Nowadays, China is the world’s second largest economy and largest carbon emitter. This paper calculates the carbon emission intensity and the carbon emissions per capita of land use in 30 provinces at the national level in China from 2006 to 2016. A spatial correlation model is used to explore its spatiotemporal features. The results show that (1) China’s land use carbon emissions continued to grow from 2006 to 2016. The spatial heterogeneity of carbon emission intensity of land use initially decreased and then increased during this period. The carbon emission of land use pattern reached a peak in 2015 and the land use carbon emission intensity was relatively lower in east China; (2) southern China accounts for a majority of the total Chinese carbon sink. Better economic structure, land use structure and industrial structure will lead to lower carbon emission intensity of land use; (3) carbon emissions per capita of land use in China are affected not only by land development intensity, urbanization level, and energy consumption structure, but also by the population policy. It is significant to formulate differentiated energy and land use policies according to local conditions. This study not only provides a scientific basis for formulating different carbon emission mitigation policies for the local governments in China, but also provides theoretical reference for other developing countries for sustainable development. It contributes to the better understanding of the land use patterns on carbon emissions in China.
The major grain-producing areas will be the key areas of future China fallow. It is important to explore the influence of farmers’ value perceptions on their fallow willingness in these areas. We analyzed this impact of value perception by using an ordered PROBIT model and survey data from the major grain-producing areas of Hubei and Hunan, China. The conclusions of this study are as follows: (1) A considerable proportion of farmers are willing to participate in farmland fallow, while a considerable proportion of farmers are neutral; (2) farmers’ value perceptions of farmland fallow have a significant positive impact on their fallow willingness; (3) farmers’ ages and education levels have a positive impact on farmers’ willingness to directly participate in farmland fallow, while per capita farmland area has a negative impact; (4) the key factors for successful fallow are solving the problem of non-agricultural employment of farmers and appropriately formulating fallow mode, scale, and subsidy standards. This study proposes that the government can develop farmers’ good value perceptions of fallow through appropriate subsidies and adequate publicity to strengthen their fallow consciousness.
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