of China's APE from the perspective of input–output. The spatial autocorrelation model and econometric model are used to calculate the spatio-temporal evolution characteristics and influencing factors of China's APE in 1990 and 2017. The results show that China's APE level is relatively low, and there are significant spatial differences. The extremely high efficiency regions are distributed in the eastern plains of China; the regions with extremely low efficiency are mainly distributed in the southwest and the western regions of China. The results of the spatial correlation effect show that the H-H agglomeration regions of APE are usually distributed in the eastern coastal areas and northeastern areas, while the L-L agglomeration regions are mainly distributed in the central mountainous areas and the border areas of western Yunnan. From 1990 to 2017, the influencing factors of APE have gradually changed, and showing a more complex trend, mainly including farmland management scale , multiple crop index, rural per capita net income, population density, and precipitation per unit area. Finally, the corresponding policy and suggestions are provided. [ABSTRACT FROM AUTHOR]