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Agricultural green development is an essential direction for global sustainable agriculture. The academic literature, however, needs to place greater emphasis on studying the factors influencing agricultural green development performance and how such performance can be improved. A theoretical framework for agricultural green development performance was constructed in this paper using the Super-SBM model, which considers undesirable outputs, to measure the agricultural green development performance of 330 cities at or above the prefecture level in China (excluding Tibet Autonomous Region, Hong Kong, Macao and Taiwan of China) from 2007 to 2018. Furthermore, the influencing mechanism of agricultural green development performance was then analyzed using a spatial econometric model. The results show that: 1) from 2007 to 2018, China's agricultural green development performance experienced three stages of evolution: 'rise, decline and rise'. 2) The regions with high performance agricultural green development are mainly distributed in eastern China, northeastern China, and southern Qinghai Province. 3) The agricultural economic level, industrialization process, and labor quality play significant roles in promoting local agricultural green development performance, while such performance is obviously inhibited by the openness level and the government's environmental regulations. Local agricultural green development performance is significant inhibited by the agricultural economic level and accelerated industrialization process in neighboring cities, while significantly promoted by the agricultural industrial structure in neighboring cities. Some suggestions for improving agricultural green development performance are proposed based on these research results, which can provide scientific references for promoting sustainable agriculture. [ABSTRACT FROM AUTHOR]

The Qinghai-Tibet Plateau (QTP) is the most unique region of human-land relations, and its main factor is population. By building a population and space dataset of the QTP at the township level from 1982 to 2017, this paper presents the pattern evolvement and regional distribution characteristics of township-level population in the QTP in detail for the first time. By using Geodetector method to analyze the influencing factors of township-level population change in the QTP, this paper provides scientific foundations for studying the Third Pole, ecological environment protection of the QTP, and human-land relations. The conclusions are as follows: 1) The population spatial distribution is not balanced at the township level, presents the regional differentiation characteristics of 'dense in southeast and sparse in northwest' along the 'Qilian-Jilong Line', and demonstrates the phenomenon of population center of gravity moving to the hinterland of the plateau at an accelerated speed; 2) The township-level population develops in a decentralized trend in general, and the cold- and hot-spot distribution of population has prominent spatial distribution characteristics. The population hot spots are concentrated in the surrounding areas of Xining, Golmud, Hotan and Lijiang; 3) The population of the QTP is increasing, and the inter-annual change of township population has a relatively stable regional regularity; 4) The level of per capita income is the leading factor in the change of township population, and its effect intensity is increasing continuously. The relative effect intensity of urbanization level and location conditions on population change has decreased significantly after 2000. The adaptability of living environment, such as topography and climate, has little influence on population change. [ABSTRACT FROM AUTHOR]

The aviation industry has become one of the top ten greenhouse gas emission industries in the world. China's aviation carbon emissions continue to increase, but the analysis of its influencing factors at the provincial level is still incomplete. This paper firstly uses Stochastic Impacts by Regression on Population, Affluence and Technology model (STIRPAT) model to analyze the time series evolution of China's aviation carbon emissions from 2000 to 2019. Secondly, it uses the Logarithmic Mean Divisia Index (LDMI) model to analyze the influencing characteristics and degree of four factors on China's aviation carbon emissions, which are air transportation revenue, aviation route structure, air transportation intensity and aviation energy intensity. Thirdly, it determines the various factors' influencing direction and evolution trend of 31 provinces' aviation carbon emissions in China (not including Hong Kong, Macao, Taiwan of China due to incomplete data). Finally, it derives the decoupling effort model and analyzes the decoupling relationship and decoupling effort degree between air carbon emissions and air transportation revenue in different provinces. The study found that from 2000 to 2019, China's total aviation carbon emissions continued to grow, while the growth rate of aviation carbon emissions showed a fluctuating downward trend. Air transportation revenue and aviation route structure promote the growth of total aviation carbon emissions, and air transportation intensity and aviation energy intensity have a restraining effect on the growth of total aviation carbon emissions. The scope of negative driving effect of air transportation revenue and air transportation intensity on total aviation carbon emissions in various provinces has increased. While the scope of positive driving influence of aviation route structure on total aviation carbon emissions of various provinces has increased, aviation energy intensity mainly has negative driving influence on total aviation carbon emissions of each province. Overall, the emission reduction trend in the areas to the west and north of the Qinling-Huaihe River Line is obvious. The decoupling mode between air carbon emissions and air transportation revenue in 31 provinces is mainly expansion negative decoupling. The air transportation intensity effect shows strong decoupling efforts in most provinces, the decoupling effort of aviation route structure effect and aviation energy intensity effect is not prominent. [ABSTRACT FROM AUTHOR]

Social assistance is the last safety net in the social security system and plays a vital role in poverty alleviation in countries around the world. Promoting the equal financial assistance is meaningful to achieve equalization of social assistance. Based on the provincial panel data from 2002 to 2017, this paper analyzes the dynamic characteristics and main influencing factors of the equity of social assistance in China, using the Theil index and geographically weighted regression (GWR) model. The results suggest that the level of per capita social assistance expenditure (PSAE) in China keeps increasing year by year, but the changes in different regions and provinces are quite different. These changes not only significantly changed the spatial pattern of PSAE in China, but also greatly improved its spatial coupling with the deeply impoverished areas. Further analysis shows that the regional inequality of PSAE between provinces is obvious during the study period, and the inter-regional inequality is significantly higher than the intra-regional inequality. This makes inter-regional inequality become the main source of the regional inequality of PSAE in China for a long time. According to GWR results, there is obvious spatiotemporal heterogeneity in the influence intensity and direction of the per capita financial revenue, urbanization rate, urban unemployment rate, natural disaster-affected area, and transfer payment intensity on the PSAE. The urbanization rate and per capita financial revenue are the main driving factors of PSAE, and the impact intensity of per capita financial revenue tends to strengthen. The remaining three factors have a positive effect on PSAE, but the effect intensity is not high. [ABSTRACT FROM AUTHOR]

The middle class in metropolitan Chinese cities has become an important social group. With the rapid development of urbanization and constant advancement of suburbanization, the middle class has increasingly come to influence city traffic. Research into middle-class commuting activities thus has practical significance for improving traffic congestion and reducing the commuting burden in metropolitan cities. Based on a dataset formed by 816 completed surveys, this paper analyzes the commuting mode, time and distance of middle-class residents in Guangzhou City using the descriptive statistical method. The results indicate that private cars are the main commuting mode, followed by public transport. Meanwhile, middle-class residents mainly undertake medium-short time and medium- short distance commuting. The study subsequently uses multilevel logistic regression and multiple linear regression models to analyze the factors that influence commuting mode choice, time and distance. The gender, age, number of family cars, housing source and jobs-housing balance are the most important factors influencing commuting mode choice; housing, population density, jobs-housing balance and commuting mode significantly affect commuting time; and transport accessibility, jobs-housing balance and commuting mode are the notable factors affecting commuting distance. Finally, this paper analyzes what is affecting the commuting activities of middle-class residents and determines the differences in commuting activity characteristics and influence factors between middle-class and ordinary residents. Policy suggestions to improve urban planning and urban management are also proposed. [ABSTRACT FROM AUTHOR]