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Addressing the issue of the healthy and coordinated development of the population and economic factors in rural areas will not only help consolidate and expand the achievements of poverty alleviation, but will also lay a foundation for comprehensive rural revitalization. In this paper, the spatial coupling relationship between the population and economic factors in rural areas in the Qinling-Daba Mountains, China, is explored to provide a reference for rural revitalization and regional sustainable development in poverty areas. Sixty-eight county units in rural areas in the Qinling-Daba Mountains, as well as the population and economic factors in rural areas, are used to study the spatial coupling relationship between population and economy, as well as the driving mechanism, in rural areas in the Qinling-Daba Mountains from 2010 to 2020. The results show that a population contraction phenomenon occurred in the rural areas in the Qinling-Daba Mountains, and the spatial agglomeration trends of the population and economic factors were consistent. The agglomeration was mainly located in the suburban areas of the municipal area, and the agglomeration degree was significantly higher in these areas than in other areas. In terms of the spatial distribution, the economic development level of the rural areas in the northeastern part of the Qinling-Daba Mountains was generally higher than that in the central and western parts, and the unbalanced trends of the population and economic spatial differentiation in the eastern and western regions were significant. The spatial coupling relationship between the population and economy changed from coordinated development to economic advancement. This was mainly due to the mutual restriction and joint actions of the industrial structure, capital situation, natural environment, policies, and institutional regulations, among which the industrial structure and capital status had significant effects. [ABSTRACT FROM AUTHOR]

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]

Since China's reform and opening up in 1978, the acceleration of industrialization and urbanization in China had led to dramatic changes in the pattern of urban-rural land use. In this paper, we focused on the rural industrialized areas in central China (Xinxiang County and Changyuan City of Henan Province). We used the average nearest neighbor index, spatial statistical analysis, and a structural equation model to analyze the spatiotemporal evolution and influencing factors of urban-rural construction land based on multi-source spatial data and survey data. The results showed that: 1) from 1975 to 2019, the spatial distribution of urban-rural construction land in rural industrialized areas had evolved from homogeneous distribution to local agglomeration. In terms of comparative analysis of cases, the spatial distribution of urban-rural construction land in Changyuan City had shown a trend from diffusion to agglomeration, and Xinxiang County had overall shown a spatial change from homogenization to agglomeration and then to regional integration development. 2) The hot spots with increased urban-rural construction land significantly expanded, and they had a high degree of spatial overlap with industrial development. Among them, Xinxiang County was concentrated in central and marginal areas, and Changyuan was mainly concentrated in central urban areas. 3) From the evolution of spatial proximity of urban-rural construction land, rural industrialized areas generally decline, showing the characteristics of internal differentiation in the rate of change. 4) Industrial development, social economy, the policy environment, and urban development played a positive role in promoting the expansion of urban-rural construction land in rural industrialized areas. To promote the optimal use of regional land and the integrated development of urban-rural areas, we should combine the advantages of regional endowment, formulate development strategies according to local conditions, and adjust the way that land is used in a timely manner. [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]

Urban comprehensive carrying capacity is an important guarantee and external representation of regional sustainable development. Based on urban comprehensive carrying capacity, this paper constructed a performance evaluation index system of urban comprehensive carrying capacity, and used entropy method, urban comprehensive carrying capacity measurement model and urban sustainable development model to measure spatial and temporal comprehensive carrying capacity of Harbin City in Heilongjiang Province from 2012 to 2017. The results show that: 1) index weight analysis suggested the regional development mode in Harbin still followed an epitaxial development mode, which pursued the expansion of scale and the growth of total amount of regional development, neglecting the effective utilization of resources and the improvement of structural benefits. 2) In the pressure system, the index of resource support has dropped sharply. The index of environmental capacity and social progress has risen circuitously, while the degree of agglomeration and the value of transportation facilities have risen steadily; in the pressure system, the index of population development and economic growth tended to fluctuate, while energy consumption and environmental pollution showed a more synchronous change in characteristics, and the livable demand remained at a high level. 3) The carrying capacity index of resources and environment in Harbin has been declining, and the acquired carrying capacity index fluctuated. The long-term regional development model has severely impaired the carrying capacity of resources and environment. 4) The comprehensive carrying capacity of Harbin has clear spatial differentiation characteristics. Finally, the paper proposes that location conditions, economic development level, government regulation, and science and technology are the main factors influencing the spatial differentiation of urban comprehensive carrying capacity. [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]

Attended collection and delivery points are vital components of 'last-mile logistics'. Based on point of interest (POI) data for Cainiao Stations and China Post stations in Changsha City, China, this paper provides a detailed exploration of the basic features, spatial distribution, and location influencing factors of attended collection and delivery points. Specifically, analyses of the types, service objects and location distributions of the attended collection and delivery points alongside a discussion of their spatial pattern and influencing factors provides a reference for their general geographic layout and characteristics. The findings of this study indicate that: 1) The main mode of operation of attended collection and delivery points is franchises, with other modes of operation rely on supermarkets and other individual shop types. 2) The main service targets of attended collection and delivery points are communities, schools, and businesses, followed by townships, enterprises, scenic spots, and administrative units. 3) Approximately 77.44% of the attended collection and delivery points are located near the exits of service areas; others are situated in the centre of the service areas. For the Cainiao Stations, 80% are located within 125 m of the exit; for the China Post stations, 80% are located within 175 m of the exit. 4) The spatial distribution of the attended collection and delivery points in Changsha is unbalanced, with 'more centre and fewer surrounding'. The centre is an 'inverted triangle', and the edge is an 'orphan', showing a northwest-southeast orientation and symmetrical along the axis. The layout of the attended collection and delivery points forms three core areas, and the number of sites decreases with the distance from the core. 5) The number and distribution of the attended collection and delivery points are strongly consistent with the regional economic development level, population, and roadway system traffic convenience. Most attended collection and delivery points are on residential, scientific and educational, and commercial and financial land. [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]