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Improving technological innovation efficiency and eco-efficiency is the key to achieving a high-quality, sustainable mining industry in China. In order to explore the internal process of technological innovation to promote economic and environmental benefits and to clarify the optimization path to improve the overall efficiency of the mining industry. A two-stage DEA model is used to construct indicators to measure Chinese 30 provinces mining technological innovation efficiency (MTIE), mining eco-efficiency (MEE), and mining comprehensive efficiency (MCE). Because of the lag in innovation, the study period was divided into nine periods from 2008 to 2018 into three-year time slices, and the dynamic evolution of time and space was analyzed. It was found that: (i) MCE and MTIE maintained the same changing trends, with the MCE being generally higher in areas with higher levels of mining economic development; (ii) the MTIE and MEE in the western area were higher than in the other regions, of which Qinghai was the only province that had efficiencies of more than 1 in both stages; (iii) most provinces belonged to type II regions with high MEE-low MTIE or type III regions with low MEE-low MTIE. The scientific achievements output in the first stage was generally insufficient, and the inputs and outputs in the second stage were redundant. There are three paths to optimize efficiency: unilateral optimization, gradual optimization, and jumping optimization. Finally, based on the above findings, policy recommendations are given from three aspects; reducing excess capacity, increasing investment, and building a platform, all of which can provide optimized plans and references for realizing the high-quality development of the Chinese mining industry. • A two-stage DEA model for measuring Chinese MTIE, MEE, and MCE from 2008 to 2018. • The MTIE and MEE in the western area were higher than in the other regions. • Most provinces belonged to type II or type III. • Three optimization paths are proposed to improve MCE. [ABSTRACT FROM AUTHOR]

The fundamental requirement of carbon abatement is to complete the carbon abatement task set, at the lowest cost. In this paper, the non-radial distance function method is used to calculate the marginal carbon abatement costs of each unit, and the statistical method is used to estimate the carbon abatement efficiency of each unit. Based on the sum of dynamic carbon abatement costs in each province, the carbon abatement task allocation is optimized, and the data before and after optimization is compared and analyzed. The main conclusions are as follows: (1) The function of carbon abatement efficiency can be estimated using the marginal cost of carbon abatement, by which, the carbon abatement cost of each province can be calculated. (2) The correlation between carbon emissions and carbon abatement efficiency of each province is weak, so the overall carbon abatement efficiency of China is low. (3) Optimizing the allocation of provincial carbon abatement tasks can significantly reduce the total carbon abatement cost and improve the carbon abatement efficiency. This study has significant theoretical and practical value for improving China's overall carbon abatement efficiency, and establishing the provincial initial carbon emission quota. [Display omitted] • We estimate carbon abatement efficiency of China and its provinces. • We improve the method for carbon abatement efficiency using the dynamic data. • We fill a gap in research on carbon abatement efficiency based task allocation method. [ABSTRACT FROM AUTHOR]