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.

There has been a growing awareness of the dietary shift from traditional staples to animal-derived foods during the urbanization of developing countries. Less discussed is how the global food landscape will accommodate such changes in diet. Our study aims to use the GTAP (Global Trade Analysis Project) model to predict the future food landscape based on the dietary shift in developing countries, represented by China, India, Bangladesh, and Myanmar, under a 2030 urbanization scenario. The results show that the average global outputs of fish, meat, and dairy products increase by 0.26–2.85%, along with an expansion in their trade volume by 2.10–13.95%, by 2030. To ensure that dietary changes can be met in developing countries, Asia and America need to strengthen their positions with respect to global food production share, while Africa is developing to become a non-negligible growing force. Accordingly, globalized food trade is characterized by a centralized export and, conversely, by a decentralized import, clearly indicating an expanding net-import tendency in populous developing countries. These findings highlight the adaptation scheme of global food production and trade patterns under a 2030 urbanization scenario, as urbanization accelerates dietary change in developing countries.

Water demand management through price and market mechanisms is crucial for agricultural water management. However, how to set an appropriate agricultural water price remains unclear due to the uncertainty regarding the response of water demand to price changes and the complexity of the hydro-economic system. Thus, this study developed a water-economic model to examine both issues in the Heihe River Basin. The empirical results revealed that the basin’s agricultural water is currently price-inelastic, with a value of −0.26, but that at 0.27 yuan/m³, elasticity is gained. At this tipping point, water demand and economic output decline by up to 10.2% and 1.6%, respectively, while water productivity increases by 7.2%. It is noteworthy that the reallocation of water and land resources from agricultural sectors to non-agricultural sectors facilitated by a water price change is the main contributor towards water productivity improvement. This signifies the importance of managing water and land resources in an integrated framework to improve water productivity in the future. Our study contributes to the literature by suggesting that future policies for water-demand management should consider pricing that encourages water saving and the reallocation of water resources to high-value uses in order to increase water productivity.

Water scarcity in arid regions can be addressed by using the virtual water concept in water resources management. This research used a compiled county-level input–output table to analyze virtual water flows for the Heihe River Basin in 2012 by applying a multi-regional input–output (MRIO) model. The results showed that the Heihe River Basin is a net virtual water exporter at a scale of 1.05 billion m³, which accounts for one third of the total amount of the basin’s water resources. The midstream area of the basin imports 96.31% of virtual water (2.04 billion m³) and exports 88.84% of virtual water (0.94 billion m³). In contrast, the upstream and downstream parts have limited virtual water flows. The agricultural sector largely consumes water in each county; maize or wheat production accounts for approximately 50% of the total water consumption. For most sectors, the virtual water content from surface water is greater than that from groundwater. The ratio of virtual surface water to virtual groundwater ranges from 1.20 to 2.91. The results for the water stress index indicated that most counties experienced water stress due to maize production. Greater attention needs to be paid to the adaptation and assessment of virtual water strategies in arid regions.

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.