With urbanization and industrialization, cultivated land in hilly regions of China has been gradually marginalized. Abandoned cultivated lands have ranged from inferior sloping land and extended to high-quality terraces. The abandonment of terraces will lead to a series of social and ecological problems, especially with large-scale abandonment. Therefore, the degree and spatial distribution of terrace abandonment should be evaluated scientifically to address the issue of abandonment as well as its effects. This study investigated the extent of terrace abandonment in China via a questionnaire sampling method. Based on 560 village questionnaires from 329 counties in China, the scale of terrace abandonment was calculated and the spatial heterogeneity characteristics and primary reasons for terrace abandonment were further analyzed. Study results showed that: (1) The phenomenon of terrace abandonment was observed throughout China, occurring in 54% of all the villages investigated; 9.79% of the total terraced areas have been abandoned. (2) The degree of terrace abandonment showed a spatial pattern of "high in the south and low in the north". The degree of terrace abandonment was higher in the southern hilly mountains, and the middle and lower reaches of the Yangtze River was the most serious. (3) The primary factors related to terrace abandonment were found to be labor migration, the degree to which terraces have been mechanized, irrigation conditions, and farming traffic conditions. Measures that include improving the degree of terrace mechanization should be enacted to address the problem of terrace abandonment. An orderly "conversion of cropland" could be applied to poor-quality terraces. Changing the planting structure, strengthening new agricultural infrastructure, and encouraging circulation and large-scale operations are options that could be applied to good-quality terraces.

Frequent terrace abandonment in hilly and mountainous areas has become a great concern for Chinese agricultural sector and academia in recent years. However, few studies concern about the impact of differences in agricultural labor transfer on farmers' terrace abandonment behavior. Taking Hunan, Fujian and Jiangxi provinces, where terraced fields are widely distributed, as study areas, this paper adopts Probit and Tobit models to analyze the impact of quantity, distance, and quality of labor off-farm transfer on farmers' terrace abandonment behavior and scale from the perspective of labor transfer difference based on survey data of 1438 households. The research shows that: (1) The quantity, distance and quality of off-farm labor transfer significantly positively impact farmers' terrace abandonment behavior and scale. (2) The scale of terrace abandonment in hilly and mountainous areas expands with the deepening of farmers' off-farm transfer. (3) The spatial distance and quality of labor transfer strengthen the impact of labor transfer quantity on farmers' terrace abandonment behavior. To alleviate terrace abandonment resulting from labor off-farm transfer, attention should be paid to the labor substitution effect of agricultural service outsourcing and mechanization in mountainous areas. It is suggested to promote the adaptability of agricultural machinery in mountainous areas, improve farmland transfer market, and encourage farmers to transfer terraced fields.

It is practical to control agricultural non-CO₂ greenhouse gases (GHG) emissions for the implementation of greenhouse gas mitigation policies in China, and has a guiding value for promoting the green transformation of agriculture and realizing rural revitalization. Based on the IPCC coefficient method, this paper accounts for the provincial agricultural non-CO₂ GHG emissions in China from 2000 to 2019, and portrays the spatial and temporal evolution patterns of agricultural non-CO₂ GHG emission intensity. Based on the STRIPAT model, the influence mechanism of agricultural non-CO₂ GHG in each region is analyzed, and the future evolution of agricultural non-CO₂ GHG under different scenarios simulated. The results show that: (1) Methane emissions from animal enteric fermentation are one of major sources of agricultural non-CO₂ greenhouse gases in China, and agricultural non-CO₂ GHG emissions in China gradually shift from the eastern coast to the western inland regions. (2) The Hu Huanyong Line is the divide between the emission intensity per unit of agricultural value added and the high value zone per unit of agricultural land area, and the agro-pastoral intersection zone is the high value zone of emission intensity per unit of agricultural value added in China. (3) The relationship between agricultural non-CO₂ GHG and per capita GDP in China has an inverted "N" type Environmental Kuznets Curve (EKC), and North, Northeast and Central China are still under pressure to reduce emissions. Effectively reducing methane emissions from animal enteric fermentation and formulating localized emission reduction policies based on regional development characteristics are the keys to reducing agricultural non-CO₂ GHG in China in the future.

To realize carbon‐related nationally determined contributions and achieve the targets of carbon peak and carbon neutrality on schedule, low-carbon development of China's service industry is an inevitable trend. On the basis of the comprehensive application of multiple spatial analysis methods, the spatiotemporal evolution and dynamic interaction characteristics of carbon intensity in China's service industry from 2005 to 2019 are analyzed from the perspective of spatiotemporal interaction. Combined with quantile regression and the nested model of spatiotemporal transition, the driving mechanism patterns of carbon intensity in China's service industry under different transition types are revealed. The results are as follows: (1) The carbon intensity in China's service industry first increased and then decreased from 2005 to 2019, showing spatially unbalanced characteristics. (2) The kernel density curve demonstrates the dynamic convergence trend of regional differences in the carbon intensity of the service industry. And the carbon intensity also showed a significant spatial agglomeration phenomenon according to the spatial autocorrelation analysis. (3) Based on the evolution analysis of the spatial correlation pattern of carbon intensity in the service industry from 2005 to 2019, a path-locking feature was shown by few spatiotemporal transitions across different types. The eastern coastal region had relatively stable spatial structure and spatial dependence direction, while the central and western regions demonstrated the opposite. (4) The spatiotemporal network pattern of carbon intensity in China's service industry was dominated by positive correlations, although a certain degree of spatiotemporal competition was found between some neighboring provinces. (5) Regional differences existed in the spatiotemporal transition driving patterns of carbon intensity in China's service industry. Specifically, the eastern coastal provinces were mainly influenced by the population-urbanization restriction mode, while most regions in the northwest, southwest, and northeast were mainly influenced by the driving pattern of technology-regulation. From the northwest to the southeast, the spatiotemporal transition patterns showed an evolutionary characteristic of "synthetic development-synthetic restriction". Therefore, the formulation of the emission reduction policies should not only consider various driving/restriction factors but also emphasize differentiated emission reduction measures in China's service industry by combining different types of carbon intensity agglomeration and transition paths, as well as avoiding the regional closure of inter-provincial emission reduction policies through synergistic emission reduction.