Industrial companies are responsible for most of the energy consumption and carbon emissions in China’s urban agglomerations. Some scholars have allocated CO2 emissions to China’s industrial sectors in reaching national reduction targets, yet industrial sectors’ burden-sharing problem for carbon mitigation at the provincial level has not been well addressed. Given the goal of realizing China’s national carbon mitigation target by 2030, we applied a nonlinear quota allocation model to obtain the optimal allocation of emission reduction quotas among 37 industrial sectors in the Jing-Jin-Ji urban agglomeration in China (comprising Beijing, Tianjin, and Hebei). Compared to Beijing and Tianjin, the secondary industry in Hebei bears the highest reduction responsibilities, given that Hebei will experience the largest carbon emissions, at 0.42 billion tons in 2030, which is 80.04% of the total emissions in the Jing-Jin-Ji urban agglomeration. Energy production and heavy manufacturing sectors serve as the major carbon emitters and have relatively high carbon intensities, which indicates that they have significant potential and major responsibilities for impacting carbon mitigation. Based on differences in urban function and development mode, the same industrial sectors in the three provinces have different obligations for emission reductions. This study is vital to allocate reduction responsibilities among industrial sectors and to discrete key sector categories bearing a higher mitigation burden.

Farmland transfer is conducive to the rational allocation of farmland resources and scaling of agricultural production in China. The Chinese government launched a pilot program to subsidize moderate-scale farmland management in 2016, yet the perception of the program and its effects are rarely empirically tested using micro-level data. Using data on 523 households extracted from a rural household survey, the Probit and Tobit model results determined a significant positive impact of the perception of moderate-scale subsidies on both farmland transfer behavior and farmland transfer area. If the household knows about the moderate-scale subsidy policy, then it is 19.2% more likely to have moderate-scale land endowment, and the household has 17.626 ha more inflow land than that who do not know the policy. The results show that only 5% of the households know the moderate-scale subsidy policy, thus hindering the process of farmland transfer. Additionally, high levels of educational attainment and non-agricultural income promote farmers’ decisions to transfer farmland and to expand farmland areas for moderate-scale households. However, age, household size, the family dependency ratio, and non-agricultural labor are obstacles to farmland transfer. The findings imply that the government should adopt a more effective policy transmission mechanism to increase the proportion of knowing the subsidy policy for both small-scale and moderate-scale households.

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